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Excel for Data Analytics - Full Course for Beginners

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Summary

Core Theme: This comprehensive Excel course for data analytics aims to equip beginners with essential spreadsheet skills, progressing from fundamental functions and charts to advanced tools like Power Query and Power Pivot, enabling learners to analyze real-world data and build a portfolio.
Key Points:
- The course covers Excel basics (functions, charts, tables) and advanced features (pivot tables, Power Query, Power Pivot, DAX).
- It includes practical, hands-on exercises and practice problems to reinforce learning.

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dat nerds welcome to this full course

tutorial on Excel for data analytics

this is the course I wish I would have

had when I first started as a data

analyst you're going to be working right

alongside me as we Master how to use a

spreadsheet starting with the basics of

functions charts and tables working our

way up to our first portfolio project

we'll then shift gears into advanced

features like pivot tables power query

and power pivot ultimately building our

second and final project analyzing real

world data now to master this tool we're

not going to go straight for 11 hours

instead we're going to break it down

into 10 to 20 minute lessons during this

we'll have exercises for you to learn

while doing not just watching followed

by practice problems to reinforce your

newly learned skills now Excel is the

most popular spreadsheet tool in the

world it's estimated to have over 1

billion users that's one in eight people

in the world and for data nerds it's one

of the most popular skills for data

analysts coming only behind SQL oh and

the same can be said for business

analysts in this Tool's popularity truth

be told Excel was one of the only skills

that I knew when I landed my first role

in data analytics but it was able to

handle everything thrown at me and so

I've been cataloging over the years all

of the most important features to

perform data analytics and I compiled it

in this course and this video is for

absolute beginners you don't need any

analytic or spreadsheet experience we'll

be starting with the first half on the

basic chapters which will build up your

knowledge on the fundamentals with

covering which versions of excel you can

use for the course along with installing

it then we'll get you familiar with

working around how to manipulate a

spreadsheet from there we'll shift into

practical exercises analyzing data using

formulas and functions and then

visualizing it using common charts and

statistical analysis at the end of the

basics chapters we'll put your skills to

the test to build an interactive

dashboard to predict one salary based on

job and location for the second half of

the course we're going to ramp up our

learnings diving into Advanced

Analytical features focusing on using

pivot tables and add-ins to dive quickly

into Data in sites we'll learn power

query to connect to a variety of data

sets and perform ETL or extract

transform and load finally we'll learn

data modeling with power pivot and

perform Advanced calculations with the

Dax Language by the end of the advanced

chapters we'll have built a full data

analytics project analyzing the data

science job market which you'll be able

to share this and the previous project

in order to Showcase your experience

with analyzing data in Excel now I'm a

big believer in open- sourcing education

so this course and all the content

required to complete the course is

completely free I not only get you set

up with Excel but I also provide all the

different Excel workbooks and sheets

needed to complete this course with this

you'll get access to the data sets

needed to make those final projects and

even how to share them now unfortunately

the AdSense Revenue alone from this

course isn't enough in order to support

all the different costs associated with

building this so I have an option for

those that want to support and help out

for those that purchase my supporter

resources you're you're going to get

access to a lot of features that are

going to help speed up your learning all

provided through this custom dashboard

to track your progress you'll get guided

practice problems to perform after each

lesson that will not only provide the

solution but also walk you through how

to get it if you get stuck along the way

you'll have access to a community of

others in order to jump in and comment

and ask for help additionally you'll be

getting my step-by-step instructions

that walk through each of the lessons as

I perform it and finally when you

complete the course I'll email you a

certificate of completion that you can

upload to LinkedIn now one quick shout

out before we jump in and that's to

Kelly Adams she helped me plan out a lot

of the different lessons for this course

along with being the brains behind a lot

of the different practice problems and

frankly if I didn't have help I probably

couldn't have completed this course so

before we go any further with what we

need to and actually diving into this

course we need to First understand what

is Excel and where the heck it came from

so in order to understand this we need

to go back oh a little too far back

ah just right ancient Babylon when we

used to trade livestock like it was

crypto now it's during this time that we

started recordkeeping and we didn't have

paper so we used Stone and we partition

it into rows and columns during the time

of the Romans they began to perfect this

even further with accounting eventually

we get some advancements in technology

we start getting this on paper this is

when the term spreadsheets gets the

introduction this maintained that

familiar row and column format in order

to catalog different things spread AC

across different sheets spread sheet

fast forward to the 1900s and we pack

rooms full of underpaid people in order

to maintain and keep track of all the

different transactions on paper

spreadsheets with the Advent of

computers in the late '70s we started to

see our first spreadsheet softwares vial

and Lotus 123 then our boy here decided

to revolutionize the world little

bit okay not with that but with this I'm

Bill Gates chairman of my

Microsoft in this video you're going to

see the future since its launch in 1985

it's been wreaking havoc in the

spreadsheet software Community

dominating market share and to continue

to dominate over the years Microsoft has

added more and more features it

initially started out to where you'd

only be using it for the cells of

entering different formulas and forming

quick calculations along with getting

different charts and Analysis shortly

thereafter it was upgraded with pivot

tables and that's my secret weapon to

quickly analyzing data as I no longer

have to remember which comes first and

index and match now VBA or Visual Basic

for applications was included in the

mid90s and it's a programming language

in order for you to automate task in

Microsoft applications now we're not

going to waste any time in this course

learning VBA frankly I feel it's

outdated you should learn python instead

and there's newer tools that actually

automate the process of data analysis

like powerquery this was first

introduced as 2010 and then rebranded to

get and transform and then rebranded

again to power query sort of similar to

what Google does with renaming products

anyway this bad boy is like washing down

a couple caffeine pills with a shot of

espresso it can ingest and clean so much

data in the blink of an eye hardcore

data nerds call this ETL or extract

transform and load power pivot was also

introduced during this time of power

query and it's like putting your

spreadsheets on steroids this allows us

to perform data modeling on data sets

greater than a million rows greater than

what Excel actually holding the

spreadsheets and combined with the power

of Dax or data analysis Expressions we

can supercharge our calculations fast

forward to today and there's been two

other major features added to excel

co-pilot which is basically chat GPT

inside of Microsoft Excel and python

Excel which is basically python inside

of excel anyway co-pilot is great wait

that's a lie so I do believe AI chat

rots are great at helping us out when we

get stuck but I don't want you rely on

that to actually learn this technology

of Excel and for Python and Excel you

need to know well python if you don't

know this yet it's completely useless

now with all these features it can make

it seem like Excel is overwhelming which

I completely get that but when you focus

on the basics and work from there I

think it makes a lot easier to learn it

it's also why this course is almost 11

hours long all right enough with the

history lesson let's actually get into

the course material and what you're

going to need for this also we're going

to be going over what data set or what

data we're going to be analyzing for the

project for this with the link provided

below you can navigate to this which is

the GitHub repo that has all the

different folders and files needed to

take the course now don't understand if

you're not familiar with GitHub we're

going to walk through this this pane

here basically outlines all the

different folders that you have access

to and if I navigate in something like

resources I can see I have a data sets

folder images folder and even a problems

folder so for those that purchase the

course practice problems you have access

to the problems inside of here and

they're broken down by chapter along

with the lesson in addition to that

resources folder you can see numbered

here we have each of those eight

chapters and if we navigate into

something like spreadsheets intro we

have a workbook for each one of the

lessons so you want to download this

file you just navigate to it click the

three dots and click download but have

an alternate method coming up in a bit

inside the workbooks I provide a blank

template for you to go through and

actually fill in and we'll be getting to

what's in this final sheet of actually

being filled in now as we move into the

advanced chapters they're going to have

something like the data sheet or you're

going to use the data from the data

sheets in order to do different

operations and we'll put those in

different sheets as well so how do we

get these files well the easiest way is

to come up here to this code and go to

download zip with the file downloaded

all you need is to unzip it and then

from there it has all the different

folders with the appropriate workbooks

inside of them now after going through a

lesson I then have practice problems for

those that purchase the course perks to

go through here's the course dashboard

that you'll get access to that breaks it

all down for the problems based on the

chapter itself and then by the lesson

and inside of each of these lessons is

multip multiple different problems for

you go through and work the other perk

that you'll receive with those practice

problems are the course notes these

break down the concepts in a similar

format of all the different chapters and

lesson here's the one on Excel install

which is going to be what we're covering

next but it provides all the different

background on all the different material

that be covering this and it's in the

same format that I'm covering it in the

video so you can follow right along just

as a reminder there's no requirement to

purchase these practice problems or

course notes just helps support me

anyway what are we actually going to be

covering in this data analysis that

we're going to be doing inside of excel

well you're going to be taking the role

of a job Seeker in exploring what are

some of the top paying roles along with

skills of data nerds for this we're

going to use the data from my app dat

nerd. Tech that is collected to this

point up to 3 million jobs it tells

based on a job title and also on a

location what are the top skills and it

not only tells us the salary of these

skills for a particular job but also the

salaries of the jobs themselves now the

main data set we're going to be using

for the majority of this course is this

one here inside the data sets folder of

data job salary all this data set

includes over 30,000 job postings from

2023 and it includes a wealth of

information such as company name salary

and location as we go through these

examples I'm going to be doing it from

the perspective of a data analyst which

is their top job in the data set but as

shown here there's a lot of different

other job titles that you can check out

and use as well so feel free to deviate

additionally I'll be primarily focusing

on the United States but there's a lot

of different countries in there as well

so feel free to plug in your home

country and analyze this instead now

with any course you're probably going to

get stuck along the way and so how do

you get help for this well I don't

recommend just jumping into the comment

section and waiting for somebody to help

you out instead I recommend using a chat

bot like chat GPT in it you can provide

whatever era you're seeing and it will

help you out and guide you along the way

on what to do and there's other great

options as well such as gemini or even

Claude so feel free to use whichever one

you're most comfortable with all right

if you haven't done so already it's your

turn now to go in and download that

GitHub repo with all the different

workbooks needed for this course in the

next lesson we're going to be getting

into installing Excel and mainly

understanding what are the different

versions that you can actually get with

Excel and which one you need for the

there let's now actually get into

working with Excel so in this lesson

we're going to be going through how to

actually inst install Excel onto your

computer assuming you don't have it but

before we get to that for those that

maybe have Excel or an older version of

Excel or have different computers we're

going to actually go through what are

the preliminary requirements you need to

have or set up in order to be able to

course now here's a breakdown of the

different chapters within this course

that is the rows here and then for the

columns are the different micro Micosoft

products that you can get in order to

have Excel now if you're running Excel

on a Windows machine either through

Microsoft 365 Microsoft Office at home

and student or even an older version of

excel up to about

2010 you're going to be fine with

completing all the different course

content however if you have the Mac

version or Mac operating system and

Excel is installed directly on that

operating system you're not going to be

able to complete the Advanced chapter

specifically on power query and on power

pivot along with the project and it's

similar as well for Microsoft 365 online

as you won't also be able to complete

the Advanced Data analysis section now

if you have any of these first three

versions of excel installed on your

computer you can skip to the next lesson

if you want I'm just be going through

before the install process of breaking

down each of these different versions so

get so let's get into breaking down all

these different versions available first

up is Microsoft

365 now with Microsoft 365 you're going

to get a host of different Microsoft

applications not only Excel but also

things like word PowerPoint and even

Outlook and there's two major plans I'm

going to recommend for this either the

family plan which allows you to give out

these keys for these different services

to up to six people or a personal plan

which allows you to give it to well

yourself now I do want to call out that

if you're a college student or maybe you

work for a big Corporation you may have

access to a free Microsoft 365 plan so

if you're in college check with your

college and if you're working for a

business check for your business if you

have access to this so you don't have to

pay money for it but regardless of that

if money is an issue Microsoft 365

family offers this free one-month trial

which I think you can complete this

course within a month so technically you

could do this for free if you don't want

to get charged you will need to actually

cancel before the end of that 30 days

and at that point you'll still have

Microsoft Excel installed on your

computer just everything will be in view

only mode you won't actually be able to

edit any of the different spreadsheets

that we've operated on during this

course let's now move into Microsoft

student now this bad boy is the

alternate recommendation I'm going to

give you if you don't want to pay for a

Microsoft 3 365 subscription this is

only a onetime purchase and it gives you

keys to Microsoft Office so you can

install all the different Microsoft

products of excel word and PowerPoint

onto your computer for the low low price

of $150 similar to Microsoft 365

subscription this will not only work on

a Windows machine but it will also work

on a Mac machine Let's now move to this

last option because it's sort of in the

now this version of Microsoft 365 is

completely free but sort of a catch to

this here I am on my web browser logged

into Microsoft 365 online and I have

access to all the different apps within

the browser including something like

Excel so we can go to it now this

version looks very similar to the

version that you can actually install

the applications on your Windows or Mac

machine there are limitations like a

disuss before about power query and

power pivot so you're going to be

limited if you're trying to follow along

in this course when we get to those

Advanced chapters also the layout on the

web browser version of this app is much

different from that that's installing

your computer so I'm not going to be

providing any support on this course on

actually actually how to navigate this

so you're going to have to figure that

out yourself so we've discussed

everything except for these Mac versions

of Microsoft 365 and office so here's a

quick recap of all the different

features and cost of the three major

versions of Microsoft that you can get

in order to get Excel on your computer

for this personally I'm using the

Microsoft 365 family plan because it

includes all the different features that

I need and it also I save cost because

I'm splitting with my brother who now

that I think of it is actually paying

for it but it provides everything that I

need and so it's the one I'm

course now before we get into the

install I want to briefly show what are

the differences between using Mac with

Excel installed Vice windows and Excel

installed on it anyway here's Excel

installed on my Windows operating system

and Excel on this operating system is in

my opinion the flagship product from

Microsoft so they're investing all of

their effort and resources into

designing this application to make it

the best possible and then from there

Excel online and then Excel for Mac are

really just copycats of this anyway the

two main differences and the problems

I've run into in the past that Excel for

Mac doesn't have are in this data tab I

have a lot of different data sources I

can choose from and that's specifically

related to our power query lesson and

then finally it has power pivot which is

just completely non-existent on Excel

for Mac now here I am on a Mac machine

and we can see that it looks very

similar to before but there's a lot of

limitations that we're going to find

with this specifically going back to

that power query not a lot of different

sources you can choose from and then

yeah Power pivot is just completely

non-existent you may be like Luke I have

a Mac machine what do I need to do in

order to have the most premier version

of Excel and use for this well for that

I recommend installing a virtual machine

and virtual machines like parallels

shown here allows you to host a

different operating system on your Mac

machine this Windows example that I was

showing earlier if I actually expanded

out you can see in the background here

I'm running this on a Mac machine and I

have full capabilities en able to carry

out and running Windows on this now I've

been paying for and using parallels over

the past 3 years and I can tell you the

support and the offers from it are

perfectly fine and I love using it now

personally I'm using the Parallels

Desktop Pro Edition but you can get by

with just using the standard edition now

they also have this onetime purchase

that you could do which is 129 but it

doesn't get any further updates and I

really like how it actually updates and

fixes any bugs that may run into now the

other reason why I like parallels is

because it has this coherence mode I

have this blue little icon that I can

click up at the top to go into coherence

mode and then wait for it it allows me

to access any of those windows inside of

my windows vers virtual machine inside

of Mac so here is Excel running right

here inside my Mac and this is not only

limited to Microsoft Excel but also

products like powerbi which I'm using

pretty frequently as a data analyst I

can also run this into coherence mode

but enough about

that now that they got that out of the

way let's actually get into installing

Excel via in your Windows machine or on

your Windows Virtual Machine so the

first thing we need to do is navigate

over to

microsoft.com and I'm going to click up

here to Microsoft 3 365 we're going to

be going through setting up the free

30-day version so I'm going to click

this of try for free and from there

start my one month trial it's going to

ask me to sync my data I'm assume you

don't have it I'm also going to assume

you don't have an account so we're going

to create one I'm going to put in my email

address and then from there create a

password after providing some personal

information you're going to need to

verify your email with the code they

send you now to be clear this is the

Microsoft 365 family plan which after

that 1 month trial it's going to be

charging you at

$99 every year so if you're just one

person and you're trying to switch to

the personal plane after this you'll

need to do that at the end or near the

end of those 30 days from there like any

company they're going to ask for some

payment methods I'm going to just go

ahead with PayPal PayPal's all set go

ahead and do more paperwork of adding

Bell and address and with that I can

start trial and pay later so now that

I'm logged in I want to install the

desktop app so it gives me access to

right here it's going to go ahead and

begin this it's going to ask if want to

allow this app to make changes to your

device yeah I trust them so only took a

few minutes and all the different

Microsoft 365 office apps were installed

so I just come down to the search bar

down here type in Excel let's pop it

open make sure it's working and in order

to get started you need to sign in in

order to verify that it's your

subscription so I put in my email and

password and already forgot my

password now I'm resetting my password

and now I'm all set up all right and we

got agre to some lawyer talk of

accepting licensing agreements at this

point I'm pretty worn out of going

through this process so I'm just going

to click through everything I'm not

going to send any optional data

personally I don't like to do that I

don't want to personalize right now and

it looks like I'm finally done all right

I'm into it and now that we're into

Excel we can see up here it should have

your name or your account that you're

going into and go in here into the blank

workbook all right so that basically

concludes this lesson on installing

Excel I do want to show real quick how

easy it is to actually cancel your

membership should you want to go about

just getting the free version or the

free 30-day trial and you want to cancel

it before any if I go back to my account

I can go in here to manage

subscriptions and here I'm inside my

Microsoft account which tells me I'm

subscribed to Microsoft 365 family I can

share it with up to zero to five people

and for that I just click on it and I

can copy a link and provide it to

whoever I want to share it with we're

going to cancel it so we can go to

manage subscriptions right here and all

we got to do is click cancel

subscriptions it's going to have me

confirm that I do want to cancel this

family plan makes me scroll all the way

to the bottom after showing me all these

different prices that I could get

instead and I'm going to say yeah I

don't want my subscription and as I'm

filming this on August 27th it basically

says hey you still have access this for

30 days until September 26th so still

technically have access to it so if you

haven't done it already it's your turn

to now go and install Microsoft Excel

the one of the options that I've shown

here in the next chapter we're going to

get into a spreadsheets intro to get you

familiar with how to actually use all

the different functionality or graphical

unit or interface gooey of excel with

one welcome to this chapter on an intro

to spreadsheets and this chapter has

three different lessons in order to

understand what we're covering those

three different lessons we need to

explore some vocabulary with it so let's

jump into Excel for this lesson we're

going to be focusing on worksheets and

that is basically as you can see this

tab here called sheet one that is how to

manipulate these different cells within

this worksheet or also known as a sheet

in the next lesson we're going to be

going into workbooks so workbooks

basically captures either one sheet like

this one sheet one if I add another one

sheet two so it encapsulates multiple

different sheets within this program of

Excel and then finally in the third

lesson of this chapter we're going to be

moving into the ribbon which is up here

at the top and has a bunch of different

functionality to extend into those

spreadsheets along with using this file

tab up here that has a whole bunch of

features within it as well now this

chapter was designed for those that may

not have experience with using Microsoft

Excel before so if you don't fall in

that category as in you've used excel in

your job and you're pretty familiar with

all those different features I just

shown you can feel free to skip this

chapter and then move into the next one

on functions along with all those

different practice problems but if

you're not comfortable with that stick

around we're going to get into

it all right so the first thing you need

to do is open up that first Excel sheet

in the files you should have downloaded

from GitHub on onecore worksheets inside

of here I have an original sheet that

allows you to actually go in and fill in

everything we're going to be doing and

manipulating during the course of this

lesson then if you get lost along the

way or want to peek ahead to see what

we're actually going to do you can

actually scroll over here or select the

final sheet to see that now I want to

make this as big as possible for you to

see so I'm going to go ahead and close

out this ribbon up here and you can just

do that by double clicking on any one of

these different items up here and then

from there I also want to zoom in so I'm

going to come down here to the bottom

right and I'm going to just zoom in to

about 200% and scroll on over now inside

the spreadsheet it has all these

different cells and it's organized in a

manner where it has rows and the rows

are labeled with numbers 1 2 3 all the

way down to about a million and then we

have the columns and the columns are

alphabetical and they all go all the way

to where they start duplicating where

they'll put another letter in front of

the other and it'll go all the way

through xfd so let's practice some data

entry here I have a table we're going to

be filling in for this lesson basically

has all the different skills associated

with it and then I want you to actually

go through while we're going through

this and you don't have to provide the

values I do you can if you want we're

going to be filling it in based on our

difficulty when we made have started it

or level and then filling out some other

self formulas as we go so we're going to

start first with Excel and then the

difficulty so I'm going to select right

here and I can see which cell is

selected because it's sort of

highlighted here on this B and also two

but also right up here next to this

formula bar I just call that formula bar

we can see that we're calling out the

name of B2 so anytime we reference any

cells it first references the column

letter and then the row number so in

this case I'm selected in C7 so I'm

going to go ahead and give this a number

I'm going to say four for myself as you

notice I I just put it right in the Box

alternatively I can also select the cell

I want to go to and then come up here

into the formula bar press what I want

so I want five for Python and go from

there whenever I press enter it then

goes down to the next cell so

technically I could just go through and

enter this all in using my keyboard and

I don't have to click or move manipulate

at all except to select the cell that

wanted so those were all numerical

values when we move into the skill known

on whether we know it or not we want to

put in whether it's known or not we want

to put true or false this is known as a

Boolean value so typing in something

like true I can see when I press enter

it actually updates to be all caps for

this Tru so it recognizes the data type

of this as Boolean now if you're taking

this course you probably don't know

Excel so we're going to put in false

instead now say I want to update the

rest of these for false false I can yeah

go through and actually type it up or I

can select this lower right hand corner

of cell C2 and now I can drag these

values down and it will autofill it in

now autofills not just limited to

Boolean values let's say I had something

like Luke I could put that here and just

drag it down it's going to fill in Luke

all the way through here a cool feature

about Excel is say I have something like

one and then two I could select both of

these cells and then when I drag it down

it's going to actually fill in three or

four now autofill can also throw you off

especially for dates so let's say we're

filling in when we're starting Excel

which is we'll put in for the today's

date in my case it's August 27

20124 I'm going to go ahead press enter

to save that in it automatically updates

to this formatting here in America if in

Europe you may see the month in a

different location anyway if I select

this and actually drag down what you'll

see is is it will do that auto fill in

but it's not going to keep that same day

per it assumes we want to increment by

one day now specifically with dates if I

want to change the format I can actually

come up here and I'll expand out this

home ribbon again and right now it's Rec

recognizing that the number is of date

and for date I have a few different

options I can do short date which is

shown here or even something like long

date I can also go even further which

we'll explore as we get further into

this course into this more number

formats and date actually has a whole

bunch of other different options that we

can choose from but for right now we're

just going to keep it this simple date

format and I'm going to click okay now

assuming you haven't started any of

these I'm going to go ahead and actually

just select all the different cells that

I want and if you were to press delete

it's only going to delete that top cell

and that's sort of annoying because I

want to delete all these different cells

instead what I'm going to do if I'm on a

Windows machine I'm G to press delete or

in my case I'm using a Mac Windows VM

I'm press function delete and it's going

to delete all the different content

right I'm also going to go ahead while

I'm here delete all that different

content down there we don't need it now

we're going to move on to level type of

diet we're going to put into this is

text so in the case of excel you're

probably a beginner so I'll put in

beginner and then if I want to I can go

through and fill out different levels

for each of these so python Advanced RBI

Advanced and so on for all these now one

thing to notice real quick is for the

date it does specify in here under this

home ribbon that it is a date but all

these other one it just characterizes as

general which is perfectly fine now for

these other options down here let's go

ahead and say I wanted to put in

beginner for all the rest of these can't

necessarily drag and drop this but what

I can do is I can actually copy it

specifically I could right click the

cell and come up here and copy it but I

don't recommend that also over here on

the home menu they have an option as

well to copy or even cut something so I

can select something like copy as well

and it's going to put these marching

ants as they call it around the cell to

tell you that hey it's actually selected

and then if I wanted to paste it I go

ahead and select down here and I could

paste it down below that's not what we

want to do I don't like going through

and actually selecting all these

different buttons I want to minimize it

as much as possible and I want to use

shortcuts so in order to stop these

marching ants I can go ahead and press

escape and I'll select the cell that I

want to copy and from there I'll press

contrl C and that copies it and then I

can go ahead and paste it below by

selecting the cell that I want and

pressing control contr V now you'll be

noticing that when I'm going through

this I have these shortcuts peing right

here next to me on the screen so you'll

be able to follow along as well as I'm

using these shortcuts the other option

is I could cut this so I could press crl

X and then paste it in here crl V but

this is going to go ahead and take this

value out of here we don't want to

necessarily do that so I'll just copy

this again crl C and then paste it right

above here contrl V shortcuts are going

to be a big timesaver and we're going to

be using them a lot throughout this

course in order to save you time and

having you to go back to your mouse in

order to manipulate it and select the different

cells all right so let's step this up a

notch and we're now going to get into

using formulas and formulas are denoted

by whenever we go into a cell like

difficulty here which we want it to be

on a 1 to 10 scale we denote formulas by

an equal sign and in this case we want

the difficulty to be on a 10-point scale

basically transition from that 5 point

scale so we need to multiply it times

two so we could do something like 4 * 2

and I press enter and it's going to give

me as I expect eight but I actually

don't recommend hardcoding values that

are already inside of excel here

specifically this four so instead of

this I'm going to remove this and I can

either type in the cell coordinates of

the cell so I could type in

B2 and as you notice it's highlighting

one the B2 is blue but then the cell B2

is highlighted in blue alternatively I

can have an equal sign here and just go

over and actually select it as well

whenever I press enter it's going to go

ahead and say a it's four now now that

I'm referencing that four I want to say

that this is 4 * 2 pressing enter we

have 8 once again we're going to use

that power of autofill so I can select

that cell of F2 and now drag it down and

what's going to be pretty interesting

about this is the two as denoted in the

formula bar and actually whenever I

click into it as well the two Remains

the Same but autofill automatically

knows to adjust the formula or the cell

coordinates for the next cell Down based

on how I did that autofill just to show

this as well I could say hey let's equal

this to B6 right below it and then if I

were to drag this over it's going going

to then put in C6 D6 E6 then F6 so

pretty cool I'm going go ahead and

delete this now the last column we're

going to be filling in is skill and

level we're also be using a formula for

this and we'll set this equal to this

skill thing and also this level so I'll

start by putting in an equal sign and

then it's not on the screen right now

but I know it's in b or sorry A2 and I

can see that selected by scrolling over

here now how am I going to get in that

F2 well I can do an Amper sand now and

from there I'll put in F2 and it has

this selected as well pressing enter

ended up in the wrong one sorry about

that should have been E2 and now I have

Excel beginner but there's no space in

between there this is sort of hard to

read so what I can do is actually

manipulate this to include another Amper

sand and then in between this I'm going

to put quotes and this is hey insert

this text character in between it

specifically I want to have a space then

a dash and then another space and then

press enter now if I tried to do this

without the quote if I just did this and

press enter I'm going to get a typo in

my formula you have to actually put

those quotes around to show that it's

text and it's trying to correct it for

some minus sign I don't really like how

it's doing it oh my gosh it's freaking

out now anyway I put the quotes back in

there pressing enter boom we have it and

like before I'm going to just do

in so let's zoom out a little bit cuz

we're going to be now be working with

ranges which is a collection of cells

now if you notice whenever I select in

this case I'm selecting B2 it says B2 up

the top but if I go to select more of

this it will actually call out that five

r or five rows by two c or two columns

and then when I Let Go it just goes back

to B2 anyway ranges are a selection of

multiple of cells so if I come over here

to i1 put it in equal sign and then if I

want to say copy this entire range I can

go ahead and select this all so it's

saying it's A1 colon G6 so start the

upper left hand corner of A1 and the

bottom right hand corner of G6 now this

is pretty cool there's a new feature of

excel of dynamic rages it's going to go

ahead and fill this in there's only one

formula in here of that A1 through j6

but you see that has this Shadow border

around here that's showing that this

dynamic range is now filling in for all

these different things and if we look at

the formula bar it's sort of gray out

here too for it only at the very

beginning does it show that A1 and G6

and then you could manipulate it so if I

wanted to I could change it to G5 and it

would just go down a row now we're not

limited to just that we could in fact

select an entire column so in this case

I'll put an equal sign and let's say I

want to do the the full column of column

a right here I can select up here a it's

going to select all the way down and if

we go over to the formula bar itself we

can see that it's saying a colon a that

means all the contents of column A are

going to be included in this and from

there it's putting a copy putting all

these different things and then when

there's not a value in it because it's a

copy similar to over here for these

dates of zero we're going to see Zero in

all these different values all the way

down now similarly I can also do a copy

of a row so in this case if I wanted to

or multiple rows if I wanted to do rows

five and six I could press enter going

to get an erir with this though and that

has to do with this Q column right here

that we're copy and pasting here so I'm

going to go ahead and delete that real

quick get rid of it and now we have that

rows five and six duplicated below along

with that shadow around it and all there

now these ranges are going to save us a

lot of time later so I'm going to go

ahead and delete this right now I don't

want any of that as later on when we get

into actually using functions within

formulas I can use something like the

average function put in a range in here

so it selects all of it and then get the

average of it in this case now one last

thing to note on this before we wrap up

here on how to save this is you may have

noticed that this date started over here

is a number and that's because that's

how Excel stores dates with within this

spreadsheet right here so if I actually

click on it go back up to home right now

it's St storing it under the format of

General right now so if I were to make

this into an actual date we can see that

it is in fact 827 2024 now just some fun

little trivia if I were to put in number

one and transition it to a date so

coming up here and selecting date that

first date starts at January 1st 19900

and then they move on the numbers from

there all right last thing we need to do

is now save the work that you just

completed with this you can do this

multiple different ways we can come up

here to the top of your Excel workbook

right here and click save you can also

as shown you can use contrs

alternatively you can come over here to

the file menu and then come on down to

save or save as and then if you wanted

to you can specify the location where

you actually want to save your file and

save it there now you do have the option

which I highly recommend if you're

working with real world files you want

to actually save them to save this

autosave feature the one caveat to this

is that your files have to be stored on

one drive right now with the plan that I

have I can store about one terabyte of

files on there so if you'd like to do

that feel free to transition your files

there I'm not going to um and I won't

have Auto saave on for this but for very

important files definitely do have

autosave set up all right for those that

have purchased the practice problems and

notes you have some practice problems to

go through and get even more familiar

with manipulating cells inside of a

spreadsheet after that we're going to be

going into manipulating a workbook with

one all right we're going to be

continuing on with this spreadsheets

intro focusing now on workbooks so

previously we were focusing on

worksheets which are a sheet inside of a

workbook now we're going to be focusing

workbooks now for this I don't want you

immediately jumping into that 2or

workbooks Excel file this really just

has all the answers in it it doesn't

have really what we need for it instead

we're going to be starting with a new

notebook and instead importing in some

data so specifically if we go into this

folder of zore resource

into data sets we have this one Excel

file called Data job salary monthly now

this is similar to the data that we're

going to be using for the remainder of

the course we're actually going to use

another Excel sheet but this one here is

pretty neat because it's broken up by

months into different sheets so all the

job postings for January are in this

sheet called Jan and so on for February

and so on for March so what we're going

to be doing in this lesson is moving we

want to just evaluate the January data

move that into a new workbook so to get

a new workbook as easy as possible we're

going to come over here to the file menu

I'm just going go to new and click blank

workbook now here I have that new Bo

notebook right now it's titled book two

because it hasn't been saved anyway

going back to that file menu just to

show you I have different options I can

get a new notebook so we went into new

and just selected uh a blank workbook

also we could use this Home tab and

select a bank blank workbook based on

that also have a bunch of different

tutorials you can check out also we have

this open tab right here which allows

you on the left hand side to select a

location like this PC or even browse

different locations in your file system

but frankly I'm using more often than

not over here on the right hand side

this right here where this shows a past

history of Excel files I've worked with

so I can go through and actually select

an Excel file pretty easily we're going

to explore more about this file menu

more in a bit let's get moving some data

first now before we get into copying

this data into the new workbook itself I

want to actually just copy it within its

own workbook so if we noce some controls

down here at the bottom we have all the

different Sheets if we want to add

another sheet which I want to copy it to

I'm just going to add this in right here

and I'm going to call this Jan copy

press enter and that's new sheet and I

and I added that by just double clicking

in there and then allowing it to addit

addition I can rightclick it and I can

do things like rename it and that will

do the same thing now there's also some

controls around here you notice there's

some arrows on right here and what that

does is just Scrolls all the way over or

incrementally over so I can see all the

different sheets in this case there's

more sheets than I'd actually see in one

view then we have the scroll bar over on

the right hand side this is actually

just controlling the scroll area within

our new sheet of Jan copy so previously

we we saw how we can copy ranges using a

formula in this case I'm entering equal

to and then I'm just going to select

this range right here press enter and I

can get it inserted in and then actually

looking at the formula it's just equal to

J1 uh colon p8 and this has its range

right there all right so I want to get

the contents into this sheet so I'm

going to start by putting an equal sign

and then I'm I go over to that Jan sheet

and when I go over here you're going to

notice that now next to that equal sign

I have Jan the name of the sheet and an

exclamation point this is identifying

the sheet and I want all this different

items so as I go to select it all you

can see that it's updating in the

formula bar right now I have A1 through

P2 selected but I actually want to

select everything in this sheet and

we're about at 3,000 rows and right now

I'm only about 500 of those this is

going to take forever so I don't

recommend necessarily doing this type of

method to try to select all your data so

I'm going to go ahead and Escape out of

this and go back to where we were at the

Gen copy instead once again I'm going to

press that equal sign go back to that

Jan sheet right up in the form bar once

again I can see that it has the Jan and

the exclamation point I'm going to

select A1 to start with and I'm going to

press the shortcut contrl shift and then

the right arrow key and now all the top

row is selected from here I'm going to

continue to hold control shift and press

control shift down and it's going to

select all the different arrows so as we

can see up here A1 to P 3103 scrolling

down we don't have any more data now all

I have to do is press enter and I did

this to basically show the nomenclature

now so now we're not only selecting a

range but we're also selecting a range

from a different sheet and this is how

Excel does the nclat or the formula

necessary to make this work and once

again this is a dynamic range appearing

inside of here but we really want to put

it inside of here into this new workbook

so what I'm going to do is I'm going to

actually delete this sheet right here

because we don't need this copy sheet in

here I don't want to actually manipulate

my data at all going to right click it

and select delete it's going to prompt

me any time that hey you're going to

permanently delete a sheet do you want

to continue yeah I want to continue now

once again I'm going to go back to that

original blank sheet that we have I want

to put it into here so I'm actually

going to name this one Jan and then

we'll call this one formula CU

technically it was a formula not a copy

I don't know why I did copy before

anyway back into A1 once again I'll

press that equal sign and then going

back to that other workbook I will

select it the first cell in there which

is actually A1 and now we can see we

have in the formul of the bar which is

actually the front of the bar which is

sort of strange in the other sheet that

our other workbook that we work with we

have inside of brackets the Excel file

name the sheet that we're in and then

the actual uh cell range of A1 we have

dollar signs around this this locks the

references of it which we're going to go

into more detail on but the main thing

to understand is this has A1 selector

right now but we want to select all this

data so that shortcut of control shift

right select all the different columns

and then control shift down okay it's

all selected I'm going to go ahead and

press enter and it's going to take me

back to my original workbook that I was

trying to work with this now that was

using formulas to copy this data we're

going to explore two more options the

second one is going to be somewhat

familiar using copy and paste so I'm

going to create this new sheet I'm going

to call it Jan copy and

paste from here I'm going to go back to

our original data that we have and since

we're at the bottom of the sheet I'm

just going to select the bottom right

hand corner press control shift left now

if you noticed it went and stopped

stopped at this Blank cell right here

which isn't a big deal I'll press it one

more time it'll go to the next cell over

that actually has a value in it and then

once again it's going to go all the way

to the end of a

3103 so basically if there's any blanks

while you're trying to do this it's

going to stop at those values there okay

and then from there I'm going to press

control shift up and as we're saying

it's going to stop at every different

Blank cell along the way this is going

to take forever unfortunately I don't

recommend you actually do that ever again

again

instead start up at the top left and do

the control shift over to the right and

then all the way down in order to select

all the cells now like we did before we

want to copy it I could either use this

up at the top in the home ribbon right

here I could actually select copy or the

shortcut which I'm going to recommend of

contrl c and from there going back into

our new workbook selecting cell A1 and

then using contrl V and pasting all this

data in now moving on to the third

example which is is actually the one I

recommend you do anytime you need to

move sheets of data basically in both of

those previous approaches you could go

about missing getting data to move over

so I don't really recommend doing that

instead I would come down here to the

Jan sheet write click it and select move

or copy so we have this new window that

pops up and it has two book right now it

has this Excel sheet selected of data

job salary monthly we don't want to move

to that we want to move to book two we

also move to a new book but book two is

open that's what we've been working in

that's what we're going move to okay we

can see we have the different sheets

that we've already made in there and it

says in this dialogue this is where you

want to put this before this sheet and

we want at the end so we'll select move

to end now we don't want to take this

sheet Jan out of here we just want a

copy of it so we're going to select this

create a copy and then click okay now JN

has moved over here but I do want to

actually differentiate this so I'm going to

copy now in the next lesson we're going

to be exploring more about the ribbon

but we're going to be exploring now more

about the file menu or also known as

backstage view we've gone through this

home new and open we also have this here

for share this is available for well if

you're sharing it via one drive this

makes it super easy to share with your

co-workers we're not going to go into a

lot of detail but this is a great option

if you're working in one drive and you

want to actually collaborate with other

co-workers you can work on Excel files

at the same time moving down to the list

here we also have get add-ins and we're

going to be actually looking at

different addins we can use in the

advanced chapters whenever we get to

that so we working with some addins with

that next up is info which has over here

on the right hand side some key metadata

about our Excel file itself then if we

want get into actually protecting our

workbook which we're going to cover in a

few chapters down the road you can get

into actually doing that the only other

thing that I find myself doing from time

to time in this section is on version

history once again this requires you to

be using one drive for it but you could

go back and revert back into a previous

version that you work with so it's great

for that now moving into save or even

save as since we haven't saved yes

they're both the same right here I'm

going to go ahead and save this but I

don't want to save this on one drive

personal I'm just going to shave this on

my desktop so I'll come and select

desktop and then I'll name this two

workbooks and save it now Beyond save as

we also have things like print which I

really don't find myself doing that too

often should be sending an electronic

version export if I wanted a pdf version

of something and then finally close as

well same thing as this x up here just a

x out of it and there's two more areas

down here that I want to call out and

that's a count and that allows you to

actually see behind the scenes of what

going on with your Microsoft account and

this is generic to all the different

Microsoft products that you have so not

just Microsoft Excel as you can see from

my information I'm actually inside the

Microsoft 365 Insider program so I get a

lot of access to Insider features get to

experiment with new stuff before any

other people do anyway this is where you

want to come anytime you want to make

sure that you have your Microsoft

products up to dat I have automatic

updates available so even I'm I check to

update now it's going to tell me hey I'm

up to date the other thing to note on

this is the different office themes that

you have on this I'm actually going to

change this right now to use system

settings which on my Mac I use dark

theme so it's going to go to that last

two options are hting down here behind

more I have feedback so if I wanted to

give feedback to this product i'

probably go to something like X or

Twitter instead and then finally options

we'll be getting to options later on in

this but this allows a very much more

advanced features that we can actually

go in and customize using this menu

especially whenever we get into add-ins

we're going to be doing that from here

all right so now you become an expert at

how to manipulate different spreadsheets

or sheets along with manipulating them

between different workbooks in the next

lesson we're going to be going into this

ribbon up here and actually exploring

everything a little bit further and

getting a sneak peek into each one of

these for those that purchase the

practice problems and course notes you

have some practice problems to go

through now and experiment working with

different workbooks with that see you in

the next one where we get into the

there all right this final lesson of the

spreadsheets intro we're going to be

getting into the ribbon inside of Excel

and better understanding what are all

the different tabs and what are the

capabilities by doing some simple

exercises for this we're going to

continue to be analyzing that January

data set that we worked from the last

Lon and we're going to actually get into

actually performing some data analysis

with it so for this lesson you can open

and use that ribbon menu Excel file

which I have right here and all the data

that we're going to be working with are

that January data is in this data tab

along with all the examples and all the

different tabs but I don't need this I'm

not going to work with this so I'm going

to close this out instead I'm going to

be working off where we left from last

time in that two workbooks where we

actually moved over that January data

set now quick disclaimer for any of

these files that you're opening up if

you're noticing the security warning of

automatic updates of links have been

disabled can go ahead and just enable

the content and then click right here on

do not ask me again for network files

and select yes cuz I want to make it a

trusted document now if you're getting

any of these areas that the file has

been moved renamed or deleted cuz mainly

you have it in a different location of

what I had it here's actually the

address of the file that I'm using I

open it up anyway this is the actual

address of where the file is anyway you

can come down here and select these

three dots on the file in question and

just select change Source go into browse

and then from there inside the actual

file itself select where this is so in

this case it's looking for that data set

file with the data job salary monthly

I'm going to select it select okay and

then it's prompting me now that this

link workbook hasn't been refreshed want

to and go ahead and refresh it and it's

going to update it all right close out

of this now anyway that was all s silly

because I'm going to go ahead and delete

this formula one right here and also

this copy and paste tab right here we

only want to keep the Mover copy which

is the actual sheet that we moved over

that has all the data for this lesson

data so let's dive into this Home tab

and this thing has a lot to do with

formatting the text and how things

appear within the spreadsheet for

example I can select all these top rows

right here so basically A1 all the way

to P1 I can change this font size to

something like 12 for the fill color or

the background color I can change it to

something like a light gray right now it

looks like it's already bold I could

turn it off or turn it back on

inspecting all these different columns I

can see that some of it is hidden

especially here this date column I can

see inside of here this is the actual

value but whenever we actually look look

at it from afar like it it has these

Amper sand signs so double clicking on

the edge of that H column right here it

actually expands out and moves it where

it needs to go you can actually do this

for all the column by just selecting all

of them and then double clicking that

last one and then that expands it all

the way we can see that that last column

is well super long so it has all the

different skills typically these titles

up the top I'd like to maintain centered

so that way I know that it's a title but

I could move it to either side also so I

can move it up or down if I wanted to

but we'll leave it right there in the

center as well getting into the number

formatting itself I can actually go and

select something like job post to date

it's going to select that whole column

if I wanted to I can turn this into a

date so in our case I want to do a short

date now other columns I would want to

format are these salary year average and

also salary hour average so besides just

clicking here I can also just select

that hey I want to use this as an

accounting number format and it's going

to automatically put these decimal

places at the end two decimal places

since we're in the 100 thousands I don't

really care about so I'm actually going

to remove them by saying decrease

decimal I'm going to do that twice now

for something like salary hour average

I'm going to also convert this to a

currency but for these these may have

two decimal places of values included in

it so I'm going to leave it now so for

the Styles and cells portion we're going

to be getting into this more especially

into conditional formatting in the

spreadsheets Advanced chapter and

chapter 4 so we'll save that for then

the next thing I want to do is get into

this editing and this is a pretty

powerful feature we can actually sort

and filter our data if we wanted to so

what I'm going to do is actually select

all these cells from P1 all the way to

A1 and then come in here inside of

editing select sord and filter and apply

this filter so let's actually get into

filtering this data specifically I'm

wanting to investigate

jobs or data analyst jobs in the United

States and specifically full-time jobs

we're going to be looking at the salary

data for this so I want to filter it

down for it so I'm going to select here

I'm going to unclick select all and

select data analyst and now it's going

to filter for all the different data

analyst roles there nothing else that's

not there additionally that job schedule

type I want to be looking at full-time

roles only I don't want to include any

other ones so I'll select fulltime I

want the country I don't want to be

skewed by any other countries I live in

the United States so I'm going to then

select United States and then finally I

only want to look at the salary or the

yearly salary data so I can actually

come over here to the salary rate and

select here I only want to look at the

year data okay so now this has

everything in it that I want we're going

to get to analyzing and visualizing this

in a second before that I want to talk

about two other features addins which we

talked about before on how you access to

the file menu you can get to addin via

this and finally analyze data which in

my opinion isn't that strong of a

feature this tab uses a little bit of

artificial intelligence behind the

scenes for you to investigate so it'll

actually provide you different

visualizations that you could actually

visualize out of your data and or even

you can go as far as asking a question

about maybe you want to see hey the

distribution of salary rate or something

like that all you have to do is come

down here and then insert in the chart

that you want to insert in I'm going to

close out of this now we can see that

we've made this salary distribution um

that we maybe want to visualize overall

though I find that this analyzed data is

pretty hit or miss so I'm not using it very

often now the insert tab is where I

spend the second most of my time after

the Home tab they conveniently put in

the correct order there's three major

use cases that I'm using out of this in

chapter 4 on the advanced use of spread

sheets we're going to be going into

tables and then in chapter five we're

going to be going into pivot tables but

even closer to that in chapter 3 we're

going to be going all into depth on how

to use these charts but let's get a

sneak peek into this specifically

remember we filtered this table down to

data analyst jobs in the United States

and specifically full-time roles we want

to visualize this salary year average

column so with column M selected I come

up here to recommend charts and it's

going to give me a visualization of some

well recommended charts now there's only

four here I can also select this other

tab up here on all chart and actually

try to see hey what would this look like

maybe in a pie chart or a bar chart

anyway I want this in a histogram which

we're going to go into more detail on

how to read this later what all have to

do is just come in here double click it

it'll insert it in now notice how

whenever this was created we now have

new tabs appear inside of here

specifically with this selected we have

this chart design and format tab if I

select off of it those tabs disappear and select it again they reappear this

and select it again they reappear this tab allows me to dive in and actually

tab allows me to dive in and actually further customize these visualizations

further customize these visualizations to how I want them to appear I can even

to how I want them to appear I can even move them to let's say a new sheet and I

move them to let's say a new sheet and I can title this something like histogram

can title this something like histogram and then move it the charge Stone always

and then move it the charge Stone always necessarily appear just like that let's

necessarily appear just like that let's actually do a deeper analysis to see

actually do a deeper analysis to see what are the different job title short

what are the different job title short columns available I want to clear all

columns available I want to clear all these different filters on here so I'm

these different filters on here so I'm going to come back up here with this one

going to come back up here with this one row selected come into editing sort in

row selected come into editing sort in filter and I'm going to say hey clear

filter and I'm going to say hey clear all the different filters now selecting

all the different filters now selecting column A going into insert and into

column A going into insert and into recommended charts it's recommended this

recommended charts it's recommended this clustered bar chart which is actually

clustered bar chart which is actually what I want to view so double clicking

what I want to view so double clicking on this this provides me a breakdown of

on this this provides me a breakdown of all the different counts of the

all the different counts of the different job titles within our our data

different job titles within our our data set and we can see things like data

set and we can see things like data scientist engineer and analyst are some

scientist engineer and analyst are some of the highest amount of job postings in

of the highest amount of job postings in this data set now unlike our histogram

this data set now unlike our histogram example this actually provides this data

example this actually provides this data in a pivot table which we're going to be

in a pivot table which we're going to be going into in the pivot table chapter

going into in the pivot table chapter which allows me to further manipulate

which allows me to further manipulate the data so say I want to actually sort

the data so say I want to actually sort this I could rightclick the values right

this I could rightclick the values right here and clict hey sort smallest to

here and clict hey sort smallest to largest and then closing out this pivot

largest and then closing out this pivot table tab right here I can actually see

table tab right here I can actually see what is the highest amount of job

what is the highest amount of job compared to the lowest which is cloud

engineer now there's remaining tabs we're going to be going and hopefully

we're going to be going and hopefully rapid fire in order to cover these as I

rapid fire in order to cover these as I find I'm using these less frequently

find I'm using these less frequently than these other tabs that we previously

than these other tabs that we previously talked about the draw tab allows you to

talked about the draw tab allows you to well draw on your spreadsheet so I can

well draw on your spreadsheet so I can just write on it if I wanted to but I

just write on it if I wanted to but I don't really find myself doing that

don't really find myself doing that except for maybe being I'm building

except for maybe being I'm building dashboards besides that use case is

dashboards besides that use case is pretty rare if I want to end do this

pretty rare if I want to end do this drawing right here I can come up here

drawing right here I can come up here and click undo or I can select contrl Z

and click undo or I can select contrl Z and it'll remove it page layout tab is

and it'll remove it page layout tab is great if you're having to print out any

great if you're having to print out any data for those co-workers that are

data for those co-workers that are living in the past and don't know how to

living in the past and don't know how to accept things digitally you can do

accept things digitally you can do everything from adjusting your page

everything from adjusting your page layout to adjusting the scale that

layout to adjusting the scale that you're actually viewing things now

you're actually viewing things now personally I find myself more using

personally I find myself more using these sheet options right here so if I

these sheet options right here so if I go to this job count tab right here if I

go to this job count tab right here if I wanted to I could turn off the grid

wanted to I could turn off the grid lines on here as you can can see it got

lines on here as you can can see it got white on the background I really like

white on the background I really like that now if I wanted to make sure they

that now if I wanted to make sure they had actual grid lines around my table I

had actual grid lines around my table I come back to the Home tab and for here I

come back to the Home tab and for here I can select borders and from there I want

can select borders and from there I want to put all borders on there so now I

to put all borders on there so now I look like I have this table right here

look like I have this table right here along with my graph super fancy next up

along with my graph super fancy next up is formulas this is where you need to go

is formulas this is where you need to go if you can't remember a function that

if you can't remember a function that maybe you want to use if it's a text

maybe you want to use if it's a text function you come in here select

function you come in here select something like text you can scroll

something like text you can scroll through and actually see even a

through and actually see even a description of of the different

description of of the different functions that are available so in this

functions that are available so in this case replace it tells you hey replace

case replace it tells you hey replace this part of a text string with a

this part of a text string with a different text string depending on what

different text string depending on what version of excel you have and the newer

version of excel you have and the newer ones you'll have this insert python to

ones you'll have this insert python to insert python functions and then finally

insert python functions and then finally they have more advanced features with

they have more advanced features with maintaining and updating and formatting

maintaining and updating and formatting your different formulas and functions

your different formulas and functions which we'll be diving to in the next

which we'll be diving to in the next chapter now besides the home and insert

chapter now besides the home and insert tab the data tab is the next tab that I

tab the data tab is the next tab that I find myself using all the time in

find myself using all the time in chapter 7 we'll be diving into Power

chapter 7 we'll be diving into Power query and we're going to be focusing

query and we're going to be focusing heavily on this getting transform data

heavily on this getting transform data and also queries and connections and

and also queries and connections and then in chapter 8 when we get to power

then in chapter 8 when we get to power pivot we're going to be going into

pivot we're going to be going into managing our data model with power pivot

managing our data model with power pivot in chapter 4 we're going to be going

in chapter 4 we're going to be going into this forecasting and we're also

into this forecasting and we're also going to be adding in some extra add-ins

going to be adding in some extra add-ins that are going to appear in this data

that are going to appear in this data tab now I sort of skipped over the data

tab now I sort of skipped over the data types and sort and filter because we've

types and sort and filter because we've saw them on the Home tab they're just

saw them on the Home tab they're just conveniently located here in bigger

conveniently located here in bigger format for you use also all right this

format for you use also all right this tab on review is probably the least

tab on review is probably the least likely for me to actually use I can

likely for me to actually use I can actually go through and check things

actually go through and check things like spelling and add comments or even

like spelling and add comments or even protect my sheet besides that I'm not

protect my sheet besides that I'm not finding I'm using that this often view

finding I'm using that this often view tab is similar to the review Tab and

tab is similar to the review Tab and that I'm using it a little bit more you

that I'm using it a little bit more you can change the format of how you

can change the format of how you actually want to view things but mainly

actually want to view things but mainly I'm finding myself using this the most

I'm finding myself using this the most of freeze pains let's say you see I'm

of freeze pains let's say you see I'm scrolling down here and I don't know

scrolling down here and I don't know what the job or what the he headers are

what the job or what the he headers are right here so going over to this data

right here so going over to this data tab I can actually come in here to

tab I can actually come in here to freeze panes and select freeze top row

freeze panes and select freeze top row or even freeze First Column so in this

or even freeze First Column so in this case that top row actually stays up

case that top row actually stays up there and I really like it like that now

there and I really like it like that now let's say I want to freeze both the top

let's say I want to freeze both the top row and that First Column there's not

row and that First Column there's not really a selection for that so here's

really a selection for that so here's what you can do you can come over here

what you can do you can come over here to freeze panes and select unfreeze

to freeze panes and select unfreeze paines and then select something like a

paines and then select something like a cell like B2 that means I want

cell like B2 that means I want everything above this and to the left of

everything above this and to the left of it to freeze so now when I select freeze

it to freeze so now when I select freeze panes this upper or top row is actually

panes this upper or top row is actually Frozen and then the actual First Column

Frozen and then the actual First Column is Frozen as well all right final tab is

is Frozen as well all right final tab is help and I'll be honest I think this is

help and I'll be honest I think this is pretty useless if I get stuck with

pretty useless if I get stuck with anything along the way I'm finding

anything along the way I'm finding myself navigating to something like chat

myself navigating to something like chat GPT and it's helping me a lot quicker

GPT and it's helping me a lot quicker than trying to navigate through this

than trying to navigate through this help box that it provides and I'm

help box that it provides and I'm already getting an error message with

already getting an error message with even accessing it so you can see how

even accessing it so you can see how often I even use it

often I even use it then now we've been doing a lot of

then now we've been doing a lot of manual clicking with using the ribbon

manual clicking with using the ribbon and I think a good resource that goes

and I think a good resource that goes with this is shortcuts so if you come

with this is shortcuts so if you come inside of the resources folder we have a

inside of the resources folder we have a Excel file here called Excel shortcuts

Excel file here called Excel shortcuts and what this has in it is a list of all

and what this has in it is a list of all the different shortcuts that I find

the different shortcuts that I find myself using anytime I'm inside of excel

myself using anytime I'm inside of excel so it's worth having all of these I'm

so it's worth having all of these I'm not going to lie committed to memory it

not going to lie committed to memory it looks like a long list but I'm telling

looks like a long list but I'm telling you by the end of this you're going to

you by the end of this you're going to have all of these basically committed to

have all of these basically committed to memory they're going to be timesaver now

memory they're going to be timesaver now although I shed on people that print out

although I shed on people that print out stuff this would be something that I do

stuff this would be something that I do recommend actually printing out and

recommend actually printing out and having next to you so that way you can

having next to you so that way you can reference really quickly while going

reference really quickly while going through this course all right now I know

through this course all right now I know we move fast through that but we're

we move fast through that but we're really going to be diving into as I

really going to be diving into as I called out during this lesson all of

called out during this lesson all of these different tabs even more as we

these different tabs even more as we advance through all the different

advance through all the different chapters that was more of a sneak peek

chapters that was more of a sneak peek into what you're going to be exposed to

into what you're going to be exposed to coming up in this course all right for

coming up in this course all right for those that purchas the practice problems

those that purchas the practice problems you have some problems to go through and

you have some problems to go through and actually experiment more with with the

actually experiment more with with the tabs in the next chapter we're going to

tabs in the next chapter we're going to be jumping into functions and also more

be jumping into functions and also more specifically formulas order to build

specifically formulas order to build them out and form data analysis on that

them out and form data analysis on that data science job posting data set with

data science job posting data set with that I'll see you in the next

one all right welcome to this chapter on formulas and functions in this lesson

formulas and functions in this lesson we're going to be focusing specifically

we're going to be focusing specifically on going a deep dive and understanding

on going a deep dive and understanding formulas then in all the follow on

formulas then in all the follow on lessons this we're going to spend the

lessons this we're going to spend the majority of our time working on

majority of our time working on functions for that we'll be exploring

functions for that we'll be exploring the entire function Library focusing on

the entire function Library focusing on the key functions within this library

the key functions within this library that I find that I'm using time and time

that I find that I'm using time and time again in data analytics so what are we

again in data analytics so what are we going to be doing in this lesson well

going to be doing in this lesson well we're going to be focusing on a

we're going to be focusing on a fictitious data set we're going to keep

fictitious data set we're going to keep it small in order for us to get more

it small in order for us to get more familiar with operating with formulas

familiar with operating with formulas and operating on this data set

and operating on this data set specifically by the end of this we're

specifically by the end of this we're going to be able to input into into this

going to be able to input into into this worksheet a number of years of

worksheet a number of years of experience or total salary and be able

experience or total salary and be able to see whether these jobs meet those

to see whether these jobs meet those conditions specifically me that I meet

conditions specifically me that I meet both of those conditions so for this you

both of those conditions so for this you can follow along by opening that

can follow along by opening that formulas intro workbook in this workbook

formulas intro workbook in this workbook will be staying in this data sheet right

will be staying in this data sheet right here all the different answers when we

here all the different answers when we get to the math operators comparison

get to the math operators comparison operators or cell referencing are shown

operators or cell referencing are shown via that sheet but we'll just be

via that sheet but we'll just be sticking for data for

now first as math operators and as shown by this table here you can use a variety

by this table here you can use a variety of different symbols for to conduct

of different symbols for to conduct different multiplication subtraction

different multiplication subtraction division operations that you want to do

division operations that you want to do so let's dive into testing some of these

so let's dive into testing some of these out we're going to be filling in each of

out we're going to be filling in each of these columns that correlate with the

these columns that correlate with the associated job title as we go through

associated job title as we go through this so the first one's going to be

this so the first one's going to be experience pretty simple right we talked

experience pretty simple right we talked about before in order to reference

about before in order to reference another cell we would use an equal sign

another cell we would use an equal sign and then from there we can either type

and then from there we can either type or select a cell I'm going to recommend

or select a cell I'm going to recommend just typing it to make it go faster C3

just typing it to make it go faster C3 it's highlighted blue because that's the

it's highlighted blue because that's the cell that's highlighted then we'll be

cell that's highlighted then we'll be using the autofill feature of this to

using the autofill feature of this to fill in all the cells below and we

fill in all the cells below and we notice that it updates to here this

notice that it updates to here this one's equal to C12 which correlates to

one's equal to C12 which correlates to this one right to the left of it so

this one right to the left of it so let's calculate our total salary and

let's calculate our total salary and this is going to be taking our annual

this is going to be taking our annual salary in column D and adding it to our

salary in column D and adding it to our bonus Max in column e so we can do this

bonus Max in column e so we can do this by specifying

by specifying D3 plus E3 and from there there pressing

D3 plus E3 and from there there pressing enter once again to autofill it I select

enter once again to autofill it I select that cell that I want and drag it on

that cell that I want and drag it on down now if I want to calculate what is

down now if I want to calculate what is the rate of bonus or the bonus rate that

the rate of bonus or the bonus rate that is going to be the bonus divided by that

is going to be the bonus divided by that salary so in this case E3 / D3 once

salary so in this case E3 / D3 once again going to use autofill drag and

again going to use autofill drag and drop it all the way down now for all

drop it all the way down now for all these values I don't like what it's

these values I don't like what it's formatted as right now I'm actually

formatted as right now I'm actually going to change this to a percentage and

going to change this to a percentage and I want to see one decimal place so I'll

I want to see one decimal place so I'll press this one to expand out one now

press this one to expand out one now anytime I do any type of mathematical

anytime I do any type of mathematical operation in Excel I always want to try

operation in Excel I always want to try to confirm it that it's correct I did

to confirm it that it's correct I did the operation correctly so in the case

the operation correctly so in the case of this bonus rate I can do this by

of this bonus rate I can do this by confirming what we got for total salary

confirming what we got for total salary previously so if we took that bonus rate

previously so if we took that bonus rate is which we want to confirm right so

is which we want to confirm right so we're going to take that and multiply it

we're going to take that and multiply it times our annual salary right so that

times our annual salary right so that should give us that bonus rate right

should give us that bonus rate right there then if we wanted to like we said

there then if we wanted to like we said we want to confirm total salary right

we want to confirm total salary right here so I can just add in that we want

here so I can just add in that we want to also add in that annual salary itself

to also add in that annual salary itself and we do have that total salary right

and we do have that total salary right here to actually confirm what's going on

here to actually confirm what's going on dragging it down and doing an autofill

dragging it down and doing an autofill all these values look like they

all these values look like they correlate to what it should be for total

correlate to what it should be for total salary so I feel we calculate a bonus

salary so I feel we calculate a bonus rate correctly now going back into the

rate correctly now going back into the formula itself you can see we have

formula itself you can see we have multiple operations in here how do we

multiple operations in here how do we know whether multiplication addition

know whether multiplication addition subtraction what comes first well really

subtraction what comes first well really if you know the order of operations it

if you know the order of operations it really is the same here here the

really is the same here here the different operators listed in their

different operators listed in their order of Precedence exponentiation comes

order of Precedence exponentiation comes first multiplication division or second

first multiplication division or second then addition and subtraction are third

then addition and subtraction are third it's Then followed by concatenation

it's Then followed by concatenation which we did in one of the previous

which we did in one of the previous lessons followed by the comparison

lessons followed by the comparison operators which we're about to get

operators which we're about to get to so with that segue here we are

to so with that segue here we are comparison operators

comparison operators for this you probably are familiar with

for this you probably are familiar with the first three the last three are

the first three the last three are something that get a little bit more

something that get a little bit more complicated whenever you have a greater

complicated whenever you have a greater than or equal to less than or equal to

than or equal to less than or equal to or in this case a not equal to so

or in this case a not equal to so previously I just sort of did a cursor

previously I just sort of did a cursor check to make sure this confirmed t

check to make sure this confirmed t total salary column equals this other

total salary column equals this other total salary column but imagine you have

total salary column but imagine you have hundreds of thousands of rows how can we

hundreds of thousands of rows how can we actually compare this and find these

actually compare this and find these values well what we can do is we can say

values well what we can do is we can say hey is G3

hey is G3 equal to I3 this looks a little bit

equal to I3 this looks a little bit confusing right CU you have two equal

confusing right CU you have two equal signs in there but everything to the

signs in there but everything to the right of the equal sign it's basically a

right of the equal sign it's basically a comparison and from there it either ends

comparison and from there it either ends up as a true or a false and we can drag

up as a true or a false and we can drag and autofile this in and everything is

and autofile this in and everything is true similarly if we want to find

true similarly if we want to find something like is the bonus Max greater

something like is the bonus Max greater than the annual salary we can do hey is

than the annual salary we can do hey is bonus Max at E3 greater than that at D3

bonus Max at E3 greater than that at D3 and the typical of any data a science

and the typical of any data a science job none of these really exceed that at

job none of these really exceed that at all all right now that we're familiar

all all right now that we're familiar with math operators and also comparison

with math operators and also comparison operators let's dive deeper into cell

operators let's dive deeper into cell referencing and we've been doing this

referencing and we've been doing this previously whenever we reference another

previously whenever we reference another cell like A2 but we're going to add a

cell like A2 but we're going to add a little twist to this I'm going to go

little twist to this I'm going to go ahead and hide some of these columns

ahead and hide some of these columns that way we clear up the Clutter going

that way we clear up the Clutter going to hide column F by right clicking it

to hide column F by right clicking it and selecting hide then I'm also going

and selecting hide then I'm also going to select all the columns H through k

to select all the columns H through k and also hide them want everything to

and also hide them want everything to appear on the same sheet so we're going

appear on the same sheet so we're going to be referencing this table down here

to be referencing this table down here for this portion of the exercise and

for this portion of the exercise and this is potentially goals that you may

this is potentially goals that you may have when you're trying to land a job

have when you're trying to land a job you may know how many years of

you may know how many years of experience or you should have know how

experience or you should have know how many years of experience you have along

many years of experience you have along with a goal total salary that you want

with a goal total salary that you want to achieve and so we're going to be

to achieve and so we're going to be building out formulas with this in order

building out formulas with this in order to be able to find out which of these

to be able to find out which of these jobs actually meet our conditions of the

jobs actually meet our conditions of the expected years of experience and total

expected years of experience and total salary for so for this we'll go with

salary for so for this we'll go with that I have five years of experience

that I have five years of experience then I'm looking at

then I'm looking at $90,000 the first we want to calculate

$90,000 the first we want to calculate in column L is whether it meets our

in column L is whether it meets our experience so for this we'll say hey is

experience so for this we'll say hey is C15 right here less than or equal to the

C15 right here less than or equal to the value right here in our experience and

value right here in our experience and as expected five is less than or equal

as expected five is less than or equal to basically equal to 5 it's true now

to basically equal to 5 it's true now we're going to run a problem now when we

we're going to run a problem now when we try to autofill this if I try to

try to autofill this if I try to autofill this down I'm getting this one

autofill this down I'm getting this one is false and then these all is true but

is false and then these all is true but I would expect especially this AI

I would expect especially this AI specialist at three it would be false

specialist at three it would be false and so let's actually inspect this well

and so let's actually inspect this well as we can see from this this is

as we can see from this this is referencing well c23 which is way down

referencing well c23 which is way down here but it's still referencing the

here but it's still referencing the correct C11 right here the problem is we

correct C11 right here the problem is we didn't really want this value up here

didn't really want this value up here this C15 to actually change whenever we

this C15 to actually change whenever we went to do the autofill down below it so

went to do the autofill down below it so what we can do here is provide a fixed

what we can do here is provide a fixed reference of that cell in order to do

reference of that cell in order to do this we're going to insert those dollar

this we're going to insert those dollar signs that we saw

signs that we saw previously before the column and then

previously before the column and then also the row so in this case I have C

also the row so in this case I have C locked and I have 15 locked now the

locked and I have 15 locked now the formula itself doesn't change at all but

formula itself doesn't change at all but now when I drag and drop this down all

now when I drag and drop this down all of these are updating correctly as

of these are updating correctly as expected AI specialist is going to be

expected AI specialist is going to be false whenever I actually click on it to

false whenever I actually click on it to inspect it it's still referencing that

inspect it it's still referencing that C15 C11 next we're going to move on to

C15 C11 next we're going to move on to column M of seeing if it meets our

column M of seeing if it meets our salary requirements so for this one

salary requirements so for this one we'll be seeing hey is the salary or

we'll be seeing hey is the salary or total salary in G3 greater than or equal

total salary in G3 greater than or equal to our total salary down here of 90,000

to our total salary down here of 90,000 now we already know we need to lock c16

now we already know we need to lock c16 of this 990,000 because we're going to

of this 990,000 because we're going to be autofilling it down I can manually

be autofilling it down I can manually type in the dollar signs but a shortcut

type in the dollar signs but a shortcut to this is just pressing F4 if you're on

to this is just pressing F4 if you're on a Mac you'll need to press function F4

a Mac you'll need to press function F4 anyway this locks this in so now

anyway this locks this in so now whenever I drag and drop this down as

whenever I drag and drop this down as expected the only other one that's less

expected the only other one that's less than 990,000 is this data analyst rule

than 990,000 is this data analyst rule right here now I want to play with this

right here now I want to play with this just a little bit more so we talked

just a little bit more so we talked about this right here putting a dollar

about this right here putting a dollar sign in front of the column and then a

dollar sign some of the row is a fixed reference they also have what is called

reference they also have what is called a mixed reference so I'm going to go

a mixed reference so I'm going to go ahead and put my cursor right there next

ahead and put my cursor right there next to G3 I'm going to press F4 and it's

to G3 I'm going to press F4 and it's going to do the absolute reference but

going to do the absolute reference but if I press it one more time it's going

if I press it one more time it's going to do a mix reference if you notice

to do a mix reference if you notice there's only a dollar sign in front of

there's only a dollar sign in front of the three or if I press it again there's

the three or if I press it again there's only a dollar sign in front of the G now

only a dollar sign in front of the G now technically this is going to work but

technically this is going to work but fine because we're going to now lock

fine because we're going to now lock this G column for this but it's going to

this G column for this but it's going to allow the three to update so I'm going

allow the three to update so I'm going to show you this now by actually

to show you this now by actually dragging and dropping this down and from

dragging and dropping this down and from there inspecting that last cell contents

there inspecting that last cell contents we can see that that g is locked as

we can see that that g is locked as expected but it moved down now instead

expected but it moved down now instead of locking just the column we could also

of locking just the column we could also lock the rows so I could also do change

lock the rows so I could also do change up c16 now instead and lock the rows of

up c16 now instead and lock the rows of c16 cuz we're going to still stay in

c16 cuz we're going to still stay in that c column right there pressing enter

that c column right there pressing enter now autofill we don't have to just go

now autofill we don't have to just go down we can also go up so inspecting it

down we can also go up so inspecting it locking it didn't really change by only

locking it didn't really change by only locking the row of 16 so let's wrap this

locking the row of 16 so let's wrap this all up by actually def finding out which

all up by actually def finding out which of these actually meet both of our

of these actually meet both of our conditions of 5 years and 990,000 well

conditions of 5 years and 990,000 well it turns out that behind the scenes true

it turns out that behind the scenes true is equal to 1 and Z is equal to false so

is equal to 1 and Z is equal to false so if actually were to take this and add

if actually were to take this and add this true to this true right here we

this true to this true right here we should get two autofilling it all the

should get two autofilling it all the way down we have two1 2 1 so basically

way down we have two1 2 1 so basically confirm that hey zero yeah false is zero

confirm that hey zero yeah false is zero because 0 plus 0 is Zer now I recommend

because 0 plus 0 is Zer now I recommend instead we're going to be going through

instead we're going to be going through and doing L3 * M3 so that way anytime

and doing L3 * M3 so that way anytime either one of these are true they will

either one of these are true they will return a one and now in order to get a

return a one and now in order to get a true or false back on whether it meets

true or false back on whether it meets both we can select that N3 and see hey

both we can select that N3 and see hey is it equal to one type over there equal

is it equal to one type over there equal to one and it evaluates to true so now

to one and it evaluates to true so now I'm going to go ahead and just hide

I'm going to go ahead and just hide these columns so we can actually see

these columns so we can actually see this a little bit better but we can

this a little bit better but we can find values in here that meet our

find values in here that meet our conditions of the 90,000 or 5 years and

conditions of the 90,000 or 5 years and let's say we're doing job searching and

let's say we're doing job searching and it lasts over a year um we have to

it lasts over a year um we have to change this to six this will

change this to six this will automatically update the formulas that

automatically update the formulas that we've used here as shown here so that's

we've used here as shown here so that's our intro to formulas and for me the

our intro to formulas and for me the hardest thing to wrap my head around

hardest thing to wrap my head around when I was first tackling this was

when I was first tackling this was around absolute and mixed references so

around absolute and mixed references so we have some practice problems for those

we have some practice problems for those that purchased the course practice

that purchased the course practice problems in order to go through and test

problems in order to go through and test this out and understanding what happens

this out and understanding what happens whenever you lock the row or lock the

whenever you lock the row or lock the column all right and after that we'll

column all right and after that we'll next be diving into an intro into

next be diving into an intro into formulas which I'll be covering for the

formulas which I'll be covering for the remainder of this chapter with that see

remainder of this chapter with that see you in the next

one for this lesson we're going to be focusing on an intro into functions

focusing on an intro into functions specifically we're going to be going

specifically we're going to be going over all the different functions that

over all the different functions that we're going to be deep diving within

we're going to be deep diving within this chapter itself along with some

this chapter itself along with some common problems you may run into and

common problems you may run into and errors and how to troubleshoot it to do

errors and how to troubleshoot it to do this we'll be continuing on from that

this we'll be continuing on from that data set that we used in the last lesson

data set that we used in the last lesson specifically we'll be calculating things

specifically we'll be calculating things like averages and counts and how many

like averages and counts and how many jobs actually meet our goals and we'll

jobs actually meet our goals and we'll be using functions for this so you can

be using functions for this so you can continue working in that workbook that

continue working in that workbook that you had from last time or open this

you had from last time or open this function intros workbook in this

function intros workbook in this function intros workbook I've gone ahead

function intros workbook I've gone ahead and moved our job goals over here to

and moved our job goals over here to that column RNs and then added in this

that column RNs and then added in this bottom portion right here for the

bottom portion right here for the averages and total counts really you can

averages and total counts really you can do and manipulate as you

want so why use functions let's look at a couple quick examples on the

a couple quick examples on the importance of these things let's say we

importance of these things let's say we wanted to get the average of each one of

wanted to get the average of each one of these Columns of experience annual

these Columns of experience annual salary and bonus Max previously we know

salary and bonus Max previously we know we can actually reference each one of

we can actually reference each one of these cells to calculate the average we

these cells to calculate the average we wanted to do that we would have to

wanted to do that we would have to actually add up all the values so I have

actually add up all the values so I have to go through select C3 C4 all the way

to go through select C3 C4 all the way down to

down to C12 and we would need to divide it by

C12 and we would need to divide it by that total number of 1 2 3 4 5 6 7 8 9

that total number of 1 2 3 4 5 6 7 8 9 10 in that case we' get the average also

10 in that case we' get the average also that me count that 10 wasn't necessarily

that me count that 10 wasn't necessarily perfect so I don't really recommend

perfect so I don't really recommend doing this but anyway nonetheless we can

doing this but anyway nonetheless we can actually do autofill to calculate the

actually do autofill to calculate the averages as the is as well as it

averages as the is as well as it automatically update the referencing

automatically update the referencing correctly to it but I don't recommend

correctly to it but I don't recommend doing that instead I recommend using

doing that instead I recommend using functions specifically we can use

functions specifically we can use something like the average function as

something like the average function as soon as I start typing a function a in

soon as I start typing a function a in this case all the functions that have

this case all the functions that have the a name pop up if I wanted to well I

the a name pop up if I wanted to well I do know I want average right here I can

do know I want average right here I can select it it provides a brief statement

select it it provides a brief statement of what it's actually going to do and

of what it's actually going to do and then I can doubleclick it to insert it

then I can doubleclick it to insert it below here it actually specifies what's

below here it actually specifies what's going on with this function here and

going on with this function here and specifically to provides me to hey

specifically to provides me to hey provide in these numbers now I could

provide in these numbers now I could select these number by number as we can

select these number by number as we can see that there's in Brackets here this

see that there's in Brackets here this number two that means it's an optional

number two that means it's an optional parameter but instead what we'll do is

parameter but instead what we'll do is we'll just provide a range providing it

we'll just provide a range providing it from C3 all the way to C12 in that case

from C3 all the way to C12 in that case I got 5.3 similar to above and then

I got 5.3 similar to above and then dragging this over we can get all the

dragging this over we can get all the other values as well as a quick example

other values as well as a quick example also previously we had made this sort of

also previously we had made this sort of convoluted formula in order to calculate

convoluted formula in order to calculate calate whether we met both conditions of

calate whether we met both conditions of mean our experience and also our salary

mean our experience and also our salary which we're specified over here well

which we're specified over here well there's actually a formula for that and

there's actually a formula for that and it's called the and formula and what it

it's called the and formula and what it takes for its arguments are logical

takes for its arguments are logical values so it can take a logical one for

values so it can take a logical one for the first parameter I can specify L3 and

the first parameter I can specify L3 and then for the second parameter I can

then for the second parameter I can specify M3 and notice how this second

specify M3 and notice how this second parameter now highlights or becomes more

parameter now highlights or becomes more bold as I put it in so you can keep

bold as I put it in so you can keep track of where you are in the formula

track of where you are in the formula any I'm going to close the parenthesis

any I'm going to close the parenthesis press enter and it evaluates to True

press enter and it evaluates to True dragging it all down these should match

dragging it all down these should match these other ones and yeah this is

these other ones and yeah this is definitely something I'd use over these

definitely something I'd use over these formulas that I've used

before so let's dive into this formula tab more and understand the capabilities

tab more and understand the capabilities that we're going to be carrying out the

that we're going to be carrying out the next lessons in this chapter the most

next lessons in this chapter the most powerful of these especially for those

powerful of these especially for those new to excel is this insert function

new to excel is this insert function anytime you're looking for a function

anytime you're looking for a function and maybe can't can't recall the name

and maybe can't can't recall the name and you're not sure what even starts

and you're not sure what even starts with you can put something in here so

with you can put something in here so say I wanted maybe the average I can

say I wanted maybe the average I can type in average and then everything that

type in average and then everything that basically calculates a different average

basically calculates a different average off of it even if they're closely

off of it even if they're closely related like this rank average will pop

related like this rank average will pop up in here along with a description

up in here along with a description below explaining it if you've used a

below explaining it if you've used a formula recently you can come in here

formula recently you can come in here under recently used and I frequently

under recently used and I frequently find myself just going back to this in

find myself just going back to this in order to select something I may have

order to select something I may have used recently now in the next seven

used recently now in the next seven lessons we're going to be diving into

lessons we're going to be diving into each one of these all the way through it

each one of these all the way through it from logical and text to look up and

from logical and text to look up and also math and trick now one note we

also math and trick now one note we won't be going into detail on this

won't be going into detail on this financial functions because I find

financial functions because I find they're sort of nuanced but we will be

they're sort of nuanced but we will be going into all the different ones that

going into all the different ones that I'm using on a daily basis as a data

I'm using on a daily basis as a data analyst that aren't specific to

analyst that aren't specific to financial

applications so let's get into understanding the basics about formulas

understanding the basics about formulas by calculating these different counts

by calculating these different counts and especially counts around whether any

and especially counts around whether any of these jobs meet our goals for this I

of these jobs meet our goals for this I know I want to use a count function so

know I want to use a count function so I'm going to go to this insert function

I'm going to go to this insert function I'm going to type in count now there's a

I'm going to type in count now there's a bunch of different ones that pop up

bunch of different ones that pop up count itself just counts the number of

count itself just counts the number of cells in a Range that contain numbers it

cells in a Range that contain numbers it has to have numbers in it if I wanted to

has to have numbers in it if I wanted to do something more around text I would

do something more around text I would say hey count the number of cells in

say hey count the number of cells in range that are not empty I could do even

range that are not empty I could do even do something conversely of counting the

do something conversely of counting the number of blank cells for us we want to

number of blank cells for us we want to actually do count so as we showed before

actually do count so as we showed before I'm just going to come in type count

I'm just going to come in type count it's going to prompt me that I need to

it's going to prompt me that I need to at least put at minimum a value and I

at least put at minimum a value and I want to count all these cells here so

want to count all these cells here so using autofill to fill it over um we can

using autofill to fill it over um we can see that all the different values are 10

see that all the different values are 10 nothing really spectacular here but now

nothing really spectacular here but now let's get into a pretty unique use case

let's get into a pretty unique use case of count so in this scenario that I'm

of count so in this scenario that I'm count trying to calculate in cell c16

count trying to calculate in cell c16 I'm trying to find out how many jobs

I'm trying to find out how many jobs above here in these 10 right here how

above here in these 10 right here how many meet our goal of less than or equal

many meet our goal of less than or equal to 5 years and I want to count the

to 5 years and I want to count the number of these so I know I want a type

number of these so I know I want a type of count I can go into insert function I

of count I can go into insert function I know it's here inside these different

know it's here inside these different statistical functions specifically I

statistical functions specifically I have these different counts right here

have these different counts right here and I'm going to scroll over this count

and I'm going to scroll over this count if right here and it's going to provide

if right here and it's going to provide me a description it says Hey counts the

me a description it says Hey counts the number of cells Within range that meet

number of cells Within range that meet the given condition and that's what we

the given condition and that's what we want to do we want to meet a condition

want to do we want to meet a condition of a certain amount of experience now it

of a certain amount of experience now it provides this box in order to help me

provides this box in order to help me input in these values so for the range

input in these values so for the range here what I can do is specify hey I want

here what I can do is specify hey I want to count inside of here if they meet a

to count inside of here if they meet a certain criteria and just going back to

certain criteria and just going back to that range right here we can see that it

that range right here we can see that it already input all those different values

already input all those different values into an array likee object okay so the

into an array likee object okay so the criteria right now is NX want to put

criteria right now is NX want to put something in here I can also press this

something in here I can also press this box and it'll make it disappear and I

box and it'll make it disappear and I want to compare it to this experience

want to compare it to this experience but I want it to be less than or equal

but I want it to be less than or equal to five so I can press enter to accept

to five so I can press enter to accept it but the problem is it's going to

it but the problem is it's going to evaluate whether five is any of these

evaluate whether five is any of these columns here and right now we see that

columns here and right now we see that there are two I'm going go ahead and

there are two I'm going go ahead and close up so we can see this better right

close up so we can see this better right now we can see that there's two fives in

now we can see that there's two fives in here that's not what we we want we want

here that's not what we we want we want to see everything that is less than or

to see everything that is less than or equal to 5 so instead what we need to

equal to 5 so instead what we need to put in here is less than or equal to 5

put in here is less than or equal to 5 now I'm going to press enter and we're

now I'm going to press enter and we're going to get an error this is pretty

going to get an error this is pretty common whenever you are manipulating

common whenever you are manipulating different formulas and you have in this

different formulas and you have in this case I have this less than or equal to

case I have this less than or equal to right here so Excel is confused by this

right here so Excel is confused by this what we need to do is actually put

what we need to do is actually put parentheses around this which basically

parentheses around this which basically sort of makes it into a string or text

sort of makes it into a string or text if you will but now it knows hey I want

if you will but now it knows hey I want you to look for less than or equal to 5

you to look for less than or equal to 5 I want you to evaluate this entire thing

I want you to evaluate this entire thing pressing enter bam we have six values

pressing enter bam we have six values here that are less than or equal to five

here that are less than or equal to five now similarly I can drag this over

now similarly I can drag this over because we want to also do this for

because we want to also do this for experience but I don't want to do less

experience but I don't want to do less than or equal to five I want to do

than or equal to five I want to do greater than or equal to

greater than or equal to 90,000 and in this case we have nine cuz

90,000 and in this case we have nine cuz we only have have one that's less than

we only have have one that's less than this but as you find out on this course

this but as you find out on this course I don't like hardcoding values into my

I don't like hardcoding values into my formulas in this case I have five inside

formulas in this case I have five inside of here but I'm already having five

of here but I'm already having five right here what happens if I want to

right here what happens if I want to change this maybe to say something like

change this maybe to say something like three well it's not going to actually

three well it's not going to actually update these values right here so I'm

update these values right here so I'm going to go ahead and actually change

going to go ahead and actually change that back to five and we're going to

that back to five and we're going to make another formula that actually fixed

make another formula that actually fixed this so I want to drag these down but we

this so I want to drag these down but we actually didn't lock either one of the

actually didn't lock either one of the these cells and it will cause errors if

these cells and it will cause errors if we do so I'll just select right next to

we do so I'll just select right next to it press F4 next to C3 I'll do the same

it press F4 next to C3 I'll do the same of f4 doing the same in this cell as

of f4 doing the same in this cell as well all right now I'll take this and

well all right now I'll take this and I'll drag this down so now let's

I'll drag this down so now let's actually fix this to be more Dynamic we

actually fix this to be more Dynamic we don't want it to be less than or equal

don't want it to be less than or equal to this five right now what we can do is

to this five right now what we can do is that Amper sand operator and then from

that Amper sand operator and then from there put in reference to S3 which

there put in reference to S3 which contains our five pressing enter bam we

contains our five pressing enter bam we got six same thing here I can delete

got six same thing here I can delete that 90,000 put in an Amper sand and

that 90,000 put in an Amper sand and then from there we're going to be

then from there we're going to be basically putting it to mashing it

basically putting it to mashing it together with that 90,000 and it

together with that 90,000 and it evaluates now when we change this

evaluates now when we change this experience to say something like two we

experience to say something like two we can see that it actually updates

can see that it actually updates appropriately to see that oh only one

appropriately to see that oh only one job meets this requirement so pretty

job meets this requirement so pretty cool I'm going change that back to

cool I'm going change that back to five now frequently you're going to run

five now frequently you're going to run into errors with your formulas let's say

into errors with your formulas let's say I wanted to divide one by zero not a

I wanted to divide one by zero not a good thing that we need to do anyway I'm

good thing that we need to do anyway I'm going to get this error right now you

going to get this error right now you can notice it because it has this green

can notice it because it has this green check on the upper left hand corner but

check on the upper left hand corner but also it starts with this hashtag and

also it starts with this hashtag and it's saying hey you have a divide by

it's saying hey you have a divide by zero error I can even come down into

zero error I can even come down into here and it tells me even more on this

here and it tells me even more on this provides help on this or if I wanted to

provides help on this or if I wanted to even ignore it now in this sheet of this

even ignore it now in this sheet of this work workbook I have a bunch of

work workbook I have a bunch of different errors in here that you may

different errors in here that you may run into from time to time again and

run into from time to time again and we're going to be running into these

we're going to be running into these errors as we go through the rest of this

errors as we go through the rest of this chapter so if you get stuck along the

chapter so if you get stuck along the way while we're going through this I

way while we're going through this I feel like this is a good reference for

feel like this is a good reference for you to maybe save somewhere in order to

you to maybe save somewhere in order to understand what is going on with the

understand what is going on with the different errors you may encounter now

different errors you may encounter now the biggest time saer I've found with

the biggest time saer I've found with any of these errors is using some sort

any of these errors is using some sort of chatbot specifically me I'm going to

of chatbot specifically me I'm going to go to something like chat GPT or even

go to something like chat GPT or even claw they're going to be able to provide

claw they're going to be able to provide really quick help in understanding what

really quick help in understanding what an error is and what I need to do to fix

an error is and what I need to do to fix it all right so now it's your turn to

it all right so now it's your turn to dive into and test Out These intro into

dive into and test Out These intro into functions and play with them and

functions and play with them and experience some of the errors of your

experience some of the errors of your own after that we'll be diving into

own after that we'll be diving into logical functions a major type of

logical functions a major type of function that you need to be aware of

function that you need to be aware of with that I'll see you in the next

one now that we have the basics down on formulas and also functions we're going

formulas and also functions we're going to be moving into one of the most

to be moving into one of the most important typ of functions to know

important typ of functions to know logical ones the most popular of these

logical ones the most popular of these are an if condition basically looking at

are an if condition basically looking at something and then providing a response

something and then providing a response based on it so for this analysis we're

based on it so for this analysis we're going to be jumping into our data

going to be jumping into our data science job salary data set but we're

science job salary data set but we're only going to focus on the first 20 rows

only going to focus on the first 20 rows of it here and on the next few lessons

of it here and on the next few lessons as well as I don't want to overwhelm you

as well as I don't want to overwhelm you with the all the data just yet now for

with the all the data just yet now for the final results we're going to be

the final results we're going to be doing two major things the first is

doing two major things the first is determining within this list of jobs

determining within this list of jobs whether they meet our conditions of

whether they meet our conditions of finding the job we want of a data

finding the job we want of a data analyst or business analyst and will

analyst or business analyst and will Market not desired or Ro desired

Market not desired or Ro desired additionally we're going to do a common

additionally we're going to do a common practice and analytics of bucketing

practice and analytics of bucketing basically taking those salaries and

basically taking those salaries and depending on the amount value putting it

depending on the amount value putting it into a certain bucket for us we're going

into a certain bucket for us we're going to be looking at whether they have

to be looking at whether they have salary data in this data set or more

salary data in this data set or more specifically if they are greater than

specifically if they are greater than our goal of 85,000

so why are these logical functions needed well let's jump into that last

needed well let's jump into that last data set real quick and simplify how we

data set real quick and simplify how we can actually use these as a quick

can actually use these as a quick example previously in this P column we

example previously in this P column we were evaluating whether they met both of

were evaluating whether they met both of our conditions of experience or salary

our conditions of experience or salary we can use an if statement in order to

we can use an if statement in order to clarify this so I can specifically call

clarify this so I can specifically call out with an if statement saying if it

out with an if statement saying if it has The Logical test that we want to

has The Logical test that we want to actually evaluate so I'm going to put in

actually evaluate so I'm going to put in P3 in this case as it's going to return

P3 in this case as it's going to return true or false and then from there the

true or false and then from there the next value in there is value if true

next value in there is value if true which what do we want to return if it is

which what do we want to return if it is true well that our goal is met and then

true well that our goal is met and then if it's not met we want to have well not

if it's not met we want to have well not met okay and then this whenever we drag

met okay and then this whenever we drag this down will provide not met or goal

this down will provide not met or goal met depending on if this is true or

met depending on if this is true or false and so that's the power of these

false and so that's the power of these if statements in helping us actually

if statements in helping us actually provide this

value so that was just a quick example of if let's actually jump into some more

of if let's actually jump into some more examples so you get more familiar with

examples so you get more familiar with how to use this so here we are in this

how to use this so here we are in this data set and I don't need all the

data set and I don't need all the columns of this data set so I'm just

columns of this data set so I'm just going to select the columns that I don't

going to select the columns that I don't need I'm going select B through G and

need I'm going select B through G and then hide it additionally I'm not going

then hide it additionally I'm not going to need I or J so I'll hide these as

to need I or J so I'll hide these as well so our first goal is to identify

well so our first goal is to identify whether these jobs meter conditions of

whether these jobs meter conditions of either a data analyst or a business

either a data analyst or a business analyst we're going to start simple by

analyst we're going to start simple by just finding out which one is a data

just finding out which one is a data analyst first and then which one is a

analyst first and then which one is a business analyst and meets those

business analyst and meets those conditions so once again we'll start

conditions so once again we'll start with that if condition and for this

with that if condition and for this we're going to put in that logical test

we're going to put in that logical test remember pretty the example we need to

remember pretty the example we need to have a return either true or false so

have a return either true or false so we're wanting to check whether senior

we're wanting to check whether senior data engineer in A2 is equal to data

data engineer in A2 is equal to data analyst in K1 now we're going to be

analyst in K1 now we're going to be autofilling this down so we need to make

autofilling this down so we need to make sure that the A2 we're fine with it

sure that the A2 we're fine with it actually adjusting as necessary K1 we

actually adjusting as necessary K1 we want it to lock at least lock on the row

want it to lock at least lock on the row value of one then if it's true we'll be

value of one then if it's true we'll be roll desired and if it's not it's not

roll desired and if it's not it's not desired as expected senior data engineer

desired as expected senior data engineer is not desired let's drag this all the

is not desired let's drag this all the way down and just double checking it we

way down and just double checking it we see that the data analyst roles are R

see that the data analyst roles are R desired okay so I can drag this over now

desired okay so I can drag this over now and just to double check it shifted over

and just to double check it shifted over to B2 but it's still but it's selecting

to B2 but it's still but it's selecting a right one of L1 so actually what I'm

a right one of L1 so actually what I'm going to do is I'm going to delete this

going to do is I'm going to delete this go back up here I'm sort of a

go back up here I'm sort of a perfectionist I'm going to end up

perfectionist I'm going to end up locking that a value so it stays in that

locking that a value so it stays in that a column none my values are going to

a column none my values are going to change here and then when I actually

change here and then when I actually drag it over I can check that okay A2 is

drag it over I can check that okay A2 is the correct one I once selected to

the correct one I once selected to compare it to business analyst in

compare it to business analyst in L1 okay then I'm going to autofill all

L1 okay then I'm going to autofill all the way down looks like there's only two

the way down looks like there's only two business analyst roles here so now how

business analyst roles here so now how can we identify that it meets both of

can we identify that it meets both of those conditions both data analyst and a

those conditions both data analyst and a business analyst well we're going to do

business analyst well we're going to do one approach first and it's called a

one approach first and it's called a nested if statement and it's not really

nested if statement and it's not really the approach I'm going to recommend but

the approach I'm going to recommend but it's something that you should be aware

it's something that you should be aware of so what I'm going to do is I'm going

of so what I'm going to do is I'm going to select cell K2 I'm going to go ahead

to select cell K2 I'm going to go ahead and copy this formula plugging it in

and copy this formula plugging it in here we have it here and making sure

here we have it here and making sure that it operates correctly yep it does

that it operates correctly yep it does so how does this nested if statement

so how does this nested if statement work well we're going to still evaluate

work well we're going to still evaluate our first condition is the first role

our first condition is the first role evaluated as data analyst does it meet

evaluated as data analyst does it meet that if it is we want to mark it as rule

that if it is we want to mark it as rule desired now we get into what happens if

desired now we get into what happens if it's not a data analyst well now we want

it's not a data analyst well now we want to now check if it's a business analyst

to now check if it's a business analyst so I'm going to close out this and what

so I'm going to close out this and what we can do is I'm going to take this

we can do is I'm going to take this business analyst formula right here

business analyst formula right here everything up to the if and I'm going to

everything up to the if and I'm going to go back in here and I'm going to drop it

go back in here and I'm going to drop it in right here inside of the value if

in right here inside of the value if false so it's an nested if statement an

false so it's an nested if statement an if inside of another if so now if we

if inside of another if so now if we don't meet this first condition of the

don't meet this first condition of the value if isn't true it will go into the

value if isn't true it will go into the nested if statement and start checking

nested if statement and start checking this condition is now the software data

this condition is now the software data engineer equal to data analyst if it is

engineer equal to data analyst if it is it's R desired if not it's not desired

it's R desired if not it's not desired so let's now drag and drop this all the

so let's now drag and drop this all the way down I'm going to expand this out a

way down I'm going to expand this out a little bit and now we can see if it's

little bit and now we can see if it's data analyst we get rule desired along

data analyst we get rule desired along now with if it's business analyst also R

desired but I'm not a fan of nessf as they're hard to read instead I like

they're hard to read instead I like using the functions of and and or and

using the functions of and and or and should be a little bit familiar because

should be a little bit familiar because we saw it from the intro lessons that we

we saw it from the intro lessons that we did previously with and it evaluates

did previously with and it evaluates whether both conditions are true so in

whether both conditions are true so in this case I'll put in condition one of

this case I'll put in condition one of B3 and then condition two of C E3 and

B3 and then condition two of C E3 and both conditions are true so it satisfies

both conditions are true so it satisfies as true dragging this all down in all

as true dragging this all down in all the following condition cases they're

the following condition cases they're not true for both conditions so

not true for both conditions so therefore it evaluates as false in or it

therefore it evaluates as false in or it checks whether condition one or

checks whether condition one or condition two is true and then will

condition two is true and then will return true so inputting in the

return true so inputting in the conditions of B3 and C3 one of the

conditions of B3 and C3 one of the conditions here are true actually both

conditions here are true actually both are dragging it down I expect yeah the

are dragging it down I expect yeah the second and third rows are also true

second and third rows are also true where the final one both are false so

where the final one both are false so therefore it is false so let's run the

therefore it is false so let's run the same Andor logic that we've run before

same Andor logic that we've run before in order to determine which one we

in order to determine which one we actually use so in this one we're

actually use so in this one we're checking whether both of these jobs of

checking whether both of these jobs of data analyst and business analyst are

data analyst and business analyst are equal to this one here senior data

equal to this one here senior data engineer as expected false and what

engineer as expected false and what should we should expect for all of these

should we should expect for all of these all of them are false because none of

all of them are false because none of these are going to be both data analyst

these are going to be both data analyst and business analyst so as you can

and business analyst so as you can probably guess or it's probably going to

probably guess or it's probably going to be the one that's going to work for us

be the one that's going to work for us we're evaluating whether either data

we're evaluating whether either data anal or business analyst are going to

anal or business analyst are going to match up to that value of senior data

match up to that value of senior data engineer in this case we're getting

engineer in this case we're getting those tree values for data analyst and

those tree values for data analyst and True Values for business analyst so now

True Values for business analyst so now we're going to put that or function

we're going to put that or function inside of that if for The Logical test

inside of that if for The Logical test and from there we can determine whether

and from there we can determine whether it's rule desired not desired dragging

it's rule desired not desired dragging all down all of it's matching as

all down all of it's matching as expected okay I'm going to go ahead and

expected okay I'm going to go ahead and hide these

rows so now what happens if we don't want just a evaluate for a true or false

want just a evaluate for a true or false condition basically we want to evaluate

condition basically we want to evaluate for multiple different conditions well

for multiple different conditions well that's going to be something that comes

that's going to be something that comes up if you need to ever bucket data which

up if you need to ever bucket data which we're going to be doing with salaries

we're going to be doing with salaries now for this first one we're going to

now for this first one we're going to just use a simple if statement we want

just use a simple if statement we want to determine whether a salary is greater

to determine whether a salary is greater than 85,000 or if it's not we want to

than 85,000 or if it's not we want to just specify that the salary is low so

just specify that the salary is low so for this we're going to be evaluating if

for this we're going to be evaluating if H2 we're going to go ahead and lock that

H2 we're going to go ahead and lock that H column is greater than that 85,000

H column is greater than that 85,000 which will lock that completely for the

which will lock that completely for the 85,000 then we want to say the salary is

85,000 then we want to say the salary is greater than 85,000 conversely if it

greater than 85,000 conversely if it doesn't meet this we want to say that

doesn't meet this we want to say that the salary is low I'm going to expand

the salary is low I'm going to expand this out a little bit and then we're

this out a little bit and then we're going to drag this down as expected we

going to drag this down as expected we have the values returning those are

have the values returning those are 85,000 and then this one at 35,000 it is

85,000 and then this one at 35,000 it is Mark is low now the problem we're

Mark is low now the problem we're running into and why we need multiple

running into and why we need multiple conditions is this is the salary is low

conditions is this is the salary is low but there's actually no data there we

but there's actually no data there we need specify in these conditions that

need specify in these conditions that well there's no data so for this we can

well there's no data so for this we can use an ifs formula and what happens with

use an ifs formula and what happens with this is you provide a test and then a

this is you provide a test and then a value if true and that's just the first

value if true and that's just the first one we can then provide another logical

one we can then provide another logical test and the value of true so the first

test and the value of true so the first thing I'm going to test is if there is

thing I'm going to test is if there is no value there I'm going to go ahead and

no value there I'm going to go ahead and lock that H column as well and when I'm

lock that H column as well and when I'm looking for a blank I'm just going to

looking for a blank I'm just going to put in two quot Mark say signifying that

put in two quot Mark say signifying that it's blank and the value of true is no

it's blank and the value of true is no data okay put another comma we can see

data okay put another comma we can see we now we're on to logical test number

we now we're on to logical test number two the next thing we want to test is if

two the next thing we want to test is if it's greater than 85,000 so we'll see H2

it's greater than 85,000 so we'll see H2 again locking that H and we want send it

again locking that H and we want send it if it's greater than or equal to that

if it's greater than or equal to that 85,000 which will lock if it is we want

85,000 which will lock if it is we want to return back that salary is greater

to return back that salary is greater than

than 85k and finally we're on to the final

85k and finally we're on to the final logical test and basically we want all

logical test and basically we want all of them to pass this condition so

of them to pass this condition so instead of providing hey salary less

instead of providing hey salary less than 85,000 we're just going to pass in

than 85,000 we're just going to pass in true because we want it to be true and

true because we want it to be true and we would expect this to be any values

we would expect this to be any values between a number that are between 0 and

between a number that are between 0 and 85,000 so like before we're going to

85,000 so like before we're going to specify salary low running this we going

specify salary low running this we going to expand this out and then drag this

to expand this out and then drag this down we have when it returns no data no

down we have when it returns no data no data salary less than 85,000 return

data salary less than 85,000 return salary low and then whenever it's

salary low and then whenever it's greater than 85 the correct results now

greater than 85 the correct results now if s functions are one of the more

if s functions are one of the more complex functions to work with so you do

complex functions to work with so you do need some practice with this like for

need some practice with this like for those that purchased course practice

those that purchased course practice problems you have some now to go into

problems you have some now to go into and actually try this out manipulate and

and actually try this out manipulate and better understand how to work with this

better understand how to work with this with that in the next one we're going to

with that in the next one we're going to be jumping into my next favorite type of

be jumping into my next favorite type of functions math functions which heavily

functions math functions which heavily used in data analytics all right with

used in data analytics all right with that I'll see you in the next one

now in this lesson we're going to be using math functions and also some

using math functions and also some statistical functions in order to

statistical functions in order to perform Eda or exploratory data analysis

perform Eda or exploratory data analysis on our job posting data set and for this

on our job posting data set and for this we're going to be focusing on the five

we're going to be focusing on the five major functions of count sum average and

major functions of count sum average and also Min and Max and we're not only

also Min and Max and we're not only going to focus on the core versions such

going to focus on the core versions such as just count but also the if an ifs

as just count but also the if an ifs version so they have multiple different

version so they have multiple different versions that we're going to get to now

versions that we're going to get to now for our analysis we're going to be

for our analysis we're going to be diving into the full data set of the

diving into the full data set of the data science job postings which has over

data science job postings which has over 30,000 different job postings and in it

30,000 different job postings and in it we're going to be specifically diving

we're going to be specifically diving into data jobs that are in the United

into data jobs that are in the United States for data analyst and we're going

States for data analyst and we're going to be able to use these sort of

to be able to use these sort of different functions that incorporate if

different functions that incorporate if and ifs in order to fine-tune in what

and ifs in order to fine-tune in what we're looking for one quick note you're

we're looking for one quick note you're not limited to using un States and data

not limited to using un States and data analyst you can use the scenario that

analyst you can use the scenario that you're in of what country you're in and

you're in of what country you're in and what job title you're most interested in

instead so we're going to be filling out this table right here and we're going to

this table right here and we're going to start on Row three focusing on those

start on Row three focusing on those count functions first now the data set

count functions first now the data set is actually much larger than this three

is actually much larger than this three columns I actually I'll unhide between a

columns I actually I'll unhide between a through K but we're not using any of

through K but we're not using any of these columns in between here so I'm

these columns in between here so I'm just hiding that them and making it

just hiding that them and making it easier for us to work with for this

easier for us to work with for this we're going to focus on the core

we're going to focus on the core function of only count and we're going

function of only count and we're going to be looking at those that have all the

to be looking at those that have all the yearly salary data in it as you can see

yearly salary data in it as you can see over here that there's missing blanks in

over here that there's missing blanks in here so we don't want to count those

here so we don't want to count those that are missing anyway what I'm going

that are missing anyway what I'm going to do here is Select column M and as you

to do here is Select column M and as you knew it selects the range of M colon M

knew it selects the range of M colon M and then from there press enter so what

and then from there press enter so what we're finding is that around 22,000 jobs

we're finding is that around 22,000 jobs out of these 30,000 we're going to find

out of these 30,000 we're going to find out have salary data and how do I know

out have salary data and how do I know about that 30,000 well let's actually

about that 30,000 well let's actually see we can actually use instead we can

see we can actually use instead we can use a count a function which stands for

use a count a function which stands for count all and it counts the number of

count all and it counts the number of cells in a Range that are not empty

cells in a Range that are not empty specifically I want to capture those in

specifically I want to capture those in the job title short column right here so

the job title short column right here so I'll do a colon alen running this we get

I'll do a colon alen running this we get to see that it's around 32,000 jobs One

to see that it's around 32,000 jobs One technical note before we continue these

technical note before we continue these are since we're doing the columns

are since we're doing the columns themselves in this case the count M it's

themselves in this case the count M it's also counting that column header in this

also counting that column header in this case so if we want to be exactly

case so if we want to be exactly accurate which in this case I just need

accurate which in this case I just need roundabout numbers if we want to be

roundabout numbers if we want to be exactly accurate technically we would

exactly accurate technically we would want to go in and S say subtract one to

want to go in and S say subtract one to get what the actual value is but frankly

get what the actual value is but frankly I'm just trying to look at General

I'm just trying to look at General numbers right now I'm not too car about

numbers right now I'm not too car about one or two off so now let's dive into

one or two off so now let's dive into analyzing this further on my needs

analyzing this further on my needs looking for specifically focus on the

looking for specifically focus on the United States first so we're going to

United States first so we're going to find those that have in the job country

find those that have in the job country here United States and for this we're

here United States and for this we're going to use the count if function and

going to use the count if function and this counts the number of cells within a

this counts the number of cells within a range that meets the given condition so

range that meets the given condition so you provided a range in this case we're

you provided a range in this case we're going to provide the range of that

going to provide the range of that column K and then the criteria itself we

column K and then the criteria itself we want to filter for United States which I

want to filter for United States which I conveniently typed above so we'll select

conveniently typed above so we'll select it right there I'm also going to lock it

it right there I'm also going to lock it by pressing F4

by pressing F4 and then running this we get that about

and then running this we get that about 25,000 jobs contain United States so now

25,000 jobs contain United States so now let's evaluate those data analyst jobs

let's evaluate those data analyst jobs using that same thing of ctif once again

using that same thing of ctif once again we provide the range in this case we're

we provide the range in this case we're looking at that job title short column

looking at that job title short column and for this we want to look for data

and for this we want to look for data analyst locking this cell we get about

analyst locking this cell we get about 9600 jobs for data analyst now next up

9600 jobs for data analyst now next up we're going to be using count ifs

we're going to be using count ifs specifically we're doing this because we

specifically we're doing this because we want to find jobs that contain not only

want to find jobs that contain not only data an but also contain that they're

data an but also contain that they're from the United States now we can't just

from the United States now we can't just add these two columns together because

add these two columns together because one it's going to as we once we add it

one it's going to as we once we add it up we see that's even greater than all

up we see that's even greater than all the jobs there that's not what we

the jobs there that's not what we actually want we want conditions like

actually want we want conditions like here on row 16 where it's a data analyst

here on row 16 where it's a data analyst and United States whereas something here

and United States whereas something here on roow 223 where it's a data analyst in

on roow 223 where it's a data analyst in s that's not going to meet our condition

s that's not going to meet our condition so we wouldn't count it so using count

so we wouldn't count it so using count ifs this counts the number of cells

ifs this counts the number of cells specified by a given set of conditions

specified by a given set of conditions or criteria for this we need to specify

or criteria for this we need to specify a range and then the criteria first

a range and then the criteria first we'll focus on the range of a for job

we'll focus on the range of a for job title short and we're looking to match

title short and we're looking to match that of data analyst which I'll lock by

that of data analyst which I'll lock by pressing F4 then now we're moving on to

pressing F4 then now we're moving on to criteria range number two where for this

criteria range number two where for this one we're looking at Job country now and

one we're looking at Job country now and for that we want to look for the

for that we want to look for the criteria of United States locking this

criteria of United States locking this with F4 closing this with parenthesis

with F4 closing this with parenthesis and then running it we get around 8,000

and then running it we get around 8,000 jobs and this makes sense right because

jobs and this makes sense right because it would be less than that 9,000 data

it would be less than that 9,000 data analyst because some of these aren't

analyst because some of these aren't going to be from the United States now

going to be from the United States now with how this is Flowing we could

with how this is Flowing we could actually make a visualization out of

actually make a visualization out of this data right here so going into

this data right here so going into insert and then recommended charts we

insert and then recommended charts we have here a funnel chart so I'm going go

have here a funnel chart so I'm going go ahead and insert that in and this

ahead and insert that in and this basically shows the funnel if you will

basically shows the funnel if you will of jobs we have we started with almost

of jobs we have we started with almost 32,000 jobs and we got towards the end

32,000 jobs and we got towards the end of the jobs that we actually care about

of the jobs that we actually care about us and data analyst at around 8,000 I'll

us and data analyst at around 8,000 I'll go ahead and move this off to the side

go ahead and move this off to the side for

now all right next moving into the sum function and the core one itself of

function and the core one itself of actual sum itself it's pretty simple we

actual sum itself it's pretty simple we have to just we're going to obviously

have to just we're going to obviously using salary year average column for

using salary year average column for this because we want to sum up the

this because we want to sum up the numbers in them and I'm put in that

numbers in them and I'm put in that column of M and we get the sum of values

column of M and we get the sum of values there now unlike count where a count has

there now unlike count where a count has a count a or count all where we're

a count a or count all where we're trying to find if there's blanks or not

trying to find if there's blanks or not that's not really applicable In Sum and

that's not really applicable In Sum and average and also in Min or Max so I'm

average and also in Min or Max so I'm actually going to go ahead and just gray

actually going to go ahead and just gray these out because we're not going to

these out because we're not going to need them now moving into suth which

need them now moving into suth which adds the cells specified by a given

adds the cells specified by a given condition or criteria this one is a

condition or criteria this one is a little bit more complex than we dealt

little bit more complex than we dealt with with count because we first want to

with with count because we first want to provide the range that we're going to be

provide the range that we're going to be evaluating for a certain criteria which

evaluating for a certain criteria which in our case the range you want to

in our case the range you want to evaluate is job country because we're

evaluate is job country because we're evaluating for if it contains United

evaluating for if it contains United States which I'll lock with that four

States which I'll lock with that four but we're not summing the countries

but we're not summing the countries because there are text column so we have

because there are text column so we have to provide this sum range which is

to provide this sum range which is column M similarly once again we can do

column M similarly once again we can do that sum if looking for data analyst so

that sum if looking for data analyst so in this case we're going to be looking

in this case we're going to be looking at column A to evaluate if it has data

at column A to evaluate if it has data analyst in it and then from there the

analyst in it and then from there the sum range once again is going to be that

sum range once again is going to be that column M now the sum ifs similar to that

column M now the sum ifs similar to that count ifs adds the cell specified by a

count ifs adds the cell specified by a given set of conditions or criteria for

given set of conditions or criteria for this one we provide the sum range first

this one we provide the sum range first so it gets a little bit confusing you

so it gets a little bit confusing you got to make sure that you're actually

got to make sure that you're actually reading the formulas in this case we're

reading the formulas in this case we're going to use M because that's the sum

going to use M because that's the sum range we want to use and then we're

range we want to use and then we're first going to evaluate for that job

first going to evaluate for that job title short that column A which we're

title short that column A which we're going to evaluate for data analyst and

going to evaluate for data analyst and then we'll evaluate for the job country

then we'll evaluate for the job country evaluating for United States closing the

evaluating for United States closing the parentheses and running this bam as

parentheses and running this bam as expected this value is less than that of

expected this value is less than that of the data

analyst now moving into the last three of average men and Max which I think are

of average men and Max which I think are actually more valuable than that sum one

actually more valuable than that sum one we did I'm not going to walk through

we did I'm not going to walk through actually typing in all these in because

actually typing in all these in because now you've had a familiarity with how I

now you've had a familiarity with how I did the sum which follows the same

did the sum which follows the same example for average men in Max feel free

example for average men in Max feel free to if you want to you can go through and

to if you want to you can go through and type it out on your own to get more

type it out on your own to get more experience doing it but overall I think

experience doing it but overall I think this has some very unique insights from

this has some very unique insights from it from this analysis we did in it we

it from this analysis we did in it we can see that salaries in the United

can see that salaries in the United States are around 125,000 where the data

States are around 125,000 where the data analyst is only around 93 and

analyst is only around 93 and specifically us data analyst is around

specifically us data analyst is around 94 so data analysts in general are lower

94 so data analysts in general are lower salaries than the other jobs in the data

salaries than the other jobs in the data science Industry as far as Min and Max

science Industry as far as Min and Max go we're having as low as

go we're having as low as 25,000 but we're having as high as well

25,000 but we're having as high as well at least for a data analyst up to

at least for a data analyst up to 650,000 and apparently there's a job in

650,000 and apparently there's a job in here around

here around $960,000 and you may be wondering what

$960,000 and you may be wondering what jobs correlate to this $155,000 or

jobs correlate to this $155,000 or $960,000 well we're going to be diving

$960,000 well we're going to be diving into that further when we get to that

into that further when we get to that lookup functions one last note on errors

lookup functions one last note on errors before we go I commonly find the most

before we go I commonly find the most common error with these functions is a

common error with these functions is a value error and that usually occurs

value error and that usually occurs whenever in this case we had column a

whenever in this case we had column a selected initially for criteria range

selected initially for criteria range number one let's say we accidentally

number one let's say we accidentally selected multiple different columns for

selected multiple different columns for this obviously we're not trying to

this obviously we're not trying to evaluate all the different columns we

evaluate all the different columns we only want to evaluate one column for

only want to evaluate one column for that criteria of if data analyst Falls

that criteria of if data analyst Falls in it anyway when I run this I get a

in it anyway when I run this I get a value ER anyway this is a common one

value ER anyway this is a common one that I see come up time and time again

that I see come up time and time again so anytime you're going through this any

so anytime you're going through this any of these or the practice problems

of these or the practice problems themselves make sure you're

themselves make sure you're investigating to see that you've

investigating to see that you've actually input in the correct ranges to

actually input in the correct ranges to evaluate cuz it's commonly causing those

evaluate cuz it's commonly causing those value errors all right with that you

value errors all right with that you have some practice problems to dive into

have some practice problems to dive into and next we'll be diving into even more

and next we'll be diving into even more statistical functions in order to really

statistical functions in order to really dive into how deep you can go with Eda

dive into how deep you can go with Eda or exploratory data analysis all right

or exploratory data analysis all right with that I'll see you in the next

one we're now going to be taking this up a notch shifting gears from focusing on

a notch shifting gears from focusing on math functions now to statistical

math functions now to statistical functions for this we're going to be

functions for this we're going to be using our job posting data set and

using our job posting data set and analyzing the salaries in this

analyzing the salaries in this specifically looking at common

specifically looking at common statistical functions like median

statistical functions like median standard deviation and even quartiles

standard deviation and even quartiles once we have the basics we're going to

once we have the basics we're going to shift into an actual analysis looking at

shift into an actual analysis looking at what is the average salary of different

what is the average salary of different job titles and we'll even get a sneak

job titles and we'll even get a sneak peek of visualizing it for this lesson

peek of visualizing it for this lesson you can start by opening this syst

you can start by opening this syst statistical functions workbook we're

statistical functions workbook we're going to be starting by filling in this

going to be starting by filling in this table here on the different statistical

table here on the different statistical functions we're going to be filling out

functions we're going to be filling out and we're still working with that data

and we're still working with that data set we did previously if you noticed

set we did previously if you noticed I've hidden a lot of the columns that we

I've hidden a lot of the columns that we won't be using for

this so we've done a few of these different type of functions already

different type of functions already let's go ahead and fill these in for

let's go ahead and fill these in for count we'll be using the count function

count we'll be using the count function specifically on that M column of salary

specifically on that M column of salary or average and like before we have

or average and like before we have around 22,000 values for average we'll

around 22,000 values for average we'll be doing the same on that M column we

be doing the same on that M column we find that's around

find that's around 123,000 for men we'll also run this on

123,000 for men we'll also run this on the M column and that's around 15,000

the M column and that's around 15,000 for Max that's going to be around

for Max that's going to be around 960,000 so let's move on to our first

960,000 so let's move on to our first true statistical function we're actually

true statistical function we're actually going to go into this to actually see

going to go into this to actually see what it does and that's median it

what it does and that's median it Returns the median or the number in the

Returns the median or the number in the middle of the set of given numbers so

middle of the set of given numbers so let's go ahead and type that out median

let's go ahead and type that out median and in there we need to specify number

and in there we need to specify number or numbers we can specify a range we're

or numbers we can specify a range we're just going to keep it simple right now

just going to keep it simple right now to actually show what this function is

to actually show what this function is actually doing it's selecting the middle

actually doing it's selecting the middle of numers so I'm just going to select

of numers so I'm just going to select these top three numbers right now and

these top three numbers right now and what I expect for this function to do is

what I expect for this function to do is to provide basically in a set of numbers

to provide basically in a set of numbers given provide the middle number so it

given provide the middle number so it should provide us 140,000 which is the

should provide us 140,000 which is the center number of these three we don't

center number of these three we don't care about the center of just three

care about the center of just three values we care about the center of

values we care about the center of basically all of our different values so

basically all of our different values so I'm going to place the entire M column

I'm going to place the entire M column into it and that is around

into it and that is around 115,000 now why is this average higher

115,000 now why is this average higher than this median well let's actually

than this median well let's actually visualize it I'm going to select this m

visualize it I'm going to select this m column and go to the insert tab going to

column and go to the insert tab going to histograms I'm going to insert a

histograms I'm going to insert a histogram and what this is showing is

histogram and what this is showing is the distribution of salaries from 15,000

the distribution of salaries from 15,000 all the way to 950,000 bottom xaxis is a

all the way to 950,000 bottom xaxis is a little confusing to read but it's

little confusing to read but it's basically a range so this case 87,000

basically a range so this case 87,000 93,000 how many counts of salaries are

93,000 how many counts of salaries are falling in between that and that's how

falling in between that and that's how large the bar is next to it anyway

large the bar is next to it anyway getting back to that original question

getting back to that original question why is the average higher than the

why is the average higher than the median itself if you call back from

median itself if you call back from definition a median is the middle number

definition a median is the middle number in our set of our list but our average

in our set of our list but our average however is taking all the different

however is taking all the different values and well averaging it out and as

values and well averaging it out and as we can see from it we have a large

we can see from it we have a large amount of salaries around well

amount of salaries around well $100,000 but we do have some up here

$100,000 but we do have some up here that are getting close to a million

that are getting close to a million dollar these basically outliers are

dollar these basically outliers are causing us to have a higher average so

causing us to have a higher average so basically those values that are near

basically those values that are near 960,000 are dragging that average way

960,000 are dragging that average way higher so that's why I prefer to use

higher so that's why I prefer to use something like the median when I can in

something like the median when I can in order to analyze these salaries because

order to analyze these salaries because they're not skewed by the these outlier

they're not skewed by the these outlier salaries that are just something that

salaries that are just something that you're probably not going to get all

you're probably not going to get all right next up is standard deviation and

right next up is standard deviation and for this you have two options standard

for this you have two options standard dev. p and standard dev. s the P stands

dev. p and standard dev. s the P stands for population and the S stands for

for population and the S stands for sample this data set is around 30,000

sample this data set is around 30,000 salaries and there's way more than

salaries and there's way more than 30,000 data science jobs available so

30,000 data science jobs available so that's a sample of the actual population

that's a sample of the actual population so we're going to be using standard Dev

so we're going to be using standard Dev s and for this we can insert a range

s and for this we can insert a range into it so what does this value actually

into it so what does this value actually mean well if we had something like a

mean well if we had something like a normal distribution which our salary

normal distribution which our salary data is somewhat close to that we'll

data is somewhat close to that we'll find that one standard deviation from

find that one standard deviation from something like the average has in this

something like the average has in this case right here 34,000 so if we went

case right here 34,000 so if we went above and below the average by one

above and below the average by one standard deviation around 68% which is a

standard deviation around 68% which is a heck a lot of data is within this one

heck a lot of data is within this one standard deviation so in our case if I

standard deviation so in our case if I was to take the average and then

was to take the average and then subtract this standard deviation along

subtract this standard deviation along with taking the average and then adding

with taking the average and then adding the standard deviation around 70% of the

the standard deviation around 70% of the salaries are going to be between 75,000

salaries are going to be between 75,000 and 170,000 but what if we wanted to be

and 170,000 but what if we wanted to be more precise about finding say something

more precise about finding say something like where does 50% of the data actually

like where does 50% of the data actually fall well we can use quartiles in this

fall well we can use quartiles in this case specifically calculating the first

case specifically calculating the first and third quartile here's a graph that I

and third quartile here's a graph that I did from my python course which when you

did from my python course which when you get done with this course feel free to

get done with this course feel free to check it out but anyway it looks at the

check it out but anyway it looks at the salary distribution of data analyst

salary distribution of data analyst United States has this histogram right

United States has this histogram right here very similar to what we plotted

here very similar to what we plotted previously in Excel but in it I'm able

previously in Excel but in it I'm able to plot out cortile one where the

to plot out cortile one where the quartile one starts and then quartile 3

quartile one starts and then quartile 3 where that one starts so between this

where that one starts so between this quartile 1 and quartile 3 marker lines

quartile 1 and quartile 3 marker lines 50% of the data Falls here with this red

50% of the data Falls here with this red dotted line being the media again which

dotted line being the media again which let's actually get to calculating this

let's actually get to calculating this so if we want to do something like the

so if we want to do something like the cortile we're going to see that there's

cortile we're going to see that there's a few different functions available for

a few different functions available for this we have exclusive and inclusive

this we have exclusive and inclusive we're going to do inclusive first and

we're going to do inclusive first and then I'll show The Exclusive after to

then I'll show The Exclusive after to basically show how it's different so

basically show how it's different so this takes two arguments the first is

this takes two arguments the first is the array so I'll put in that range of

the array so I'll put in that range of the M column and then lastly it takes

the M column and then lastly it takes the quartile and we have one for the

the quartile and we have one for the first quartile two for the median three

first quartile two for the median three for the third quartile anyway I have

for the third quartile anyway I have these values over in the U column so

these values over in the U column so I'll just select that and use that for

I'll just select that and use that for this and for the second quartile we're

this and for the second quartile we're seeing that basically as a just red

seeing that basically as a just red that's also equal to the median now I'm

that's also equal to the median now I'm going to go ahead and get rid of these

going to go ahead and get rid of these Min and Max CU we can also use that by

Min and Max CU we can also use that by with our quartile function and I'm going

with our quartile function and I'm going to go ahead and drag and drop this up

to go ahead and drag and drop this up and then also below so what we can see

and then also below so what we can see from this with this first and third

from this with this first and third quartile is that around 50% of the data

quartile is that around 50% of the data Falls between 90 ,000 and

Falls between 90 ,000 and 150,000 so frankly when it comes to

150,000 so frankly when it comes to using quartiles like here and standard

using quartiles like here and standard deviation I find myself more gravitating

deviation I find myself more gravitating towards quartiles anyway what about that

towards quartiles anyway what about that other quartile function specifically

other quartile function specifically that one around exclusive values well

that one around exclusive values well once again I can select the array that

once again I can select the array that we're going to use we're going to use M

we're going to use we're going to use M and then finally the quartile itself now

and then finally the quartile itself now notice for this one this one doesn't

notice for this one this one doesn't have a value of 0 and four that you

have a value of 0 and four that you actually can put in for the Min and Max

actually can put in for the Min and Max it's exclusive so it excludes those

it's exclusive so it excludes those outliers basically of the Min and Max so

outliers basically of the Min and Max so specifying that column next to it when I

specifying that column next to it when I actually drag this down we can see that

actually drag this down we can see that the Min and Max AR provided in this but

the Min and Max AR provided in this but it's the same values for that se first

it's the same values for that se first second and third quartile if you notice

second and third quartile if you notice here we get this numb error and as we

here we get this numb error and as we inspected when going through this

inspected when going through this formula zero and four were not available

formula zero and four were not available to actually input into the formula so

to actually input into the formula so any time you're inputting things into a

any time you're inputting things into a formula that doesn't necessarily exist

formula that doesn't necessarily exist you're going to get this numb error all

you're going to get this numb error all right the last function to investigate

right the last function to investigate is the mode and this returns a vertical

is the mode and this returns a vertical array of the most frequently occurring

array of the most frequently occurring or repetitive values in any array in our

or repetitive values in any array in our case we'll once again provide column M

case we'll once again provide column M and surprisingly we find that 90,000 is

and surprisingly we find that 90,000 is one of the most repetitive values if we

one of the most repetitive values if we go back to that histogram we plotted

go back to that histogram we plotted earlier we can see that the largest line

earlier we can see that the largest line right here with a value of 19 25

right here with a value of 19 25 occurrences occurs between 87,000 and

occurrences occurs between 87,000 and 93,000 so this makes sense on the 90,000

93,000 so this makes sense on the 90,000 being the

mode so let's get into some data analysis Now by actually ranking the

analysis Now by actually ranking the average salaries of these different job

average salaries of these different job tiles I'm going to go ahead and hide the

tiles I'm going to go ahead and hide the columns v through R now in order to rank

columns v through R now in order to rank the salaries of the different job tiles

the salaries of the different job tiles that I have this list here for you where

that I have this list here for you where you need to First calculate the average

you need to First calculate the average salaries of each of these job titles so

salaries of each of these job titles so for this we're going to be using as last

for this we're going to be using as last time average if first we need to specify

time average if first we need to specify the range that we're going to be

the range that we're going to be basically running that if on not

basically running that if on not necessarily the values but the range of

necessarily the values but the range of the job titles next we need to provide

the job titles next we need to provide the criteria for this we'll provid it of

the criteria for this we'll provid it of data analyst which is in W2 and then

data analyst which is in W2 and then finally the actual average range of

finally the actual average range of column M dragging this all the way down

column M dragging this all the way down we have our different averages for all

we have our different averages for all the job tiles one note real quick in

the job tiles one note real quick in future lessons we're going to be jumping

future lessons we're going to be jumping into using

into using median to evaluate these job tiles cuz

median to evaluate these job tiles cuz personally I like that more but that's a

personally I like that more but that's a slightly more complex problem so we're

slightly more complex problem so we're going to stick simple for now anyway

going to stick simple for now anyway with these advertisers we can now

with these advertisers we can now actually rank it and this Returns the

actually rank it and this Returns the rank of a number in a list of numbers it

rank of a number in a list of numbers it size relative to other values in the

size relative to other values in the list so first we need to put in the

list so first we need to put in the number that we want to rank in this case

number that we want to rank in this case we're want to do that of data analyst

we're want to do that of data analyst and then from there they have the ref or

and then from there they have the ref or the reference array in this case we're

the reference array in this case we're going to provide it right here from X2

going to provide it right here from X2 all the way down to X11 now I can change

all the way down to X11 now I can change this from descending to ascending but

this from descending to ascending but I'm going to keep it how it is now I'm

I'm going to keep it how it is now I'm going to drag and drop all the rest of

going to drag and drop all the rest of these and we had a little bit of an

these and we had a little bit of an issue CU we have repeating numbers right

issue CU we have repeating numbers right here it's obviously because I didn't

here it's obviously because I didn't lock my cells appropriately so selecting

lock my cells appropriately so selecting this range that I want to actually lock

this range that I want to actually lock and pressing F4 go ahead and lock that

and pressing F4 go ahead and lock that and then we'll drag and drop this again

and then we'll drag and drop this again hopefully this works this time and boom

hopefully this works this time and boom we have all these ranked from highest to

we have all these ranked from highest to lowest we can see business analyst or

lowest we can see business analyst or some of the lowest thata analyst not far

some of the lowest thata analyst not far behind and Senior data scientist has the

behind and Senior data scientist has the highest I'm going to take this one step

highest I'm going to take this one step further I'm going to highlight

further I'm going to highlight everything from job title down to the

everything from job title down to the bottom salary for software Engineers

bottom salary for software Engineers going to go into insert in here and go

going to go into insert in here and go to recommended charts and basically the

to recommended charts and basically the first one that pops up this clustered

first one that pops up this clustered bar chart I'm going to insert in and I

bar chart I'm going to insert in and I can just change the salary up here by

can just change the salary up here by double clicking in here and I put

double clicking in here and I put average salary of data science jobs and

average salary of data science jobs and there we have some data analysis is

there we have some data analysis is actually viewing these one minor touch

actually viewing these one minor touch to this I really don't like how these

to this I really don't like how these are unordered right now so I could

are unordered right now so I could actually go up here select these three

actually go up here select these three titles right here and then under the

titles right here and then under the Home tab select I want to actually

Home tab select I want to actually filter it and then order this rank from

filter it and then order this rank from well we'll say largest to smallest one

well we'll say largest to smallest one note you may not have been able to see

note you may not have been able to see it but it actually rearranged the data

it but it actually rearranged the data inside of our data set that's not a big

inside of our data set that's not a big deal for me I'm not caring too much but

deal for me I'm not caring too much but that is something that will be effective

that is something that will be effective whenever you do this anyway with this we

whenever you do this anyway with this we can see things like senior roles or

can see things like senior roles or getting paid the most and things like

getting paid the most and things like analyst are sometimes getting paid the

analyst are sometimes getting paid the least compared to these all right you

least compared to these all right you now have some practice problems to go

now have some practice problems to go into and thus practice your skills with

into and thus practice your skills with these statistical functions after that

these statistical functions after that we're going to be jumping in the next

we're going to be jumping in the next lesson into arrays which is a super

lesson into arrays which is a super powerful feature sort of new to excel in

powerful feature sort of new to excel in the past few years all right with that

the past few years all right with that I'll see you in the next

one we're going to be now shifting gears and jumping into a more advanced topic

and jumping into a more advanced topic of arrays and with arrays what you can

of arrays and with arrays what you can do is typing a formula in a single cell

do is typing a formula in a single cell we can use this to fill in cells below

we can use this to fill in cells below it or cells to the side of it all with

it or cells to the side of it all with one single formula so we're going to be

one single formula so we're going to be slowly working up to an easy then a

slowly working up to an easy then a medium and then a hard problem and how

medium and then a hard problem and how to use these first up with the easy one

to use these first up with the easy one we're going to go through and basically

we're going to go through and basically identify all the unique job titles and

identify all the unique job titles and then go through and actually sort it

then go through and actually sort it alphabetically using arrays next we're

alphabetically using arrays next we're going to move into to our median problem

going to move into to our median problem of calculating the median salary if you

of calculating the median salary if you recall back to our last lesson we were

recall back to our last lesson we were calculating the average salary based on

calculating the average salary based on a job tile well we can use a raise to

a job tile well we can use a raise to calculate the median and then finally

calculate the median and then finally one of the most hardest problems we're

one of the most hardest problems we're going to get into actually looking at

going to get into actually looking at based on the month how many different

based on the month how many different jobs were submitted during that month

jobs were submitted during that month and before this we'll be using the Su

and before this we'll be using the Su product formula and a combination of

product formula and a combination of other ones using arrays for this be

other ones using arrays for this be using the arrays formula Excel

workbook now before we jump into those problems we need to First understand

problems we need to First understand that there's actually two different

that there's actually two different types of arrays we're going to start

types of arrays we're going to start with the first one of modern dynamic

with the first one of modern dynamic arrays which we've seen before and with

arrays which we've seen before and with this what we can do is using a formula

this what we can do is using a formula we can specify a range to identify and

we can specify a range to identify and then whenever we press enter B2 to B5

then whenever we press enter B2 to B5 it's going to actually fill in with all

it's going to actually fill in with all these we can see that it's modern or

these we can see that it's modern or dynamic because it has this Shadow

dynamic because it has this Shadow around the edge if I select any of the

around the edge if I select any of the other ones and not the core one where

other ones and not the core one where this one's actually highlighted when the

this one's actually highlighted when the other ones these are grayed out taking

other ones these are grayed out taking this a step further with array

this a step further with array multiplication we can actually go in and

multiplication we can actually go in and multiply this column one of A2 to A5 and

multiply this column one of A2 to A5 and multiply it times B2 to B5 anyway in

multiply it times B2 to B5 anyway in this sequence you can see that it goes

this sequence you can see that it goes down 1 * 1 is 1 whereas 4 * 4 is well 16

down 1 * 1 is 1 whereas 4 * 4 is well 16 anyway that's modern dynamic arrays

anyway that's modern dynamic arrays classical arrays let's say we want to do

classical arrays let's say we want to do the same thing in this case well we're

the same thing in this case well we're going to have to go about it a little

going to have to go about it a little bit differently we need to select all

bit differently we need to select all the cells that we want to fill in first

the cells that we want to fill in first is a very key concept to get for right

is a very key concept to get for right first then from there we can start

first then from there we can start entering our formula so I put in equal

entering our formula so I put in equal in this case we want to do the same

in this case we want to do the same array multiplication I'll take A2 to A5

array multiplication I'll take A2 to A5 times it time B2 to B5 now whenever I am

times it time B2 to B5 now whenever I am done with this and I want to actually

done with this and I want to actually execute this I don't just press enter I

execute this I don't just press enter I have to press contrl shift enter and

have to press contrl shift enter and then it fills in the array notice it's

then it fills in the array notice it's not grayed out around the edges like

not grayed out around the edges like this as a shadow this one does not do

this as a shadow this one does not do that and all of the different formulas

that and all of the different formulas are now filled in below this and you'll

are now filled in below this and you'll notice that there's a curly bracket

notice that there's a curly bracket around this this was used prior to

around this this was used prior to around

around 2020 and so you may come into contact

2020 and so you may come into contact with Excel spreadsheets that have this

with Excel spreadsheets that have this and if you don't know about it if you

and if you don't know about it if you come into here and say you want to like

come into here and say you want to like mess with this formula and you press

mess with this formula and you press enter you're going to get an error

enter you're going to get an error message but now let's say we have some

message but now let's say we have some additional values in it we'll say We'll

additional values in it we'll say We'll add five to each to the bottom of these

add five to each to the bottom of these if I wanted to adjust this array if I

if I wanted to adjust this array if I came in here and then change this to six

came in here and then change this to six for both the bottom and the top and

for both the bottom and the top and press control shift enter it's only

press control shift enter it's only going to adjust the ones that were

going to adjust the ones that were previously selected so now if I want to

previously selected so now if I want to include this bottom row right here for

include this bottom row right here for modern dynamic arrays it's pretty easy I

modern dynamic arrays it's pretty easy I can just come in here and adjust this to

can just come in here and adjust this to six and this is done however for

six and this is done however for classical arrays or classic arrays not

classical arrays or classic arrays not classical I have to actually select all

classical I have to actually select all these different cells and then go in and

these different cells and then go in and actually enter the formula that I want

actually enter the formula that I want to enter if I try and press enter it's

to enter if I try and press enter it's going to give me an error message and I

going to give me an error message and I realize okay I have to press control

realize okay I have to press control shift enter and it'll actually fill in

shift enter and it'll actually fill in anyway the main point of this is

anyway the main point of this is classical arrays or a mess we're going

classical arrays or a mess we're going to be focusing on Modern and or dynamic

to be focusing on Modern and or dynamic arrays for the remainder of this course

arrays for the remainder of this course but you need to be aware of classical

but you need to be aware of classical arrays in case you encounter them in the

arrays in case you encounter them in the wild

so jumping into our data analysis we're going to be focusing with the data set

going to be focusing with the data set that we've been focusing on before and

that we've been focusing on before and I've hidden any columns that I don't

I've hidden any columns that I don't feel are relevant for our future

feel are relevant for our future analysis that we're going to do anyway

analysis that we're going to do anyway the first thing we're going do is find

the first thing we're going do is find the unique job titles and for this we

the unique job titles and for this we can use the unique function and this

can use the unique function and this Returns the unique values from a range

Returns the unique values from a range or array so the first thing we need to

or array so the first thing we need to do is actually put in the array itself I

do is actually put in the array itself I don't want to actually select this

don't want to actually select this column A because I don't want this job

column A because I don't want this job title short to appear so I'm going to

title short to appear so I'm going to select A2 and then press control shift

select A2 and then press control shift down to select all the way to the bottom

down to select all the way to the bottom I'm going close this parenthesis and we

I'm going close this parenthesis and we have all the different unique titles in

have all the different unique titles in there now I want to get the sorted job

there now I want to get the sorted job titles out of this so as you guess we're

titles out of this so as you guess we're going to use the sort function and for

going to use the sort function and for this all we really need to do is specify

this all we really need to do is specify the array now if you notice from this

the array now if you notice from this one whenever I went ahead and selected

one whenever I went ahead and selected it it specifies that R2 pound and that

it it specifies that R2 pound and that basically says that hey there's an array

basically says that hey there's an array basically formula inside side of R2 we

basically formula inside side of R2 we want to extract all the contents of that

want to extract all the contents of that using R2 pound and so that's going to

using R2 pound and so that's going to work to be able to provide us all those

work to be able to provide us all those values and then it's going to sort it in

values and then it's going to sort it in this case we have it sorted in

this case we have it sorted in alphabetical order one thing I haven't

alphabetical order one thing I haven't called out both times is these are once

called out both times is these are once again dynamic or modern arrays you can

again dynamic or modern arrays you can see that gray box around each of these

see that gray box around each of these but just to show this also works by

but just to show this also works by specifying R2 to R11 it's going to

specifying R2 to R11 it's going to provide us the exact same results but I

provide us the exact same results but I really like the shorthand nomenclature

really like the shorthand nomenclature of the R2 hashtag

sign now we're going to get into calculating the median salary and if you

calculating the median salary and if you recall back to our last lesson on

recall back to our last lesson on statistical functions we went through

statistical functions we went through and calculated the average salary for

and calculated the average salary for each of these job titles using an

each of these job titles using an average IF function but as it discussed

average IF function but as it discussed last time when comparing something like

last time when comparing something like the average to the median the average in

the average to the median the average in this data set is slightly higher due to

this data set is slightly higher due to those basically outliers of those High

those basically outliers of those High salaries around 960,000 so we want to

salaries around 960,000 so we want to use median so what are we going to be

use median so what are we going to be eventually calculating and now that's

eventually calculating and now that's this table right here where we sorted

this table right here where we sorted our business or job titles themselves

our business or job titles themselves and then we go into actually calculating

and then we go into actually calculating the median salary based on these

the median salary based on these different job titles from our data set

different job titles from our data set now there's a pretty complex formula

now there's a pretty complex formula going into here so because of this we're

going into here so because of this we're actually going to break it down step by

actually going to break it down step by step by step going through each columns

step by step going through each columns explaining how this actual process works

explaining how this actual process works in order for us to get to this final

in order for us to get to this final value for this we're going to be doing

value for this we're going to be doing it for data analyst only as we can see

it for data analyst only as we can see the final value we're going to get to is

the final value we're going to get to is 990,000 which over here which our final

990,000 which over here which our final results 90,000 so I'm going to go ahead

results 90,000 so I'm going to go ahead and delete this to actually start with

and delete this to actually start with now we need to look for two separate

now we need to look for two separate conditions the first one we need to look

conditions the first one we need to look to find do the job titles here actually

to find do the job titles here actually match up to this value here of data

match up to this value here of data analyst and this provides booing values

analyst and this provides booing values back where we get to this value down

back where we get to this value down here for true as expected in row 16 we

here for true as expected in row 16 we have data analyst now if we scroll down

have data analyst now if we scroll down further we can see that our next data

further we can see that our next data analyst job doesn't have a salary for IT

analyst job doesn't have a salary for IT these type of things will throw off our

these type of things will throw off our final median function that we're going

final median function that we're going to actually be calculating and so we

to actually be calculating and so we need to basically filter it out as well

need to basically filter it out as well well so with the salary dat data set

well so with the salary dat data set selected I'm going to then go through

selected I'm going to then go through and filter this basically not equal to a

and filter this basically not equal to a blank value and as expected we're

blank value and as expected we're getting false values for these blank

getting false values for these blank ones now similar to what we saw in the

ones now similar to what we saw in the intro in arrays where we were

intro in arrays where we were multiplying different arrays together

multiplying different arrays together we're going to do the same thing here

we're going to do the same thing here with these bolean values for this I'm

with these bolean values for this I'm taking that formula and wrapping it in

taking that formula and wrapping it in parenthesis it needs to be in

parenthesis it needs to be in parenthesis in order to execute properly

parenthesis in order to execute properly for the we contains that analyst and

for the we contains that analyst and then the second condition that the

then the second condition that the salary can't be blank whenever we

salary can't be blank whenever we multiply these two Boolean values

multiply these two Boolean values together we get returned back either a

together we get returned back either a zero or one and the only way we get a

zero or one and the only way we get a one back is if both these values are

one back is if both these values are true which is the condition we want to

true which is the condition we want to meet now for zero or one values we can

meet now for zero or one values we can actually see if we did an if statement

actually see if we did an if statement here if we did a logical test of zero

here if we did a logical test of zero what is it going to return whether true

what is it going to return whether true or false so for Z returns false and for

or false so for Z returns false and for one we'd expect to turn true anyway we

one we'd expect to turn true anyway we don't want to necessarily return true in

don't want to necessarily return true in this case we want to return the salary

this case we want to return the salary that corresponds to that Row in the data

that corresponds to that Row in the data set so I'm going to go ahead and delete

set so I'm going to go ahead and delete this so for this we're going to start

this so for this we're going to start with that if function itself then I want

with that if function itself then I want to place all the different contents that

to place all the different contents that we saw in that previous V column now we

we saw in that previous V column now we want to return the salary which are

want to return the salary which are these contents right here so I'll be our

these contents right here so I'll be our value if true and then if false we just

value if true and then if false we just want it to be FAL false which we can

want it to be FAL false which we can just leave blank so now scrolling down

just leave blank so now scrolling down we can see that we have nothing but

we can see that we have nothing but those values for data analyst scroll

those values for data analyst scroll over just to confirm 129 yep that

over just to confirm 129 yep that analyst all right the last step we need

analyst all right the last step we need to go ahead and put inside of our median

to go ahead and put inside of our median formula all those contents that we had

formula all those contents that we had before that entire if statement itself

before that entire if statement itself to evaluate so that array that it's

to evaluate so that array that it's going to basically find out for all

going to basically find out for all those salary for data analyst and it's

those salary for data analyst and it's return back the median salary now this

return back the median salary now this also works for other function so let's

also works for other function so let's say we wanted to use the mode we want to

say we wanted to use the mode we want to use a mode if condition they don't have

use a mode if condition they don't have this available so we could just plug

this available so we could just plug this inside of mode and then running

this inside of mode and then running this we can see that well the most

this we can see that well the most common value for thata analyst

common value for thata analyst apparently also the median of 90,000 so

apparently also the median of 90,000 so going back to our data sheet let's

going back to our data sheet let's actually go through and stepbystep

actually go through and stepbystep calculate it for each of these different

calculate it for each of these different sorted unique job tiles that we did

sorted unique job tiles that we did previously and we're going to be

previously and we're going to be building this step by step how i'

building this step by step how i' normally build a for so the first thing

normally build a for so the first thing we going to look for the job titles

we going to look for the job titles itself do they match to that business

itself do they match to that business analyst so selecting column A2 and then

analyst so selecting column A2 and then control shift down to select all the

control shift down to select all the contents on the cell we want to see if

contents on the cell we want to see if that's equal to this business analyst

that's equal to this business analyst rule right here and now remember we're

rule right here and now remember we're going to be dragging these Downs do an

going to be dragging these Downs do an autofill so we need to be particular

autofill so we need to be particular about how we lock these cells

about how we lock these cells specifically we do need to lock these

specifically we do need to lock these values right here and just for safe

values right here and just for safe measure I'm going to lock the column of

measure I'm going to lock the column of this one okay pressing enter all right

this one okay pressing enter all right we we have our array back looking for

we we have our array back looking for business analyst and we can see that

business analyst and we can see that it's working by what we see down here in

it's working by what we see down here in row 84 so let's actually do that array

row 84 so let's actually do that array multiplication by now filtering out

multiplication by now filtering out salary that doesn't have values or

salary that doesn't have values or blanks so we're going to put another set

blanks so we're going to put another set of parentheses next to it we'll put in

of parentheses next to it we'll put in our salary data and that it's not equal

our salary data and that it's not equal to blank running this we confirm that

to blank running this we confirm that the first value of business analyst that

the first value of business analyst that has a salary has a one now we need to

has a salary has a one now we need to wrap this all inside of an if to

wrap this all inside of an if to basically return instead of that one we

basically return instead of that one we want it to return the salary itself so

want it to return the salary itself so for the value of true I'm going to put

for the value of true I'm going to put in the selection of the salary yearly

in the selection of the salary yearly running this we confirm this is again

running this we confirm this is again correct looking at row 180 almost done

correct looking at row 180 almost done just now need to wrap this all inside of

just now need to wrap this all inside of a median function and Bam

a median function and Bam 85,000 and hopefully we actually locked

85,000 and hopefully we actually locked all the cells properly dragging it Down

all the cells properly dragging it Down Bam looks like we got all our things and

Bam looks like we got all our things and we slightly messed up our formatting

we slightly messed up our formatting here so I'm going to go ahead and put a

here so I'm going to go ahead and put a thick outside border on again to make

thick outside border on again to make that right again all right so that's how

that right again all right so that's how you basically transform any function in

you basically transform any function in Excel that doesn't have that you know

Excel that doesn't have that you know count if or average IF function or

count if or average IF function or capability into other

functions now moving into probably the most complex example that we're going to

most complex example that we're going to be be using not only this lesson

be be using not only this lesson probably in the entire course so if you

probably in the entire course so if you get around this you're going to be good

get around this you're going to be good to go for the rest of the course anyway

to go for the rest of the course anyway what we're trying to look at here is the

what we're trying to look at here is the count of job postings based on the month

count of job postings based on the month that it was posted in and we're going to

that it was posted in and we're going to be using the sum product function for

be using the sum product function for this now sum product is not anything

this now sum product is not anything that you should be afraid of basically

that you should be afraid of basically before we were doing whenever we were

before we were doing whenever we were doing the intro and we were talking

doing the intro and we were talking about array multiplication how went

about array multiplication how went through line by line based on this and

through line by line based on this and we have our values of 1 4 9 16 and 25

we have our values of 1 4 9 16 and 25 line by line well if we were to do the

line by line well if we were to do the sum

sum product of the values in column A along

product of the values in column A along with the values in column B we're going

with the values in column B we're going to get 55 which when we look at the sum

to get 55 which when we look at the sum of these values here we can see that it

of these values here we can see that it is 55 so it's a sum of the product of

is 55 so it's a sum of the product of the arrays so getting back to our

the arrays so getting back to our example that we're going to be solving

example that we're going to be solving we're trying to aggregate it by these

we're trying to aggregate it by these names of these months if we actually

names of these months if we actually scroll over to the data set itself the

scroll over to the data set itself the job posted date is in a date time format

job posted date is in a date time format so similar to the last example I'm going

so similar to the last example I'm going to be walking you through column by

to be walking you through column by column by column on how we get to this

column by column on how we get to this final value that we're going to be

final value that we're going to be eventually putting into our table here

eventually putting into our table here to thus calculate these values for the

to thus calculate these values for the counts per month so we go ahead and

counts per month so we go ahead and clear these cells to start and we're

clear these cells to start and we're going to start first by we want to

going to start first by we want to extract out the month from this job

extract out the month from this job posted date column so for this we can

posted date column so for this we can use the text function which we're sort

use the text function which we're sort of jumping ahead because we'll be doing

of jumping ahead because we'll be doing text functions upcoming lessons but

text functions upcoming lessons but there a good little sneak peek anyway we

there a good little sneak peek anyway we can plug in here something like a date

can plug in here something like a date time value and then from there we wanted

time value and then from there we wanted to Output what is the format text for

to Output what is the format text for well I know that if we do three M's it's

well I know that if we do three M's it's going to provide me the shorthand month

going to provide me the shorthand month of this additionally if I do fourms it's

of this additionally if I do fourms it's going to provide me the lonand month of

going to provide me the lonand month of this and there's a host of different

this and there's a host of different format codes that you can provide sh by

format codes that you can provide sh by this table here when I'm looking it up

this table here when I'm looking it up in something like perplexity that says

in something like perplexity that says that hey if you provide certain things

that hey if you provide certain things like if I provided a Double Y it's going

like if I provided a Double Y it's going to provide the two-digit year and so on

to provide the two-digit year and so on for other values you look this up in

for other values you look this up in something like chat GPT anyway get back

something like chat GPT anyway get back to this example itself I want to

to this example itself I want to actually autofill this all the way

actually autofill this all the way through it's not around any other

through it's not around any other columns that I can actually autofill all

columns that I can actually autofill all the way down and I don't want to sit

the way down and I don't want to sit here and drag it all the way so what I

here and drag it all the way so what I can do is select the column itself and

can do is select the column itself and then when it has these basically four

then when it has these basically four arrows I can then drag it where I want

arrows I can then drag it where I want I'm going to drag it right next to here

I'm going to drag it right next to here and then now actually autofill it all

and then now actually autofill it all the way down now that I have it complete

the way down now that I have it complete I'm just select this column again make

I'm just select this column again make sure I have those 4 hours again and drag

sure I have those 4 hours again and drag it back to the column it needs to be now

it back to the column it needs to be now seeing what you did here you probably

seeing what you did here you probably like Luke can't you use something like a

like Luke can't you use something like a count if in order to calculate the

count if in order to calculate the months now using this and you'd be

months now using this and you'd be correct with that remember call back for

correct with that remember call back for the count if s we can provide a criteria

the count if s we can provide a criteria range in this case we're going to

range in this case we're going to provide it column V and then for the

provide it column V and then for the criteria itself will provide the actual

criteria itself will provide the actual month and then actually dragging and

month and then actually dragging and dropping this all the way down once

dropping this all the way down once again my formatting got messed up so I'm

again my formatting got messed up so I'm put that thick outside border back on

put that thick outside border back on there anyway these values here for what

there anyway these values here for what we're going to get finally are the same

we're going to get finally are the same and so you really could stop this lesson

and so you really could stop this lesson right here and if you want to do this of

right here and if you want to do this of creating a new column and then just

creating a new column and then just using count ifs you can do that but this

using count ifs you can do that but this is a lesson on arrays so we're going to

is a lesson on arrays so we're going to get more complex with this in order how

get more complex with this in order how to use the arays in order to actually

to use the arays in order to actually calculate this without having to create

calculate this without having to create these extra columns so I'm going to go

these extra columns so I'm going to go ahead and hide this cuz we're not going

ahead and hide this cuz we're not going to use it so before we can actually

to use it so before we can actually summing up we need to get an array of

summing up we need to get an array of all the values that we'll say equal to

all the values that we'll say equal to January so so we'll start by creating

January so so we'll start by creating that text function it's going to be

that text function it's going to be slightly different before cuz we're

slightly different before cuz we're going to be making it out of array we

going to be making it out of array we want to actually select all the values

want to actually select all the values from H2 all the way down to the bottom

from H2 all the way down to the bottom we want to then go ahead and lock it we

we want to then go ahead and lock it we want it to be evaluating for that long

want it to be evaluating for that long month name so four lowercase M's and

month name so four lowercase M's and when I want to check if it's equal to in

when I want to check if it's equal to in our case we're looking for January we'll

our case we're looking for January we'll look up here at this U2 or U1 I got a

look up here at this U2 or U1 I got a typo up there update that to U1 anyway

typo up there update that to U1 anyway we now have okay that this value is true

we now have okay that this value is true right here and we can tell from row 11

right here and we can tell from row 11 that this is in January it is true so

that this is in January it is true so it's working out just fine so now if I

it's working out just fine so now if I tried to actually run a su product which

tried to actually run a su product which is what we're finally trying to do on

is what we're finally trying to do on all the contents of this array itself

all the contents of this array itself we'll do W2 uh hashtag we're going to

we'll do W2 uh hashtag we're going to get back zero because this isn't in the

get back zero because this isn't in the format that we want we actually need to

format that we want we actually need to convert this unfortunately although it

convert this unfortunately although it is on the back end is zero and on the

is on the back end is zero and on the actual functions themselves can't

actual functions themselves can't actually calculate it so we can do this

actually calculate it so we can do this by basically converting it and the first

by basically converting it and the first thing we can do actually is just we'll

thing we can do actually is just we'll put one negative sign and then I'll put

put one negative sign and then I'll put in that W2 hashtag and what this does is

in that W2 hashtag and what this does is it negates the Boolean values so

it negates the Boolean values so basically true which is normally a one

basically true which is normally a one it negates it and makes it negative one

it negates it and makes it negative one zero a negative Z is negative anyway we

zero a negative Z is negative anyway we need to actually apply two negative

need to actually apply two negative signs CU we don't want it to be negative

signs CU we don't want it to be negative one we want it to be positive one so

one we want it to be positive one so doing this one more time we now have

doing this one more time we now have positive ones in there so now we are

positive ones in there so now we are using some product because some product

using some product because some product I feel are better with arrays but we

I feel are better with arrays but we could use in this case where it's a

could use in this case where it's a single array we could use actual just

single array we could use actual just sum itself I didn't want to show that

sum itself I didn't want to show that and we get that value of 3102 which

and we get that value of 3102 which correlates to what I expect as the value

correlates to what I expect as the value but we're going to use some product

but we're going to use some product because as you'll find out in future

because as you'll find out in future lessons we're actually going to be

lessons we're actually going to be modifying it even further what's inside

modifying it even further what's inside of here and so we need this Su product

of here and so we need this Su product in order to do those anyway we get the

in order to do those anyway we get the same value of

same value of 3,12 so going back to our data tab let's

3,12 so going back to our data tab let's actually calculate this fully for all of

actually calculate this fully for all of these different values walking through

these different values walking through it step by step by step as we do

it step by step by step as we do previously we're going to start with our

previously we're going to start with our text function and we want to look at

text function and we want to look at that job posted date column I'm going go

that job posted date column I'm going go ahead and lock all those cells it's very

ahead and lock all those cells it's very important for this going be dragging and

important for this going be dragging and dropping that down and remember for the

dropping that down and remember for the format text to this we want it to be

format text to this we want it to be four lowercase M and in this we're

four lowercase M and in this we're checking whether it's equal to this

checking whether it's equal to this value here of V2 which is January and

value here of V2 which is January and I'm going to go ahead and actually lock

I'm going to go ahead and actually lock just that column pressing enter to make

just that column pressing enter to make sure it goes correctly yep we got True

sure it goes correctly yep we got True Value here for our row 15 value first

Value here for our row 15 value first thing we want to do is do that double

thing we want to do is do that double negation which we need to actually wrap

negation which we need to actually wrap these in this whole formula itself in

these in this whole formula itself in parenthesis in order to get our Z and

parenthesis in order to get our Z and one values and then finally we're going

one values and then finally we're going to wrap this all once again in Su

to wrap this all once again in Su product putting that closing parentheses

product putting that closing parentheses on there pressing enter get 3102 and

on there pressing enter get 3102 and then doing autofill all the way down we

then doing autofill all the way down we have all our values once again format is

have all our values once again format is messed up I'm going put that thick

messed up I'm going put that thick outside border now the other reason why

outside border now the other reason why we're using some product in this case is

we're using some product in this case is because in older versions of excel

because in older versions of excel before we had these uh modern dynamic

before we had these uh modern dynamic arrays some is not going to to be able

arrays some is not going to to be able to work over a raise and you actually

to work over a raise and you actually have to use some product so this allows

have to use some product so this allows us also to have a safe way to

us also to have a safe way to calculate using arrays and then give it

calculate using arrays and then give it to people that may be archaic and have

to people that may be archaic and have older versions of excel all right it's

older versions of excel all right it's your turn now to jump into some practice

your turn now to jump into some practice problems to get more familiar with

problems to get more familiar with working with arrays inside of formulas

working with arrays inside of formulas in the next lesson we're going to be

in the next lesson we're going to be getting into probably I think one of the

getting into probably I think one of the most funnest types of functions lookup

most funnest types of functions lookup functions like vlookup and X look up and

functions like vlookup and X look up and things like that which are super helpful

things like that which are super helpful for data analysis all right with that

for data analysis all right with that I'll see you in the next

one lookup functions are one of the most I'd say funnest functions whenever

I'd say funnest functions whenever you're learning to be a freak in the

you're learning to be a freak in the sheets specifically we're going to be

sheets specifically we're going to be focusing on three different lookup

focusing on three different lookup functions vlookup H lookup and X lookup

functions vlookup H lookup and X lookup V and V lookup stands for vertical H and

V and V lookup stands for vertical H and H lookup stands for horizont and x and x

H lookup stands for horizont and x and x look up just uh they wouldn't be

look up just uh they wouldn't be different in order to learn about these

different in order to learn about these functions we're going to be performing

functions we're going to be performing some data analysis and if you recall

some data analysis and if you recall back from our math and statistical

back from our math and statistical functions lessons we found out what the

functions lessons we found out what the median Min and Max salaries were but for

median Min and Max salaries were but for the things like the Min and Max what

the things like the Min and Max what were those different job postings that

were those different job postings that correlated to that well based on the

correlated to that well based on the structure of our data set we can use the

structure of our data set we can use the vlookup and also X lookup functions in

vlookup and also X lookup functions in order to find this out now because of

order to find this out now because of the structure of our data we're going to

the structure of our data we're going to have to do something different in order

have to do something different in order to implement H lookups and for this

to implement H lookups and for this we're going to be able to get out or

we're going to be able to get out or extract out horizontal type data we're

extract out horizontal type data we're going to basically transpose it into a

going to basically transpose it into a vertical format using H lookup but if

vertical format using H lookup but if there's anything you remember from this

there's anything you remember from this lesson it's that of X lookup this one is

lesson it's that of X lookup this one is the most dynamic and flexible and how it

the most dynamic and flexible and how it can be used and we're going to be doing

can be used and we're going to be doing in a final example using this in order

in a final example using this in order to bucket our salary data set allowing

to bucket our salary data set allowing us to categorize it into different

us to categorize it into different ranges and whether it has data or not

ranges and whether it has data or not all using xlup for this we can start

all using xlup for this we can start using the lookup functions workbook we

using the lookup functions workbook we have two main tabs in this data and

have two main tabs in this data and dataor 2 Data ones where we're going to

dataor 2 Data ones where we're going to start in first for this section on

start in first for this section on vlookups so for this we're going to be

vlookups so for this we're going to be using that job posting data set I've

using that job posting data set I've hidden any unnecessary columns and we're

hidden any unnecessary columns and we're going to be filling in this table right

going to be filling in this table right here so what I'm trying to do with this

here so what I'm trying to do with this is fill in based on this Min as you can

is fill in based on this Min as you can see the formula for Min the formula for

see the formula for Min the formula for max and the formula for median where we

max and the formula for median where we actually calculate this from the Sal

actually calculate this from the Sal year average column we want to then

year average column we want to then extract out based on these values the

extract out based on these values the company name a job title associated with

company name a job title associated with it and then the country associated with

it and then the country associated with it so we're going to start with V lookup

it so we're going to start with V lookup first and V lookup looks in a vertical

first and V lookup looks in a vertical type format specifically it says it

type format specifically it says it looks for a value in the leftmost column

looks for a value in the leftmost column of a table and then returns a value in

of a table and then returns a value in the same Row from a column you specify

the same Row from a column you specify so for the first value of this we want

so for the first value of this we want to provide the lookup value in this case

to provide the lookup value in this case we want to look up 15,000 from that

we want to look up 15,000 from that salary year average column then from

salary year average column then from there we need to provide the table array

there we need to provide the table array now remember for this it needs to be the

now remember for this it needs to be the leftmost column of the table and we want

leftmost column of the table and we want to get columns M and O I'm going to

to get columns M and O I'm going to select column o because if we start at M

select column o because if we start at M and try to go down it's going to mess up

and try to go down it's going to mess up cuz there's blank in it so I'm just

cuz there's blank in it so I'm just going to do control shift over and then

going to do control shift over and then control shift down to select all the

control shift down to select all the data and then change this a column to M

data and then change this a column to M instead the next thing we need to

instead the next thing we need to specify is the column index number and

specify is the column index number and right now we're in column M so that

right now we're in column M so that would be the First Column so MN o we're

would be the First Column so MN o we're in the third column you can imagine if

in the third column you can imagine if we have a buttload of columns what kind

we have a buttload of columns what kind of problems are going to run into so

of problems are going to run into so we'll get to that when we get to it okay

we'll get to that when we get to it okay now they have a range lookup we're going

now they have a range lookup we're going to leave that blank for the time being

to leave that blank for the time being we're just going to execute this formula

we're just going to execute this formula as is and for this we're getting an NA

as is and for this we're getting an NA error if we actually click into it value

error if we actually click into it value not available error and why is that well

not available error and why is that well if we actually go back to that vlookup

if we actually go back to that vlookup function in the definition that it

function in the definition that it provides for it the last statement is by

provides for it the last statement is by default the table must be sorted in

default the table must be sorted in ascending order right now our salary

ascending order right now our salary values are not sorted so it's having

values are not sorted so it's having issues going through it and actually

issues going through it and actually finding that 15,000 because it's

finding that 15,000 because it's unsorted anyway we're not going to

unsorted anyway we're not going to actually sort that table that's going to

actually sort that table that's going to be too much work we can actually now go

be too much work we can actually now go into that fourth parameter of range

into that fourth parameter of range lookup and instead of doing an

lookup and instead of doing an approximate match which was the default

approximate match which was the default we're going to do an exact match by

we're going to do an exact match by providing false in that case we find

providing false in that case we find that net two Source Inc is the company

that net two Source Inc is the company name of the job with 15,000 now I want

name of the job with 15,000 now I want to autofill for this but we need to

to autofill for this but we need to actually lock some cells real quick so

actually lock some cells real quick so I'm going to lock this right now by

I'm going to lock this right now by pressing F4 then from there we'll drag

pressing F4 then from there we'll drag it down now one thing to note on vlookup

it down now one thing to note on vlookup X lookup and also H lookup this is just

X lookup and also H lookup this is just going to return the first value so in

going to return the first value so in this case of this 115,000 it says it's

this case of this 115,000 it says it's Volt Technical Resources however I do a

Volt Technical Resources however I do a contrl f of

contrl f of 115,000 we'll find that yes it's at row

115,000 we'll find that yes it's at row 19 for Volt Technical Resources the

19 for Volt Technical Resources the first one that provides but it's also in

first one that provides but it's also in row 42 with northr Gan so it's only

row 42 with northr Gan so it's only providing that first match now what

providing that first match now what happens if we wanted to next get things

happens if we wanted to next get things like the job title or the country itself

like the job title or the country itself well if I were put in the first two

well if I were put in the first two values the lookup value and then the

values the lookup value and then the table array what will we put for the

table array what will we put for the column index number remember in vlookup

column index number remember in vlookup the leftmost column of the table itself

the leftmost column of the table itself is what we're going to be looking up but

is what we're going to be looking up but however columns A and K are even well

however columns A and K are even well more left of that table so unfortunately

more left of that table so unfortunately we can't use vck up for this but we will

we can't use vck up for this but we will be using X lookup for this that's why

be using X lookup for this that's why I'm going to recommend it over vlookup

I'm going to recommend it over vlookup but I think you guys start at the Bas

but I think you guys start at the Bas phics

first however before we get into that we're going to now shift gears and cover

we're going to now shift gears and cover H look up in order to look up values in

H look up in order to look up values in a horizontally oriented table this case

a horizontally oriented table this case this is horizontally oriented because we

this is horizontally oriented because we have things like the months across the

have things like the months across the Horizon if you will and then we have in

Horizon if you will and then we have in the columns in the column standpoint we

the columns in the column standpoint we have the job titles of the different

have the job titles of the different ones of data analyst and your data analy

ones of data analyst and your data analy so on now the data in this table is

so on now the data in this table is calculated using the data from the data

calculated using the data from the data tab in order to get the counts of months

tab in order to get the counts of months and you've previously seen this in the

and you've previously seen this in the last lesson where we went in that hard

last lesson where we went in that hard example of some product where we now go

example of some product where we now go through and do some array multiplication

through and do some array multiplication in order to find out the different

in order to find out the different counts for the job titles based on a

counts for the job titles based on a month anyway for this H look up we want

month anyway for this H look up we want to look up based on a month what is the

to look up based on a month what is the associated job count for a specific job

associated job count for a specific job type

type so let's say we want to just look at

so let's say we want to just look at that may column well we can put in h

that may column well we can put in h lookup and this looks for a value in the

lookup and this looks for a value in the top row of a table or array of values

top row of a table or array of values and Returns the value in the same column

and Returns the value in the same column from a row you specify so only selects

from a row you specify so only selects from that top row for this we provide a

from that top row for this we provide a lookup value in this case let's say

lookup value in this case let's say we're looking up January then from there

we're looking up January then from there we provide the table array itself we can

we provide the table array itself we can go and just select this data now I could

go and just select this data now I could technically I could select all this data

technically I could select all this data because it's just going to go to the

because it's just going to go to the associated column associated with this

associated column associated with this so that we included row a doesn't really

so that we included row a doesn't really matter then from there we want the row

matter then from there we want the row index number what value do we want from

index number what value do we want from this January do we want data analyst

this January do we want data analyst senior data analyst senior data

senior data analyst senior data scientist so we can just count down what

scientist so we can just count down what we want we'll start with data analyst

we want we'll start with data analyst first so we'll put in that's the second

first so we'll put in that's the second row in this so let's try to enter this

row in this so let's try to enter this and for this we get 753 which if you go

and for this we get 753 which if you go back to this we're doing Jan A1 through

back to this we're doing Jan A1 through M7 and then the second one so why are we

M7 and then the second one so why are we getting

getting 753 well once again this has to do with

753 well once again this has to do with the range lookup we're doing an

the range lookup we're doing an approximate match similar to vlookup it

approximate match similar to vlookup it expects that these values for that top

expects that these values for that top row are in in this case alphabetical

row are in in this case alphabetical order in order to perform that

order in order to perform that approximate maass

approximate maass these aren't in alphabetical order

these aren't in alphabetical order they're actually in chronological order

they're actually in chronological order so instead we need to specify false now

so instead we need to specify false now running it we get the correct value of

running it we get the correct value of 982 now we can also apply this to a

982 now we can also apply this to a situation where maybe we want to

situation where maybe we want to transpose these values into this new

transpose these values into this new table that we have here on month and

table that we have here on month and count and then up here I'm going to also

count and then up here I'm going to also just specify what we're looking at we're

just specify what we're looking at we're going to look at data analyst now with

going to look at data analyst now with our H lookup we're going to be providing

our H lookup we're going to be providing that lookup value the table array and

that lookup value the table array and then the row index number say if we

then the row index number say if we wanted to go in here instead of data

wanted to go in here instead of data analysts we wanted to look at data

analysts we wanted to look at data engineer instead how can we get this to

engineer instead how can we get this to update well we can use another function

update well we can use another function for this specifically we can use the

for this specifically we can use the match function for this and this Returns

match function for this and this Returns the relative position of an item in

the relative position of an item in Array that matches a specified value in

Array that matches a specified value in a specified order so in this case I want

a specified order so in this case I want to look up data engineers in the array

to look up data engineers in the array from a 2 to A7 it's providing me a one

from a 2 to A7 it's providing me a one cuz it's not it's doing the approximate

cuz it's not it's doing the approximate match again once again they're not in

match again once again they're not in alphatic so I have to specify exact

alphatic so I have to specify exact match using zero okay and now I get data

match using zero okay and now I get data engineers in the fifth place I'm also

engineers in the fifth place I'm also going to move this column over and make

going to move this column over and make this a little bit bigger going back into

this a little bit bigger going back into that H lookup that we're going to use

that H lookup that we're going to use for this we're going to provide that

for this we're going to provide that lookup value which we want to actually

lookup value which we want to actually lock by pressing F4 then we're going to

lock by pressing F4 then we're going to provide the table once again I said you

provide the table once again I said you can select that a column if want or not

can select that a column if want or not we're going to lock all these values as

we're going to lock all these values as well because we'll be dragging it down

well because we'll be dragging it down from there we'll be providing the row

from there we'll be providing the row index number which we've calculated

index number which we've calculated right here in this P based on that match

right here in this P based on that match that we're performing want to lock this

that we're performing want to lock this as well and as far as the range lookup

as well and as far as the range lookup well we want to do exact match running

well we want to do exact match running this we get an NA error because I was

this we get an NA error because I was silly and the lookup value we want to

silly and the lookup value we want to actually do is for the month of January

actually do is for the month of January not the data engineer actual lookup

not the data engineer actual lookup confusing this with h lookup sorry about

confusing this with h lookup sorry about that so we'll put in 03 for this instead

that so we'll put in 03 for this instead and then running it and now we're

and then running it and now we're getting back to 236 which is not that

getting back to 236 which is not that Engineers thing we're one off and this

Engineers thing we're one off and this has to do with how we did our match up

has to do with how we did our match up here which specified A2 to A7 basically

here which specified A2 to A7 basically we're counting down from the second one

we're counting down from the second one where in h lookup we included all the

where in h lookup we included all the way up to that first row so this is just

way up to that first row so this is just a simple fix by changing this one up

a simple fix by changing this one up here to A1 and now our values update

here to A1 and now our values update appropriately and then I can go ahead

appropriately and then I can go ahead and just drag and drop this all the way

and just drag and drop this all the way down and once again going to get into

down and once again going to get into some troubleshooting because this is all

some troubleshooting because this is all the same values and that's because I

the same values and that's because I fully locked this actual month number

fully locked this actual month number and instead I wanted to press F4 and

and instead I wanted to press F4 and only lock the column of O now finally

only lock the column of O now finally getting to the final answer we have it

getting to the final answer we have it and we can confirm this that data

and we can confirm this that data Engineers should have 396 on the

Engineers should have 396 on the December value that's correct and now we

December value that's correct and now we can do things like this where I can go

can do things like this where I can go in and say hey instead I want to look at

in and say hey instead I want to look at Dana analyst and it will update for this

Dana analyst and it will update for this instead now once again with h lookup we

instead now once again with h lookup we run into issues like vlookup if there's

run into issues like vlookup if there's values Above This top row I can't really

values Above This top row I can't really think of that any applications that

think of that any applications that that's applicable in this but it is a

that's applicable in this but it is a limitation anyway this is why we're

limitation anyway this is why we're going to be shifting to the next

topic and that is using xlookup to now based on these salaries that we were

based on these salaries that we were previously trying to identify

previously trying to identify identifying a job title and a country

identifying a job title and a country associated with it so what is the

associated with it so what is the definition of xlup and this searches a

definition of xlup and this searches a range or an array for a match and

range or an array for a match and Returns the corresponding item from a

Returns the corresponding item from a second range or array by default an

second range or array by default an exact match is used that's pretty

exact match is used that's pretty awesome considering all the issues ran

awesome considering all the issues ran to with h look up and V lookup anyway

to with h look up and V lookup anyway instead of using a single table we're

instead of using a single table we're going to be using multiple ranges for

going to be using multiple ranges for this let's get into it first we're going

this let's get into it first we're going to provide the lookup value which in

to provide the lookup value which in this case is 15,000 and then we want to

this case is 15,000 and then we want to provide the lookup array so we need to

provide the lookup array so we need to select this entire M column here for

select this entire M column here for what we want to actually look up but we

what we want to actually look up but we have these blanks in here so I'm going

have these blanks in here so I'm going to just do a trick of selecting the O

to just do a trick of selecting the O column selecting all the way down and

column selecting all the way down and then from here I'm going to just go in

then from here I'm going to just go in and actually change these values to M

and actually change these values to M instead now we want this to remain the

instead now we want this to remain the same so I'm going to press F4 to

same so I'm going to press F4 to actually lock this now that was our

actually lock this now that was our lookup array now we want to get into

lookup array now we want to get into what return array or where we want

what return array or where we want actually look to see and that's to the

actually look to see and that's to the left of this in this job title short

left of this in this job title short column these arrays have to match up in

column these arrays have to match up in where they are uh where you're selecting

where they are uh where you're selecting them so in this case I selected over

them so in this case I selected over here in the second row I need to do the

here in the second row I need to do the same for the job title then from there

same for the job title then from there pressing control shift down I select all

pressing control shift down I select all of them once again I'm going to lock all

of them once again I'm going to lock all of these by pressing F4 now let's close

of these by pressing F4 now let's close the parentheses and go ahead and execute

the parentheses and go ahead and execute it we can see see that data engineer is

it we can see see that data engineer is the lowest paid salary with this 15,000

the lowest paid salary with this 15,000 now we can also add in this default

now we can also add in this default parameter in case you can't find a value

parameter in case you can't find a value you can put not found but in our case we

you can put not found but in our case we made or we calculated this minmax and

made or we calculated this minmax and median from our data set so technically

median from our data set so technically this isn't really necessary anyway let's

this isn't really necessary anyway let's see what the other job titles are for

see what the other job titles are for these Max and median looks like it's

these Max and median looks like it's data scientist and then the data

data scientist and then the data engineer for the median which is that

engineer for the median which is that first one that appears right over here

first one that appears right over here in row 19

in row 19 now doing the same for the country I'm

now doing the same for the country I'm going to go ahead and just copy and

going to go ahead and just copy and paste that formula in that we had from

paste that formula in that we had from the other cell and I'm going to just

the other cell and I'm going to just adjust this now to use column K instead

adjust this now to use column K instead of column A for the actual return array

of column A for the actual return array okay with that updated press enter and

okay with that updated press enter and we can see Brazil has the lowest one and

we can see Brazil has the lowest one and what is the highest one United States

what is the highest one United States and also the median United

States all right we're going to crank this up a notch and now we're going to

this up a notch and now we're going to jump into actually bucketing our salary

jump into actually bucketing our salary using X lookup specifically I want to

using X lookup specifically I want to use this table that I've created in

use this table that I've created in order to properly categorize different

order to properly categorize different values based on this so in this case we

values based on this so in this case we have this value of 140,000 it's going to

have this value of 140,000 it's going to fall into our bucket of

fall into our bucket of 125,00 th000 there's no data in this one

125,00 th000 there's no data in this one so I want to say no data this one's

so I want to say no data this one's greater than 200,000 so I want to say

greater than 200,000 so I want to say greater than 200,000 so for this we're

greater than 200,000 so for this we're going to be creating a new column column

going to be creating a new column column Q and we're going to call it salary year

Q and we're going to call it salary year bucket I'm going to go ahead also and

bucket I'm going to go ahead also and cod this column o for the time being we

cod this column o for the time being we don't really need this for this now

don't really need this for this now technically you already have the

technically you already have the requisite knowledge in order to bucket

requisite knowledge in order to bucket it I could put in a nested IF function

it I could put in a nested IF function similar to below and it has 1 2 3 four

similar to below and it has 1 2 3 four five if you will nested ifs to go

five if you will nested ifs to go through and basically check each of the

through and basically check each of the different values as it's going through

different values as it's going through in order to bucket it appropriately

in order to bucket it appropriately in this case it correctly categorizes it

in this case it correctly categorizes it and then if I wanted to I can drag and

and then if I wanted to I can drag and drop it all the way down but now this

drop it all the way down but now this sheet is filled with all of these nested

sheet is filled with all of these nested if statements this is really going to

if statements this is really going to slow your spreadsheet down so I don't

slow your spreadsheet down so I don't recommend doing this also building

recommend doing this also building something this like this you've now

something this like this you've now hardcoded in your values into it and

hardcoded in your values into it and what is if you want to change this later

what is if you want to change this later you'd have to update all your formulas

you'd have to update all your formulas it's a mess don't recommend doing it so

it's a mess don't recommend doing it so I'm going to select all this control

I'm going to select all this control shift down and then just delete it all

shift down and then just delete it all instead we're going to be using X lookup

instead we're going to be using X lookup for this specifically we need to look up

for this specifically we need to look up the lookup value which is going to be

the lookup value which is going to be the same one that we did before that M2

the same one that we did before that M2 and then we want to look up the lookup

and then we want to look up the lookup array now I conveniently made this table

array now I conveniently made this table here that it's providing values at if

here that it's providing values at if you will the higher end of the bucket so

you will the higher end of the bucket so we're not going to necessarily do an

we're not going to necessarily do an exact match for this we'll get to that

exact match for this we'll get to that in a second anyway now we want to look

in a second anyway now we want to look at what do we want to return the return

at what do we want to return the return array which is on the left side of this

array which is on the left side of this table that's the values I actually want

table that's the values I actually want to return back in that column value if

to return back in that column value if not found is not necessarily applicable

not found is not necessarily applicable so now getting into how we're actually

so now getting into how we're actually going to match based on these salary

going to match based on these salary buckets based on these values

buckets based on these values highlighted in this T column right here

highlighted in this T column right here well we need to do not exact match we

well we need to do not exact match we need to do exact match or next larger

need to do exact match or next larger item and this is the value of one

item and this is the value of one basically in this case of this 12850

basically in this case of this 12850 it's going to look for initially an

it's going to look for initially an exact match of 128 of 50 and it's going

exact match of 128 of 50 and it's going to see that nothing's there so then it's

to see that nothing's there so then it's going to look for the next larger item

going to look for the next larger item which is that 200,000 so therefore it's

which is that 200,000 so therefore it's going to return as we're going to find

going to return as we're going to find out the

out the 125,000 to

125,000 to 200,000 now I can try to drag and drop

200,000 now I can try to drag and drop this down but I'm going to run into

this down but I'm going to run into errors because I didn't lock my formulas

errors because I didn't lock my formulas correctly so I need to go back in lock

correctly so I need to go back in lock that s column with F4 and lock that t

that s column with F4 and lock that t column with F4 and then I'm just going

column with F4 and then I'm just going to autofill all the way down and now we

to autofill all the way down and now we have all of our different job postings

have all of our different job postings bucketed into these different salaries

bucketed into these different salaries so instead I wanted to go through and

so instead I wanted to go through and actually change this to be

actually change this to be 150k and then match this to

150k and then match this to 150,000 I go do it and it would update

150,000 I go do it and it would update appropriately I also need to update this

appropriately I also need to update this column as well but now it all updates

column as well but now it all updates and it's in one single location so this

and it's in one single location so this is really the power of using that X

is really the power of using that X lookup over the ifs in order to perform

lookup over the ifs in order to perform this type of bucketing all right you now

this type of bucketing all right you now got some practice problems go through

got some practice problems go through and get more familiar with using these

and get more familiar with using these different Lookout functions as I said

different Lookout functions as I said before make sure you're prioritizing

before make sure you're prioritizing understanding that X lookup it's the

understanding that X lookup it's the most powerful but the one caveat to X

most powerful but the one caveat to X lookup is that it was introduced around

lookup is that it was introduced around the 2020s so anybody using once again an

the 2020s so anybody using once again an archaic version of excel Beyond or

archaic version of excel Beyond or before this year they're going to have

before this year they're going to have compatibility issues using this so

compatibility issues using this so that's why you need to also be familiar

that's why you need to also be familiar with that V lookup and also H lookup are

with that V lookup and also H lookup are going to encounter them in the while all

going to encounter them in the while all right with that I'll see you in the next

right with that I'll see you in the next one where we're jumping into text

functions now I know this is a course on data analysis but text functions are

data analysis but text functions are actually imperative for performing

actually imperative for performing analysis on Text data and for this we're

analysis on Text data and for this we're going to be working in this lesson on a

going to be working in this lesson on a data set of job applicants and we're

data set of job applicants and we're going to take it a step further using

going to take it a step further using text functions in order to analyze

text functions in order to analyze specifically for our final analysis we

specifically for our final analysis we have information on the different skills

have information on the different skills that each one of these job applicants

that each one of these job applicants knows so we're going to be able to

knows so we're going to be able to perform an analysis to see what are the

perform an analysis to see what are the most common skills from these applicants

most common skills from these applicants but before we get to that final analysis

but before we get to that final analysis we first need to beef up our knowledge

we first need to beef up our knowledge we're going to focus on three main areas

we're going to focus on three main areas the first one is text combination we're

the first one is text combination we're going to be working to combine different

going to be working to combine different columns into a single column from there

columns into a single column from there we'll move into the second one of of

we'll move into the second one of of text extraction being able to out of a

text extraction being able to out of a single column extract multiple values

single column extract multiple values and finally in the third one performing

and finally in the third one performing some sort of text search in order to

some sort of text search in order to also extract out in this case we're

also extract out in this case we're going to be extracting out the state

going to be extracting out the state name from an address that contains a

name from an address that contains a city state and area code so for this you

city state and area code so for this you can start up by opening up the text

can start up by opening up the text functions workbook and in the data tab

functions workbook and in the data tab we have this data set which you haven't

we have this data set which you haven't seen before it's only about 20 R and

seen before it's only about 20 R and includes a list of job applicants now

includes a list of job applicants now we're not using the full data science

we're not using the full data science job posting data set because a lot of

job posting data set because a lot of the examples we're going to do in this

the examples we're going to do in this it would be basically bogged down your

it would be basically bogged down your Excel spreadsheet so especially how

Excel spreadsheet so especially how we're going to be implementing these

we're going to be implementing these it's really meant to be used for smaller

it's really meant to be used for smaller data sets you may be like Luke what ends

data sets you may be like Luke what ends if a bigger data set and need to clean

if a bigger data set and need to clean up the text well that's where power

up the text well that's where power query comes in which we'll be covering

query comes in which we'll be covering in the advanced chapters so stick around

in the advanced chapters so stick around for that

anyway moving into text combination we want to Target these columns right here

want to Target these columns right here f and g we want to combine them into one

f and g we want to combine them into one line to have a single address so I'm

line to have a single address so I'm going to go ahead and hide this column H

going to go ahead and hide this column H for the time being we're going to be

for the time being we're going to be putting that full address in column J

putting that full address in column J and this one's pretty simple all we're

and this one's pretty simple all we're going to do is text join which

going to do is text join which concatenates a list or range of text

concatenates a list or range of text strings using a delimiter the first

strings using a delimiter the first thing I need to specify is the delimiter

thing I need to specify is the delimiter how am I going to to separate that

how am I going to to separate that street and the city state all I want to

street and the city state all I want to do is a space so I'll do that en closing

do is a space so I'll do that en closing it in double quotes next is ignore empty

it in double quotes next is ignore empty basically if there was an empty cell in

basically if there was an empty cell in here it would just ignore this and it's

here it would just ignore this and it's not going to input multiple different

not going to input multiple different spaces between it just ignore it so we

spaces between it just ignore it so we want to in that case we're just going to

want to in that case we're just going to put in true the final one is text and we

put in true the final one is text and we can specify you could do text and then

can specify you could do text and then comma and then text to um that's really

comma and then text to um that's really Vose I don't really like doing that

Vose I don't really like doing that instead I'm just going to select the

instead I'm just going to select the range of F2 to G2 now we can see that

range of F2 to G2 now we can see that the address is fully concatenated and we

the address is fully concatenated and we can drag it on down and it works for all

can drag it on down and it works for all of

it now the opposite of combo is extraction which we going to get into

extraction which we going to get into next and in this case we're just going

next and in this case we're just going to use a single column and extract out

to use a single column and extract out multiple values in this case we have

multiple values in this case we have this full name column we want to extract

this full name column we want to extract out the first name and the last name go

out the first name and the last name go ahead and hide these other columns we're

ahead and hide these other columns we're not using

not using in this case we're going to specify the

in this case we're going to specify the text split and it says it splits text

text split and it says it splits text into rows or columns using delimiters so

into rows or columns using delimiters so we'll first start by specifying the text

we'll first start by specifying the text which is B2 in this case and then the

which is B2 in this case and then the column delimiter which in our case is

column delimiter which in our case is going to be that space once again we're

going to be that space once again we're going to use that double quotes for that

going to use that double quotes for that space and then end Double quotes and

space and then end Double quotes and then this is going to be a dynamic array

then this is going to be a dynamic array and it has these two values here now

and it has these two values here now dragging this all down down we see that

dragging this all down down we see that it fills in for all these different

it fills in for all these different names now we just split text there also

names now we just split text there also could be cases where we maybe want to

could be cases where we maybe want to extract out certain amount of values or

extract out certain amount of values or certain amount of text from a column in

certain amount of text from a column in this case we also have our application

this case we also have our application ID number which is a combination of

ID number which is a combination of letters and numbers but as you can see

letters and numbers but as you can see from this there's some values in here

from this there's some values in here that are actually repeating sometimes we

that are actually repeating sometimes we want to refer to this the shorthand of

want to refer to this the shorthand of this and let's say we only want to get

this and let's say we only want to get the last three digits of the applicant

the last three digits of the applicant ID because we know that's always

ID because we know that's always different well in this case we can

different well in this case we can specify the right function and it

specify the right function and it Returns the specified number of

Returns the specified number of characters from the end of the text

characters from the end of the text string we specify the text itself and

string we specify the text itself and then the number of characters in this

then the number of characters in this case we can just say three and it's

case we can just say three and it's going to provide back that 548 we could

going to provide back that 548 we could also just change that to include all the

also just change that to include all the text numbers in case this number gets

text numbers in case this number gets bigger than that and then go ahead and

bigger than that and then go ahead and drag it all the way down

now one last one before we get into actually performing that analysis we

actually performing that analysis we want to we want to go through and

want to we want to go through and extract out the state from this city

extract out the state from this city state and zip and as you notice from all

state and zip and as you notice from all these they have a common format in that

these they have a common format in that the city has a comma and then the state

the city has a comma and then the state starts and then there's another comma

starts and then there's another comma following that so we're going to be

following that so we're going to be using those basically delimiters if you

using those basically delimiters if you will in order to identify where we

will in order to identify where we should potentially extract out this

should potentially extract out this state value from where this state these

state value from where this state these two L twetter value so the approach

two L twetter value so the approach we're going to use for this is as we go

we're going to use for this is as we go through this is we're going to find the

through this is we're going to find the location first of that first Common

location first of that first Common space before this the next we'll find

space before this the next we'll find where it actually ends and then finally

where it actually ends and then finally well using those values will actually

well using those values will actually extract out using the mid function that

extract out using the mid function that state abbreviation so the first thing we

state abbreviation so the first thing we need to do is find that comma and this

need to do is find that comma and this Returns the starting position of one

Returns the starting position of one text string within another text string

text string within another text string so in this I'm going to specify that

so in this I'm going to specify that we're the fine text we're going to be

we're the fine text we're going to be looking for is the comma itself and

looking for is the comma itself and we're going to be looking at within text

we're going to be looking at within text obviously G2 now we also need to find

obviously G2 now we also need to find the second comma in this we can use that

the second comma in this we can use that find function again specifically we're

find function again specifically we're finding that comma specifying that

finding that comma specifying that within text of G2 and now we have the

within text of G2 and now we have the second optional parameter of start

second optional parameter of start number we want to start from nine which

number we want to start from nine which is the first one we found this in

is the first one we found this in running this we get nine now the problem

running this we get nine now the problem here is because we're starting as the

here is because we're starting as the exact number that the comma actually

exact number that the comma actually starts that's why we're getting that

starts that's why we're getting that back that value of nine we need slightly

back that value of nine we need slightly actually bigger than nine but anyway

actually bigger than nine but anyway we'll fix that in a bit instead let's

we'll fix that in a bit instead let's actually get into extracting out that or

actually get into extracting out that or at least trying to extract out that CA

at least trying to extract out that CA of this value and then we'll fix that

of this value and then we'll fix that issue in cell R2 so for this we're going

issue in cell R2 so for this we're going to be using the mid function which which

to be using the mid function which which similar to that right function is

similar to that right function is Returns the characters from the middle

Returns the characters from the middle of a text string given a starting

of a text string given a starting position and length so in this case we

position and length so in this case we want to extract out G2 and we'll provide

want to extract out G2 and we'll provide it the start number of well what's

it the start number of well what's valuable in Q2 and the number of

valuable in Q2 and the number of characters and for right now we'll just

characters and for right now we'll just put in we know we want to extract out

put in we know we want to extract out two so we're going to put in two now

two so we're going to put in two now we're running into issues we're only

we're running into issues we're only getting back a comma if will and if we

getting back a comma if will and if we actually make this longer to actually

actually make this longer to actually zoom in on here we get commas space CA

zoom in on here we get commas space CA now when providing four and this has to

now when providing four and this has to do with right here this value on the

do with right here this value on the start number isn't correct this nine

start number isn't correct this nine right here is exactly at the comma we

right here is exactly at the comma we need to actually specify for that start

need to actually specify for that start number of where the C is and these are

number of where the C is and these are all two spaces over so I'm going to come

all two spaces over so I'm going to come in here and I'm just going to modify

in here and I'm just going to modify this shortly and add two to this this is

this shortly and add two to this this is also going to fix our previous one that

also going to fix our previous one that we had when finding this of 13 because

we had when finding this of 13 because 13 now has all the way over and then

13 now has all the way over and then finally that mid is fixed we can change

finally that mid is fixed we can change this now to back to two now you know me

this now to back to two now you know me I don't like hardcoding values something

I don't like hardcoding values something like this to and really what we're doing

like this to and really what we're doing here is we're doing adding two based on

here is we're doing adding two based on the length of the comma and then the

the length of the comma and then the space after it so there's two characters

space after it so there's two characters in there two this is still that 11 value

in there two this is still that 11 value that we saw before similarly inside of

that we saw before similarly inside of our mid function I don't like doing this

our mid function I don't like doing this two here because States maybe could be

two here because States maybe could be more than two so I don't want to hold it

more than two so I don't want to hold it necessarily to that so instead I'm going

necessarily to that so instead I'm going to do R2 minus Q2 which in our case is

to do R2 minus Q2 which in our case is going to be two and we have California

going to be two and we have California all right now we can take all the

all right now we can take all the different values actually drag it on

different values actually drag it on down and we get all of our states

down and we get all of our states extracted from this

all right diving into our final analysis we're actually combine all of these

we're actually combine all of these different functions we just learned

different functions we just learned about specifically with this data set we

about specifically with this data set we have this column H right here and it's a

have this column H right here and it's a list of different skills that each one

list of different skills that each one of these job applicants have we want to

of these job applicants have we want to combine this and aggregate this in order

combine this and aggregate this in order to analyze the most common skills for

to analyze the most common skills for this we're going to have to walk through

this we're going to have to walk through four different steps in order to get

four different steps in order to get this into our final visualization that

this into our final visualization that we can actually visualize and see here

we can actually visualize and see here so I'm going to go ahead and clear all

so I'm going to go ahead and clear all these values so we can get started

these values so we can get started actually doing this the first thing I

actually doing this the first thing I want to do is actually combine all of

want to do is actually combine all of these values into a single long text

these values into a single long text string and we're already having the

string and we're already having the separator of a comma and space between

separator of a comma and space between each skill so we're going to use that

each skill so we're going to use that same separator to continue separating

same separator to continue separating this so using text join we're going to

this so using text join we're going to first specify the delimiter of that

first specify the delimiter of that comma and a space it's asking if I want

comma and a space it's asking if I want to ignore those hidden or empty cells I

to ignore those hidden or empty cells I do and then finally we need to provide

do and then finally we need to provide the actual text itself so we'll go down

the actual text itself so we'll go down through and select in our data tab H2 to

through and select in our data tab H2 to h21 going back up into the formula bar

h21 going back up into the formula bar closing this parenthesis and then

closing this parenthesis and then pressing an enter look I have a like

pressing an enter look I have a like slight typo in here I need to actually

slight typo in here I need to actually put double quotes around both of them

put double quotes around both of them you can't mix double and single quotes

you can't mix double and single quotes now we have this super long list uh that

now we have this super long list uh that has all of our different skills in it it

has all of our different skills in it it looks like it's properly delimited now

looks like it's properly delimited now that we have all these values in one

that we have all these values in one cell we can then use the text split

cell we can then use the text split function to now separate this into

function to now separate this into different cells because we're going to

different cells because we're going to want to then move into transposing it

want to then move into transposing it next and for this once again the

next and for this once again the delimiter we're using is that comma and

delimiter we're using is that comma and space running this we have all the

space running this we have all the different values separated out by

different values separated out by different cells so now almost there we

different cells so now almost there we need to get into making a table

need to get into making a table right here basically having skills in

right here basically having skills in the left hand column and then the counts

the left hand column and then the counts of those skills from what's above here

of those skills from what's above here so first thing we need to do is get the

so first thing we need to do is get the unique values of this but if we just run

unique values of this but if we just run unique on that row six we're going to

unique on that row six we're going to run into an issue to where it actually

run into an issue to where it actually goes out to the right and actually

goes out to the right and actually doesn't get the unique values for all

doesn't get the unique values for all these so the first thing we need to do

these so the first thing we need to do is actually

is actually transpose which moving it from

transpose which moving it from horizontal to vertic vertical of that

horizontal to vertic vertical of that row six okay so it's now up and down all

row six okay so it's now up and down all the way now in this case we want to run

the way now in this case we want to run the unique function on this to extract

the unique function on this to extract out all those unique values and

out all those unique values and scrolling down looks like we have all

scrolling down looks like we have all the unique values it does have a zero

the unique values it does have a zero because that we did that row six and so

because that we did that row six and so when we get to these empty cells over

when we get to these empty cells over keep on scrolling over here it records

keep on scrolling over here it records as zero I'm fine with that for the time

as zero I'm fine with that for the time being and we'll continue last thing we

being and we'll continue last thing we had to do is use basically a count if to

had to do is use basically a count if to count these different skills based on

count these different skills based on whether they appear or how often they

whether they appear or how often they appear in this row of six so I'll type

appear in this row of six so I'll type in count if we need to specify the range

in count if we need to specify the range first and we'll do six I want it to stay

first and we'll do six I want it to stay there uh as we're because we're going to

there uh as we're because we're going to autofill down so I'm going to F4 that

autofill down so I'm going to F4 that and then from there specify the criteria

and then from there specify the criteria which is going to be a n Kafka okay so

which is going to be a n Kafka okay so three values for that one and then

three values for that one and then dragging this all the way down bam got

dragging this all the way down bam got this all filled in all right the last

this all filled in all right the last thing we need to do is actually

thing we need to do is actually visualize this cuz we want to visualize

visualize this cuz we want to visualize these skill counts select the area that

these skill counts select the area that we want we're going to go in and insert

we want we're going to go in and insert in under recommended charts you can do a

in under recommended charts you can do a bar chart but I'm more a fan of

bar chart but I'm more a fan of horizontal bar charts especially when we

horizontal bar charts especially when we have text values and we need to be able

have text values and we need to be able to see all the different names so I'm

to see all the different names so I'm going to have to expand that out a bit

going to have to expand that out a bit and I'm going to change this title up

and I'm going to change this title up here just to something like skill count

here just to something like skill count of applicants and Bam now we can see

of applicants and Bam now we can see things some Trends out of this that a

things some Trends out of this that a lot of people are claiming to have

lot of people are claiming to have experience with data bricks which that's

experience with data bricks which that's unusually high there probably something

unusually high there probably something I want to investigate for this but a

I want to investigate for this but a good little thing that we actually can

good little thing that we actually can analyze and see from this analysis that

analyze and see from this analysis that we did one minor note I would normally

we did one minor note I would normally go through and actually sort this from

go through and actually sort this from high to low and you can definitely do

high to low and you can definitely do this you'd have to copy and paste the

this you'd have to copy and paste the values over you wouldn't be able to use

values over you wouldn't be able to use these values right here and S sort and

these values right here and S sort and filter them because we're using the

filter them because we're using the modern or dynamic array to find these

modern or dynamic array to find these unique values so that's definitely an

unique values so that's definitely an option if you want to do and I

option if you want to do and I definitely would recommend you do

definitely would recommend you do something like that before sharing some

something like that before sharing some sort of visualization like this all

sort of visualization like this all right you now got some practice problems

right you now got some practice problems to go through and get more familiar with

to go through and get more familiar with these text functions which like I said

these text functions which like I said are imperative for de analysis in the

are imperative for de analysis in the next lesson we're going to be moving

next lesson we're going to be moving into our last one in this chapter on

into our last one in this chapter on formulas and functions on date and time

formulas and functions on date and time functions with that I'll see you in the

functions with that I'll see you in the next one

all right saving the shortest lesson for last we're going to be focusing on date

last we're going to be focusing on date and time functions and for this we're

and time functions and for this we're going to be using that same data set

going to be using that same data set from that last lesson which is about 20

from that last lesson which is about 20 rows of job applicants now similar to

rows of job applicants now similar to text functions we're not using that full

text functions we're not using that full data science job data set that we've

data science job data set that we've been using previously because I find

been using previously because I find it's not common to really use these date

it's not common to really use these date and time functions on a large set of

and time functions on a large set of data because it's going to slow down

data because it's going to slow down your sheets so that's why we're using

your sheets so that's why we're using this smaller data set for this once

this smaller data set for this once again if we're needed to actually clean

again if we're needed to actually clean up date and time stuff we're going to

up date and time stuff we're going to use something like power query which

use something like power query which we're going to be getting to in the

we're going to be getting to in the advanced chapter anyway we're going to

advanced chapter anyway we're going to be focusing on two main types of

be focusing on two main types of functions first up our date functions

functions first up our date functions which going to be able to extract out

which going to be able to extract out things like month day and year and then

things like month day and year and then from there we're going to transition

from there we're going to transition into time functions extracting things

into time functions extracting things out like hour minutes and seconds

out like hour minutes and seconds finally we're going to move into that

finally we're going to move into that final analysis looking at what is the

final analysis looking at what is the time that is most likely for applicants

time that is most likely for applicants to apply to jobs for this we're going to

to apply to jobs for this we're going to be using the date and time functions

be using the date and time functions workbook and we'll be working in this

workbook and we'll be working in this data sheet for this filling in certain

data sheet for this filling in certain values as we go through this I'm going

values as we go through this I'm going to go ahead and hide some of these

to go ahead and hide some of these unnecessary columns so we have more

unnecessary columns so we have more space to work with

this anyway jumping right in if we want to calculate what the month is we have

to calculate what the month is we have something like the month number putting

something like the month number putting that in that's D2 similarly we can get

that in that's D2 similarly we can get the day by using something like day and

the day by using something like day and once again providing it D2 then finally

once again providing it D2 then finally something like year we can provide D2 We

something like year we can provide D2 We Get 2023 now if I wanted to only extract

Get 2023 now if I wanted to only extract out of this date out of this date time

out of this date out of this date time if I were to use this date function it

if I were to use this date function it Returns the number that represents the

Returns the number that represents the date in Microsoft Excel okay date time

date in Microsoft Excel okay date time code got it we're going to put in the

code got it we're going to put in the year so we need to provide the year

year so we need to provide the year first month and then from there day boom

first month and then from there day boom and analyzing this we see it is febru 14

and analyzing this we see it is febru 14 2023 one quick refresher on how Excel

2023 one quick refresher on how Excel stores those datetime objects so right

stores those datetime objects so right now it's in as a the number format of

now it's in as a the number format of date if I change this back to General

date if I change this back to General it's going to shift to this number and

it's going to shift to this number and if we recall this stores the values in

if we recall this stores the values in it if we start at something like one

it if we start at something like one converting it to a short date we can see

converting it to a short date we can see that it starts at January 1st 1900 now

that it starts at January 1st 1900 now if you're working with dates before 1900

if you're working with dates before 1900 let's say we put in something like

let's say we put in something like negative 1 I converted it here to a date

negative 1 I converted it here to a date it's going to just provide all these

it's going to just provide all these different Amber Sands here there's a few

different Amber Sands here there's a few different workarounds for that that's

different workarounds for that that's beyond the scope of this course main

beyond the scope of this course main thing to understand is how it's actually

thing to understand is how it's actually stored within Excel anyway I'm going to

stored within Excel anyway I'm going to convert this back up into a date and for

convert this back up into a date and for each of these I want to actually fill in

each of these I want to actually fill in the values all the way down bam all

the values all the way down bam all right close up this home ribbon all

right close up this home ribbon all right next up is today say we needed to

right next up is today say we needed to today's date well I can put in the today

today's date well I can put in the today function this actually takes no

function this actually takes no arguments and will provide us the date

arguments and will provide us the date I'm filming this on September the 3rd

I'm filming this on September the 3rd now the last common function that I find

now the last common function that I find myself using all the time are when I

myself using all the time are when I want to calculate the days since

want to calculate the days since something happen in this case we want to

something happen in this case we want to find out how many days has it been since

find out how many days has it been since they have applied to the job so we can

they have applied to the job so we can use the date diff function for this now

use the date diff function for this now the one thing to note with this is I'm

the one thing to note with this is I'm typing it in there's no if I type in

typing it in there's no if I type in just date there's no date diff in there

just date there's no date diff in there there's no documentation that Excel

there's no documentation that Excel natively actually includes for you to

natively actually includes for you to use this so this is like a function you

use this so this is like a function you just have to know about anyway it takes

just have to know about anyway it takes three parameters basically the start

three parameters basically the start date that we want to start from the

date that we want to start from the reference date that we want to basically

reference date that we want to basically subtract from this which is today we

subtract from this which is today we want to actually go ahead and lock this

want to actually go ahead and lock this I'm going to lock this with F4 and we

I'm going to lock this with F4 and we want to provide this in the format of

want to provide this in the format of days which we provide this text

days which we provide this text character of D and this tells us it's

character of D and this tells us it's been about 567 days since Valentine's

been about 567 days since Valentine's Day in 2023 anyway updating all these

Day in 2023 anyway updating all these cells for this we now have this

data shifting gears into our time functions as we can expect a lot of

functions as we can expect a lot of these are going to be the same hour we

these are going to be the same hour we use hour function minute has a function

use hour function minute has a function as well as second but this doesn't

as well as second but this doesn't really to show seconds but we can see up

really to show seconds but we can see up here it is is actually included in your

here it is is actually included in your data similar to the date function for

data similar to the date function for time we have to provide three parameters

time we have to provide three parameters of hour minute and then also second drag

of hour minute and then also second drag and drop this all the way down we can

and drop this all the way down we can see that yep it's correlating correctly

see that yep it's correlating correctly one note for the hour that we previous

one note for the hour that we previous calculated this is in military time or

calculated this is in military time or if you're in Europe you also do it this

if you're in Europe you also do it this way anyway I really like this for an

way anyway I really like this for an analysis purpose especially when we get

analysis purpose especially when we get into analyzing it now conversely we can

into analyzing it now conversely we can also use for time and also date you

also use for time and also date you could use the text function which we

could use the text function which we previously saw when we were extracting

previously saw when we were extracting out the month out of date Times by

out the month out of date Times by providing a value and then the format

providing a value and then the format text which we're going to say in this

text which we're going to say in this case is just hour hour minute minute if

case is just hour hour minute minute if I wanted that am PM format not that

I wanted that am PM format not that military time format I can just add in

military time format I can just add in Here Am Pm and it converts it

Here Am Pm and it converts it appropriately dragging this all down and

appropriately dragging this all down and then filling it in we get

then filling it in we get it now moving into that final analysis

it now moving into that final analysis we want to analyze when are these job

we want to analyze when are these job postings Happening by hour of day the

postings Happening by hour of day the first thing we need to actually do is

first thing we need to actually do is get a colum here of the hours in the day

get a colum here of the hours in the day so we can do some sort of like count if

so we can do some sort of like count if on it in order to calculate that so for

on it in order to calculate that so for this I'm going to use the sequence

this I'm going to use the sequence function and I went 24 rows with it

function and I went 24 rows with it column's going to leave blank and I want

column's going to leave blank and I want to start at one and it's going to fill

to start at one and it's going to fill down from 1 all the way to 24 and now we

down from 1 all the way to 24 and now we need to run a c if basically for each

need to run a c if basically for each one of these conditions run down this

one of these conditions run down this list basically matching to see what is

list basically matching to see what is the hour for these things so I have it

the hour for these things so I have it hidden but I'm going to go ahead and

hidden but I'm going to go ahead and make column again for hour and I'll put

make column again for hour and I'll put in here hour and unlike last time I'm

in here hour and unlike last time I'm actually just going to put the whole

actually just going to put the whole range in here and it's going to provide

range in here and it's going to provide me back it in a modern array now with

me back it in a modern array now with this I can actually now use this in the

this I can actually now use this in the count if we want to First provide it a

count if we want to First provide it a range which is our modern array so it's

range which is our modern array so it's going to do I2 hashtag and then a

going to do I2 hashtag and then a criteria for the hour we want to search

criteria for the hour we want to search for we want to search for that one A2

for we want to search for that one A2 from here we want to fill it all in and

from here we want to fill it all in and we have some reference errors because we

we have some reference errors because we didn't lock our cells specifically we

didn't lock our cells specifically we didn't lock this cell right here this I2

didn't lock this cell right here this I2 so I'm going press f4 on that to

so I'm going press f4 on that to actually lock that then dragging it all

actually lock that then dragging it all the way down we have it okay our last

the way down we have it okay our last portion of this is actually visualizing

portion of this is actually visualizing this so we're going to go in select all

this so we're going to go in select all that data go to insert go to recommended

that data go to insert go to recommended charts and I'm more of a fan of column

charts and I'm more of a fan of column charts with this type of data so I'm

charts with this type of data so I'm going to go ahead and put this in and

going to go ahead and put this in and I'm going to change this to job postings

I'm going to change this to job postings per hour and Bam now from this we're

per hour and Bam now from this we're seeing that basically people are

seeing that basically people are applying during normal working hours and

applying during normal working hours and apparently they're waiting until the end

apparently they're waiting until the end of the day to actually submit their job

of the day to actually submit their job applications maybe to get in before a

applications maybe to get in before a deadline or something all right this is

deadline or something all right this is the last lesson on functions and

the last lesson on functions and formulas in the next chapter we're going

formulas in the next chapter we're going to be moving deeper into understanding

to be moving deeper into understanding how to actually make these different

how to actually make these different visualizations I've only been showing

visualizations I've only been showing you a sneak peek at it right now to get

you a sneak peek at it right now to get you familiar with how to easily create

you familiar with how to easily create it but we're going to go in into a lot

it but we're going to go in into a lot greater detail up coming up next now we

greater detail up coming up next now we spent almost nine lessons on these

spent almost nine lessons on these functions and it's because I feel

functions and it's because I feel functions are one of the most important

functions are one of the most important things to understand about Excel because

things to understand about Excel because it also transfers to other portions

it also transfers to other portions specifically we're going to be learning

specifically we're going to be learning more about the Dax language in the

more about the Dax language in the advanced chapter and we're going to

advanced chapter and we're going to apply a lot of our knowledge that we

apply a lot of our knowledge that we already know about these Excel functions

already know about these Excel functions to Dax functions they're very similar

to Dax functions they're very similar anyway you got some practice problems to

anyway you got some practice problems to go through in work in order to

go through in work in order to understand better how to use these

understand better how to use these datetime functions and from there we'll

datetime functions and from there we'll get into that chart chapter with that

get into that chart chapter with that I'll see you in the next

one welcome to this chapter on charts and as much as I love using something

and as much as I love using something like python a programming language for

like python a programming language for making

making visualizations I feel that Excel has

visualizations I feel that Excel has some capabilities built into it that

some capabilities built into it that allow it to basically exceed any

allow it to basically exceed any programming language and the

programming language and the customization that you can do to charts

customization that you can do to charts that we'll be finding out in this

that we'll be finding out in this chapter for this chapter we have four

chapter for this chapter we have four lessons this lesson right here is an

lessons this lesson right here is an intro to chart so we're going to be

intro to chart so we're going to be focusing on understanding the basics of

focusing on understanding the basics of using charts and specifically looking at

using charts and specifically looking at three types of charts specifically line

three types of charts specifically line charts pie charts and bar or column

charts pie charts and bar or column charts so technically that's four in the

charts so technically that's four in the second lesson we're going to move into

second lesson we're going to move into more advanced charts such as Scatter

more advanced charts such as Scatter Plots and also map charts along with

Plots and also map charts along with understanding more advanced

understanding more advanced customizations that we can do to these

customizations that we can do to these charts in the third lesson we're going

charts in the third lesson we're going to go Harden the paint in order to

to go Harden the paint in order to understand statistical charts

understand statistical charts specifically histograms and then also

specifically histograms and then also box and whisker charts which are

box and whisker charts which are imperative to understand statistical

imperative to understand statistical distributions of our data we'll finally

distributions of our data we'll finally wrap this all up with a final lesson

wrap this all up with a final lesson focusing on spark lines which basically

focusing on spark lines which basically allow us to put charts inside of

allow us to put charts inside of individual cells

individual cells in Excel pretty neat all right for this

in Excel pretty neat all right for this lesson we're going to be using the

lesson we're going to be using the charts intro

workbook first thing to understand is terminology Microsoft refers to all

terminology Microsoft refers to all these different visualizations diagrams

these different visualizations diagrams plots whatever you want to call it they

plots whatever you want to call it they refer to it as chart basically they want

refer to it as chart basically they want to use a safe term that encompasses all

to use a safe term that encompasses all the different type of visualizations we

the different type of visualizations we can build with this so you may hear me

can build with this so you may hear me from time to time call this a plot or

from time to time call this a plot or visualization basically mean a chart

visualization basically mean a chart anyway why do we use charts well looking

anyway why do we use charts well looking these six examples here we can see some

these six examples here we can see some different characteristics about this

different characteristics about this data that we're looking at but what if

data that we're looking at but what if we looked at just the core data itself

we looked at just the core data itself which is this table right here looking

which is this table right here looking at what is the number of job postings

at what is the number of job postings per month if we look at this visually

per month if we look at this visually we're not able to see necessarily what

we're not able to see necessarily what is the highest month and also what is

is the highest month and also what is the lowest month I mean you can figure

the lowest month I mean you can figure out eventually but it's not easy to spot

out eventually but it's not easy to spot and that's why charts are so powerful

and that's why charts are so powerful and so I have a variety of

and so I have a variety of visualizations here in order to Showcase

visualizations here in order to Showcase that same table that we were just

that same table that we were just looking at in basically a variety of

looking at in basically a variety of different forms here even have a few

different forms here even have a few below here down below it but we need to

below here down below it but we need to understand which chart to use because

understand which chart to use because let's say we wanted to use this pie

let's say we wanted to use this pie chart here is that actually a good chart

chart here is that actually a good chart to use to visualize this or instead

to use to visualize this or instead should we be using something like this

should we be using something like this line chart to better show a trend over

line chart to better show a trend over time while also showing a magnitude of

time while also showing a magnitude of difference anyway as we go through this

difference anyway as we go through this lesson I'm going to be calling out when

lesson I'm going to be calling out when you should use certain charts as best

you should use certain charts as best practice along with my recommended tips

practice along with my recommended tips for how to customize it to show them

best so for our first chart as I hinted to we're going to be making this job

to we're going to be making this job posting count into a line chart and this

posting count into a line chart and this is the chart I'd use typically for any

is the chart I'd use typically for any time series like data as it's great at

time series like data as it's great at showing a trend over time and how it's

showing a trend over time and how it's connected so how do we do this well

connected so how do we do this well we're going to select all the data here

we're going to select all the data here all the way from A1 down to B13 come up

all the way from A1 down to B13 come up into insert and we're going to dive into

into insert and we're going to dive into each one of these charts individually

each one of these charts individually but I would encourage you to actually

but I would encourage you to actually just start with recommended charts I

just start with recommended charts I really jump to it every time I use it

really jump to it every time I use it anyway first thing they has two tabs

anyway first thing they has two tabs here recommended charts and all charts

here recommended charts and all charts for recommended charts usually provides

for recommended charts usually provides a lot of good tips that you could

a lot of good tips that you could potentially use for different charts

potentially use for different charts sometimes however I do find that I want

sometimes however I do find that I want a particular chart and it's not here and

a particular chart and it's not here and that's when I'm going to go to this all

that's when I'm going to go to this all charts Tab and frankly it provides a lot

charts Tab and frankly it provides a lot more control while allowing you to

more control while allowing you to actually visualize your different data

actually visualize your different data in our case I know I want a line chart

in our case I know I want a line chart on this but now I can go in and actually

on this but now I can go in and actually plot it with markers or even change it

plot it with markers or even change it into a 3D line chart highly don't

into a 3D line chart highly don't recommend this we're going to be

recommend this we're going to be sticking to a line chart for this and

sticking to a line chart for this and I'm going to go ahead and click okay I'm

I'm going to go ahead and click okay I'm not going to lie this chart is getting

not going to lie this chart is getting us 90% of the way there now if you

us 90% of the way there now if you notice for this when we clicked on the

notice for this when we clicked on the chart we have certain values highlighted

chart we have certain values highlighted here basically this purple outline is

here basically this purple outline is showing that this is the X values right

showing that this is the X values right here and then the blue coordinates right

here and then the blue coordinates right here are showing the actual values

here are showing the actual values themselves and then conveniently they

themselves and then conveniently they put the job posting count which is

put the job posting count which is highlighted in Orange as the title we'll

highlighted in Orange as the title we'll be jumping into how to customize this

be jumping into how to customize this area in the advanced section but that's

area in the advanced section but that's in the next lesson now for those new to

in the next lesson now for those new to charts there's a bunch of different

charts there's a bunch of different elements and I can come up here and I

elements and I can come up here and I can click this plus icon right here and

can click this plus icon right here and it shows all the different elements on

it shows all the different elements on here I can use the checkbox to control

here I can use the checkbox to control whether I want to include the axes or

whether I want to include the axes or not in this case I do want to include it

not in this case I do want to include it and then I can even find tune it further

and then I can even find tune it further to select which one I'm talking about am

to select which one I'm talking about am I talking about the horizontal or am I

I talking about the horizontal or am I talking about the vertical

talking about the vertical just going through these in Rapid

just going through these in Rapid fashion access titles allow us to

fashion access titles allow us to provide titles for the X and Y AIS the

provide titles for the X and Y AIS the chart title shown above I can remove it

chart title shown above I can remove it or keep it on if I want to include data

or keep it on if I want to include data labels I can do this along with

labels I can do this along with controlling what position of them I want

controlling what position of them I want to go with I could also include

to go with I could also include something like a data table below but

something like a data table below but personally I find this is sometimes

personally I find this is sometimes sensory overload I don't really use that

sensory overload I don't really use that much next are airb bars for data grid

much next are airb bars for data grid lines whether I want to have horizontal

lines whether I want to have horizontal vertical some minor ones or some other

vertical some minor ones or some other minor ones a legend if there's more than

minor ones a legend if there's more than one data I probably want this a trend

one data I probably want this a trend line which will be adding in this a

line which will be adding in this a little bit and then up and down bars

little bit and then up and down bars which are going to show whether the data

which are going to show whether the data goes up or down based on each set but

goes up or down based on each set but not really necessarily applicable to

not really necessarily applicable to this one now I find this plus icon is

this one now I find this plus icon is where I go most of the time but I could

where I go most of the time but I could also go to this chart design tab up here

also go to this chart design tab up here and it has this box of add chart

and it has this box of add chart elements and basically you can go

elements and basically you can go through and adjust all the different

through and adjust all the different ones along with showing a more visual

ones along with showing a more visual indication of what's going on here here

indication of what's going on here here showing that I was actual up down bars

showing that I was actual up down bars to actually see what they actually look

to actually see what they actually look like you can also use this quick layouts

like you can also use this quick layouts to quickly try out different themes that

to quickly try out different themes that Excel has so doy myself from time to

Excel has so doy myself from time to time using this so this chart is almost

time using this so this chart is almost done all I do want to do first is change

done all I do want to do first is change the title and I usually like to either

the title and I usually like to either provide some sort of snippet of

provide some sort of snippet of information from it or ask a question

information from it or ask a question that I want the reader of this graph to

that I want the reader of this graph to understand or take away from this chart

understand or take away from this chart so I can put in something like how did

so I can put in something like how did jobs Trend in 2023 so it also tells what

jobs Trend in 2023 so it also tells what year what's going on here and it asks

year what's going on here and it asks them to look at hey what is the trend

them to look at hey what is the trend going on here which it looks like we

going on here which it looks like we have a peak up in January and a peek up

have a peak up in January and a peek up in August now I try to minimize the

in August now I try to minimize the amount of access titles on here because

amount of access titles on here because like in the month's case that's pretty

like in the month's case that's pretty self-explanatory however the number in

self-explanatory however the number in the y- AIS is not so self-explanatory so

the y- AIS is not so self-explanatory so in that case I would want to include it

in that case I would want to include it in this case give it a representative

in this case give it a representative name of counts of jobs the last thing I

name of counts of jobs the last thing I want to do with this is just add a trend

want to do with this is just add a trend line and there's multiple different

line and there's multiple different options for this we can do linear

options for this we can do linear exponential a linear forecast where it

exponential a linear forecast where it actually goes into the future and then

actually goes into the future and then even a two period moving average which

even a two period moving average which is pretty neat I'm going to just stick

is pretty neat I'm going to just stick with the basic one right now of linear

with the basic one right now of linear and Bam that's our first chart so let's

and Bam that's our first chart so let's move in the next

one now if we go back to our original data set in the data tab we have a

data set in the data tab we have a column here on job no degree mention and

column here on job no degree mention and basically this column right here

basically this column right here includes whether there's a mention of a

includes whether there's a mention of a degree in a job posting so in this case

degree in a job posting so in this case where we have two different values we're

where we have two different values we're trying to determine what are the

trying to determine what are the proportions of each a way to compare

proportions of each a way to compare this we could either compare this in

this we could either compare this in like a bar or column chart but I feel a

like a bar or column chart but I feel a better one for this is a pie chart so

better one for this is a pie chart so I've gone through and calculated a count

I've gone through and calculated a count of the jobs with a no degree mention

of the jobs with a no degree mention along with those that have a mention of

along with those that have a mention of a degree I calculated the total and then

a degree I calculated the total and then from that I calculated their individual

from that I calculated their individual percentages now I'm not going to just

percentages now I'm not going to just select all the data here because I don't

select all the data here because I don't want to plot all of it I'm going to

want to plot all of it I'm going to select the first two values here of A2

select the first two values here of A2 A3 press control and then also select C2

A3 press control and then also select C2 to C3 then from here now I'm I'm going

to C3 then from here now I'm I'm going to go insert those recommended charts

to go insert those recommended charts like got a lad two bar and column charts

like got a lad two bar and column charts come up but the one we're going to be

come up but the one we're going to be using for this it's a pie chart so I'm

using for this it's a pie chart so I'm going to go ahead and insert that in now

going to go ahead and insert that in now personally I'm not a fan of this layout

personally I'm not a fan of this layout here so I'm going to come up into chart

here so I'm going to come up into chart designs into Quick layouts and I'm going

designs into Quick layouts and I'm going to just experiment with different ones

to just experiment with different ones looking at them and frankly I like the

looking at them and frankly I like the one this one right here actually where

one this one right here actually where we've removed the legend and put the

we've removed the legend and put the actual values themselves along with

actual values themselves along with their titles inside the pie chart itself

their titles inside the pie chart itself to make it super simple to see which one

to make it super simple to see which one is which now Excel sometimes gets crazy

is which now Excel sometimes gets crazy with the colors I actually don't

with the colors I actually don't recommend using a lot of different

recommend using a lot of different colors because it could be very

colors because it could be very confusing for viewers on where to look

confusing for viewers on where to look personally I want to highlight more of

personally I want to highlight more of the no degree mentioned so I'm going to

the no degree mentioned so I'm going to use this single color palette right here

use this single color palette right here or this monochromatic color palette

or this monochromatic color palette right here that has these different

right here that has these different shades of blue and and I feel the ey is

shades of blue and and I feel the ey is going to go more to the darker blue now

going to go more to the darker blue now with each of these labels here I can

with each of these labels here I can actually select it I double clicked it

actually select it I double clicked it over time I can actually drag it and

over time I can actually drag it and drop it and move it around where I want

drop it and move it around where I want it to be I would probably want it to be

it to be I would probably want it to be more over here I want the degree

more over here I want the degree mentioned to be stacked basically I want

mentioned to be stacked basically I want them opposite of each other now you may

them opposite of each other now you may have noticed I can't really read this

have noticed I can't really read this text right here and even this text is

text right here and even this text is hard to read as well so what I can do is

hard to read as well so what I can do is I'll just click outside real quick and

I'll just click outside real quick and clicking back in I'm going to double

clicking back in I'm going to double click and this is going to bring up the

click and this is going to bring up the format data labels if double clicking

format data labels if double clicking isn't work you can just select it go

isn't work you can just select it go into the format tab up here and select

into the format tab up here and select format selection anyway there's a lot to

format selection anyway there's a lot to unpack in this Pane and we'll be

unpack in this Pane and we'll be unpacking it as we go along this entire

unpacking it as we go along this entire chapter but the main thing to understand

chapter but the main thing to understand is they have label options and text

is they have label options and text options we want to adjust the text

options we want to adjust the text options and this has things like text

options and this has things like text fill and outline text effects and then

fill and outline text effects and then also the text box for this we're trying

also the text box for this we're trying to fill the text fill and outline

to fill the text fill and outline specifically this drop down here of text

specifically this drop down here of text fill we want to change the color so we

fill we want to change the color so we want to change it to White now if you

want to change it to White now if you notice only one of these change and

notice only one of these change and that's because I only had one of the

that's because I only had one of the boxes selected so actually actually

boxes selected so actually actually click out of this double click back into

click out of this double click back into this and then make sure both of these

this and then make sure both of these are actually selected go back into text

are actually selected go back into text options go into text fill and then

options go into text fill and then change this color and then it's going to

change this color and then it's going to change both of these colors

change both of these colors now I'm fine with this text now but

now I'm fine with this text now but let's say I wanted to customize further

let's say I wanted to customize further the percentage here maybe I want to

the percentage here maybe I want to include one more decimal place clicking

include one more decimal place clicking on the box itself I can now have this

on the box itself I can now have this option for label options and then under

option for label options and then under well label options again I can scroll

well label options again I can scroll all the way down or I can actually cover

all the way down or I can actually cover this up and then unhide this number I

this up and then unhide this number I can change the number formatting itself

can change the number formatting itself in this case I do want to still do a

in this case I do want to still do a percentage and then maybe I want to do

percentage and then maybe I want to do one decimal place personally I think

one decimal place personally I think there's a little a little bit too much

there's a little a little bit too much dat so we're just going to keep it with

dat so we're just going to keep it with the zero all right that's the final

the zero all right that's the final customization the last thing we want to

customization the last thing we want to do is just add a title and I want a very

do is just add a title and I want a very compelling title what do they want to

compelling title what do they want to look at for this I want them to

look at for this I want them to understand what jobs mention a degree

understand what jobs mention a degree and now with this we have a pretty great

and now with this we have a pretty great visual indication of that about one of

visual indication of that about one of jobs have no degree mention in them

jobs have no degree mention in them which personally I think that's a pretty

which personally I think that's a pretty high percentage and hopefully gets

higher so we have data similar to our first chart that basically explains how

first chart that basically explains how many counts of jobs for the different

many counts of jobs for the different job titles now this isn't chronological

job titles now this isn't chronological so I don't necessarily recommend using

so I don't necessarily recommend using something like a line chart for this

something like a line chart for this that's why we're going to be making

that's why we're going to be making column and bar charts for this also let

column and bar charts for this also let explain the difference between the two

explain the difference between the two anyway I'm using the formulas that we

anyway I'm using the formulas that we previously have covered you can dive

previously have covered you can dive into it if you want to basically using

into it if you want to basically using unique and then also a c if formula in

unique and then also a c if formula in order to count each one of these in

order to count each one of these in their data tab anyway if I actually go

their data tab anyway if I actually go to graph these by selecting all these

to graph these by selecting all these things go to insert and recommended

things go to insert and recommended charts here provides the recommended

charts here provides the recommended charts and we're going to start with a

charts and we're going to start with a column chart first I start with this one

column chart first I start with this one first because we're already running into

first because we're already running into problems with how long these labels are

problems with how long these labels are we can see that we have these three

we can see that we have these three ellipses here basically telling the that

ellipses here basically telling the that the rest of the name is hidden here so

the rest of the name is hidden here so not all the names are shown here the

not all the names are shown here the other problem that we're getting into

other problem that we're getting into with this column chart um named after

with this column chart um named after the fact that it looks like columns is

the fact that it looks like columns is that it's not in an organized manner I

that it's not in an organized manner I would expect to see it high to low to

would expect to see it high to low to make it more easily to compare values to

make it more easily to compare values to each other and also how they rank so

each other and also how they rank so we'll go ahead and delete this bad boy

we'll go ahead and delete this bad boy anyway this table is organized based on

anyway this table is organized based on this unique function which doesn't

this unique function which doesn't necessarily put things in the correct

necessarily put things in the correct order and I won't be able to actually go

order and I won't be able to actually go through and filter it or soter it

through and filter it or soter it appropriately So Below this I made a

appropriately So Below this I made a different table that I basically use

different table that I basically use sort to sort these values from above by

sort to sort these values from above by their job count in descending order now

their job count in descending order now since it's in this order I could

since it's in this order I could actually select a few less of this

actually select a few less of this remember how it was cut off last time I

remember how it was cut off last time I could select only the top six go into

could select only the top six go into here go into recommended charts and once

here go into recommended charts and once again and put in our clustered column

again and put in our clustered column chart now this one I can play around

chart now this one I can play around with and as you see as I expand it out I

with and as you see as I expand it out I can actually see all the different names

can actually see all the different names here but once again I'm not a fan of

here but once again I'm not a fan of this column chart I'm not going to be

this column chart I'm not going to be using it for this case instead we're

using it for this case instead we're going to try out a bar chart instead so

going to try out a bar chart instead so selecting all this data to show the

selecting all this data to show the power of these bar charts and then

power of these bar charts and then coming in I can put in that bar chart

coming in I can put in that bar chart now I do like this one better because

now I do like this one better because all the titles are organ ganized and

all the titles are organ ganized and they're right off to the side and so

they're right off to the side and so this is a much more easier read the

this is a much more easier read the problem now is I'm really nitpicky with

problem now is I'm really nitpicky with my charts the problem now is I don't

my charts the problem now is I don't like the order that this is in what

like the order that this is in what happens is is Excel starts plotting

happens is is Excel starts plotting these although it's in descending order

these although it's in descending order in our table as shown over here it's

in our table as shown over here it's going to be plotting them starting at

going to be plotting them starting at this zero axis up here and then plotting

this zero axis up here and then plotting from there so technically we don't even

from there so technically we don't even want it like this instead what I can do

want it like this instead what I can do is reverse the sort order here I'm just

is reverse the sort order here I'm just controlling it by using uh either one or

controlling it by using uh either one or netive one in that sort order portion

netive one in that sort order portion anyway with this order now now we can

anyway with this order now now we can finally get into the final bar chart

finally get into the final bar chart that we want to actually put in and I'm

that we want to actually put in and I'm just going to skip this recommended

just going to skip this recommended charts come up here into the column and

charts come up here into the column and then the bar charts we want this one

then the bar charts we want this one inserted in and I'm also going to zoom

inserted in and I'm also going to zoom out some now this is more in lined with

out some now this is more in lined with what I want let's actually clean up this

what I want let's actually clean up this visualization to identify what we want

visualization to identify what we want I'm actually more curious about what are

I'm actually more curious about what are the top jobs in data science so that's

the top jobs in data science so that's what we'll name it additionally feel the

what we'll name it additionally feel the titles are pretty self-explanatory based

titles are pretty self-explanatory based on that title but I would need something

on that title but I would need something for the x-axis down here so we'll add an

for the x-axis down here so we'll add an axis title calling this count of job

axis title calling this count of job postings now with this question I'm

postings now with this question I'm asking of what are the top jobs in data

asking of what are the top jobs in data science I'm not really feeling like we

science I'm not really feeling like we need to include things like machine

need to include things like machine learning Engineers software Engineers

learning Engineers software Engineers cloudware Engineers or business business

cloudware Engineers or business business analyst how could I actually adjust this

analyst how could I actually adjust this well one way is I could control what

well one way is I could control what areas are highlighted over here and I

areas are highlighted over here and I could actually drag this and change this

could actually drag this and change this to whichever ones I want um but I'm not

to whichever ones I want um but I'm not necessarily going to recommend that

necessarily going to recommend that instead I'm going to select our data

instead I'm going to select our data make sure all the columns are selected

make sure all the columns are selected themselves rightclick it and then go to

themselves rightclick it and then go to select data and this new window is going

select data and this new window is going to pop up here this tells us a lot of

to pop up here this tells us a lot of great things about our visualization

great things about our visualization first is the chart data range it tells

first is the chart data range it tells us we're selected from a25 to b35 so we

us we're selected from a25 to b35 so we could change that here if we wanted to

could change that here if we wanted to the next thing is the two windows down

the next thing is the two windows down here of the legend entries and the

here of the legend entries and the horizontal axis so this controls our job

horizontal axis so this controls our job count I'm going to scroll this over here

count I'm going to scroll this over here we could just remove job count but it's

we could just remove job count but it's not going to do anything this guys

not going to do anything this guys mainly right here the access labels we

mainly right here the access labels we can control so I know I want data

can control so I know I want data analyst and all the way up down to

analyst and all the way up down to senior data analyst I can actually go

senior data analyst I can actually go through and select remove business

through and select remove business analyst machine learning engineer

analyst machine learning engineer software engineer and Cloud engineer and

software engineer and Cloud engineer and then click okay and it will remove it

then click okay and it will remove it from this visualization while still

from this visualization while still keeping this data here so I can easily

keeping this data here so I can easily go back and add or remove job titles as

go back and add or remove job titles as necessary and now we have our final

necessary and now we have our final visualization earlier I did go through

visualization earlier I did go through and actually delete the chart and start

and actually delete the chart and start over but you do have this option in the

over but you do have this option in the chart design tab of change chart type

chart design tab of change chart type and allows you to basically go through

and allows you to basically go through and try out different ones if I wanted

and try out different ones if I wanted to go back to that column chart I could

to go back to that column chart I could and it would show me an example of what

and it would show me an example of what it looks like now there is one last

it looks like now there is one last thing that I want to format on this I do

thing that I want to format on this I do find it a little difficult to read

find it a little difficult to read exactly what are the amount of job

exactly what are the amount of job postings that they have here so I'm

postings that they have here so I'm going to add data labels to this we have

going to add data labels to this we have a couple different options we can be

a couple different options we can be inside end which can't read at all

inside end which can't read at all inside Base outside end which I'm more

inside Base outside end which I'm more for and then also a data call that's

for and then also a data call that's just too much there we're going to do

just too much there we're going to do outside end now with this these numbers

outside end now with this these numbers I don't like the level of detail I don't

I don't like the level of detail I don't need down to the single or the on

need down to the single or the on digigit place to tell what it is instead

digigit place to tell what it is instead I would rather it shows something like

I would rather it shows something like 9.6k or 9.6000 so we can actually format

9.6k or 9.6000 so we can actually format that so double clicking on one of those

that so double clicking on one of those labels this format short area is going

labels this format short area is going to pop up again and for this I'm going

to pop up again and for this I'm going to go under label options and then label

to go under label options and then label options again and finally number and for

options again and finally number and for this I'm going to use use instead of uh

this I'm going to use use instead of uh any one of these I'm going to use a

any one of these I'm going to use a custom type now I have a few of these

custom type now I have a few of these already built into here and so they may

already built into here and so they may not pop up to you but this is actually

not pop up to you but this is actually sneak peek this is actually what we want

sneak peek this is actually what we want but if you don't have this popping up

but if you don't have this popping up right now what you can do is actually go

right now what you can do is actually go in in this case I'll just show a

in in this case I'll just show a different value what we're going to

different value what we're going to first say is how we want this formated

first say is how we want this formated with how many decimal places so I want

with how many decimal places so I want all the values before the decimal place

all the values before the decimal place then a decimal place and then I only

then a decimal place and then I only want in this case let's go with two

want in this case let's go with two places after the decimal place and then

places after the decimal place and then from there I want a K on the end so

from there I want a K on the end so basically to show this as a thousand so

basically to show this as a thousand so I'm going to use a parenthesis put a k

I'm going to use a parenthesis put a k and then close parenthesis and I'm going

and then close parenthesis and I'm going to click add okay so now this changes it

to click add okay so now this changes it to the double digits for explaining that

to the double digits for explaining that this is the thousands this automatically

this is the thousands this automatically whenever I do that K parentheses it

whenever I do that K parentheses it automatically does the math to basically

automatically does the math to basically divide that by a th and transfer this to

divide that by a th and transfer this to K instead of the thousands anyway I

K instead of the thousands anyway I don't really I'm going to go with the

don't really I'm going to go with the original one I had of only one decimal

original one I had of only one decimal place and Bam that's our final

place and Bam that's our final visualization and we can see from this

visualization and we can see from this that we have a lot of insights into

that we have a lot of insights into understanding that more Junior roles

understanding that more Junior roles like dat analyst dat scientist dat

like dat analyst dat scientist dat Engineers are more prevalent than the

Engineers are more prevalent than the senior roles and that luckily it seems

senior roles and that luckily it seems like there's a lot more data analyst

like there's a lot more data analyst roles than data scientists and data

roles than data scientists and data Engineers all right you now some

Engineers all right you now some practice problems to go through and get

practice problems to go through and get more familiar with those four major type

more familiar with those four major type of visualizations that frankly I feel

of visualizations that frankly I feel I'm using on a daily basis anytime I'm

I'm using on a daily basis anytime I'm making visualizations so don't think

making visualizations so don't think that they're just too plain or too

that they're just too plain or too simple they're really powerful and

simple they're really powerful and explaining data in the next lesson we're

explaining data in the next lesson we're going to be jumping into not only more

going to be jumping into not only more advanced charts but even more advanced

advanced charts but even more advanced customization so with that I'll see you

customization so with that I'll see you in that

one we're going to crank this up a notch and get into some more advanced

and get into some more advanced visualizations specifically on this

visualizations specifically on this we're going to be doing a deeper dive

we're going to be doing a deeper dive dive into the pay of different jobs not

dive into the pay of different jobs not only based on the different job titles

only based on the different job titles but also based on where a job is located

but also based on where a job is located using things like a map chart and so for

using things like a map chart and so for all these charts also we're going to be

all these charts also we're going to be looking into how we can further get into

looking into how we can further get into deeper customization of

these so Scatter Plots are great at comparing two numerical values in our

comparing two numerical values in our data set we have these two columns here

data set we have these two columns here one on the salary year average and the

one on the salary year average and the other on the salary hour average just as

other on the salary hour average just as a background on why it's called average

a background on why it's called average at the end of these sometimes job

at the end of these sometimes job postings have a range of salary and so I

postings have a range of salary and so I took the average of the Min and Max and

took the average of the Min and Max and hence I named this average anyway we

hence I named this average anyway we have yearly salary data and we have

have yearly salary data and we have hourly salary data what it did next is

hourly salary data what it did next is get the unique value of the job titles

get the unique value of the job titles and then from there using that median

and then from there using that median basically modified median IF function

basically modified median IF function got the yearly median salaries and then

got the yearly median salaries and then the hourly median salaries so because we

the hourly median salaries so because we have these two numerical values to

have these two numerical values to compare basically we want to see if

compare basically we want to see if there's a trend correlated between the

there's a trend correlated between the two because well there is we're going to

two because well there is we're going to find out I'm going to go ahead and

find out I'm going to go ahead and select these all then from there go into

select these all then from there go into insert and we can come into charts I

insert and we can come into charts I know I want a scatter plot and if we go

know I want a scatter plot and if we go to insert it in can't see cuz it's

to insert it in can't see cuz it's hidden behind here well we'll just go

hidden behind here well we'll just go ahead and show it this isn't necessarily

ahead and show it this isn't necessarily showing us what I want us to show with

showing us what I want us to show with this it's basically showing hey this is

this it's basically showing hey this is the yearly data up here in the blue and

the yearly data up here in the blue and then this is the hourly data since

then this is the hourly data since hourly data it's super low it didn't

hourly data it's super low it didn't work out how I wanted to by selecting

work out how I wanted to by selecting all the data like we've previously been

all the data like we've previously been doing instead I'm going to go ahead and

doing instead I'm going to go ahead and delete this what we're going to do is

delete this what we're going to do is we're only going to select basically

we're only going to select basically this B and C column of data once again

this B and C column of data once again we're going to try again inserting that

we're going to try again inserting that scatter plot and at this point it's

scatter plot and at this point it's actually working correctly as we want it

actually working correctly as we want it unfortunately we can't tell there's no

unfortunately we can't tell there's no basically like data labels for this to

basically like data labels for this to understand what are the different job

understand what are the different job titles associated with it even with the

titles associated with it even with the graph we can see that it's only

graph we can see that it's only highlighting this also the incorrect

highlighting this also the incorrect titles up here it's not just hourly

titles up here it's not just hourly median salary we're going to fix all

median salary we're going to fix all this anyway the first thing that I want

this anyway the first thing that I want to clean up is actually the selection of

to clean up is actually the selection of data right now we can see these numbers

data right now we can see these numbers are overlapping down here also it goes

are overlapping down here also it goes all the way down to this zero axis on

all the way down to this zero axis on both the X and Y I want to change that

both the X and Y I want to change that so I'm going to double click this x axis

so I'm going to double click this x axis and format access pane pops up and we

and format access pane pops up and we can see that we have bounds here 0 to

can see that we have bounds here 0 to 180,000 I can see that there's no values

180,000 I can see that there's no values under about 75,000 so I'm going to go

under about 75,000 so I'm going to go ahead and put that in for the minimum

ahead and put that in for the minimum and press enter so it's going to jumate

and press enter so it's going to jumate this way now I want to do the same thing

this way now I want to do the same thing for the Y AIS I'll just double click it

for the Y AIS I'll just double click it and this one didn't necessarily go where

and this one didn't necessarily go where I wanted it to go I wanted to actually

I wanted it to go I wanted to actually change the values here so we can go

change the values here so we can go under access options under access

under access options under access options again and under access options

options again and under access options again we can change this minimum maximum

again we can change this minimum maximum I'm going to change it to looks like

I'm going to change it to looks like there's nothing above 20 or below 25 so

there's nothing above 20 or below 25 so we're going to go with that now even

we're going to go with that now even with this change in the formatting of

with this change in the formatting of the values here the minimum I can still

the values here the minimum I can still see that there's overlap here so I want

see that there's overlap here so I want to update this similar to last time

to update this similar to last time basically cut it off the thousands place

basically cut it off the thousands place and place and put a k at the end so

and place and put a k at the end so under access options access options

under access options access options again I'm going to close this drop down

again I'm going to close this drop down of access options also instead we're

of access options also instead we're going to go to number for this we want a

going to go to number for this we want a custom type and I do have some values in

custom type and I do have some values in here but we're just going to go if you

here but we're just going to go if you don't have them in here we're going to

don't have them in here we're going to add a new one specifically with this I

add a new one specifically with this I wanted to show one I wanted to show a

wanted to show one I wanted to show a dollar sign at the front and I don't

dollar sign at the front and I don't want any decimal places whatsoever so

want any decimal places whatsoever so I'm just going to put a zero in there

I'm just going to put a zero in there and then from there like last time I

and then from there like last time I want to format this in the thousand's

want to format this in the thousand's place so I'm going to put a comma and

place so I'm going to put a comma and then double quotes to put around the K

then double quotes to put around the K which signifies I want to formulate this

which signifies I want to formulate this in the thousand's place I'm going go

in the thousand's place I'm going go ahead and click add and now this is much

ahead and click add and now this is much more readable not so much sensory

more readable not so much sensory overload for our y AIS I don't care at

overload for our y AIS I don't care at all about this decimal place right here

all about this decimal place right here so going back into numbers again I can

so going back into numbers again I can just format the decimal place places as

just format the decimal place places as zero and I'll just leave this one as an

zero and I'll just leave this one as an accounting category now which one's

accounting category now which one's yearly and which one hourly salary well

yearly and which one hourly salary well we need to include actual access titles

we need to include actual access titles for this so I'll go ahead and enable

for this so I'll go ahead and enable that and then for this we're going to do

that and then for this we're going to do something a little bit different I'm

something a little bit different I'm going to select this ya AIS title and

going to select this ya AIS title and instead of actually typing in values in

instead of actually typing in values in I want to use actually the column header

I want to use actually the column header right here so I'm going to come up into

right here so I'm going to come up into the formula bar type equal to I'm going

the formula bar type equal to I'm going select C1 and then press enter and now

select C1 and then press enter and now this updates for that column head I can

this updates for that column head I can do the same thing here for the x-axis

do the same thing here for the x-axis title selecting it then from there going

title selecting it then from there going to the formula bar put an equal and

to the formula bar put an equal and selecting cell B1 and pressing enter for

selecting cell B1 and pressing enter for the title we don't want that hourly

the title we don't want that hourly median salary we're really trying to

median salary we're really trying to find out what jobs have the highest pay

find out what jobs have the highest pay and we can basically tell it from this

and we can basically tell it from this all right so let's actually finally get

all right so let's actually finally get to adding data labels to this and we can

to adding data labels to this and we can see what data labels are actually

see what data labels are actually available but scrolling over the

available but scrolling over the different options here we're going to

different options here we're going to just go with above for the time being

just go with above for the time being then I'm going to close on out of this

then I'm going to close on out of this and I'm going to select the data labels

and I'm going to select the data labels themselves and format data labels should

themselves and format data labels should pop up if it doesn't you can also go

pop up if it doesn't you can also go about doing it by right-clicking this

about doing it by right-clicking this and going to format data labels anyway

and going to format data labels anyway for this I don't want to actually show

for this I don't want to actually show The X or the Y value for this anyway uh

The X or the Y value for this anyway uh I made I made it disappear by actually

I made I made it disappear by actually closing out of that so actually I going

closing out of that so actually I going have to add those data labels again

have to add those data labels again again anyway going back into it under

again anyway going back into it under label options label options then label

label options label options then label options again I'm going to leave that y

options again I'm going to leave that y value selected for right now but what I

value selected for right now but what I want to do now is provide the job title

want to do now is provide the job title itself right next to the data point so I

itself right next to the data point so I can do this option here so label

can do this option here so label contains value from cells and it's going

contains value from cells and it's going to ask me to select the data label range

to ask me to select the data label range and so now this is when I'm going to

and so now this is when I'm going to select all of these different job titles

select all of these different job titles here and press okay so now we have these

here and press okay so now we have these values from cells I no longer want this

values from cells I no longer want this y values and I do want to include this

y values and I do want to include this leader lines because we're going to be

leader lines because we're going to be actually dragging this around because as

actually dragging this around because as you can see some of these values are

you can see some of these values are overlapping now also I'm noticing that

overlapping now also I'm noticing that this is really busy right now with all

this is really busy right now with all this text and stuff so I'm actually

this text and stuff so I'm actually going to remove the grid lines for the

going to remove the grid lines for the time being actually for the remainder of

time being actually for the remainder of this cuz I I don't feel like it really

this cuz I I don't feel like it really needs the grid lines in general and now

needs the grid lines in general and now I have a little bit less sensory

I have a little bit less sensory overload so I can go through and

overload so I can go through and actually clean up where a lot of these

actually clean up where a lot of these different job titles are located by just

different job titles are located by just selecting it and then dragging it and

selecting it and then dragging it and you notice uh we had that leader line

you notice uh we had that leader line selected so I have arrows or basically

selected so I have arrows or basically lines going to each of these ones to

lines going to each of these ones to signify which one is which so now I've

signify which one is which so now I've dragging these all over so that way

dragging these all over so that way they're basically more represent I want

they're basically more represent I want sometimes if I dragged off of this and

sometimes if I dragged off of this and drag maybe the whole chart itself and

drag maybe the whole chart itself and make a mistake I press just control Z

make a mistake I press just control Z and it reverts it back to where I'm

and it reverts it back to where I'm going and then I just continue on to

going and then I just continue on to selecting the box that I want and moving

selecting the box that I want and moving it anyway this is pretty neat now I

it anyway this is pretty neat now I could actually go in if I wanted to and

could actually go in if I wanted to and add a trend line to this and basically

add a trend line to this and basically it shows for an increase in that yearly

it shows for an increase in that yearly salary I expect the same with the hourly

salary I expect the same with the hourly data in this case I don't find it as

data in this case I don't find it as much useful so I'm going to just keep

much useful so I'm going to just keep leave that off but in general it is

leave that off but in general it is pretty neat to see the trend that's

pretty neat to see the trend that's going on with this that senior data

going on with this that senior data Engineers although they're underpaid

Engineers although they're underpaid compared to senior data scientist in

compared to senior data scientist in yearly salary you could get the hookup

yearly salary you could get the hookup if in instead you look for an hourly gig

if in instead you look for an hourly gig instead in order to get a little bit

instead in order to get a little bit higher pay a similar Dynamic happens

higher pay a similar Dynamic happens between business analysts and data

between business analysts and data analyst so if you're a data analyst and

analyst so if you're a data analyst and you're looking for a job maybe on upwork

you're looking for a job maybe on upwork maybe you should advertise as a business

maybe you should advertise as a business analyst

instead all right going back to our data set itself we have another column in

set itself we have another column in here I want to investigate and that's

here I want to investigate and that's specifically around the country is

specifically around the country is called job country basically where the

called job country basically where the job is located at and I like to

job is located at and I like to visualize these type of things well on a

visualize these type of things well on a map to actually see how it affects

map to actually see how it affects others so I've made this table here

others so I've made this table here under the map chart tab where we have

under the map chart tab where we have our all the different countries in the

our all the different countries in the data set then from there we use a count

data set then from there we use a count if to determine how many counts for each

if to determine how many counts for each of the countries and then our modified

of the countries and then our modified median if in order to determine what the

median if in order to determine what the median salary is in each of these

median salary is in each of these countries I've also had to wrap this one

countries I've also had to wrap this one in an if error because some of these if

in an if error because some of these if there's no values it throws an error and

there's no values it throws an error and I didn't want that popping up in the

I didn't want that popping up in the chart so so I had it disappear or make

chart so so I had it disappear or make it basically a blank value if it does

it basically a blank value if it does have an error anyway let's get into

have an error anyway let's get into visualizing this we're going to first

visualizing this we're going to first just visualize what are the counts of

just visualize what are the counts of these different jobs based on the

these different jobs based on the country so I'm going to select column A

country so I'm going to select column A and B go to insert and then maps and go

and B go to insert and then maps and go to this map chart now you may have a

to this map chart now you may have a pop-up warning that comes up during this

pop-up warning that comes up during this that says data needed to create your map

that says data needed to create your map chart will be set to B and I'm fine with

chart will be set to B and I'm fine with sending this data to being you should be

sending this data to being you should be fine too with it so feel free to accept

fine too with it so feel free to accept this then you shouldn't get this pop up

this then you shouldn't get this pop up anymore anyway this chart's pretty neat

anymore anyway this chart's pretty neat because it goes and shows we have a

because it goes and shows we have a heavy concentration of jobs basically

heavy concentration of jobs basically from the United States for my job

from the United States for my job scraper I'm heavily aggregating jobs

scraper I'm heavily aggregating jobs from this country compared to other

from this country compared to other countries sorry other countries out

countries sorry other countries out there but I am still n less collecting

there but I am still n less collecting from other countries like us has 25,000

from other countries like us has 25,000 India is around 580 for this one I'm

India is around 580 for this one I'm going to change the title to where are

going to change the title to where are most jobs in Luke's data set from

most jobs in Luke's data set from there's not to say the United States has

there's not to say the United States has more jobs than other countries this is

more jobs than other countries this is just how my data set is and how I

just how my data set is and how I extracted the data so don't want you to

extracted the data so don't want you to come up with the wrong conclusions from

come up with the wrong conclusions from this now the visualization that I really

this now the visualization that I really care about is comparing these countries

care about is comparing these countries to the median salary so holding control

to the median salary so holding control I select a and then C I'm going to do

I select a and then C I'm going to do recommended charge from this cuz I'm

recommended charge from this cuz I'm having problems using the maps one

having problems using the maps one anyway I see that it has the filled map

anyway I see that it has the filled map here I'm going to select okay and I have

here I'm going to select okay and I have all the data filled in all right with

all the data filled in all right with this visualization we we can now dive in

this visualization we we can now dive in we can see that we have a range of these

we can see that we have a range of these median salaries from over 157,000 down

median salaries from over 157,000 down to 30,000 with country like China having

to 30,000 with country like China having around 68,000 and then over in Africa we

around 68,000 and then over in Africa we have Algeria at

have Algeria at 45,000 so looks like we have a lower

45,000 so looks like we have a lower salary in the African continent over in

salary in the African continent over in North America and also South America

North America and also South America pretty high salaries along with

pretty high salaries along with Australia as well anyway pretty cool

Australia as well anyway pretty cool visualization we were able to generate

visualization we were able to generate out of this I mean I love data and I

out of this I mean I love data and I just love this visual a with this I'm

just love this visual a with this I'm going to change the title to what are

going to change the title to what are top paying countries now the last thing

top paying countries now the last thing is a minor Point sometimes if you're

is a minor Point sometimes if you're going ahead and actually moving maybe

going ahead and actually moving maybe columns around you'll notice that my

columns around you'll notice that my visualization is also moving as well and

visualization is also moving as well and this can wreak havoc especially whenever

this can wreak havoc especially whenever you've made your dash or made your chart

you've made your dash or made your chart a certain size and then move columns

a certain size and then move columns around and it messes everything up we

around and it messes everything up we can fix this so I'm going to go ahead

can fix this so I'm going to go ahead and contrl Z both of those column moves

and contrl Z both of those column moves to get it back to where I had previously

to get it back to where I had previously and then from there I'm just going to

and then from there I'm just going to double click on the chart itself go

double click on the chart itself go under chart options and once again this

under chart options and once again this like resizing one here and going under

like resizing one here and going under properties right now it's selected under

properties right now it's selected under move and size with cells we don't want

move and size with cells we don't want to do that basically we don't want to

to do that basically we don't want to move or size with the cells so I'm going

move or size with the cells so I'm going to select that now closing out of this

to select that now closing out of this whenever I go to adjust the column size

whenever I go to adjust the column size it's not going to adjust the

it's not going to adjust the visualization at all this is much more

visualization at all this is much more of what I want also one last note on

of what I want also one last note on this I do do have a filter currently

this I do do have a filter currently applied to this data set specifically I

applied to this data set specifically I go into it it's a custom filter and I

go into it it's a custom filter and I wanted to make sure that I had basically

wanted to make sure that I had basically removed any na values so I put hey I

removed any na values so I put hey I want values that are median Sal greater

want values that are median Sal greater than zero and are less than 200,000 so

than zero and are less than 200,000 so if I go ahead and clear this filter we

if I go ahead and clear this filter we can see that we have some other values

can see that we have some other values up here basically rushes up here at

up here basically rushes up here at 300,000 for a median salary and if we

300,000 for a median salary and if we actually go in investigate Russia we'll

actually go in investigate Russia we'll see that they only have around four jobs

see that they only have around four jobs with salary data listed so I feel like

with salary data listed so I feel like this salary is more of an outlier than

this salary is more of an outlier than anything so that's why I'm applying this

anything so that's why I'm applying this filter of 0 to 200,000 applying this

filter of 0 to 200,000 applying this filter again we get final visualization

filter again we get final visualization now you could also play around with this

now you could also play around with this and filter it based on the number of

and filter it based on the number of counts to make sure you have values that

counts to make sure you have values that are above a certain count that's also an

are above a certain count that's also an option and probably maybe even a better

option and probably maybe even a better option as well all right chch turn now

option as well all right chch turn now to dive into those practice problems to

to dive into those practice problems to try out some different Advanced

try out some different Advanced visualizations and along with some

visualizations and along with some Advanced customization with that in the

Advanced customization with that in the next lesson we're going to be diving

next lesson we're going to be diving deeper into understanding how to use

deeper into understanding how to use statistical analysis specifically box

statistical analysis specifically box and wher charts and also histograms and

and wher charts and also histograms and how to read them with that see you in

how to read them with that see you in the next

one this lesson is going to be focused on actually visualizing a lot of the

on actually visualizing a lot of the things that or a lot of the functions

things that or a lot of the functions that we used in that statistical

that we used in that statistical functions lesson where we're looking

functions lesson where we're looking visually at things like the median and

visually at things like the median and core tiles specifically we're going to

core tiles specifically we're going to do a refresher on histograms we've seen

do a refresher on histograms we've seen it a few time reality but we're going to

it a few time reality but we're going to dive into further understanding how

dive into further understanding how salaries are distributed specifically

salaries are distributed specifically for a target audience of data analyst in

for a target audience of data analyst in the United States you can feel feel free

the United States you can feel feel free to do whoever you want and then from

to do whoever you want and then from there based on the limitations of it

there based on the limitations of it only be able to visualize one job title

only be able to visualize one job title we're going to shift Vex to looking at

we're going to shift Vex to looking at box and whisker charts and these are

box and whisker charts and these are great at also showing statistical

great at also showing statistical distributions like a histogram but we

distributions like a histogram but we can take it a step further and we

can take it a step further and we compare different values specifically in

compare different values specifically in this case we're going to compare them

this case we're going to compare them across the different job titles on how

across the different job titles on how they're distributed now box and whisker

they're distributed now box and whisker charts aren't probably a chart that

charts aren't probably a chart that you're familiar with or most people are

you're familiar with or most people are familiar with so we're going to go

familiar with so we're going to go through a review and understand and

through a review and understand and break them down to understand those

break them down to understand those Concepts we talked about previously

Concepts we talked about previously about median and quartiles and where

about median and quartiles and where they fall into this for this we're going

they fall into this for this we're going to be using the charts statistics

to be using the charts statistics workbook specifically we're going to be

workbook specifically we're going to be starting in this data Tab and for all

starting in this data Tab and for all this we're going to be analyzing salary

this we're going to be analyzing salary data in this video we're going to be

data in this video we're going to be focusing specifically though on that

focusing specifically though on that yearly salary

data so let's actually go back into breaking down how to read a histogram we

breaking down how to read a histogram we go back into insert recommended charts

go back into insert recommended charts and then from there select histogram and

and then from there select histogram and insert in the histogram I don't like

insert in the histogram I don't like where it is right now I'm actually going

where it is right now I'm actually going to move this chart into a new sheet now

to move this chart into a new sheet now quick refresher on histograms each one

quick refresher on histograms each one of these bars represents a count of

of these bars represents a count of values within a range so in this case

values within a range so in this case there's 920 values between the range of

there's 920 values between the range of oh my gosh so hard to read 75,000 to

oh my gosh so hard to read 75,000 to 81,000 and as we're noting by this we

81,000 and as we're noting by this we have a large number over here if gets

have a large number over here if gets even out to 960,000 this would be called

even out to 960,000 this would be called a skewed right distribution now this is

a skewed right distribution now this is different from a column chart because

different from a column chart because this data down here on the xaxis is

this data down here on the xaxis is basically continuous data when one bin

basically continuous data when one bin stops so this first bin of 15,000 to

stops so this first bin of 15,000 to 21,000 the next bin picks up now the

21,000 the next bin picks up now the first problem with this histogram is

first problem with this histogram is this is for all salary data specifically

this is for all salary data specifically all job titles across all countries I

all job titles across all countries I want to actually find tune to look at my

want to actually find tune to look at my specific use case of data analyst in the

specific use case of data analyst in the United States so you can come here into

United States so you can come here into the histogram 2 Tab and I have the four

the histogram 2 Tab and I have the four Columns of interest that I want to use

Columns of interest that I want to use from the data Tab and I already have the

from the data Tab and I already have the filters applied but if you want to you

filters applied but if you want to you can come in here and actually select to

can come in here and actually select to clear these filters and I'll just select

clear these filters and I'll just select it here from that Home tab then from

it here from that Home tab then from there I'm going to go through and select

there I'm going to go through and select data analyst roles that are full-time

data analyst roles that are full-time only that are in the United States and

only that are in the United States and then finally I don't want any of these

then finally I don't want any of these blank values here so I'm going to

blank values here so I'm going to uncheck this value here for blanks now

uncheck this value here for blanks now we'll say filtering this data did take

we'll say filtering this data did take some time to actually do so don't be

some time to actually do so don't be alarmed if this taken more than 10 or 15

alarmed if this taken more than 10 or 15 seconds all right so back in let's

seconds all right so back in let's actually make a histogram with this data

actually make a histogram with this data we'll go into insert from here I'm going

we'll go into insert from here I'm going to insert in a histogram now once again

to insert in a histogram now once again this distribution is so the last one

this distribution is so the last one skewed right and we have a heavy amount

skewed right and we have a heavy amount of outline s right here even out this

of outline s right here even out this one value around 370,000 I don't think

one value around 370,000 I don't think this provides a lot of value instead I

this provides a lot of value instead I want to actually focus more into these

want to actually focus more into these this actual distribution and not

this actual distribution and not actually on this portion out here that

actually on this portion out here that we have just outliers anyway I'm going

we have just outliers anyway I'm going to come in here into our filters up here

to come in here into our filters up here insert a number filter and that it's

insert a number filter and that it's less than 300,000 click okay all right

less than 300,000 click okay all right this is looking a lot more readable

this is looking a lot more readable which we can actually see now the x-axis

which we can actually see now the x-axis now each one of these bars right here or

now each one of these bars right here or what what you would see in like a column

what what you would see in like a column chart are called the bins and they're

chart are called the bins and they're all equally space but we can control the

all equally space but we can control the width of each one of those bins that

width of each one of those bins that they Encompass specifically I can double

they Encompass specifically I can double click on the chart to bring up that pane

click on the chart to bring up that pane to the right selecting the x axis I can

to the right selecting the x axis I can then go into access options and then

then go into access options and then once again access options we can go into

once again access options we can go into something right now we're noticing that

something right now we're noticing that the bins are automatically determined we

the bins are automatically determined we can actually change this binwidth I'm

can actually change this binwidth I'm going to change this something to like

going to change this something to like 15,000 notice that it is bigger in this

15,000 notice that it is bigger in this case the bins are bigger than they were

case the bins are bigger than they were previously you can feel free to test

previously you can feel free to test different options if you will I feel if

different options if you will I feel if you go too small in the case let's say

you go too small in the case let's say we went down to 1,000 it just gets too

we went down to 1,000 it just gets too noisy and also you can't necessarily see

noisy and also you can't necessarily see the distribution as well so really you

the distribution as well so really you just have to play around with it until

just have to play around with it until you get to what you want to find as far

you get to what you want to find as far as the access goes this is a little bit

as the access goes this is a little bit this is sensory overload for me way too

this is sensory overload for me way too many zeros in here so I'm going to move

many zeros in here so I'm going to move this selecting the xaxis we can see that

this selecting the xaxis we can see that has format access now I can go under

has format access now I can go under number and once again we can go in our

number and once again we can go in our custom type none of the ones that I've

custom type none of the ones that I've previously done are here sometimes it

previously done are here sometimes it pops up sometimes it doesn't we're going

pops up sometimes it doesn't we're going to go ahead and just put in we want the

to go ahead and just put in we want the dollar sign zero and then formatted with

dollar sign zero and then formatted with the K value basically removing all those

the K value basically removing all those uh thousands zeros and I'm going to go

uh thousands zeros and I'm going to go ahead and click add all right this is a

ahead and click add all right this is a lot more readable to actually see what

lot more readable to actually see what those different ranges are

those different ranges are and from there I'm going to change the

and from there I'm going to change the title of how much do data analysts in

title of how much do data analysts in the United States make probably also

the United States make probably also best practice here to add a title on the

best practice here to add a title on the Y AIS for count of jobs and B now we

Y AIS for count of jobs and B now we have this final visualization show on

have this final visualization show on our histogram we can see that a lot of

our histogram we can see that a lot of the salaries are more around the range

the salaries are more around the range of 85,000 to 100,000 which 70,000 85,000

of 85,000 to 100,000 which 70,000 85,000 is coming up next so this show is really

is coming up next so this show is really visually great and at where I can expect

visually great and at where I can expect to have a salary as a starting data

analyst but now what if we want to analyze multiple different job titles

analyze multiple different job titles which we're going eventually get to is

which we're going eventually get to is this box plot here where we're plotting

this box plot here where we're plotting it for all the different job tiles we'll

it for all the different job tiles we'll be able to actually compare different

be able to actually compare different values across each other but before we

values across each other but before we get to that we need to First understand

get to that we need to First understand how to read a box plot also sometimes I

how to read a box plot also sometimes I call it a box plot but it's also known

call it a box plot but it's also known as a box and whiskers chart anyway I

as a box and whiskers chart anyway I made this visualization here you don't

made this visualization here you don't have to do it there's a bunch of

have to do it there's a bunch of customization along with it the main

customization along with it the main purpose of this is to demonstrate or

purpose of this is to demonstrate or help understand how to read a box and

help understand how to read a box and whiskers chart so I took our data that

whiskers chart so I took our data that we previously were analyzing for data

we previously were analyzing for data analyst in the United States it was a

analyst in the United States it was a full-time role along with all the salary

full-time role along with all the salary data and then I use like we previously

data and then I use like we previously did calculating things like the Min

did calculating things like the Min first quartile median average third

first quartile median average third quartile and Max just ignore this

quartile and Max just ignore this portion right here it was used to make

portion right here it was used to make build this visualization right here

build this visualization right here anyway I tried as best as possible to

anyway I tried as best as possible to line up this histogram where we have the

line up this histogram where we have the x-axis going from 25,000 to 285,000 with

x-axis going from 25,000 to 285,000 with the box and whiskers chart I may below

the box and whiskers chart I may below it from 25,000 to 285,000 so the Box

it from 25,000 to 285,000 so the Box itself signifies what that nerds call

itself signifies what that nerds call the inter quartile range basically all

the inter quartile range basically all the values between q1 or quartile 1 and

the values between q1 or quartile 1 and cortile 3 had a typo there got to fix

cortile 3 had a typo there got to fix that anyway that's why it was so

that anyway that's why it was so important that previously we calculated

important that previously we calculated that first quartile and third quartile

that first quartile and third quartile and if you remember from that there

and if you remember from that there quartiles so 50% of the data Falls

quartiles so 50% of the data Falls within this box and if we look up we

within this box and if we look up we were to draw imaginary lines into our

were to draw imaginary lines into our histogram we can see that about 50% of

histogram we can see that about 50% of the data does fall within this the next

the data does fall within this the next up inside of here is a line that is for

up inside of here is a line that is for the median in this case our median is

the median in this case our median is 990,000 and then we have our average of

990,000 and then we have our average of 90

90 5,000 which as we discussed previously

5,000 which as we discussed previously the average is going to be higher here

the average is going to be higher here because we have things all the way out

because we have things all the way out here called outliers basically dragging

here called outliers basically dragging that average higher and outliers are

that average higher and outliers are signified by these dots outside of the

signified by these dots outside of the whiskers themselves these whiskers are

whiskers themselves these whiskers are the lines and the lines themselves

the lines and the lines themselves extend to the minimum and the maximum

extend to the minimum and the maximum and these are just relative mins and

and these are just relative mins and Maxes they're not necessarily the true

Maxes they're not necessarily the true men and Max anyway so that's a box and

men and Max anyway so that's a box and whisker chart and frankly by themselves

whisker chart and frankly by themselves I don't think they're really great but

I don't think they're really great but when you pair them with other

when you pair them with other categorical values I find them super

categorical values I find them super interesting so let's actually build this

interesting so let's actually build this visualization so you can come over to

visualization so you can come over to this box plot2 Tab and I have our data

this box plot2 Tab and I have our data inside of it none of it is filtered it

inside of it none of it is filtered it has all the different job titles and all

has all the different job titles and all their Associated salaries for this I'm

their Associated salaries for this I'm going to select column M and then also

going to select column M and then also holding control I'm going to select

holding control I'm going to select column A then from there go in and

column A then from there go in and insert and go to recommended and from

insert and go to recommended and from there look at the box and whiskers chart

there look at the box and whiskers chart which looks like it's already pulling it

which looks like it's already pulling it up for us so let's pop this bad boy in

up for us so let's pop this bad boy in now one drawback of these box and

now one drawback of these box and whisker charts in Excel is unlike that

whisker charts in Excel is unlike that last box plot that I made I custom made

last box plot that I made I custom made this in order to make it appear in this

this in order to make it appear in this horizontal fashion you can actually do

horizontal fashion you can actually do that you can only have the option to

that you can only have the option to have them vertical up and down anyway

have them vertical up and down anyway this is pretty close of what we want to

this is pretty close of what we want to get the main problem I'm noticing right

get the main problem I'm noticing right now is we have outliers up to 1.2

now is we have outliers up to 1.2 million and it's really with the data

million and it's really with the data around 100 150,000 it's really hard to

around 100 150,000 it's really hard to actually look into those boxes so I'm

actually look into those boxes so I'm going to change this yvalue scale double

going to change this yvalue scale double clicking on the Y AIS I'm going to

clicking on the Y AIS I'm going to change the maximum to 300,000

change the maximum to 300,000 additionally since we're here I'm going

additionally since we're here I'm going to change that number formatting to use

to change that number formatting to use that 0k value then also I'm finding the

that 0k value then also I'm finding the color is a little hard to actually see

color is a little hard to actually see these x's in here so under series option

these x's in here so under series option selecting fill in line fill I'm going to

selecting fill in line fill I'm going to change this color to more of a lighter

change this color to more of a lighter blue okay and that's definitely easier

blue okay and that's definitely easier to read I'm going to add a vertical

to read I'm going to add a vertical access of salary USD I'm also going to

access of salary USD I'm also going to bold it all to make it a little bit more

bold it all to make it a little bit more readable and then from there change that

readable and then from there change that chart title to what are the top paying

chart title to what are the top paying jobs in data science all right getting

jobs in data science all right getting into actually analyzing this and getting

into actually analyzing this and getting insights from it now one drawback out of

insights from it now one drawback out of this is there's not an easy way to sort

this is there's not an easy way to sort these values right here right now I'd

these values right here right now I'd normally put them high to low I'd

normally put them high to low I'd probably put them high to low based on

probably put them high to low based on median salary but they've been put into

median salary but they've been put into this graph based on the order that they

this graph based on the order that they first appear over here in column A and

first appear over here in column A and that's when they pop up so that's the

that's when they pop up so that's the order so technically I could go through

order so technically I could go through and sort this column

and sort this column alphabetically but that's going to take

alphabetically but that's going to take a little bit too much time if you want

a little bit too much time if you want to do that feel free to try that out

to do that feel free to try that out anyway it looks like roles like machine

anyway it looks like roles like machine learning engineers and also software

learning engineers and also software Engineers have a pretty large inter

Engineers have a pretty large inter cortile range or that where that 50% of

cortile range or that where that 50% of that data Falls so there's a basically a

that data Falls so there's a basically a wide range of data or salaries you could

wide range of data or salaries you could find with that whereas data nerds data

find with that whereas data nerds data scientists data analysts and data

scientists data analysts and data Engineers have a tighter band also as

Engineers have a tighter band also as expected those data analysts and

expected those data analysts and business analysts have some of the

business analysts have some of the lowest median salaries where something

lowest median salaries where something like the data engineers and the senior

like the data engineers and the senior roles have even higher median salaries

roles have even higher median salaries overall this is pretty great at going in

overall this is pretty great at going in comparing values I would probably work

comparing values I would probably work with this more to fine tune it to only

with this more to fine tune it to only have a couple of job titles in it and

have a couple of job titles in it and for that we can use something like

for that we can use something like slicers which will be covering in an

slicers which will be covering in an upcoming chapter well the next chapter

upcoming chapter well the next chapter when we get into Advanced Techniques in

when we get into Advanced Techniques in Excel so we'll be able to customize this

Excel so we'll be able to customize this further once you have that knowledge all

further once you have that knowledge all right you now have some practice

right you now have some practice problems to go through and get more

problems to go through and get more familiar with those histograms and all

familiar with those histograms and all scope box and whisker charts in the next

scope box and whisker charts in the next lesson which is a quick one we're going

lesson which is a quick one we're going to be moving into spark lines which is

to be moving into spark lines which is the final lesson in this chart overview

the final lesson in this chart overview with that I'll see you in the next

one moving into this last lesson on charts focusing on spark line spark

charts focusing on spark line spark lines are basically ways to insert mini

lines are basically ways to insert mini charts into a cell that summarizes data

charts into a cell that summarizes data that's next to it if your data is coming

that's next to it if your data is coming in a horizontal form similar to this

in a horizontal form similar to this table you probably have the possibility

table you probably have the possibility of considering inserting a spark line

of considering inserting a spark line we're going to going through how to make

we're going to going through how to make them but also customizing it all right

them but also customizing it all right for this we're going to be using the

for this we're going to be using the spark lines workbook for this we have

spark lines workbook for this we have like usual our data Tab and then our

like usual our data Tab and then our original tab that calculates data off it

original tab that calculates data off it and for this data set we're just looking

and for this data set we're just looking at what are the counts of the different

at what are the counts of the different job titles based on month so this is

job titles based on month so this is basically horizontally oriented this is

basically horizontally oriented this is great for a spar

line so how we're going to do this well we'll go ahead and select the data only

we'll go ahead and select the data only so C4 to n10 then come up into the

so C4 to n10 then come up into the insert tab then right here we have this

insert tab then right here we have this section on spark lines we can insert a

section on spark lines we can insert a line column or a win loss we'll just

line column or a win loss we'll just start with column to start with and it

start with column to start with and it fills in for the data range C4 to 10 but

fills in for the data range C4 to 10 but it wants us to choose where you want the

it wants us to choose where you want the spark lines to be placed so the location

spark lines to be placed so the location range and click this Arrow here and then

range and click this Arrow here and then from there actually drag it next to it

from there actually drag it next to it all close this Arrow back and click okay

all close this Arrow back and click okay anyway I wanted to demonstrate that bar

anyway I wanted to demonstrate that bar chart because it's not really that great

chart because it's not really that great for here remember anytime we're doing

for here remember anytime we're doing continuous data in this case we're doing

continuous data in this case we're doing that monthly data I'm going to want to

that monthly data I'm going to want to use something like a line chart instead

use something like a line chart instead so I can easily change it by coming up

so I can easily change it by coming up here selecting all of our different data

here selecting all of our different data selecting that spark Line tab and then

selecting that spark Line tab and then just changing it to I can change

just changing it to I can change something like win loss which no really

something like win loss which no really data from this line chart that's what we

data from this line chart that's what we really want from this now getting into

really want from this now getting into the customization of this I really

the customization of this I really personally I'm like blue so we're going

personally I'm like blue so we're going to stick with the blue color but we

to stick with the blue color but we could change the color if we want to and

could change the color if we want to and the other thing we change is the marker

the other thing we change is the marker color right now we don't have any

color right now we don't have any markers on it we can actually change

markers on it we can actually change which markers are right here in the show

which markers are right here in the show selection right here so I can select the

selection right here so I can select the high points right now it's going to

high points right now it's going to highlight all of them red uh low point

highlight all of them red uh low point also red negative points there's no

also red negative points there's no negative point you also do the first

negative point you also do the first point which I don't really find much

point which I don't really find much value in that or last point and then

value in that or last point and then actual finally the markers itself you

actual finally the markers itself you just put every single one of them with a

just put every single one of them with a marker I really like this High Point and

marker I really like this High Point and this low point and we can customize this

this low point and we can customize this the high points I would really want to

the high points I would really want to call out to be a green color right now

call out to be a green color right now this green that's sort of hard to see so

this green that's sort of hard to see so I'm going to change it to something a

I'm going to change it to something a little bit darker and Bam we can see

little bit darker and Bam we can see that one a little better the red for the

that one a little better the red for the low point I'm going to keep it as is and

low point I'm going to keep it as is and the last thing is all this data has

the last thing is all this data has Bally a grid around it I'm just going to

Bally a grid around it I'm just going to add that in real quick by selecting all

add that in real quick by selecting all the cells come up into home into the

the cells come up into home into the borders I'm going to put in all borders

borders I'm going to put in all borders around it then it looks like I have a

around it then it looks like I have a double line right here for this lower

double line right here for this lower one so I'll insert this bottom double

one so I'll insert this bottom double border and then finally I'm going to put

border and then finally I'm going to put a thick border around this all bam we

a thick border around this all bam we have our final visualization there now I

have our final visualization there now I can go through and see things like okay

can go through and see things like okay with that analyst and other analyst we

with that analyst and other analyst we saw spikes in January but things like

saw spikes in January but things like thata Engineers we didn't see a spike

thata Engineers we didn't see a spike however all the job titles ran to a

however all the job titles ran to a similar problem where apparently they

similar problem where apparently they ran out of budget and the least amount

ran out of budget and the least amount of jobs were posted in November and

of jobs were posted in November and December so this's a pretty cool feature

December so this's a pretty cool feature to show some quick snapshots about the

to show some quick snapshots about the data you're looking at right you now

data you're looking at right you now have some practice problems to go

have some practice problems to go through and basically practice making

through and basically practice making some of these spark lines we're going to

some of these spark lines we're going to next be jumping in the next chapter it's

next be jumping in the next chapter it's our final chapter of the basic section

our final chapter of the basic section and it's going to be focusing on

and it's going to be focusing on Advanced features inside spreadsheets

Advanced features inside spreadsheets such as tables formatting and how to

such as tables formatting and how to collaborate with others it's our last

collaborate with others it's our last section before we build our first

section before we build our first project so with that I'll see you in the

project so with that I'll see you in the next chapter on Advanced

spreadsheets then nerds welcome to this last chapter in the basic section

last chapter in the basic section focusing on Advanced features and

focusing on Advanced features and spreadsheets there's a last chapter

spreadsheets there's a last chapter we're going to be covering before we get

we're going to be covering before we get into our first project and this chapter

into our first project and this chapter is broken into three different lessons

is broken into three different lessons this one right here is going to be on

this one right here is going to be on tables how to use tables how to use

tables how to use tables how to use things like slicers and how to

things like slicers and how to manipulate them second lesson is on

manipulate them second lesson is on formatting not just on making cells look

formatting not just on making cells look pretty but developing conditional

pretty but developing conditional formatting rules in order to highlight

formatting rules in order to highlight CES according to well a certain rule

CES according to well a certain rule pretty interesting feature within Excel

pretty interesting feature within Excel and the third lesson is on collaboration

and the third lesson is on collaboration for a project we're going to be making a

for a project we're going to be making a dashboard and so we need to enact

dashboard and so we need to enact certain measures in order to protect it

certain measures in order to protect it and prevent people from going in and

and prevent people from going in and messing it up and so we're going to go

messing it up and so we're going to go over a lot of features in order to set

over a lot of features in order to set it up properly anyway back to this

it up properly anyway back to this lesson what are we going to be doing for

lesson what are we going to be doing for it well first we're going to start out

it well first we're going to start out by using a smaller subset of our data

by using a smaller subset of our data set basically 15 rows and creating your

set basically 15 rows and creating your first table we're going to be

first table we're going to be manipulating it using custom formulas

manipulating it using custom formulas that we really haven't seen before along

that we really haven't seen before along with using some other ones that we have

with using some other ones that we have seen before in order to calculate totals

seen before in order to calculate totals subtotals and Aggregates by the end of

subtotals and Aggregates by the end of this lesson we're going to be building a

this lesson we're going to be building a mini dashboard to analyze that histogram

mini dashboard to analyze that histogram that we talked about in our previous

that we talked about in our previous lessons specifically we're going to add

lessons specifically we're going to add slicers to it in order to be able to

slicers to it in order to be able to filter down and look at a subset of data

filter down and look at a subset of data that we're most interested about and

that we're most interested about and that's all could be done without the

that's all could be done without the help of tables for this lesson we're

help of tables for this lesson we're going to be using the tables workbook in

going to be using the tables workbook in chapter

4 for this you're going to start in the tables intro original sheet and then the

tables intro original sheet and then the final one's going to be what we're going

final one's going to be what we're going to eventually get to all these are going

to eventually get to all these are going to be labeled similarly with the

to be labeled similarly with the original and final and we're all going

original and final and we're all going to be working with the original it

to be working with the original it should look like the final when you get

should look like the final when you get done with this so let's dive into

done with this so let's dive into creating our first table first thing you

creating our first table first thing you have to do is make sure that we're

have to do is make sure that we're selected somewhere in here we don't

selected somewhere in here we don't necessarily need to select the full

necessarily need to select the full table but just somewhere in here from

table but just somewhere in here from there we'll go into the insert Tab and

there we'll go into the insert Tab and we'll insert a table also notice that we

we'll insert a table also notice that we can use the shortcut control t for this

can use the shortcut control t for this so I'm going to do that instead and for

so I'm going to do that instead and for this it automatically pinpoints the

this it automatically pinpoints the rightmost cell and the bottom most cell

rightmost cell and the bottom most cell and we need to make sure we have this

and we need to make sure we have this check mark enabled of my table has

check mark enabled of my table has headers because we have well call them

headers because we have well call them headers and Bam we just made our first

headers and Bam we just made our first table this lesson's over but seriously

table this lesson's over but seriously let's actually get into exploring this

let's actually get into exploring this table design tab that now appears

table design tab that now appears anytime you're selected to the table if

anytime you're selected to the table if I click off of it it disappears anyway

I click off of it it disappears anyway we're going to first look at the table

we're going to first look at the table name and i' like to have a table name

name and i' like to have a table name that's easy to reference so I'm going to

that's easy to reference so I'm going to just name it something like jobs it's

just name it something like jobs it's going to come into handy naming it

going to come into handy naming it something simple whenever we're making

something simple whenever we're making formulas later for this now we'll get to

formulas later for this now we'll get to this section in a little bit on tool and

this section in a little bit on tool and external table data but I want to move

external table data but I want to move over to the style options you can play

over to the style options you can play around with some of these options here

around with some of these options here where you can highlight the First Column

where you can highlight the First Column or you can highlight the last column has

or you can highlight the last column has a lot of different formatting options

a lot of different formatting options with it but what I really like is this

with it but what I really like is this color formatting if I'm not really

color formatting if I'm not really liking the color that it's given to me

liking the color that it's given to me just come over here select a new one so

just come over here select a new one so we'll get back to table design in a bit

we'll get back to table design in a bit but what's really the benefit of this

but what's really the benefit of this table well one thing is you can easily

table well one thing is you can easily add data to a table and it will will

add data to a table and it will will autofill let me show you let's say I

autofill let me show you let's say I wanted to add a new column with a solid

wanted to add a new column with a solid year average copy whenever I enter this

year average copy whenever I enter this new column name and press enter it

new column name and press enter it automatically fills this in I can the

automatically fills this in I can the skills are sort of covering this up

skills are sort of covering this up right now sorry about that and I can

right now sorry about that and I can make this a little bit bigger but you

make this a little bit bigger but you can see we have salary or average copy

can see we have salary or average copy now included within this table and I can

now included within this table and I can verify that it's included also in this

verify that it's included also in this table by if I want to go to resize table

table by if I want to go to resize table it will say that now it goes to

it will say that now it goes to k16 now for this I just want to copy the

k16 now for this I just want to copy the results of the salary year average

results of the salary year average column over here in h so what I'm going

column over here in h so what I'm going to do is press equal to and I'm just

to do is press equal to and I'm just going to select the cell over here of H2

going to select the cell over here of H2 now this is what I was talking about

now this is what I was talking about whenever I said tables have their own

whenever I said tables have their own unique formulas what it's going and

unique formulas what it's going and doing here is it's referencing the

doing here is it's referencing the salary or average column which is this

salary or average column which is this portion right here and then it's also

portion right here and then it's also using this at symbol to basically refer

using this at symbol to basically refer to this is the same point in the row of

to this is the same point in the row of H2 that is a K2 anyway when I go ahead

H2 that is a K2 anyway when I go ahead and press enter Watch What Happens we

and press enter Watch What Happens we actually fill in all the different

actually fill in all the different values of this so if I were to actually

values of this so if I were to actually double click into this one down here we

double click into this one down here we still have that same syntax of we're

still have that same syntax of we're selecting the Sal your average column

selecting the Sal your average column and we're using that at value value to

and we're using that at value value to get the one that corresponds in that

get the one that corresponds in that same row now let's dive deeper into

same row now let's dive deeper into these different formulas we can use for

these different formulas we can use for this table so I'm going to come over

this table so I'm going to come over here into column n and for this remember

here into column n and for this remember we named our table jobs so I'm just

we named our table jobs so I'm just going to type in jobs and I have two

going to type in jobs and I have two tables in here one called job one jobs

tables in here one called job one jobs you only have one popping in here anyway

you only have one popping in here anyway it automatically pops up so I'm going to

it automatically pops up so I'm going to select jobs and now whenever I do this

select jobs and now whenever I do this I'm going to press enter it's using our

I'm going to press enter it's using our modern dynamic arrays basically to fill

modern dynamic arrays basically to fill in all the data that we have over here

in all the data that we have over here inside of our table so pretty unique in

inside of our table so pretty unique in how we can reference this now what

how we can reference this now what happens if we wanted to also include the

happens if we wanted to also include the column headers up at the top well I can

column headers up at the top well I can type in jobs and then from there I'm

type in jobs and then from there I'm going to add a square bracket and we

going to add a square bracket and we have a few options popping up right now

have a few options popping up right now it looks like it's just a column titles

it looks like it's just a column titles but if we scroll down we have these

but if we scroll down we have these values here with hashtags in it

values here with hashtags in it specifically I want with the column

specifically I want with the column headers so I'm going to put hashtag

headers so I'm going to put hashtag headers I'm going to put a close bracket

headers I'm going to put a close bracket on this and then press enter and now we

on this and then press enter and now we have the column headers across the top

have the column headers across the top now that's a little bit too much work

now that's a little bit too much work having to do two different formulas for

having to do two different formulas for this if instead I wanted to do job and

this if instead I wanted to do job and then square bracket and see the options

then square bracket and see the options available I can see I have an all a data

available I can see I have an all a data only a headers and a totals row totals

only a headers and a totals row totals row we're going to get to a little bit

row we're going to get to a little bit so we'll do the all for now and if I go

so we'll do the all for now and if I go ahead and press enter bam we now have

ahead and press enter bam we now have our data with our column headers and

our data with our column headers and also the data itself but what happens if

also the data itself but what happens if you want to just access certain columns

you want to just access certain columns well I thought you never asked that well

well I thought you never asked that well once again I can type in something like

once again I can type in something like jobs but the square bracket and then we

jobs but the square bracket and then we have a list of different columns

have a list of different columns available let's do the salary year

available let's do the salary year average and do a close bracket once

average and do a close bracket once again this is going to provide the data

again this is going to provide the data values only if we wanted to include the

values only if we wanted to include the specific header for this I once again

specific header for this I once again need to put in jobs and this time I'm

need to put in jobs and this time I'm going need to specify not only the

going need to specify not only the headers so I need to put this in its own

headers so I need to put this in its own square brackets but I'm also going to

square brackets but I'm also going to have to do a comma put another square

have to do a comma put another square brackets and put salary year average

brackets and put salary year average within its own brackets so it's almost

within its own brackets so it's almost like a list of items if you're familiar

like a list of items if you're familiar with python this would be like a list

with python this would be like a list anyway we have the headers in Brackets

anyway we have the headers in Brackets and we have salary year average in

and we have salary year average in Brackets pressing enter we get salary

Brackets pressing enter we get salary your average up at the top now honestly

your average up at the top now honestly an easier way to do this all is to well

an easier way to do this all is to well use that all command or hashtag all but

use that all command or hashtag all but it has to be put within its own square

it has to be put within its own square brackets then from there a comma and

brackets then from there a comma and then we want to say hey the subset only

then we want to say hey the subset only that we're providing for this is salary

that we're providing for this is salary year average close that bracket and then

year average close that bracket and then close the entire brackets for jobs now

close the entire brackets for jobs now from there when we run it we get the Sal

from there when we run it we get the Sal year average along with all the column

year average along with all the column values at any time if you forget that

values at any time if you forget that it's not that big of a deal as you can

it's not that big of a deal as you can just go through and put an equal sign

just go through and put an equal sign and like we did previously I could just

and like we did previously I could just highlight well not that um our salary

highlight well not that um our salary your average column and look it

your average column and look it automatically populates with that same

automatically populates with that same formula above here and when I press

formula above here and when I press enter boom it pops up there so don't

enter boom it pops up there so don't think you have to memorize these

think you have to memorize these formulas that I just went over but what

formulas that I just went over but what do all these formulas actually provide

do all these formulas actually provide any value value for well let's look at a

any value value for well let's look at a use case let's say I wanted to identify

use case let's say I wanted to identify jobs that whenever we looked at the

jobs that whenever we looked at the skills we could find out if they

skills we could find out if they contained the skill of Excel or not so

contained the skill of Excel or not so I'm going to create this new column over

I'm going to create this new column over here and call it Excel and for this

here and call it Excel and for this we're going to be using the search

we're going to be using the search function which we need to provide what

function which we need to provide what text we want to actually find

text we want to actually find conveniently I put it in the column

conveniently I put it in the column header so I'll go ahead and just select

header so I'll go ahead and just select it and automatically populates the

it and automatically populates the formula for this then from that we need

formula for this then from that we need to go to the next parameter of within

to go to the next parameter of within text we're trying to look at that job

text we're trying to look at that job skills column it puts that at symbol at

skills column it puts that at symbol at the front of job skills to basically

the front of job skills to basically signify look at that row then from there

signify look at that row then from there I'm going to go ahead and close the

I'm going to go ahead and close the parentheses and press enter so for that

parentheses and press enter so for that search function it provides the N

search function it provides the N numerical location of excel in here

numerical location of excel in here Excel is 36 characters deep into this so

Excel is 36 characters deep into this so I'm just going to modify this cuz I

I'm just going to modify this cuz I don't really care about the number of

don't really care about the number of that I'm going to say I'm going to use

that I'm going to say I'm going to use the is number function which checks if

the is number function which checks if it's a number and then returns true or

it's a number and then returns true or false in this case we have True Values

false in this case we have True Values so we know that for these columns if

so we know that for these columns if they contain Excel or not they'll have

they contain Excel or not they'll have true so that's how I find myself using

true so that's how I find myself using these different formulas and

these different formulas and understanding how to actually manipulate

understanding how to actually manipulate them anyway let's get into our next step

them anyway let's get into our next step let's say we wanted to include some sort

let's say we wanted to include some sort of totals Row in order to maybe

of totals Row in order to maybe calculate median salary how many job

calculate median salary how many job postings there were Etc so we'll go into

postings there were Etc so we'll go into this table design Tab and I'm going

this table design Tab and I'm going going to select the total row and now

going to select the total row and now down here in row 17 we have total

down here in row 17 we have total written down here along with a bunch of

written down here along with a bunch of well blank values except for all the way

well blank values except for all the way to the right looks like it puts us the

to the right looks like it puts us the number of 15 which is the total of these

number of 15 which is the total of these now going over to that salary year

now going over to that salary year average column I can basically select

average column I can basically select this totals row right here and you

this totals row right here and you notice a drop down appears right here

notice a drop down appears right here from here we can select some basic

from here we can select some basic statistics average count min max

statistics average count min max variance go ahead and select average

variance go ahead and select average that's the average of this column right

that's the average of this column right here so pretty neat I'd go through and

here so pretty neat I'd go through and if I wanted to do other columns as well

if I wanted to do other columns as well that now you can also go into here and

that now you can also go into here and select more functions and then like we

select more functions and then like we said we want to calculate Median on this

said we want to calculate Median on this salary we could go ahead and select this

salary we could go ahead and select this function of median but I'm actually

function of median but I'm actually going to recommend another approach you

going to recommend another approach you see if we double click inside of here we

see if we double click inside of here we actually see that this totals column is

actually see that this totals column is using a function specifically the

using a function specifically the subtotal function function so let's

subtotal function function so let's actually build this out from scratch

actually build this out from scratch without selecting it luckily we have the

without selecting it luckily we have the salary your average copy column over

salary your average copy column over here so I'm going to go in and I'm going

here so I'm going to go in and I'm going to type in subtotal and it returns a

to type in subtotal and it returns a subtotal in a list or database first is

subtotal in a list or database first is the function number what do we want it

the function number what do we want it to actually do and this has even more

to actually do and this has even more values available to it that you can

values available to it that you can actually select from and perform on this

actually select from and perform on this so in this case let's say I wanted to

so in this case let's say I wanted to find out what the max value is I would

find out what the max value is I would plug this in it would be 104 and then

plug this in it would be 104 and then for the reference for this well we're

for the reference for this well we're just going to select this salary year

just going to select this salary year average copy column it automatically

average copy column it automatically transformed into this special syntax and

transformed into this special syntax and then add a closing parenthesis and press

then add a closing parenthesis and press enter and so now we have the max salary

enter and so now we have the max salary which looking at this it's true but if

which looking at this it's true but if we go back into this and actually

we go back into this and actually inspect what values are available in

inspect what values are available in this function number we can see that

this function number we can see that median is not available in here so what

median is not available in here so what are we going to do well there's another

are we going to do well there's another function we're not going to use median

function we're not going to use median but that I recommend instead of using

but that I recommend instead of using sub total and for this one we're going

sub total and for this one we're going to use the aggregate function and this

to use the aggregate function and this returns an aggregate in a list or

returns an aggregate in a list or database it's similarly designed where

database it's similarly designed where it has a function number but with this

it has a function number but with this one we have a lot more options including

one we have a lot more options including things like CTO and stuff like that

things like CTO and stuff like that anyway it has median available as number

anyway it has median available as number 12 now the second parameter on options

12 now the second parameter on options allows us to select a host of options uh

allows us to select a host of options uh no pun intended for allowing us how we

no pun intended for allowing us how we want to actually perform this aggregate

want to actually perform this aggregate basically do we want to maybe ignore

basically do we want to maybe ignore hidden rows or do we want to ignore

hidden rows or do we want to ignore error values in my case I don't really

error values in my case I don't really want to ignore anything so I'm just

want to ignore anything so I'm just going to do number four and then finally

going to do number four and then finally we need to insert the array or the

we need to insert the array or the column itself in this case we want

column itself in this case we want salary year average closing the

salary year average closing the parentheses on this and pressing enter

parentheses on this and pressing enter we get our median value of 94,000

now depending how fast your computer is you're going to run into some

you're going to run into some limitations here I have in the table

limitations here I have in the table limits original tab which is the next

limits original tab which is the next one we're going to be working with in

one we're going to be working with in this uh portion of the lesson it has

this uh portion of the lesson it has around well 32,000 which is in the data

around well 32,000 which is in the data set anyway we're going to run into some

set anyway we're going to run into some limitations as I'm going to show I'm

limitations as I'm going to show I'm going to encourage you to just watch

going to encourage you to just watch along uh me do this and then from there

along uh me do this and then from there basically decide if you think you have a

basically decide if you think you have a strong enough computer or not to

strong enough computer or not to continue on to do this

continue on to do this um but if you have a pretty uh basically

um but if you have a pretty uh basically slow computer I wouldn't necessarily

slow computer I wouldn't necessarily follow along with this anyway I'm going

follow along with this anyway I'm going to convert this into table by selecting

to convert this into table by selecting any portion in here pressing contrl T it

any portion in here pressing contrl T it selected all the different values and

selected all the different values and that table has CS so now we've converted

that table has CS so now we've converted this into a table and one of the

this into a table and one of the benefits we haven't really discussed yet

benefits we haven't really discussed yet is the ability to actually filter data

is the ability to actually filter data because it automatically provides this

because it automatically provides this filter up at the top now I'm going to go

filter up at the top now I'm going to go ahead and filter this down based on a

ahead and filter this down based on a data analyst job title and when I go

data analyst job title and when I go through and actually select this to just

through and actually select this to just select it at analyst and press okay it

select it at analyst and press okay it runs pretty quickly but I have run into

runs pretty quickly but I have run into problems in the past especially working

problems in the past especially working with smaller computers where it takes a

with smaller computers where it takes a while to do this I'm working with about

while to do this I'm working with about 24 GB of RAM on this virtual machine so

24 GB of RAM on this virtual machine so if you're something at like8 or even 4

if you're something at like8 or even 4 I'm going to highly recommend that you

I'm going to highly recommend that you may not perform this exercise

so moving to this last exercise of this lesson I've gone ahead and condensed

lesson I've gone ahead and condensed down this data set you can go into

down this data set you can go into histogram original and our previous data

histogram original and our previous data set I basically shorn it down to these

set I basically shorn it down to these four columns and limited to only

four columns and limited to only positions that have a salary year

positions that have a salary year average value listed basically if

average value listed basically if there's blanks I remove those rows so

there's blanks I remove those rows so it's about 208,000 rows anyway this is

it's about 208,000 rows anyway this is what we're going to be manipulating for

what we're going to be manipulating for this this shouldn't lock up your

this this shouldn't lock up your computer if you have a basically a

computer if you have a basically a computer with less RAM and we're going

computer with less RAM and we're going to convert this into a table first

to convert this into a table first pressing control T I select all the

pressing control T I select all the values on here and press okay so now we

values on here and press okay so now we have a title now also in this sheet you

have a title now also in this sheet you may have noticed hopefully that it's

may have noticed hopefully that it's been on the screen I have this histogram

been on the screen I have this histogram here which is basically aggregating the

here which is basically aggregating the data from this Delta column on salary

data from this Delta column on salary year average anyway we're going to be

year average anyway we're going to be manipulating this further we want to

manipulating this further we want to basically make this into a dashboard so

basically make this into a dashboard so we can go through and maybe filter for

we can go through and maybe filter for different job title different job

different job title different job schedule types or different job

schedule types or different job countries and it can be mildly

countries and it can be mildly inconvenient to come up here and

inconvenient to come up here and actually select this arrow and then go

actually select this arrow and then go through and select the values want

through and select the values want that's why slicers are great so with our

that's why slicers are great so with our table selected I'm going to go into

table selected I'm going to go into table design and then from there under

table design and then from there under Tools I'm going go to insert slicer

Tools I'm going go to insert slicer we're going to be entering in both a job

we're going to be entering in both a job tile short job schedule type and a job

tile short job schedule type and a job country slicer so all three are here now

country slicer so all three are here now I'm going to go ahead and position them

I'm going to go ahead and position them make them look a lot neater all right

make them look a lot neater all right got them cleaned up and then from there

got them cleaned up and then from there I can go ahead and actually select the

I can go ahead and actually select the slider sir and if you notice this slicer

slider sir and if you notice this slicer tab pops up conveniently labeled this

tab pops up conveniently labeled this slicer has a caption on it or a title as

slicer has a caption on it or a title as well and I can just rename it basically

well and I can just rename it basically to a better visually appealing title in

to a better visually appealing title in this case I want it to call job title

this case I want it to call job title and then it updates here for job title

and then it updates here for job title I'm going to do the same for the other

I'm going to do the same for the other two updating it to schedule type and

two updating it to schedule type and then also Country Now by default this

then also Country Now by default this slicer and all the slicers have all the

slicer and all the slicers have all the value selected so if I wanted to to go

value selected so if I wanted to to go in to actually select a value I could do

in to actually select a value I could do something like well we want to look at

something like well we want to look at data analyst I just select data analyst

data analyst I just select data analyst it's going to clear all those other ones

it's going to clear all those other ones and then only select that analyst as you

and then only select that analyst as you notice it took a second for it to

notice it took a second for it to actually load that's why with this

actually load that's why with this 20,000 rows of data even that's a little

20,000 rows of data even that's a little high for tables I recommend it around

high for tables I recommend it around 10,000 if you're using tables anyway we

10,000 if you're using tables anyway we have it filtered down to data analyst I

have it filtered down to data analyst I could also do it down to

could also do it down to fulltime along with filtering it for U

fulltime along with filtering it for U basically

basically uh I want to do United States if you

uh I want to do United States if you notice these values are gray out that

notice these values are gray out that means there's no country basically

means there's no country basically available with the current selections

available with the current selections that I have of data analyst in full-time

that I have of data analyst in full-time so that's what that means there but I

so that's what that means there but I can go into that for United States

can go into that for United States selecting it and Bam we now have our

selecting it and Bam we now have our final basically visualization but what

final basically visualization but what happens if I want to maybe look at

happens if I want to maybe look at multiple different values what if I

multiple different values what if I maybe want to look at both data analyst

maybe want to look at both data analyst and business analyst well in that case

and business analyst well in that case you want to select this box up here and

you want to select this box up here and it allows multi I select and so I enable

it allows multi I select and so I enable it and now I can go through and select

it and now I can go through and select something like business analyst and this

something like business analyst and this provides both those values along with I

provides both those values along with I wanted to look at full-time and also

wanted to look at full-time and also part-time I could enable the multi

part-time I could enable the multi select on this schedule type and select

select on this schedule type and select part-time and Bam now we have multiple

part-time and Bam now we have multiple values selected for this along with the

values selected for this along with the United States and this makes the

United States and this makes the dashboards that you're building a lot

dashboards that you're building a lot more interactive and a little bit fun to

more interactive and a little bit fun to play around and to visualize the

play around and to visualize the different data all right we have some

different data all right we have some practice problems for you now to go

practice problems for you now to go through and dive into not only creating

through and dive into not only creating tables manipulating them but also adding

tables manipulating them but also adding and playing with slicers as well with

and playing with slicers as well with that we'll see you in the next lesson

that we'll see you in the next lesson we're going to be jumping into

we're going to be jumping into formatting specifically conditional

formatting specifically conditional formatting so see you

there in this lesson we're going to be focusing on formatting and not just self

focusing on formatting and not just self formatting where we're going through and

formatting where we're going through and adding borders and colors but also

adding borders and colors but also conditional formatting where a cell's

conditional formatting where a cell's basically formatting highlighting will

basically formatting highlighting will update dynamically based on a value in

update dynamically based on a value in the first example we're going to focus

the first example we're going to focus on Cell formatting specifically we're

on Cell formatting specifically we're going to go back to that table that

going to go back to that table that we've worked with previously that does a

we've worked with previously that does a count of data science jobs over the

count of data science jobs over the month anyway we're going to go through

month anyway we're going to go through and actually format it using all the

and actually format it using all the different functions we can in order to

different functions we can in order to make it look pretty like I made it from

make it look pretty like I made it from there we're going to move into our first

there we're going to move into our first conditional formatting example where

conditional formatting example where we're going to look at basically

we're going to look at basically highlighting based on a job title those

highlighting based on a job title those that are basically high and those that

that are basically high and those that are low highlighting them appropriately

are low highlighting them appropriately green or red and then in our final

green or red and then in our final example we're going to move on besides

example we're going to move on besides using color scales to also using things

using color scales to also using things like datab bars and also icon sets to

like datab bars and also icon sets to make it look a lot more Dynamic we're

make it look a lot more Dynamic we're also going to go over best practices on

also going to go over best practices on what not to do cuz sometimes you can go

what not to do cuz sometimes you can go overboard in how much you're actually

overboard in how much you're actually coloring a table and you can make it a

coloring a table and you can make it a little distracting and and ultimately

little distracting and and ultimately not meet your goal for this lesson we'll

not meet your goal for this lesson we'll be working with our formatting notebook

be working with our formatting notebook in chapter 4 as usual all the data is

in chapter 4 as usual all the data is located in the little data Tab and we'll

located in the little data Tab and we'll be starting with the underscore original

be starting with the underscore original of each of these sheets and then it

of each of these sheets and then it we'll get to in this case format

we'll get to in this case format original we'll have what it looks like

original we'll have what it looks like format

final for the cell formatting we're going to be using this format original

going to be using this format original sheet and we're going to be focused on

sheet and we're going to be focused on this Home tab here so I'm actually going

this Home tab here so I'm actually going to leave it expanded and for this we're

to leave it expanded and for this we're going to make this to where well what

going to make this to where well what this table looks like by going through

this table looks like by going through and actually formatting using all the

and actually formatting using all the different features in here so the first

different features in here so the first thing we need to do is highlight it all

thing we need to do is highlight it all and actually remove the formatting so

and actually remove the formatting so with it all selected I can go to editing

with it all selected I can go to editing and then clear and I can either clear

and then clear and I can either clear all which is what I don't want to do I

all which is what I don't want to do I want to do clear format and Bam now we

want to do clear format and Bam now we have an ugly table that doesn't really

have an ugly table that doesn't really make a lot of sense now previously we

make a lot of sense now previously we were mess with tables so I could

were mess with tables so I could highlight from B3 to 010 and make this

highlight from B3 to 010 and make this into a table by coming up here to format

into a table by coming up here to format as table basically selecting the color

as table basically selecting the color that I want saying that it has headers

that I want saying that it has headers and allowing it to update there's

and allowing it to update there's definitely an option um but I'm not

definitely an option um but I'm not necessarily a fan of this so I'm going

necessarily a fan of this so I'm going to clear this by pressing contrl Z Now

to clear this by pressing contrl Z Now an underused feature of formatting is

an underused feature of formatting is this cell Styles tab right here so I'm

this cell Styles tab right here so I'm going to go ahead and select the months

going to go ahead and select the months up here basically the titles and for

up here basically the titles and for cell Styles they actually have a lot of

cell Styles they actually have a lot of pretty unique formatting you can see

pretty unique formatting you can see happening in the background so I'm going

happening in the background so I'm going to try out in this case I'm going to try

to try out in this case I'm going to try out heading two which is pretty neat

out heading two which is pretty neat because it makes it bold slight bigger

because it makes it bold slight bigger and it puts a little line underneath it

and it puts a little line underneath it I could do something also where I

I could do something also where I highlight all the rows over here and

highlight all the rows over here and then make this into maybe heading three

then make this into maybe heading three and then all these values in here are

and then all these values in here are calculations so technically I could just

calculations so technically I could just highlight this all and for the cell

highlight this all and for the cell Styles I could come up to the top here

Styles I could come up to the top here and select hey this is a calculation and

and select hey this is a calculation and this not a bad looking table uh but not

this not a bad looking table uh but not necessarily all I want to do so I'm

necessarily all I want to do so I'm going to just remove this all instead

going to just remove this all instead I'm going to start with my months I'm

I'm going to start with my months I'm going to make them bold and also add a

going to make them bold and also add a light gray background I'm going to do

light gray background I'm going to do the same thing over here for the values

the same thing over here for the values in my rows and then from here we're

in my rows and then from here we're going to get the actual column grid

going to get the actual column grid lines put in I'm going to only select C3

lines put in I'm going to only select C3 all the way down to o10 I'm going to

all the way down to o10 I'm going to show you why and I'm going to add an all

show you why and I'm going to add an all borders so this is NE it add it adds all

borders so this is NE it add it adds all borders to it what I'm going to also add

borders to it what I'm going to also add this which will add a little bit of

this which will add a little bit of flare to it is a thick outside border so

flare to it is a thick outside border so now we got a thick outside border around

now we got a thick outside border around all of this and I'm going to do the same

all of this and I'm going to do the same with this one of an all borders and then

with this one of an all borders and then a thick outside border now it did remove

a thick outside border now it did remove that thick outside border that I had on

that thick outside border that I had on this line between B and C so I'm

this line between B and C so I'm actually going to go ahead and put that

actually going to go ahead and put that back in by just clicking it next thing I

back in by just clicking it next thing I want to do is format these with a comma

want to do is format these with a comma so I'm going to come up here and well

so I'm going to come up here and well add a comma and then unfortunately it

add a comma and then unfortunately it adds this space in here and makes this

adds this space in here and makes this table bigger than what you can see now

table bigger than what you can see now I'm going to first remove the decimal

I'm going to first remove the decimal places and then in order order to fix

places and then in order order to fix this I'm going to highlight all the

this I'm going to highlight all the different columns through here to

different columns through here to January and just double click on one of

January and just double click on one of them to make them slightly smaller

them to make them slightly smaller anyway it's still not fitting completely

anyway it's still not fitting completely on here and I want this to fit within

on here and I want this to fit within the view here so I'm just going to

the view here so I'm just going to select this all and I'm actually going

select this all and I'm actually going to make these values slightly smaller

to make these values slightly smaller and I'm not liking the positioning of

and I'm not liking the positioning of these it looks like it's lower now that

these it looks like it's lower now that I made this smaller so I'm going to

I made this smaller so I'm going to actually Center this this do a middle

actually Center this this do a middle align basically move it up slightly all

align basically move it up slightly all right my OCD is no looking good all

right my OCD is no looking good all right now this is looking good now the

right now this is looking good now the last thing we want to do is add a title

last thing we want to do is add a title to this basically describe what is this

to this basically describe what is this table that we're looking at and I want

table that we're looking at and I want to insert this in up on the top row but

to insert this in up on the top row but I basically want it centered over this

I basically want it centered over this table so what I can do is highlight from

table so what I can do is highlight from b11 and from there select up here for

b11 and from there select up here for merge and also I want to Center because

merge and also I want to Center because that's I want my text Center during this

that's I want my text Center during this and from there I put in hey this is the

and from there I put in hey this is the data science job count tracker and for

data science job count tracker and for the cell style I'll make this heading

one now let's get into conditionally formatting this table and specifically I

formatting this table and specifically I want to say if I'm looking at data

want to say if I'm looking at data analyst I want to be able to look across

analyst I want to be able to look across here and see which ones are the highs

here and see which ones are the highs and the lows right now I have this grid

and the lows right now I have this grid lines and I can see that based on the

lines and I can see that based on the green and red or the highs and lows but

green and red or the highs and lows but I want to actually be able to see this

I want to actually be able to see this in this table right here and so

in this table right here and so underneath the Home tab we have this

underneath the Home tab we have this conditional formatting available we're

conditional formatting available we're going to focus on these three right here

going to focus on these three right here first and that is datab bars and you can

first and that is datab bars and you can see if I put it in it's basically

see if I put it in it's basically looking like a you know like a bar chart

looking like a you know like a bar chart color scales allows us to do well

color scales allows us to do well different color formatting with it and

different color formatting with it and then an icon set basically allows us to

then an icon set basically allows us to put in a nice looking icon and we're

put in a nice looking icon and we're going to stick simple for now we're

going to stick simple for now we're going to do color scales right now I

going to do color scales right now I have C4 through N4 selected I'm going to

have C4 through N4 selected I'm going to go ahead and select this green to Red

go ahead and select this green to Red which is not bad if we're looking this

which is not bad if we're looking this right this is doing exactly what I want

right this is doing exactly what I want I want August which is the highest to be

I want August which is the highest to be highlighted green to attract my eyes to

highlighted green to attract my eyes to it and then I want the red to be

it and then I want the red to be November and December cuz a Lis I want

November and December cuz a Lis I want to attract attention to it but we want

to attract attention to it but we want to highlight the entire table here so if

to highlight the entire table here so if I were to actually select the entire

I were to actually select the entire table if you will from C4 all the way

table if you will from C4 all the way down to n10 go into conditional

down to n10 go into conditional formatting color scales and do the same

formatting color scales and do the same thing you're going to notice it

thing you're going to notice it basically does these bands but it does

basically does these bands but it does this entire

this entire table all formatted together and this is

table all formatted together and this is not what we necessarily want of course

not what we necessarily want of course the total road is going to be the

the total road is going to be the highest I want to look through that row

highest I want to look through that row and actually see where I should be

and actually see where I should be actually looking so anytime we need a

actually looking so anytime we need a clear mess with any rules we come into

clear mess with any rules we come into conditional formatting and go to clear

conditional formatting and go to clear rules you have clear from selected cells

rules you have clear from selected cells or entire sheet we're just going to do

or entire sheet we're just going to do the entire sheet then we're going to go

the entire sheet then we're going to go back to where we were before of

back to where we were before of selecting just the data analyst values

selecting just the data analyst values going into conditional formatting color

going into conditional formatting color scales and I'm going to go to this green

scales and I'm going to go to this green white red I actually want to try to

white red I actually want to try to limit as many colors as I do two is

limit as many colors as I do two is enough so I'm going to go green white

enough so I'm going to go green white red red and I really like this one

red red and I really like this one better now I don't need to necessarily

better now I don't need to necessarily go through once again of selecting

go through once again of selecting senior data analyst doing this again

senior data analyst doing this again what I would do instead is I'm going to

what I would do instead is I'm going to select data analyst here and then come

select data analyst here and then come into this home menu up here and you

into this home menu up here and you notice this paintbrush this is a format

notice this paintbrush this is a format painter in the instructions it basically

painter in the instructions it basically says select the content with with the

says select the content with with the format you like click format painter and

format you like click format painter and then select something else to

then select something else to automatically apply the formatting so

automatically apply the formatting so from here I can just paint my formatting

from here I can just paint my formatting on unfortunately this doesn't have a

on unfortunately this doesn't have a shortcut so I have to go do go back up

shortcut so I have to go do go back up every single time it removes their

every single time it removes their marching ants reselect the format

marching ants reselect the format painter and go through and select it but

painter and go through and select it but now we have this formatted how I want it

now we have this formatted how I want it where I can look at a certain Row in

where I can look at a certain Row in this case I look at data analyst see

this case I look at data analyst see what some of the highest are and Senior

what some of the highest are and Senior data Engineers I can see how they

data Engineers I can see how they contrast to the other job titles

contrast to the other job titles additionally which going be jump into a

additionally which going be jump into a little bit more later is we can go into

little bit more later is we can go into manage rules and we can see the current

manage rules and we can see the current conditional formatting appli

conditional formatting appli right now I have show matting formatting

right now I have show matting formatting rules for current selection I'm selected

rules for current selection I'm selected the top cell right up here so there's no

the top cell right up here so there's no conditional formatting if I were to

conditional formatting if I were to change this to just this worksheet I can

change this to just this worksheet I can then if I expand this down I can see how

then if I expand this down I can see how this applies this this type of

this applies this this type of formatting of the red white green

formatting of the red white green applies to each of the different cells

applies to each of the different cells and if I needed to actually control what

and if I needed to actually control what cells are actually selected I could do

cells are actually selected I could do that I could have also gone through

that I could have also gone through instead of done that copy formatting and

instead of done that copy formatting and pasting I could done a duplicate Rule

pasting I could done a duplicate Rule and modifying the code as well but I

and modifying the code as well but I decided to do my way instead anyway this

decided to do my way instead anyway this is where you need to go if anytime you

is where you need to go if anytime you need a manage conditional formatting we

need a manage conditional formatting we cck

okay let's crank this up a notch and get into using some more advanced

into using some more advanced functionality with conditional

functionality with conditional formatting here we have a new table you

formatting here we have a new table you haven't seen before basically it has all

haven't seen before basically it has all the different job titles the counts of

the different job titles the counts of those jobs aggregated from our data

those jobs aggregated from our data sheet the median salary what is their

sheet the median salary what is their work from home percentage or likelihood

work from home percentage or likelihood based on the jobs and then finally I

based on the jobs and then finally I have this job rank right here which

have this job rank right here which basically uses these cells that are

basically uses these cells that are hidden right here that if we actually

hidden right here that if we actually expand it out goes through and

expand it out goes through and normalizes the values so in this case

normalizes the values so in this case the job count normalize it between zero

the job count normalize it between zero and one so this job count is 90 is the

and one so this job count is 90 is the highest so it gets a value of one where

highest so it gets a value of one where it's the lowest gets a value of zero

it's the lowest gets a value of zero anyway I did this for all the different

anyway I did this for all the different values and then from there provide a

values and then from there provide a certain waiting factor of like 0453 and

certain waiting factor of like 0453 and 0.15 in order to wait it appropriately

0.15 in order to wait it appropriately this is all my bias and how I wanted to

this is all my bias and how I wanted to actually do it so feel free to adjust it

actually do it so feel free to adjust it to what you want anyway we have this

to what you want anyway we have this final job rank in order to assess based

final job rank in order to assess based on these three values and this is

on these three values and this is commonly done especially in like kpis

commonly done especially in like kpis and stuff like that so we're going to be

and stuff like that so we're going to be making like icons for this column so

making like icons for this column so let's get into formatting our first

let's get into formatting our first column we're going to do job count first

column we're going to do job count first and for this one I want to have data bar

and for this one I want to have data bar so I'm going to come down into condition

so I'm going to come down into condition formatting into data bars and we'll add

formatting into data bars and we'll add these data bars right here I like the

these data bars right here I like the bars in this case because we're dealing

bars in this case because we're dealing with a count and we can really see

with a count and we can really see especially data analysts scientist

especially data analysts scientist Engineers they really make up the

Engineers they really make up the majority of the data here so it really

majority of the data here so it really draws your attention to it next up is a

draws your attention to it next up is a median salary we're going to do similar

median salary we're going to do similar to last time maintain a color scale

to last time maintain a color scale we're just going to do this first one

we're just going to do this first one right here where green is the highest

right here where green is the highest salary and red is the lowest and then

salary and red is the lowest and then one more we're going to do that work for

one more we're going to do that work for home we're also going to do it in a

home we're also going to do it in a color scale but for this one let's

color scale but for this one let's actually do a different color go into

actually do a different color go into more rules and in this case we have this

more rules and in this case we have this new formatting rule window right here I

new formatting rule window right here I have two colors just say I want to do

have two colors just say I want to do one color I'm going to do white from the

one color I'm going to do white from the lowest value and then we'll do like

lowest value and then we'll do like purple for the highest value anyway this

purple for the highest value anyway this is all basically to show a point this is

is all basically to show a point this is becoming

becoming entirely entirely too much visually

entirely entirely too much visually distracting if you're if you were to

distracting if you're if you were to give this to somebody else or a

give this to somebody else or a stakeholder where are they supposed to

stakeholder where are they supposed to look and actually organize their

look and actually organize their thoughts on where they should

thoughts on where they should potentially pursue a job right now I'm

potentially pursue a job right now I'm thoroughly confused at looking at this

thoroughly confused at looking at this so let's clean this up a bit and for

so let's clean this up a bit and for this I want to make it to where I like

this I want to make it to where I like maintaining a solid coloro across so

maintaining a solid coloro across so that way you know like hey if this color

that way you know like hey if this color is darker or there's more of this color

is darker or there's more of this color I should be looking there so in this

I should be looking there so in this case we'll make this job count we're

case we'll make this job count we're going to just clean it up slight

going to just clean it up slight slightly for the data bars B going to

slightly for the data bars B going to make this like gradient appearance cuz

make this like gradient appearance cuz then I feel we can see the numbers

then I feel we can see the numbers better and it's not too visually

better and it's not too visually distracting for the median salary I

distracting for the median salary I really my goal of this is to find jobs

really my goal of this is to find jobs that are look say greater than 100,000

that are look say greater than 100,000 so let's actually just make highlighting

so let's actually just make highlighting that highlights those jobs that are

that highlights those jobs that are greater than this value in this case I'm

greater than this value in this case I'm going to come to conditional formatting

going to come to conditional formatting and enter a new rule this new formatting

and enter a new rule this new formatting rule popup comes up against once again

rule popup comes up against once again and we have a select a rule type this

and we have a select a rule type this allows us to do things like format all

allows us to do things like format all cells based on the value format only top

cells based on the value format only top or bottom rank values format only values

or bottom rank values format only values that are above or below average I

that are above or below average I personally like this one of use a

personally like this one of use a formula to determine which cells to

formula to determine which cells to format and in this case I want to say

format and in this case I want to say I'm going to collect this formula thing

I'm going to collect this formula thing right here I want to look at you can

right here I want to look at you can just select the first item in the item

just select the first item in the item selected so I'm select D3 it's going to

selected so I'm select D3 it's going to go through and actually do all of these

go through and actually do all of these don't worry we'll see and for that we

don't worry we'll see and for that we want to highlight those that are greater

want to highlight those that are greater than

than 100,000 and press enter and then right

100,000 and press enter and then right now it doesn't have any format set so

now it doesn't have any format set so I'm going to change this to format and

I'm going to change this to format and we can control a whole host of things

we can control a whole host of things such as the fill border font and the

such as the fill border font and the number formatting itself but we're going

number formatting itself but we're going to stick with that blue theme I'm going

to stick with that blue theme I'm going to just come down in here and I'm going

to just come down in here and I'm going just select this blue color right here

just select this blue color right here and click okay and then okay again now

and click okay and then okay again now you notice my formatting is not

you notice my formatting is not appearing that's because we have

appearing that's because we have multiple formatting applied to a cell

multiple formatting applied to a cell which you can do so in order to fix this

which you can do so in order to fix this we need to come into manage rules and as

we need to come into manage rules and as we see we have both of these applied to

we see we have both of these applied to it so I actually need to select this one

it so I actually need to select this one and I need to delete this Rule and click

and I need to delete this Rule and click apply and then okay now we're running

apply and then okay now we're running into our second issue and I slightly

into our second issue and I slightly misled you earlier when I said that D3

misled you earlier when I said that D3 works if we go back into manage our

works if we go back into manage our rules and we see our formula right here

rules and we see our formula right here I'm going to double click it we don't

I'm going to double click it we don't need to actually provide an absolute

need to actually provide an absolute reference to a D3 because it's actually

reference to a D3 because it's actually going to evaluate all those cells based

going to evaluate all those cells based on D3 instead we want it to be D3

on D3 instead we want it to be D3 without the dollar sign so it's not an

without the dollar sign so it's not an absolute reference and therefore

absolute reference and therefore whenever I click okay and okay again bam

whenever I click okay and okay again bam now it knows appropriately to check the

now it knows appropriately to check the actual cell that it's looking at within

actual cell that it's looking at within the range on whether to highlight it or

the range on whether to highlight it or not moving on to the work from home

not moving on to the work from home we're going to keep this similar in that

we're going to keep this similar in that not going to be purple though we're

not going to be purple though we're going to change this to Blue instead so

going to change this to Blue instead so going into manage rules we have the

going into manage rules we have the actual color right here selected I'm

actual color right here selected I'm going to just go in and change this to

going to just go in and change this to this color that we used previously and

this color that we used previously and click okay and then okay as well so that

click okay and then okay as well so that way it applies it all right the last

way it applies it all right the last thing is this the job rank itself and

thing is this the job rank itself and for this we're going to be using icon

for this we're going to be using icon set

set specifically I like this one over here

specifically I like this one over here on ratings but this becomes a little bit

on ratings but this becomes a little bit over helming when where we have this

over helming when where we have this rating and also the number next to it so

rating and also the number next to it so we can actually remove this number in

we can actually remove this number in the column we go back into manage rules

the column we go back into manage rules we can double click on that icon set

we can double click on that icon set Rule and we can even further customize

Rule and we can even further customize when these stars are appearing but I'm

when these stars are appearing but I'm going to just go ahead and get to this

going to just go ahead and get to this portion where it says show icon only

portion where it says show icon only this allows us to only show the value so

this allows us to only show the value so going into applying this bam it's now

going into applying this bam it's now showing the icon I want that icon

showing the icon I want that icon centered both vertically and also

centered both vertically and also horizontally so bam now whenever I look

horizontally so bam now whenever I look at this I can see especially since it's

at this I can see especially since it's all one color my eyes really gravitate

all one color my eyes really gravitate to well data scientists and data

to well data scientists and data Engineers based on this full star rating

Engineers based on this full star rating and more of the blue being in this

and more of the blue being in this region and that's what I would hope

region and that's what I would hope people would go to or gravitate to as

people would go to or gravitate to as well when they're looking at it one

well when they're looking at it one quick note in this condition conditional

quick note in this condition conditional format we didn't cover this highlight

format we didn't cover this highlight cell rules where you highlight greater

cell rules where you highlight greater than or less than or you do a top uh

than or less than or you do a top uh bottom rule where you can highlight the

bottom rule where you can highlight the top 10% or top 10 you can also adjust

top 10% or top 10 you can also adjust that number anyway I find that myself

that number anyway I find that myself more using custom rules instead by

more using custom rules instead by coming in here into new rule and then

coming in here into new rule and then actually fine-tuning what I want to do

actually fine-tuning what I want to do so with the practice problems I'd really

so with the practice problems I'd really dive into actually relying on using

dive into actually relying on using these type of options instead and so as

these type of options instead and so as I desly hinted to you have some practice

I desly hinted to you have some practice problems now to go through and really

problems now to go through and really practice how to do formatting and also

practice how to do formatting and also more specifically conditional formatting

more specifically conditional formatting in the next lesson we're going to be

in the next lesson we're going to be move into collaboration and covering how

move into collaboration and covering how to actually protect your workbooks and

to actually protect your workbooks and your worksheets so that way whenever you

your worksheets so that way whenever you share these with co-workers or friends

share these with co-workers or friends they don't go through and actually mess

they don't go through and actually mess them up all right with that I'll see you

them up all right with that I'll see you in the next

one welcome to this last lesson in spreadsheets advance for we jump into

spreadsheets advance for we jump into our project and this lesson itself is on

our project and this lesson itself is on collaboration which sounds sort of

collaboration which sounds sort of cheesy but in order to demonstrate what

cheesy but in order to demonstrate what we're actually going to be learning in

we're actually going to be learning in this lesson we need to actually jump

this lesson we need to actually jump fast forward a little bit and jump into

fast forward a little bit and jump into our project so I'm going to open up the

our project so I'm going to open up the salary dashboard which is located under

salary dashboard which is located under project One dashboard so here's the

project One dashboard so here's the dashboard that we're going to build in

dashboard that we're going to build in it they have three boxes that you can go

it they have three boxes that you can go through and select this is going to be

through and select this is going to be using data validation which we're going

using data validation which we're going to be learning about in this lesson but

to be learning about in this lesson but it allows you to basically standardize

it allows you to basically standardize the inputs that we want somebody to

the inputs that we want somebody to actually select in in order to get the

actually select in in order to get the results and it prevents them from

results and it prevents them from putting in values that maybe don't exist

putting in values that maybe don't exist and then breaking our dashboard so for

and then breaking our dashboard so for each of these job titles country and

each of these job titles country and types we have an Associated

types we have an Associated visualization for each showing the

visualization for each showing the salary by job title the salary by region

salary by job title the salary by region and then also salary by job type finally

and then also salary by job type finally at the bottom I have some I call them

at the bottom I have some I call them kpi cards basically outlining certain

kpi cards basically outlining certain characteristics or certain indications

characteristics or certain indications of the median salary what is the top job

of the median salary what is the top job platform and then what what is a account

platform and then what what is a account of jobs but I can come in here and

of jobs but I can come in here and select something like maybe I wanted to

select something like maybe I wanted to look at business analyst and it's going

look at business analyst and it's going to filter Down based on this telling me

to filter Down based on this telling me what their median salary is that

what their median salary is that LinkedIn is probably the best place to

LinkedIn is probably the best place to go to for this what are the different

go to for this what are the different types of rollers availables and what's

types of rollers availables and what's available in the job database so the

available in the job database so the other feature we're going to be going

other feature we're going to be going through besides this data validation

through besides this data validation process that we can do right here is

process that we can do right here is actually protecting your sheets which

actually protecting your sheets which you can find this here underneath review

you can find this here underneath review under protect but anyway if you try to

under protect but anyway if you try to move these cells around you're not able

move these cells around you're not able to at all so we're going to be able to

to at all so we're going to be able to design this dashboard in a way that

design this dashboard in a way that other co-workers won't be able to

other co-workers won't be able to destroy it additionally if you notice

destroy it additionally if you notice down here at the bottom there's only one

down here at the bottom there's only one sheet in here there's actually other

sheet in here there's actually other Sheets if I go to unhide here there's

Sheets if I go to unhide here there's other sheets I'll just unhide one of

other sheets I'll just unhide one of them we'll just unhide data there's

them we'll just unhide data there's other sheets inside of here but if

other sheets inside of here but if they're not applicable to my co-workers

they're not applicable to my co-workers or stakeholders I don't need to have

or stakeholders I don't need to have them so I can hide them so that's the

them so I can hide them so that's the another feature we're go on over in

this all right nothing be yaen let's actually get into this lesson for this

actually get into this lesson for this we're going to be using the

we're going to be using the collaboration workbook in chapter 4 now

collaboration workbook in chapter 4 now we're going to be building out these

we're going to be building out these three sheets as we go along and as a

three sheets as we go along and as a sneak peek in this first example we're

sneak peek in this first example we're going to be building out this little

going to be building out this little portion right here this is going be

portion right here this is going be basically preparing us for our project

basically preparing us for our project so a lot of this work is going to be put

so a lot of this work is going to be put to good use anyway we're going to be

to good use anyway we're going to be building the simple one right here I'm

building the simple one right here I'm going zoom in where we have based on the

going zoom in where we have based on the job title we can go through and select

job title we can go through and select it so senior. engineer it's going to pop

it so senior. engineer it's going to pop up with our median salary so that's what

up with our median salary so that's what we're going to be building with this and

we're going to be building with this and specifically we're going to be using

specifically we're going to be using this feature of data validation so I'm

this feature of data validation so I'm going to create a new sheet to start

going to create a new sheet to start with because I don't want to start with

with because I don't want to start with the answer right there I'm going just

the answer right there I'm going just call it calculator I'm going to put in

call it calculator I'm going to put in job title here and then median salary

job title here and then median salary below I'm also going to bold these by

below I'm also going to bold these by pressing B and then these are where next

pressing B and then these are where next to it in column C is where we're

to it in column C is where we're actually going to use the actual control

actually going to use the actual control of this now we need to get a list of job

of this now we need to get a list of job titles to put in this so I'm going to

titles to put in this so I'm going to create a new sheet and call it

create a new sheet and call it validation and basically what I going to

validation and basically what I going to do with this is create a sheet of all of

do with this is create a sheet of all of the different job titles available

the different job titles available specifically I'm going to say this is

specifically I'm going to say this is going to be from the column job title

going to be from the column job title short and we're going to be using in

short and we're going to be using in order to get the unique values of it

order to get the unique values of it well the unique function we need to

well the unique function we need to provide it an array so I'm going come

provide it an array so I'm going come back over here down to column A2 use

back over here down to column A2 use control shift select all the way down

control shift select all the way down close the parenthesis press enter okay

close the parenthesis press enter okay so now we have all of our different

so now we have all of our different values I'm going expand this out I'm

values I'm going expand this out I'm also going to zoom in a little bit now

also going to zoom in a little bit now whenever I do this drop- down menu I

whenever I do this drop- down menu I want it in some sort of order

want it in some sort of order specifically I wanted in probably what

specifically I wanted in probably what is the highest count value I wanted it

is the highest count value I wanted it appearing at the top and those that are

appearing at the top and those that are less likely down at the bottom so what

less likely down at the bottom so what I'm going to do is actually just copy

I'm going to do is actually just copy this value right here because this is

this value right here because this is what we actually want to use what we

what we actually want to use what we want to do is a count ifs we want to

want to do is a count ifs we want to count based on a condition for the

count based on a condition for the criteria range we're going to be

criteria range we're going to be providing that job title short column

providing that job title short column from our table and then for the criteria

from our table and then for the criteria we're going to be selecting right next

we're going to be selecting right next to it A2 B there we'll just autofill it

to it A2 B there we'll just autofill it all the way down and then finally we

all the way down and then finally we want to now sort it by this so I'll use

want to now sort it by this so I'll use job title short sorted from there we'll

job title short sorted from there we'll use the sort function to then sort this

use the sort function to then sort this by the second column position in

by the second column position in descending order so bam this is more

descending order so bam this is more like I want I want those data analysts

like I want I want those data analysts that scientist engineers at the top and

that scientist engineers at the top and the senior roles and so on cloud

the senior roles and so on cloud Engineers car Bel so we now have this

Engineers car Bel so we now have this list available that we want to use for

list available that we want to use for data validation we speak of I'm going to

data validation we speak of I'm going to go back to the calculator tab that I

go back to the calculator tab that I made and for this we're going to go to

made and for this we're going to go to the data tab specifically under data

the data tab specifically under data tools they have this this selection

tools they have this this selection available where where data validation

available where where data validation actually is and now this is going to

actually is and now this is going to allow us to well customize it right now

allow us to well customize it right now the data validation for this cell is any

the data validation for this cell is any value I can place any value into it I

value I can place any value into it I could limit it to a whole number I could

could limit it to a whole number I could limit it to decimals a list a date a

limit it to decimals a list a date a time a bunch of things we're going to

time a bunch of things we're going to limit it to basically a list of values

limit it to basically a list of values and we need to basically so provide a

and we need to basically so provide a source for this so for the source we're

source for this so for the source we're going to go in and select the validation

going to go in and select the validation tab that we just made and I'm going to

tab that we just made and I'm going to select all the different jobs right here

select all the different jobs right here and then press enter from here I'm going

and then press enter from here I'm going to accept this and press okay now as you

to accept this and press okay now as you can see we have this little drop down

can see we have this little drop down right next to it and I have different

right next to it and I have different selections actually available of data

selections actually available of data engineer if I were to go into here

engineer if I were to go into here because I have this uh set to data

because I have this uh set to data validation if I was going to put in

validation if I was going to put in something like data nerd which isn't

something like data nerd which isn't available and press enter it says this

available and press enter it says this value doesn't match the data validation

value doesn't match the data validation uh restriction defined for this cell

uh restriction defined for this cell therefore I have to go in and retry so

therefore I have to go in and retry so so only values within there are going to

so only values within there are going to be able to work in this so now let's

be able to work in this so now let's actually get into calculating that

actually get into calculating that median salary and for this we're going

median salary and for this we're going to create a new sheet similar to this

to create a new sheet similar to this median salary sheet we're going to call

median salary sheet we're going to call this one salary wrong spot need to

this one salary wrong spot need to actually enter it down here and call

actually enter it down here and call this one salary throw this all the way

this one salary throw this all the way over first I need the names of job title

over first I need the names of job title short and all that kind of good stuff so

short and all that kind of good stuff so what I'll do is I'll come over to our

what I'll do is I'll come over to our validation Tab and I've selected equal

validation Tab and I've selected equal to already I'm going to select these

to already I'm going to select these cells right here press enter so now

cells right here press enter so now they're all appearing here now I'm going

they're all appearing here now I'm going to calculate the median salary for all

to calculate the median salary for all these jobs I know our calculator or

these jobs I know our calculator or dashboard has uh only one value that is

dashboard has uh only one value that is calculating a time but in our dashboard

calculating a time but in our dashboard we're going to build we're actually

we're going to build we're actually going to build a graph with all these

going to build a graph with all these median salaries so we just need to

median salaries so we just need to calculate them now all the median

calculate them now all the median salaries and then basically calculate

salaries and then basically calculate using data validation and also an X look

using data validation and also an X look up what the median salary is going to be

up what the median salary is going to be here so for this we're going to be using

here so for this we're going to be using the median function and specifically

the median function and specifically we're going to be using that if inside

we're going to be using that if inside of it because median if isn't available

of it because median if isn't available we first want to check does the job

we first want to check does the job title here of data analyst meet our

title here of data analyst meet our condition of the job title short so I'm

condition of the job title short so I'm going to type in the table itself of

going to type in the table itself of jobs and then the column of job title

jobs and then the column of job title short close bracket and set an equal

short close bracket and set an equal sign equal to A2 then I'm going to close

sign equal to A2 then I'm going to close the parentheses on this and actually we

the parentheses on this and actually we need to wrap all this in parentheses

need to wrap all this in parentheses because we have to do multiple different

because we have to do multiple different conditions we're going to do some array

conditions we're going to do some array multiplication the other thing we have

multiplication the other thing we have to check is that the values are not

to check is that the values are not blank or not equal to zero so once again

blank or not equal to zero so once again I'll put in jobs again and we're going

I'll put in jobs again and we're going to be using that salary year average

to be using that salary year average column and we want to make sure that it

column and we want to make sure that it doesn't equal to zero and so that's the

doesn't equal to zero and so that's the condition we're checking for and so now

condition we're checking for and so now what do we want to return if true well

what do we want to return if true well we want to return the salary so we'll do

we want to return the salary so we'll do jobs and then salary year average I'll

jobs and then salary year average I'll then close the brackets on that then we

then close the brackets on that then we need to close one parentheses I can see

need to close one parentheses I can see a red parentheses still and then a final

a red parentheses still and then a final black parentheses NOS I'm good press

black parentheses NOS I'm good press enter looks like I got it right on the

enter looks like I got it right on the first try let's actually drag this down

first try let's actually drag this down boom this is pretty nice so now we have

boom this is pretty nice so now we have all the median salaries for these

all the median salaries for these different job titles I'm also going to

different job titles I'm also going to take this a step further of actually

take this a step further of actually sorting this by the med CER because I

sorting this by the med CER because I know I'm going to be actually

know I'm going to be actually visualizing this in the Project's lesson

visualizing this in the Project's lesson so we'll go ahead and sort this as well

so we'll go ahead and sort this as well sorting it on the second index in

sorting it on the second index in descending order so now we need to

descending order so now we need to provide the value in this case data

provide the value in this case data Engineers there is selected we need to

Engineers there is selected we need to provide based on this value the median

provide based on this value the median salary and I want to just calculate it

salary and I want to just calculate it over here just in case I need to go back

over here just in case I need to go back to it so for this I want basically

to it so for this I want basically 125,000 to here right here in G2 so I'm

125,000 to here right here in G2 so I'm going to provide an X lookup and the

going to provide an X lookup and the first thing is this lookup value right

first thing is this lookup value right we're going to look up the data engineer

we're going to look up the data engineer in this now I'm not going to use a cell

in this now I'm not going to use a cell reference of going over here of

reference of going over here of selecting this cell of data engineer

selecting this cell of data engineer which is calculator C2 I'm actually

which is calculator C2 I'm actually going to escape out of this we're going

going to escape out of this we're going to stop this right here I want to go

to stop this right here I want to go back to this I actually instead because

back to this I actually instead because I'm going to be referencing these cells

I'm going to be referencing these cells specifically well this what s right here

specifically well this what s right here a lot I'm going to just rename this from

a lot I'm going to just rename this from C2 to title so right now I can see that

C2 to title so right now I can see that it is named title so going back over to

it is named title so going back over to that salary tab again now we can perform

that salary tab again now we can perform our X lookup and for the lookup value

our X lookup and for the lookup value we're trying to look up the title for

we're trying to look up the title for the lookup array we're looking up

the lookup array we're looking up through this job titles right here and

through this job titles right here and then for a return array the actual

then for a return array the actual salary values so now we're getting that

salary values so now we're getting that data engineer value of

data engineer value of 125,000 similarly I also want to name

125,000 similarly I also want to name this cell as well I'm going to name this

this cell as well I'm going to name this one median salary pressing enter boom

one median salary pressing enter boom locks it in so now when I come back over

locks it in so now when I come back over to my calculator tab I can just put in

to my calculator tab I can just put in here equal to median salary I'm also

here equal to median salary I'm also going to go through and format this to

going to go through and format this to make this look

better so just playing around with this I can see that I can put in something

I can see that I can put in something like senior data analyst and then a job

like senior data analyst and then a job the associated Med and seller is going

the associated Med and seller is going to come up with it but let's say now I

to come up with it but let's say now I want to give this to a coworker right

want to give this to a coworker right how can I prevent them from going in and

how can I prevent them from going in and potentially you know entering in this

potentially you know entering in this cell and then breaking it well we can

cell and then breaking it well we can come up here to review and in this case

come up here to review and in this case we're going to select this of protect

we're going to select this of protect sheet now the first thing you can do you

sheet now the first thing you can do you can set a password to unprotect sheet

can set a password to unprotect sheet I'm not going to put a password but say

I'm not going to put a password but say you wanted to put one you could and then

you wanted to put one you could and then we have these options for for what you

we have these options for for what you can actually protect whether that's

can actually protect whether that's select lock cells or select unlock cells

select lock cells or select unlock cells to protect we're just going to leave

to protect we're just going to leave both of these checked for the time being

both of these checked for the time being click okay and now while one we can see

click okay and now while one we can see that underneath protect here it now says

that underneath protect here it now says instead of protect sheet it says

instead of protect sheet it says unprotect sheet whenever I go through

unprotect sheet whenever I go through this and say I want to change it any

this and say I want to change it any value whatsoever I can't change it so

value whatsoever I can't change it so it's good because the numbers can't

it's good because the numbers can't change or the median tile can't change

change or the median tile can't change but now I can't change B job title which

but now I can't change B job title which is a little bit of a pain so

is a little bit of a pain so unfortunately Excel doesn't necessarily

unfortunately Excel doesn't necessarily make this the easiest I'm going to start

make this the easiest I'm going to start over again and just click unprotect

over again and just click unprotect sheet and what we want to do is we're

sheet and what we want to do is we're going to select all the cells in here so

going to select all the cells in here so with all the cells selected I'm going to

with all the cells selected I'm going to press control and unselect C2 then right

press control and unselect C2 then right clicking it I'm going to go into format

clicking it I'm going to go into format cells now under this protection tab

cells now under this protection tab right here we're going to notice we have

right here we're going to notice we have options for locked and hidden we want to

options for locked and hidden we want to actually be able to lock all the cells

actually be able to lock all the cells except for C2 we don't want to hide any

except for C2 we don't want to hide any so we're not going to adjust that right

so we're not going to adjust that right now but now we're going to have the

now but now we're going to have the ability to adjust whether it's locked or

ability to adjust whether it's locked or not this doesn't actually change

not this doesn't actually change anything right now so if I go into here

anything right now so if I go into here yes I locked those certain cells but if

yes I locked those certain cells but if I were to type into here it's still

I were to type into here it's still going to allow it to be changed so now

going to allow it to be changed so now what I can do is go into protect sheet

what I can do is go into protect sheet and previously we had both of these

and previously we had both of these selected of Select lock cells and select

selected of Select lock cells and select unlock cells and in this case because we

unlock cells and in this case because we locked all the cells except for C2 we

locked all the cells except for C2 we only want to allow people to select the

only want to allow people to select the unlocked cell of C2 so I'm going to

unlocked cell of C2 so I'm going to uncheck this click okay and now I can't

uncheck this click okay and now I can't click anywhere else except for where

click anywhere else except for where I've set up that data validation in this

I've set up that data validation in this cell and I can still change it and it

cell and I can still change it and it will manipulate the value now we could

will manipulate the value now we could also go through and protect the workbook

also go through and protect the workbook itself I don't necessarily manipulate

itself I don't necessarily manipulate with this as much instead what would I

with this as much instead what would I would want to do in in this case is

would want to do in in this case is actually hide all these other sheets

actually hide all these other sheets with the exception of this calculator

with the exception of this calculator and so I can do this by right clicking a

and so I can do this by right clicking a tab and selecting hide so I'm going to

tab and selecting hide so I'm going to go through and actually hide all of them

go through and actually hide all of them so now we have everything as shown by

so now we have everything as shown by this tab down here of calculator we have

this tab down here of calculator we have every tab hidden except for that and if

every tab hidden except for that and if I wanted it to

I wanted it to reappear or get a sheet to reappear I

reappear or get a sheet to reappear I would just right click it click unhide

would just right click it click unhide and then it's going to allow me to

and then it's going to allow me to select which option I can unhide and and

select which option I can unhide and and if I do want to make it to where a user

if I do want to make it to where a user can't go in and necessarily unhide

can't go in and necessarily unhide sheets well I can go in here and select

sheets well I can go in here and select protect workbook once again I can enter

protect workbook once again I can enter a password if I wanted to I'm going to

a password if I wanted to I'm going to just set this up but now when I come

just set this up but now when I come down here to rightclick it there's no

down here to rightclick it there's no option to hide or unhide a sheet so the

option to hide or unhide a sheet so the entire workbook is now protected so I'm

entire workbook is now protected so I'm not going to lie that was definitely an

not going to lie that was definitely an advanced intro into Data validation and

advanced intro into Data validation and also protecting your workbooks but I

also protecting your workbooks but I promise it's going to just come into

promise it's going to just come into great use for whenever we're building

great use for whenever we're building this project which will we get to next

this project which will we get to next now we do have some practice problems

now we do have some practice problems for you go through and just test out all

for you go through and just test out all these different features and with that

these different features and with that we'll be jumping in the next lesson and

we'll be jumping in the next lesson and actually building this data science

actually building this data science salary dashboard with that I'll see you

salary dashboard with that I'll see you in that

one all right let's now dive in and build our first project with Excel which

build our first project with Excel which is this data science salary dashboard

is this data science salary dashboard this project is going to combine

this project is going to combine everything that we've used and learned

everything that we've used and learned up to this point from formulas and

up to this point from formulas and functions to charts and then even to

functions to charts and then even to data validation we're going to start

data validation we're going to start first by looking at the dashboard itself

first by looking at the dashboard itself you can just go to the project One

you can just go to the project One dashboard folder and Open salary

dashboard folder and Open salary dashboard workbook now in this right now

dashboard workbook now in this right now you're only going to see one sheet and

you're only going to see one sheet and as you try to click around you're not

as you try to click around you're not going be able to do anything so as a

going be able to do anything so as a refresher if you want to actually dive

refresher if you want to actually dive in and see what's going on behind the

in and see what's going on behind the scenes you'll need to First if you want

scenes you'll need to First if you want to actually touch any of these points

to actually touch any of these points actually go into the review Tab and

actually go into the review Tab and click unprotect sheet then you'll be

click unprotect sheet then you'll be able to investigate how I name certain

able to investigate how I name certain cells and whatnot additionally if you

cells and whatnot additionally if you want to investigate any of the workbooks

want to investigate any of the workbooks that I worked on you'll need to go into

that I worked on you'll need to go into unhide and select the appropriate

unhide and select the appropriate workbook that you want to well unhide so

workbook that you want to well unhide so for this we're going to be building it

for this we're going to be building it out section by section specifically

out section by section specifically we're going to start up at the top

we're going to start up at the top building these data validation drop-down

building these data validation drop-down menus then from from there we'll go into

menus then from from there we'll go into building the different graphs associated

building the different graphs associated with it and then finally we'll end up

with it and then finally we'll end up with these kpi cards now powering each

with these kpi cards now powering each one of these major topics I've built

one of these major topics I've built individual seats so for things like jobs

individual seats so for things like jobs I have all the jobs along with any key

I have all the jobs along with any key information to then build the

information to then build the visualizations in it so here is the

visualizations in it so here is the basically the table that I made in order

basically the table that I made in order to show the graphic right here similarly

to show the graphic right here similarly for Country I have all the different

for Country I have all the different countries and then they're Associated

countries and then they're Associated Med and salaries and I use that to not

Med and salaries and I use that to not only make the drop down but also make

only make the drop down but also make the graph same thing for type and then

the graph same thing for type and then finally for platform anyway that's just

finally for platform anyway that's just a quick overview to make sure that

a quick overview to make sure that you're under familiar with how we're

you're under familiar with how we're going to be working through this but

going to be working through this but let's actually dive into

it for this I recommend picking up where we left off in the last lesson on

we left off in the last lesson on collaboration did a lot of work for that

collaboration did a lot of work for that so we're going to use this workbook

so we're going to use this workbook first thing I'm going to do once this is

first thing I'm going to do once this is open I'm going to go in and actually

open I'm going to go in and actually save it as this final dashboard and I

save it as this final dashboard and I recommend that during this you're saving

recommend that during this you're saving this pretty frequently so we don't lose

this pretty frequently so we don't lose progress first thing I'm going to do is

progress first thing I'm going to do is start moving this around I basically

start moving this around I basically know where I want to get these different

know where I want to get these different titles of these drop downs and then

titles of these drop downs and then where I want to put the drop downs we're

where I want to put the drop downs we're not going to be using meeting salary for

not going to be using meeting salary for a little bit so I'm just going to take

a little bit so I'm just going to take that control xit and place it down at

that control xit and place it down at the bottom then take the job title put

the bottom then take the job title put it in C3 and then move the data

it in C3 and then move the data validation to right below that we'll fix

validation to right below that we'll fix all the format add in when we get later

all the format add in when we get later on it okay so we have the job title now

on it okay so we have the job title now the next thing we need to jump into is

the next thing we need to jump into is country and we'll be putting that right

country and we'll be putting that right under this portion right here for this

under this portion right here for this I'm going to create a new sheet and call

I'm going to create a new sheet and call this country with all these sheets I

this country with all these sheets I want to have them pretty much similar to

want to have them pretty much similar to what the title is above it so in this

what the title is above it so in this case here where we had median salary

case here where we had median salary it's actually the titles um you have

it's actually the titles um you have named it in the previous one salary so

named it in the previous one salary so let's go ahead and just name this title

let's go ahead and just name this title anyway going back to that country tab

anyway going back to that country tab that's where similar to the title tab if

that's where similar to the title tab if you see we first grab the names of the

you see we first grab the names of the job titles from there and then calculate

job titles from there and then calculate the median salaries for each we're going

the median salaries for each we're going to be doing something similar in the

to be doing something similar in the country tab with first putting in the

country tab with first putting in the country names and then from there

country names and then from there putting in that median salary but I want

putting in that median salary but I want to keep a similar format as in this

to keep a similar format as in this title case remember we actually pulled

title case remember we actually pulled this from the data valid ation tab which

this from the data valid ation tab which we're pulling here so I want to keep

we're pulling here so I want to keep this consistent anytime we're creating

this consistent anytime we're creating anything for those drop downs we're

anything for those drop downs we're going to make it here in this data

going to make it here in this data validation tab so I'm going to create a

validation tab so I'm going to create a column here called job country and then

column here called job country and then in this I want to get the unique values

in this I want to get the unique values from our data set specifically that jobs

from our data set specifically that jobs table it's still named that jobs table

table it's still named that jobs table and of that column job country go ahead

and of that column job country go ahead and close the brackets and then close

and close the brackets and then close parentheses and now we have all of these

parentheses and now we have all of these different countries not sure why but

different countries not sure why but this is bolded I'm going to go ahead and

this is bolded I'm going to go ahead and remove that anyway I want this in a

remove that anyway I want this in a sorted format I'm not going to

sorted format I'm not going to necessarily sort it like count like we

necessarily sort it like count like we did here with the job tiles I'm just

did here with the job tiles I'm just going to sort it in alphabetical order

going to sort it in alphabetical order so I'm going to use the sort function

so I'm going to use the sort function and I'm just going to identify that we

and I'm just going to identify that we wanted to use

wanted to use G2 hashtag and Bam now we have all of

G2 hashtag and Bam now we have all of this also name this appropriately of job

this also name this appropriately of job country sorted so now we have our list

country sorted so now we have our list we can go back into here and actually

we can go back into here and actually put in the country for the data

put in the country for the data validation portion we do that by going

validation portion we do that by going to the data tab selecting data

to the data tab selecting data validation and the values we want to

validation and the values we want to provide a list to this and for the

provide a list to this and for the source we go back to that data Val

source we go back to that data Val station tab close this out and we

station tab close this out and we basically want to select all these

basically want to select all these values here so I'll just do control

values here so I'll just do control shift down pressing enter we now have

shift down pressing enter we now have everything all the criteria for this I'm

everything all the criteria for this I'm going to go and click okay and I get

going to go and click okay and I get this error message and there's a problem

this error message and there's a problem with this formula for some reason I

with this formula for some reason I guess when I move back it added this

guess when I move back it added this extra sheet in here I'm not too sure

extra sheet in here I'm not too sure this extra data I can't even select in

this extra data I can't even select in here anyway just make sure it's only one

here anyway just make sure it's only one sheet there it's going to work fine

sheet there it's going to work fine country is now in here I can s something

country is now in here I can s something like Argentina next value that we're

like Argentina next value that we're going to be looking at is the job type

going to be looking at is the job type so part-time full-time whatnot with this

so part-time full-time whatnot with this although we're not going to use it yet

although we're not going to use it yet I'm going to create a new sheet and call

I'm going to create a new sheet and call it type and also move that to the end

it type and also move that to the end but now we want to get the unique values

but now we want to get the unique values of job schedule type so I'm put in the

of job schedule type so I'm put in the column here of job schedule type and

column here of job schedule type and then from there we want to get the once

then from there we want to get the once again unique values for this we're using

again unique values for this we're using the jobs table specifically that job

the jobs table specifically that job schedule type column and Bam now you

schedule type column and Bam now you will notice from this one this one it's

will notice from this one this one it's a little bit this needs some data clean

a little bit this needs some data clean up with it there's a lot of values in

up with it there's a lot of values in here like it sometimes it has combined

here like it sometimes it has combined values like full-time part-time and

values like full-time part-time and internship and and whatnot we really I'm

internship and and whatnot we really I'm actually going to expand this colum out

actually going to expand this colum out we really just want the single values

we really just want the single values from this so something like fulltime

from this so something like fulltime contractor part-time internship and then

contractor part-time internship and then also temp work so the first thing I'm

also temp work so the first thing I'm noticing about the thing ones we want to

noticing about the thing ones we want to remove is that they contain the word and

remove is that they contain the word and so we'll first identify those that con

so we'll first identify those that con turn and we do this using the search

turn and we do this using the search function which is a text function to

function which is a text function to find text specifically we're looking for

find text specifically we're looking for that keyword of and with intext we want

that keyword of and with intext we want to just look through the whole array so

to just look through the whole array so we'll put in J2

we'll put in J2 hashtag and I got a little error message

hashtag and I got a little error message I need to make sure I use double quotes

I need to make sure I use double quotes for the text itself and running this now

for the text itself and running this now I have basically number values for where

I have basically number values for where the and is located at and it looks like

the and is located at and it looks like yeah it looks like we're good on

yeah it looks like we're good on everything with the exception of the

everything with the exception of the zero which we'll get in a little bit

zero which we'll get in a little bit okay so we need to convert this into

okay so we need to convert this into basically Boolean values because we're

basically Boolean values because we're going to end end up using this to to

going to end end up using this to to pull out that we want using a filter

pull out that we want using a filter function so we're going to wrap this in

function so we're going to wrap this in the is number and we're going to get

the is number and we're going to get false or true and whatnot anyway all

false or true and whatnot anyway all right so now we have false or true the

right so now we have false or true the last thing we need to do is use well not

last thing we need to do is use well not the last thing second last thing we're

the last thing second last thing we're going to use the filter function and in

going to use the filter function and in this we provided the array so in this

this we provided the array so in this case it's going to be J2 hashtag and

case it's going to be J2 hashtag and then for what we want to include is this

then for what we want to include is this other array that we just did so I'm

other array that we just did so I'm going go ahead and close this and see

going go ahead and close this and see what we get returned back and we're

what we get returned back and we're returning now only the values that have

returning now only the values that have and in it we actually wanted to do

and in it we actually wanted to do opposite of that right we want the

opposite of that right we want the values that don't have an and so in

values that don't have an and so in order to do that we're going to fix this

order to do that we're going to fix this entire statement right here for the

entire statement right here for the include portion we're going to wrap it

include portion we're going to wrap it in a giant knot to turn everything

in a giant knot to turn everything around add an extra parenthesis on the

around add an extra parenthesis on the end bam now we have full-time contractor

end bam now we have full-time contractor part time we got the zero in there

part time we got the zero in there internship and temp work we just need to

internship and temp work we just need to remove this zero out of it so we just

remove this zero out of it so we just need to modify once again this right

need to modify once again this right here this portion of this include we're

here this portion of this include we're going to do some array multiplication

going to do some array multiplication basically once again looking through and

basically once again looking through and making sure no values equal to zero so

making sure no values equal to zero so I'm going to do a multiplication do an

I'm going to do a multiplication do an opening closing parenthesis and

opening closing parenthesis and basically we're just checking whether J2

basically we're just checking whether J2 hashtag is not equ equal to Zer let's go

hashtag is not equ equal to Zer let's go ahead and enter this boom now we have it

ahead and enter this boom now we have it down to the values that we want for this

down to the values that we want for this I'm going to name this appropriately job

I'm going to name this appropriately job schedule type sorted also for some

schedule type sorted also for some reason this is in this column we're

reason this is in this column we're going to move it over looks like we're

going to move it over looks like we're buing one spacing anyway now we need to

buing one spacing anyway now we need to go back to our basic calculator Tab and

go back to our basic calculator Tab and we need to enter data validation in this

we need to enter data validation in this portion to make sure can select the

portion to make sure can select the right type so going select data

right type so going select data validation once again allow values of

validation once again allow values of list and then for the actual Source

list and then for the actual Source itself we'll go to that data validation

itself we'll go to that data validation tab select all these values in here

tab select all these values in here press enter and enter okay so now we

press enter and enter okay so now we have the type in here so all of our data

have the type in here so all of our data validation portions are now

built next thing up is moving into building the three different charts here

building the three different charts here we're actually going to start with the

we're actually going to start with the country chart because it's the easiest

country chart because it's the easiest and a sneak peek of what data is

and a sneak peek of what data is actually needed for this I can go to the

actually needed for this I can go to the country tab inside my final salary

country tab inside my final salary dashboard and all we really need to do

dashboard and all we really need to do is for each country calculate the median

is for each country calculate the median salary and then throw it into a map

salary and then throw it into a map graph so back to our Excel worksheet

graph so back to our Excel worksheet first thing we need to do is get those

first thing we need to do is get those list of countries and remember we

list of countries and remember we already have that so I'm put equal sign

already have that so I'm put equal sign it's inside of our data validation here

it's inside of our data validation here with these sorted values I want all

with these sorted values I want all these values here here so I'm going to

these values here here so I'm going to do H2 hashtag press enter we have all

do H2 hashtag press enter we have all them all so let's actually start

them all so let's actually start developing the formula for building this

developing the formula for building this out using only we're just going to

out using only we're just going to calculate first the median salary for

calculate first the median salary for that country and then also remember in

that country and then also remember in the past we've have to filter out any

the past we've have to filter out any values that basically equal zero so for

values that basically equal zero so for that if condition for The Logical test

that if condition for The Logical test we're going to do we're going to have to

we're going to do we're going to have to do array multiplication and for our

do array multiplication and for our first array we're going to be checking

first array we're going to be checking for the job country right so we do that

for the job country right so we do that jobs table and specifically that job

jobs table and specifically that job country column and we want to make sure

country column and we want to make sure that it's equal to basically A2 in this

that it's equal to basically A2 in this case the country right next to it

case the country right next to it additionally we want to check that

additionally we want to check that there's 9 zero vales and so we're going

there's 9 zero vales and so we're going to be checking the salary year average

to be checking the salary year average column and making sure that it's not

column and making sure that it's not equal to zero so now moving on to the

equal to zero so now moving on to the value if true we basically want to use

value if true we basically want to use the salary year average column value

the salary year average column value false not applicable here go ahead and

false not applicable here go ahead and close this looks like we have a typo it

close this looks like we have a typo it went ahead and added that extra

went ahead and added that extra parenthesis and we have a median salary

parenthesis and we have a median salary now and go ahead and copy that all the

now and go ahead and copy that all the way down now this is great but remember

way down now this is great but remember in our if I go here back to to the basic

in our if I go here back to to the basic calculator tab we also want to not only

calculator tab we also want to not only filter for a specific country but also

filter for a specific country but also we're going to need to filter for a job

we're going to need to filter for a job title and also for a job type so we need

title and also for a job type so we need to include not necessarily the country

to include not necessarily the country because we're doing it for each country

because we're doing it for each country but we need to include the job title and

but we need to include the job title and the type now in order to add that this

the type now in order to add that this formula is going to get a lot longer and

formula is going to get a lot longer and it's now getting hard to read so I want

it's now getting hard to read so I want to actually I want to one I want to

to actually I want to one I want to operate in this formula bar if you press

operate in this formula bar if you press control shift U it expands it out and

control shift U it expands it out and then from there you can actually change

then from there you can actually change it to the desired length that you want

it to the desired length that you want so what I'm going to do now is actually

so what I'm going to do now is actually break this into new lines I can press on

break this into new lines I can press on a Mac you're going to press Alt Enter on

a Mac you're going to press Alt Enter on the Mac I'm pressing option return

the Mac I'm pressing option return anyway I've went ahead broken this into

anyway I've went ahead broken this into different lines I've also inserted some

different lines I've also inserted some spaces in there to basically put in some

spaces in there to basically put in some indentation so I can read it better

indentation so I can read it better don't have to necessarily do that but

don't have to necessarily do that but now I feel like this is much readable

now I feel like this is much readable for my eyes go ahead and execute this

for my eyes go ahead and execute this and Bam we have all the results and if I

and Bam we have all the results and if I do a drag and drop all the way down all

do a drag and drop all the way down all the other ones are updated as well so

the other ones are updated as well so the first thing we need to add to this

the first thing we need to add to this is to check for the job title itself so

is to check for the job title itself so I'm going put a multiplication there go

I'm going put a multiplication there go to the next line pressing Alt Enter and

to the next line pressing Alt Enter and for this I want to check jobs

for this I want to check jobs specifically I want to check that job

specifically I want to check that job title short column and whether it's

title short column and whether it's equal to basically title remember we

equal to basically title remember we created title so I'm going go ahead and

created title so I'm going go ahead and press enter and it looks like we have a

press enter and it looks like we have a typo because I forgot to insert a

typo because I forgot to insert a parentheses at the end press enter looks

parentheses at the end press enter looks like I misspelled the actual table at

like I misspelled the actual table at itself my bad press enter again now I'm

itself my bad press enter again now I'm getting this name error right here and

getting this name error right here and that's because of this title that we're

that's because of this title that we're using if we go back to that basic

using if we go back to that basic calculator and select that cell C4 right

calculator and select that cell C4 right here it's named titlecore exe and I can

here it's named titlecore exe and I can inspect the different names assigned to

inspect the different names assigned to cells by going to formulas Define names

cells by going to formulas Define names and then the name manager now I started

and then the name manager now I started directly with this workbook before we

directly with this workbook before we actually created all these variables

actually created all these variables here so what we'll do is this I'm going

here so what we'll do is this I'm going to go ahead and actually just delete

to go ahead and actually just delete this titlecore ex that was just an

this titlecore ex that was just an example that's why it says ex then from

example that's why it says ex then from there I'm going to just rename it I'm

there I'm going to just rename it I'm going to select the cell itself of C4

going to select the cell itself of C4 and I'm going to change it back to title

and I'm going to change it back to title okay now it's Title Here back to the

okay now it's Title Here back to the country tab uh we have this updated for

country tab uh we have this updated for the title it's actually appearing now no

the title it's actually appearing now no name eror and I'll go ahead and drag it

name eror and I'll go ahead and drag it all the way down there's going to be a

all the way down there's going to be a lot less values for this cuz we're

lot less values for this cuz we're further filtering this so I'm seeing

further filtering this so I'm seeing some num erors that's as expected all

some num erors that's as expected all right the last condition we need to now

right the last condition we need to now take into account is this type right

take into account is this type right here and we haven't named this cell

here and we haven't named this cell already so I'm selecting K4 and I've

already so I'm selecting K4 and I've come up here and I'm going to select

come up here and I'm going to select type and now I've rename that as type so

type and now I've rename that as type so we can finish this formula off we wanted

we can finish this formula off we wanted to I'm going to do a multiplication sign

to I'm going to do a multiplication sign start a new line by pressing Alt Enter

start a new line by pressing Alt Enter then do open and closeing parenthesis

then do open and closeing parenthesis for this we want to check if the job

for this we want to check if the job schedule type column is equal to type

schedule type column is equal to type okay I'm going to go ahead and press

okay I'm going to go ahead and press enter for this looks we have a value I

enter for this looks we have a value I expect a few more even filtered from

expect a few more even filtered from here okay not a lot now one note on this

here okay not a lot now one note on this this formula is perfectly fine for

this formula is perfectly fine for checking the job schedule tyght I'm

checking the job schedule tyght I'm going to make it slightly better and

going to make it slightly better and actually slightly more correct if I go

actually slightly more correct if I go over to that data validation tab I'm

over to that data validation tab I'm going to press uh control shift U to

going to press uh control shift U to actually close that formul bar if you

actually close that formul bar if you remember

remember from our job schedule tites yeah we

from our job schedule tites yeah we narrowed it down to this list but

narrowed it down to this list but actually there were the true list is

actually there were the true list is this so what we actually need to do is

this so what we actually need to do is check if a value is in here so in our

check if a value is in here so in our case we want to check whether the type

case we want to check whether the type is in here so if we select part-time we

is in here so if we select part-time we will also match on this job type here

will also match on this job type here where it says full-time parttime or this

where it says full-time parttime or this one here where it says full-time

one here where it says full-time part-time temp work and we can do that

part-time temp work and we can do that using the search function so we can find

using the search function so we can find something like part time within text of

something like part time within text of right here and it's going to give us

right here and it's going to give us back a number and then if it's not there

back a number and then if it's not there if I were to actually drag it down to

if I were to actually drag it down to something like third column it's not

something like third column it's not there it's going to get a a a value

there it's going to get a a a value error so I'm going to come back into

error so I'm going to come back into this and expand out the formula bar and

this and expand out the formula bar and I'm going to change this formula right

I'm going to change this formula right here to basically get that condiction

here to basically get that condiction remember we want to use the search

remember we want to use the search function we want to find the text of the

function we want to find the text of the type which is that variable that we have

type which is that variable that we have for the job type and we'll be searching

for the job type and we'll be searching the job schedule type column now

the job schedule type column now remember this is going to return back a

remember this is going to return back a number of the position if it's there so

number of the position if it's there so we're going to need to wrap this all in

we're going to need to wrap this all in a is number function and then put

a is number function and then put closing parentheses so I'm going to

closing parentheses so I'm going to autofill this all the way down again and

autofill this all the way down again and it doesn't look like any values at least

it doesn't look like any values at least in view actually changed underneath this

in view actually changed underneath this formul bar for right now so I'm going to

formul bar for right now so I'm going to go ahead and hide it and then for this

go ahead and hide it and then for this when we go to plot it we actually need

when we go to plot it we actually need to remove these numb values from here so

to remove these numb values from here so in order to do this I'm going to I'll

in order to do this I'm going to I'll create this new one called job country

create this new one called job country filter and we're going to be using the

filter and we're going to be using the well filter function and for this we

well filter function and for this we need to include the array so everything

need to include the array so everything from here downwards pressing control

from here downwards pressing control shift down to select that and then what

shift down to select that and then what do we want to actually include well we

do we want to actually include well we want to check to include anything in

want to check to include anything in that b column so is a number we going to

that b column so is a number we going to check those values are equal to a number

check those values are equal to a number so I entered in that b column then as

so I entered in that b column then as well all right let's go ahead and run

well all right let's go ahead and run this and it looks like it has all of our

this and it looks like it has all of our values I don't like the order I'd rather

values I don't like the order I'd rather it sorted this is just me preference I'd

it sorted this is just me preference I'd rather the numerical values be sorted so

rather the numerical values be sorted so I'm going to wrap this all in a sort

I'm going to wrap this all in a sort function and this is the array we're

function and this is the array we're applying to it we want to sort it on the

applying to it we want to sort it on the second index and for for this we wanted

second index and for for this we wanted to put it in we'll say descending order

to put it in we'll say descending order and well Puerto Rico has some of the

and well Puerto Rico has some of the highest jobs may have to move there and

highest jobs may have to move there and okay we're going to get into applying

okay we're going to get into applying this now I want to make sure that we

this now I want to make sure that we have the maximum amount of values

have the maximum amount of values present there's a lot of countries

present there's a lot of countries missing that I know we available so I'm

missing that I know we available so I'm going to just select the most basic job

going to just select the most basic job possible to make sure that we have all

possible to make sure that we have all the jobs that we can appear so so we'll

the jobs that we can appear so so we'll just select data analyst United States

just select data analyst United States fulltime okay now we can go about

fulltime okay now we can go about selecting column d and e and then

selecting column d and e and then inserting in our map now I don't want

inserting in our map now I don't want this here so I'm actually going to grab

this here so I'm actually going to grab this map and then come over here and put

this map and then come over here and put it in I'm only going to do some minor

it in I'm only going to do some minor cleanup right now I'm going to remove

cleanup right now I'm going to remove the chart title and also leged but we

the chart title and also leged but we now have this chart map available for

now have this chart map available for countries that shows the median salary

countries that shows the median salary one quick note you are going to have

one quick note you are going to have this sort of warning right here if I

this sort of warning right here if I click on it and it says hey we plotted

click on it and it says hey we plotted 74% of the location from the data with

74% of the location from the data with high confidence basically some of the

high confidence basically some of the countries in there couldn't align

countries in there couldn't align properly in my opinion it picked out a

properly in my opinion it picked out a lot of the major countries so I'm really

lot of the major countries so I'm really fine with that I'm fine if I didn't

fine with that I'm fine if I didn't identify all of them 74 is good enough

identify all of them 74 is good enough back to the final dashboard so we made

back to the final dashboard so we made this country map right here now we need

this country map right here now we need to make these other two one thing to

to make these other two one thing to call out with this which I don't think

call out with this which I don't think I've called out before if we notice

I've called out before if we notice whenever we select a job so in this case

whenever we select a job so in this case I'll select data scientist it makes that

I'll select data scientist it makes that barall are a darker color blue the way

barall are a darker color blue the way your eyes go towards it and then you can

your eyes go towards it and then you can compare it to the other ones so how did

compare it to the other ones so how did I do this well if I go to my jobs tab my

I do this well if I go to my jobs tab my final jobs tab what I'm doing here is I

final jobs tab what I'm doing here is I have all the median salaries which we

have all the median salaries which we calculated already in ours but I added

calculated already in ours but I added this over here basically I have one

this over here basically I have one column without we have data scientist

column without we have data scientist selected right now so I have one column

selected right now so I have one column without the value appear in and then one

without the value appear in and then one value with it appearing in and then what

value with it appearing in and then what we'll do from there is just some

we'll do from there is just some basically manipulation of the graph to

basically manipulation of the graph to make it to where in this case data

make it to where in this case data scientist appears so going back to our

scientist appears so going back to our worksheet of our fancy Dancy dashboard

worksheet of our fancy Dancy dashboard we have so far going to go to that title

we have so far going to go to that title sheet remember we already did all this

sheet remember we already did all this portion of the last section first thing

portion of the last section first thing we do is well we need to do some cleanup

we do is well we need to do some cleanup we need to get rid of this name error

we need to get rid of this name error also we are going to create those extra

also we are going to create those extra columns right here for basically what

columns right here for basically what job title selected but we need need to

job title selected but we need need to more importantly if I expand out the

more importantly if I expand out the formula bar we need to update this

formula bar we need to update this median salary similar to what we do with

median salary similar to what we do with job type to not only take into account

job type to not only take into account the job title but also the country and

the job title but also the country and the job schedule type so I'm all for not

the job schedule type so I'm all for not repeating our work I'm going to go back

repeating our work I'm going to go back over to the country tab select the

over to the country tab select the median salary and I'm going to basically

median salary and I'm going to basically just copy all that portion that's in

just copy all that portion that's in there anyway I'm going to escape out of

there anyway I'm going to escape out of that come back into the job job title

that come back into the job job title tab select B2 and I'll go ahead and just

tab select B2 and I'll go ahead and just press uh Alt Enter insert all that in

press uh Alt Enter insert all that in and then now I just want to clean this

and then now I just want to clean this up we do want this country which we're

up we do want this country which we're going to have to

going to have to fix but we don't need these middle two

fix but we don't need these middle two right here that we already basically

right here that we already basically have specifically with the job country

have specifically with the job country though so remember this thing's

though so remember this thing's calculating the median salary based on

calculating the median salary based on the job title selected in this col here

the job title selected in this col here and column A so this A2 is going to work

and column A so this A2 is going to work here previously we were doing the same

here previously we were doing the same thing with country we don't need to do

thing with country we don't need to do country anymore we need to actually put

country anymore we need to actually put in a variable of country which we

in a variable of country which we haven't created yet so I'm just going to

haven't created yet so I'm just going to enter country in it's going to give me

enter country in it's going to give me an error this name error I'm going to

an error this name error I'm going to come back over to the basic calculator

come back over to the basic calculator tab select this and then rename G4 to

tab select this and then rename G4 to Country press enter come back to the

Country press enter come back to the title tab we're no longer getting that

title tab we're no longer getting that name error looks like it's executing

name error looks like it's executing just right I'm going to go ahead and

just right I'm going to go ahead and drag it all the way down and we do have

drag it all the way down and we do have an error in my formula I have this comma

an error in my formula I have this comma right here this is supposed to actually

right here this is supposed to actually be an array right this whole thing is

be an array right this whole thing is supposed to be um an array so now let's

supposed to be um an array so now let's try it again press enter okay 990,000

try it again press enter okay 990,000 for data analyst in the United States I

for data analyst in the United States I know that's true and now we're filling

know that's true and now we're filling it in for all the rest okay so we have

it in for all the rest okay so we have what we need I'm going close out the

what we need I'm going close out the formula bar and remember we want to

formula bar and remember we want to basically in one column if it has the

basically in one column if it has the word data analist we want to not include

word data analist we want to not include it and then another one we want to only

it and then another one we want to only include that one so we're going to use

include that one so we're going to use an if for this so if this value which

an if for this so if this value which we're going to go ahead and lock the

we're going to go ahead and lock the column is not equal to the title then

column is not equal to the title then we're going to basically display those

we're going to basically display those results which I'm going to lock the

results which I'm going to lock the column for this otherwise I just wanted

column for this otherwise I just wanted to display an A and not a value Okay g

to display an A and not a value Okay g to go ahead and enter this and it is dat

to go ahead and enter this and it is dat analyst so it's not going to appear

analyst so it's not going to appear there but it will appear all the rest of

there but it will appear all the rest of these and so I locked those columns so I

these and so I locked those columns so I can just drag this over and now with

can just drag this over and now with this other one I want to do the opposite

this other one I want to do the opposite basically if it's equal to title I want

basically if it's equal to title I want it to appear and then I'll drag and drop

it to appear and then I'll drag and drop it all the way down so these are the

it all the way down so these are the values I want to plot so I'm going to

values I want to plot so I'm going to select D2 to d11 then holding control

select D2 to d11 then holding control also select these values right here go

also select these values right here go in and insert recommended charts and

in and insert recommended charts and first one up is actually the one that I

first one up is actually the one that I want so we'll go ahead and insert that

want so we'll go ahead and insert that so I'll take this chart and also move

so I'll take this chart and also move that right here into the basic

that right here into the basic calculator tab with this one once again

calculator tab with this one once again I don't want a chart title and I don't

I don't want a chart title and I don't want a legend the other thing are the

want a legend the other thing are the values the horizontal values down here

values the horizontal values down here I'm going to go ahead and double click

I'm going to go ahead and double click on that scroll down here all the way to

on that scroll down here all the way to number and we're going to do that custom

number and we're going to do that custom formatting that we've done previously if

formatting that we've done previously if it's not peering uh feel free to type

it's not peering uh feel free to type the code in but we're going to use this

the code in but we're going to use this to basically format it as with the

to basically format it as with the dollar sign in the front and then also

dollar sign in the front and then also the k for the thousands place all right

the k for the thousands place all right the last thing is you know I don't like

the last thing is you know I don't like to use a lot of different colors in this

to use a lot of different colors in this so making sure the graph is selected go

so making sure the graph is selected go to chart design and then into chart

to chart design and then into chart colors right now it's set under colorful

colors right now it's set under colorful which I think is awful default value I'm

which I think is awful default value I'm going to come down here and select not

going to come down here and select not this monochromatic palette 4 five sorry

this monochromatic palette 4 five sorry the but the monochromatic palette 12 and

the but the monochromatic palette 12 and that's because now data analyst will be

that's because now data analyst will be the darkest blue the other ones will be

the darkest blue the other ones will be light so that way my eyes go to that one

light so that way my eyes go to that one instead so now what we just did with the

instead so now what we just did with the job title we need to repeat it for job

job title we need to repeat it for job type so a lot of copy and pase in so

type so a lot of copy and pase in so we're going to move a lot faster with

we're going to move a lot faster with this one because we've done most of this

this one because we've done most of this before for this we're going to be

before for this we're going to be entering in the type sheet and I'm going

entering in the type sheet and I'm going to go ahead and pull all those things in

to go ahead and pull all those things in from data validation tab now we need to

from data validation tab now we need to get the median salaries for that I'm

get the median salaries for that I'm just going to come back over to the

just going to come back over to the title sheet come into here and actually

title sheet come into here and actually just copy this en typable formula then

just copy this en typable formula then expanding this out with control shift U

expanding this out with control shift U pasting this in here now we need to just

pasting this in here now we need to just change this up slightly so for the job

change this up slightly so for the job title we need to actually use the job

title we need to actually use the job title whereas conversely for the job

title whereas conversely for the job type we no longer want to use type we

type we no longer want to use type we want to use what's available in A2

want to use what's available in A2 pressing enter we get our value for

pressing enter we get our value for full-time 990,000 of data analyst that's

full-time 990,000 of data analyst that's correct and then drag it on down I'm

correct and then drag it on down I'm going to go ahead and close this for of

going to go ahead and close this for of the bar and for this I'm going to use uh

the bar and for this I'm going to use uh similar to what we did in that Country

similar to what we did in that Country Sheet in where we not only filter the

Sheet in where we not only filter the data to make sure we include is numbers

data to make sure we include is numbers but also we sorted it and that's because

but also we sorted it and that's because sometimes these values sometimes we may

sometimes these values sometimes we may not have values and we go back to this

not have values and we go back to this type tab sometimes there may not be a

type tab sometimes there may not be a certain job schedule type so I'm going

certain job schedule type so I'm going to go ahead and paste this in now it is

to go ahead and paste this in now it is working I know there will always be five

working I know there will always be five values so I'm going to actually change

values so I'm going to actually change this to B6 here and also B6 here and

this to B6 here and also B6 here and press enter now I also realized I made a

press enter now I also realized I made a mistake earlier whenever I went to the

mistake earlier whenever I went to the title sheet this is only doing the sort

title sheet this is only doing the sort function and we may have a condition

function and we may have a condition where in certain countries they don't

where in certain countries they don't have all these different job titles

have all these different job titles available so we need to do its similar

available so we need to do its similar Hill here as well so I'm going to paste

Hill here as well so I'm going to paste that formula into here and then adjust

that formula into here and then adjust it because I know there's always 10 job

it because I know there's always 10 job titles so it's going to go down to 11 in

titles so it's going to go down to 11 in this case and 11 here we go ahead and

this case and 11 here we go ahead and run that there's going to be no change

run that there's going to be no change the one issue though is in this case if

the one issue though is in this case if I go back to that basic calculator it

I go back to that basic calculator it doesn't do it in the order that I want

doesn't do it in the order that I want so going back to that title sheet I'm

so going back to that title sheet I'm going to change that sorting value from

going to change that sorting value from a negative one to a one so that way it

a negative one to a one so that way it goes in basically ascending order and I

goes in basically ascending order and I need to do the same thing here here as

need to do the same thing here here as well in the type sheet where it's also

well in the type sheet where it's also in ascending order cuz we're going to be

in ascending order cuz we're going to be making the same graph all right similar

making the same graph all right similar to last time I wanted to if the value is

to last time I wanted to if the value is selected I want it to be highlighted so

selected I want it to be highlighted so we need to make those same columns again

we need to make those same columns again so if this is not equal to the type I

so if this is not equal to the type I want the value to appear and it be na

want the value to appear and it be na because right now fulltime is selected

because right now fulltime is selected dragging it over and then adjusting it

dragging it over and then adjusting it for equal instead and then dragging it

for equal instead and then dragging it down I do want it to appear if it's

down I do want it to appear if it's full-time now I'm going to select

full-time now I'm going to select D2 D6 and then these values in f and g

D2 D6 and then these values in f and g once again we're going to go to insert

once again we're going to go to insert recommended charts I don't like these

recommended charts I don't like these clustered columns I prefer a clustered

clustered columns I prefer a clustered bar chart so I'm going to take this and

bar chart so I'm going to take this and then put it in here make similar format

then put it in here make similar format and changes as well of removing the

and changes as well of removing the title and then also the legend updating

title and then also the legend updating the xaxis by going into numbers and

the xaxis by going into numbers and changing the format to a custom format

changing the format to a custom format to using the K value instead and then

to using the K value instead and then finally the actual color Itself by going

finally the actual color Itself by going to that monoch chromatic the color

to that monoch chromatic the color palette 12 so bam now we have a lot of

palette 12 so bam now we have a lot of this made so I can go through now and

this made so I can go through now and select say data data scientist it will

select say data data scientist it will update for selecting data scientist and

update for selecting data scientist and then you see all these other values

then you see all these other values update as well I can also select the

update as well I can also select the different type um part-time in this case

different type um part-time in this case and then the values still remain the the

and then the values still remain the the same it just changes the bar that it's

same it just changes the bar that it's selected

to all right the last major thing before we get into formatting we're going to

we get into formatting we're going to make these three kpi cards one is for

make these three kpi cards one is for the median salary the next is for the

the median salary the next is for the top job platform and then finally on the

top job platform and then finally on the job count itself for how many counts of

job count itself for how many counts of jobs for all of these now one quick

jobs for all of these now one quick thing Excel doesn't necessarily have kpi

thing Excel doesn't necessarily have kpi cards like if you use something like

cards like if you use something like powerbi or looker they provide cards to

powerbi or looker they provide cards to this we're going to do some sort of

this we're going to do some sort of backdoor approach if you will to make

backdoor approach if you will to make this into a kpi card basically I'm going

this into a kpi card basically I'm going to insert in a text box and we're going

to insert in a text box and we're going to put a cell equal to it you'll see

to put a cell equal to it you'll see what we're going to do with it but the

what we're going to do with it but the main point is these values this value

main point is these values this value itself is not as you can see it's a

itself is not as you can see it's a rectangle it's not in a Cell per se but

rectangle it's not in a Cell per se but it is calculated within the workbook

it is calculated within the workbook anyway what we're going to be doing I

anyway what we're going to be doing I don't need this down here this median

don't need this down here this median salary what we did from the last lesson

salary what we did from the last lesson I'm gonna go ahead and delete this but

I'm gonna go ahead and delete this but the first we want to calculate is that

the first we want to calculate is that median salary and we basically have it

median salary and we basically have it already and I'm going to calculate it

already and I'm going to calculate it right here in this column of I2 and for

right here in this column of I2 and for this we're just going to use a simple x

this we're just going to use a simple x lookup and the value we want to look up

lookup and the value we want to look up is based on the job title selected so

is based on the job title selected so title and the lookup array is this array

title and the lookup array is this array right here and then the final return

right here and then the final return array is right next to it there's a

array is right next to it there's a missing value right now because Cloud

missing value right now because Cloud Engineers is not available in the

Engineers is not available in the currenc are selected so make sure you're

currenc are selected so make sure you're selecting the full values and we going

selecting the full values and we going to go ahead and close it but we have now

to go ahead and close it but we have now the median salary so I'm going to

the median salary so I'm going to actually rename this I2 cell to median

actually rename this I2 cell to median salary and then going back into our

salary and then going back into our basic calculator tab remember I'm not

basic calculator tab remember I'm not going to insert it into a sell in here

going to insert it into a sell in here but instead we go into insert and then

but instead we go into insert and then illustrations and I'm just going to

illustrations and I'm just going to insert a simple old textt box I'll drag

insert a simple old textt box I'll drag it right there now the thing is I don't

it right there now the thing is I don't want to type inside of here what I'm

want to type inside of here what I'm actually do is I'm going to select the

actually do is I'm going to select the Box itself so you no longer have that

Box itself so you no longer have that blinking cursor in there come up into

blinking cursor in there come up into the formula bar up here type in equal to

the formula bar up here type in equal to median salary and Bam now if you notice

median salary and Bam now if you notice it copied the formatting that we

it copied the formatting that we previously have right here as a cluster

previously have right here as a cluster number looking at right there it copied

number looking at right there it copied the same formatting that we're using

the same formatting that we're using here in I2 so what I'm going to do is

here in I2 so what I'm going to do is just go in here and change this

just go in here and change this formatting to a currency with zero

formatting to a currency with zero decimal places and then once we have

decimal places and then once we have this value actually updated go back to

this value actually updated go back to basic calculator we can see boom looks a

basic calculator we can see boom looks a lot nicer we'll adjust the formatting as

lot nicer we'll adjust the formatting as far as the size and stuff in a little

far as the size and stuff in a little bit after we calculate all the other

bit after we calculate all the other ones the next one from our final

ones the next one from our final dashboard is the top job platform so

dashboard is the top job platform so we've only calculated things associated

we've only calculated things associated with the job title the job country and

with the job title the job country and the job type so we need to make a new

the job type so we need to make a new sheet and we'll rename it platform and

sheet and we'll rename it platform and technically the column name is job via

technically the column name is job via and for this we need to get the unique

and for this we need to get the unique values of the job via column now for

values of the job via column now for this one we're trying to get the top job

this one we're trying to get the top job platform so we're not necessarily doing

platform so we're not necessarily doing that based on what is the top median

that based on what is the top median salary on this I just want where are the

salary on this I just want where are the most jobs actually located so we're

most jobs actually located so we're going to be doing a count using control

going to be doing a count using control shift U to expand the we've been using

shift U to expand the we've been using this median with this if array in it

this median with this if array in it we've already built this out already

we've already built this out already which this formula does so you could so

which this formula does so you could so we're going to use this I'm going to go

we're going to use this I'm going to go ahead and copy it by pressing contrl C

ahead and copy it by pressing contrl C coming over to platform and then pasting

coming over to platform and then pasting it in with contrl v okay and instead of

it in with contrl v okay and instead of median we're going to use count and the

median we're going to use count and the only other thing we need to update on

only other thing we need to update on this is we stole it from the job country

this is we stole it from the job country page is we need to update the job

page is we need to update the job country to be well country and we need

country to be well country and we need to check one more condition so we need

to check one more condition so we need to add to this array I'm going press uh

to add to this array I'm going press uh Alt Enter to create a new line and we

Alt Enter to create a new line and we want to check that job via is equal to

want to check that job via is equal to in this case A2 and we go ahead and

in this case A2 and we go ahead and press enter looks like 10 were available

press enter looks like 10 were available for Via script zip recruiter and then it

for Via script zip recruiter and then it calculates all the way down now remember

calculates all the way down now remember our data set also has hourly data in

our data set also has hourly data in there as well so technically if you

there as well so technically if you wanted to which I'm going to I'm going

wanted to which I'm going to I'm going to remove move this condition right here

to remove move this condition right here that we're checking that it's not equal

that we're checking that it's not equal to zero basically it's also going to

to zero basically it's also going to include if there's a job that has an

include if there's a job that has an hourly salary included so I'm going to

hourly salary included so I'm going to go ahead and backspace out of that press

go ahead and backspace out of that press enter and then from there drag and drop

enter and then from there drag and drop it down and I can see we added a few

it down and I can see we added a few more values because of this I'm close

more values because of this I'm close this formula bar control shift you all

this formula bar control shift you all right so now I need to sort these values

right so now I need to sort these values basically from high to low selecting all

basically from high to low selecting all the values using control shift down the

the values using control shift down the sword index we want to use the second

sword index we want to use the second index and we want to put this one in

index and we want to put this one in descending order cuz we want the highest

descending order cuz we want the highest one up at the top and for this it looks

one up at the top and for this it looks like snag a job is the highest anyway uh

like snag a job is the highest anyway uh this is what we want this first one

this is what we want this first one actually appearing in our kpi card but

actually appearing in our kpi card but if you notice all of these have via in

if you notice all of these have via in front of it so what I'm going to use is

front of it so what I'm going to use is a text function of substitute which

a text function of substitute which replaces existing test with a new text

replaces existing test with a new text and for our text in D2

and for our text in D2 the old text that I want to replace is

the old text that I want to replace is via with a space and the new text is

via with a space and the new text is just a blank value so snag job is now up

just a blank value so snag job is now up the top this is what I want to be known

the top this is what I want to be known as we're going to rename this variable

as we're going to rename this variable to platform then we do the same thing on

to platform then we do the same thing on our dashboard of inserting a text value

our dashboard of inserting a text value and for this I'm going to select it and

and for this I'm going to select it and say that it's equal to platform all

say that it's equal to platform all right so snag a job and for this one

right so snag a job and for this one this one is well somewhat simple but in

this one is well somewhat simple but in our data validation tab we were in the

our data validation tab we were in the very beginning in the last lesson we

very beginning in the last lesson we were calculating the count and we were

were calculating the count and we were calculating a generic count of all of

calculating a generic count of all of them so we need to once again modify

them so we need to once again modify this because we want the count based on

this because we want the count based on our three conditions here so what I'm

our three conditions here so what I'm going to do is just basically steal it

going to do is just basically steal it from what we did previously go into that

from what we did previously go into that B2 cell in the platform sheet go ahead

B2 cell in the platform sheet go ahead and copy this all and then then in here

and copy this all and then then in here I'm going to expand this formula out I'm

I'm going to expand this formula out I'm going to go ahead and replace that in B2

going to go ahead and replace that in B2 with this now a few modifications we can

with this now a few modifications we can make to this we're no longer checking

make to this we're no longer checking the job via column we're not trying to

the job via column we're not trying to check that for the count that was

check that for the count that was specific to where we stole that from so

specific to where we stole that from so I'm going to delete that and also this

I'm going to delete that and also this uh multiplication point and then this is

uh multiplication point and then this is checking all of the things selected of

checking all of the things selected of country title and type we're wanting to

country title and type we're wanting to check the count of a certain title so

check the count of a certain title so instead of having title we'll put in a

instead of having title we'll put in a A2 pressing enter we have a lower value

A2 pressing enter we have a lower value because we've the current filters are

because we've the current filters are lower and then we'll fill it all the way

lower and then we'll fill it all the way down closing the formula bar out we now

down closing the formula bar out we now want to get the count for whatever is

want to get the count for whatever is selected so I'm going to go to an empty

selected so I'm going to go to an empty column over here right here and we're

column over here right here and we're going to be doing an X lookup again the

going to be doing an X lookup again the lookup value is what is the title that

lookup value is what is the title that we're using the lookup array is we'll

we're using the lookup array is we'll use this one right here and then for as

use this one right here and then for as far as the return array right next to it

far as the return array right next to it pressing enter boom get a value of 537

pressing enter boom get a value of 537 now just to be safe in case there aren't

now just to be safe in case there aren't any results like say it was zero or

any results like say it was zero or something or not applicable it's going

something or not applicable it's going to be basically not applicable I do want

to be basically not applicable I do want to include if not found I'm going to

to include if not found I'm going to enter in no results and I'm going to do

enter in no results and I'm going to do the same thing underneath the title

the same thing underneath the title sheet for where we calculated the median

sheet for where we calculated the median salary put for no results

salary put for no results so I'm going go ahead we want to get

so I'm going go ahead we want to get that count in there so we insert that

that count in there so we insert that illustration again for us we're going to

illustration again for us we're going to insert a text box and that textbox is

insert a text box and that textbox is going to be equal to count which I don't

going to be equal to count which I don't think we actually named yet so I

think we actually named yet so I actually need to go back to escape out

actually need to go back to escape out of this go back to the data validation

of this go back to the data validation tab rename this count and then from

tab rename this count and then from there with the text box selected I'm

there with the text box selected I'm going put that equal to count now for

going put that equal to count now for each one of these text boxes I need to

each one of these text boxes I need to go through and actually

go through and actually as you can see the we have a text box

as you can see the we have a text box for the value but I actually want to use

for the value but I actually want to use a shape basically background to tell us

a shape basically background to tell us what we're actually performing or

what we're actually performing or calculation that this kpi is showing so

calculation that this kpi is showing so I'm going come in here and to insert

I'm going come in here and to insert illustrations for shapes we're going to

illustrations for shapes we're going to keep it actually we'll say a rectangle

keep it actually we'll say a rectangle this time and then we'll go ahead and

this time and then we'll go ahead and draw it now for the shape format itself

draw it now for the shape format itself I'm going to go to this one right here

I'm going to go to this one right here basically a blue around with white on

basically a blue around with white on the front and with these shapes you can

the front and with these shapes you can still put in text in here so I can put

still put in text in here so I can put in something like median salary and I

in something like median salary and I can open up the Home tab and I can

can open up the Home tab and I can actually customize this further so I can

actually customize this further so I can make this bold I can put in the center I

make this bold I can put in the center I actually want Center top and I'm going

actually want Center top and I'm going to make this slightly bigger by 20 point

to make this slightly bigger by 20 point also I'm noticing this box is a green

also I'm noticing this box is a green outline I don't really like that I'd

outline I don't really like that I'd rather a blue outline so we have that

rather a blue outline so we have that now okay so how do we get that number if

now okay so how do we get that number if you notice the number is no long it's

you notice the number is no long it's hidden behind here we can do a couple

hidden behind here we can do a couple different ways but I'm just going to

different ways but I'm just going to rightclick this object and then under

rightclick this object and then under shape format you can go to send

shape format you can go to send backwards specifically I want to send

backwards specifically I want to send all the way to the back now getting into

all the way to the back now getting into the actual text box itself if you notice

the actual text box itself if you notice there's a little bit of a a box around

there's a little bit of a a box around it I don't really like that I'm also

it I don't really like that I'm also going to exp expand it all the way to

going to exp expand it all the way to the edges I'm going to format this one

the edges I'm going to format this one as well to be centered bold and then

as well to be centered bold and then we're going to make the font much bigger

we're going to make the font much bigger on this and I'm going to once I like I

on this and I'm going to once I like I talked about remove that shape outline

talked about remove that shape outline right now it has a a light one I'm going

right now it has a a light one I'm going to say no outline okay so now it looks

to say no outline okay so now it looks like a kpi card copying this I'm going

like a kpi card copying this I'm going to then make two more and for each of

to then make two more and for each of these I'm going to send them back to the

these I'm going to send them back to the back name appropriately to top job

back name appropriately to top job platform and job count for this I'm

platform and job count for this I'm going to just copy this text box here

going to just copy this text box here that has the median salary in it and I

that has the median salary in it and I just want to copy the formatting to the

just want to copy the formatting to the other ones as well so we can

other ones as well so we can conveniently use this paintbrush this

conveniently use this paintbrush this format prer and I'll select this one it

format prer and I'll select this one it disappeared I have to reselect it and

disappeared I have to reselect it and I'll also select this one if you notice

I'll also select this one if you notice the names are cutting off so it's really

the names are cutting off so it's really important that you extend it all the way

important that you extend it all the way over same thing with the job count as

well now we're getting into the format portion of actually just doing some

portion of actually just doing some final touches on here I don't like grid

final touches on here I don't like grid lines so under view tab I'm going to

lines so under view tab I'm going to select remove grid lines for each of

select remove grid lines for each of these charts I don't really like those

these charts I don't really like those outlines I want it just to sort of blend

outlines I want it just to sort of blend in to make it look like it's there so

in to make it look like it's there so for the shape outline I'm going to

for the shape outline I'm going to change each of them to no outline up in

change each of them to no outline up in our data validation point I want to make

our data validation point I want to make the spacing right I'm also going to make

the spacing right I'm also going to make these titles slightly bigger for the

these titles slightly bigger for the dropdowns themselves I want them to

dropdowns themselves I want them to basically pop out so I'm going to change

basically pop out so I'm going to change this formatting I'm going to go to the

this formatting I'm going to go to the cell Styles and I really like this one

cell Styles and I really like this one of input because it sort of calls your

of input because it sort of calls your eyes to what you need to go to I'm going

eyes to what you need to go to I'm going to make this G column slightly bigger

to make this G column slightly bigger and then shift the type over some the

and then shift the type over some the other thing I want to do is add a title

other thing I want to do is add a title up here at the top for what this

up here at the top for what this dashboard actually does so I'm going to

dashboard actually does so I'm going to select cells B1 through L1 I'm going to

select cells B1 through L1 I'm going to do merge and center and I'm going to

do merge and center and I'm going to change this to data science salary

change this to data science salary calculator along with going to the cell

calculator along with going to the cell style we'll do heading one for right now

style we'll do heading one for right now I want that to still be slightly bigger

I want that to still be slightly bigger okay now we're going to to start moving

okay now we're going to to start moving stuff around but I want to get in it's

stuff around but I want to get in it's like its final form that I'm going to

like its final form that I'm going to give to colleagues and co-workers and

give to colleagues and co-workers and I'm going to give it with the Home tab

I'm going to give it with the Home tab closed and also with if I view this can

closed and also with if I view this can remove headings so it moved the column

remove headings so it moved the column headers the A and the B and then the row

headers the A and the B and then the row numbers as well so it looks like

numbers as well so it looks like everything's upda correctly one minor

everything's upda correctly one minor thing this job count I want to make sure

thing this job count I want to make sure after I select it fulltime I saw that

after I select it fulltime I saw that the formatting of the thousands with the

the formatting of the thousands with the Comm is not there so going back into

Comm is not there so going back into that data validation tab I'm going to

that data validation tab I'm going to select this go to home make it a comma

select this go to home make it a comma and remove all the decimal places okay

and remove all the decimal places okay looking good all right now we need to

looking good all right now we need to get this set up to give to colleagues I

get this set up to give to colleagues I don't want them to have all these other

don't want them to have all these other tabs or all these other sheets so I'm

tabs or all these other sheets so I'm going to go through and actually just

going to go through and actually just hide the ones that aren't applicable for

hide the ones that aren't applicable for them Additionally the sheet of basic

them Additionally the sheet of basic calculator doesn't really make sense

calculator doesn't really make sense anymore cuz that was for that first

anymore cuz that was for that first lesson I'm going to actually name this

lesson I'm going to actually name this to salary calculator now call could

to salary calculator now call could still potentially go in and they could

still potentially go in and they could mess up these formulas and so we need to

mess up these formulas and so we need to now protect our worksheet and we only

now protect our worksheet and we only want them to be able to manipulate these

want them to be able to manipulate these three cells so we're going to be going

three cells so we're going to be going through protecting the sheet but we need

through protecting the sheet but we need to actually recall that we have to pick

to actually recall that we have to pick what cells that we want to lock right we

what cells that we want to lock right we need to select all the cells and I

need to select all the cells and I preemptively told you to hide the

preemptively told you to hide the headings you need to go back into view

headings you need to go back into view and show the headings again cuz we need

and show the headings again cuz we need to be able to select this triangle in

to be able to select this triangle in the upper left hand order to select all

the upper left hand order to select all the different cells and then from there

the different cells and then from there holding control unselect these three

holding control unselect these three cells and then from there we're going to

cells and then from there we're going to right click in there go to format cells

right click in there go to format cells under protection and we want to make in

under protection and we want to make in that case that they are locked or

that case that they are locked or basically we are going to be able to

basically we are going to be able to lock them conversely we need to escape

lock them conversely we need to escape out of this and now select the three

out of this and now select the three cells that we want to unlock right click

cells that we want to unlock right click go to format cells and for these we want

go to format cells and for these we want to make sure that they are not checked

to make sure that they are not checked for this so basically unlocked whenever

for this so basically unlocked whenever we go ahead and protect the sheet so now

we go ahead and protect the sheet so now whenever I go into review go to protect

whenever I go into review go to protect sheet I want to be able to select unlock

sheet I want to be able to select unlock cells once again if you want to enter a

cells once again if you want to enter a password you can I'm going to click okay

password you can I'm going to click okay so now I can't click anywhere else

so now I can't click anywhere else except for where we have our data

except for where we have our data validation so I can go through and

validation so I can go through and select things like data scientist and

select things like data scientist and turkey now I'm just going to add that

turkey now I'm just going to add that last final touch of removing the

last final touch of removing the headings

headings bam we have our dashboard now I promise

bam we have our dashboard now I promise last last thing before we go I'm

last last thing before we go I'm noticing and you're probably noticing as

noticing and you're probably noticing as well if you're going through and

well if you're going through and manipulating these values in this case

manipulating these values in this case let's go from data analyst from previous

let's go from data analyst from previous selected data scientists this me talking

selected data scientists this me talking in real time I want to show it takes how

in real time I want to show it takes how long it takes to load and it takes

long it takes to load and it takes forever to load why is it doing this

forever to load why is it doing this this is not good for stakeholders

this is not good for stakeholders they're going to get annoyed if it takes

they're going to get annoyed if it takes this long I'm going go ahead and unhide

this long I'm going go ahead and unhide some of our sheet repats specifically

some of our sheet repats specifically that platform one now these formulas

that platform one now these formulas that we're using um the array formulas

that we're using um the array formulas to calculate these values it's F so in

to calculate these values it's F so in this platforms one we have like oh my

this platforms one we have like oh my gosh in this case we have close to 200

gosh in this case we have close to 200 oh no it's like slowing down even going

oh no it's like slowing down even going through this we're executing this

through this we're executing this hundreds of times in here whereas if I

hundreds of times in here whereas if I compare it to something like the title

compare it to something like the title sheet we're only running this you know n

sheet we're only running this you know n 10 times which I feel isn't that big but

10 times which I feel isn't that big but if we're running this formula hundreds

if we're running this formula hundreds of times it's going to slow down this

of times it's going to slow down this sheet so I have a quick fix for this and

sheet so I have a quick fix for this and it involves we're not going to

it involves we're not going to especially for this sheet here platform

especially for this sheet here platform sheets we're not going to use this um

sheets we're not going to use this um array multiplication order to calculate

array multiplication order to calculate this instead we're going to use a count

this instead we're going to use a count ifs the first thing we're going to do is

ifs the first thing we're going to do is check that the Java is equal to the

check that the Java is equal to the criteria one of A2 so basically job

criteria one of A2 so basically job platform is what it is says it is from

platform is what it is says it is from there we'll check the job title short

there we'll check the job title short column to make sure it makes up with

column to make sure it makes up with title we'll check the job country is

title we'll check the job country is equal to Country and then finally we're

equal to Country and then finally we're going to check that the job schedule

going to check that the job schedule type is equal to type and then we're

type is equal to type and then we're going to go ahead and execute this and

going to go ahead and execute this and then we're going to autofill it all the

then we're going to autofill it all the way down notice that 1490 it's actually

way down notice that 1490 it's actually going to go down slightly to

going to go down slightly to 1426 and that's because we've now

1426 and that's because we've now changed this condition inside of this

changed this condition inside of this count ifs specifically if I go back to

count ifs specifically if I go back to that title sheet you remember whenever

that title sheet you remember whenever we match for this we did a really

we match for this we did a really indepth search so if any job schedule

indepth search so if any job schedule type contain those keywords we match to

type contain those keywords we match to it now we're only matching it if it

it now we're only matching it if it exactly matches but since this job

exactly matches but since this job platform is just providing it's not

platform is just providing it's not providing a numerical value it's

providing a numerical value it's providing what is the Top Value I don't

providing what is the Top Value I don't think the Top Value is going to change

think the Top Value is going to change that much so I don't think we're being

that much so I don't think we're being inaccurate about this if we change this

inaccurate about this if we change this formula anyway going back to the actual

formula anyway going back to the actual dashboard itself now whenever I change

dashboard itself now whenever I change this from data analyst to data scientist

this from data analyst to data scientist it is much faster so now I'm go ahead

it is much faster so now I'm go ahead and hide those sheets and we are done so

and hide those sheets and we are done so that was a heck of a lot of work so in

that was a heck of a lot of work so in the next lesson we're going to be

the next lesson we're going to be getting into how you can actually go

getting into how you can actually go through and share this dashboard

through and share this dashboard specifically for those that have a

specifically for those that have a Microsoft description you can use

Microsoft description you can use something like Microsoft online because

something like Microsoft online because it has all these features that we have

it has all these features that we have within here and host it there for others

within here and host it there for others to use additionally we're going to get

to use additionally we're going to get into my recommended method of sharing

into my recommended method of sharing any your projects and that's via linked

any your projects and that's via linked in now just a heads up we will be

in now just a heads up we will be getting into git and GitHub after

getting into git and GitHub after project 2 at the very end of this course

project 2 at the very end of this course and during that portion we'll talk about

and during that portion we'll talk about how to share not only project 2 but also

how to share not only project 2 but also this project here but that's more

this project here but that's more complicated and I really want to focus

complicated and I really want to focus on Excel so with that we're going to be

on Excel so with that we're going to be shifting in the next lesson to quickly

shifting in the next lesson to quickly share it and then moving into the

share it and then moving into the advanced chapter all right with that

advanced chapter all right with that I'll see you in the next

I'll see you in the next [Music]

one first up congratulations on completing your first project in Excel

completing your first project in Excel and building this salary dashboard been

and building this salary dashboard been nothing short of your hard work and you

nothing short of your hard work and you shouldn't let that hard work go

shouldn't let that hard work go unnoticed so in this lesson we're going

unnoticed so in this lesson we're going to be going over different methods you

to be going over different methods you could go about actually sharing this

could go about actually sharing this project to your social network and to

project to your social network and to others to help out in the job search or

others to help out in the job search or future employment now if you were just

future employment now if you were just learning these skills for fun you had no

learning these skills for fun you had no intent getting a new job or increasing

intent getting a new job or increasing your pay in your current job then you

your pay in your current job then you can feel free to skip this and go to the

can feel free to skip this and go to the next chapter on pivot

tables so there's a few different ways you can go about sharing your work that

you can go about sharing your work that you did we're not going to go dive into

you did we're not going to go dive into deep any of these we're going to look at

deep any of these we're going to look at these more at a high level before

these more at a high level before jumping into one of the options first up

jumping into one of the options first up is a portfolio website here I have luk

is a portfolio website here I have luk bru.com and if I wanted to I could come

bru.com and if I wanted to I could come inside of here and edit it and include

inside of here and edit it and include my project here along with what I did

my project here along with what I did for others to see another option even if

for others to see another option even if you don't have a big following on

you don't have a big following on YouTube is you could actually go in and

YouTube is you could actually go in and record and describe what you did within

record and describe what you did within your dashboard and host it somewhere

your dashboard and host it somewhere like YouTube now for both those options

like YouTube now for both those options you may be like Luke how do I actually

you may be like Luke how do I actually actually share my Excel file that

actually share my Excel file that actually went through well that's where

actually went through well that's where we run into a little bit of issues as as

we run into a little bit of issues as as yes we created this Excel file right

yes we created this Excel file right here but how do you actually go about

here but how do you actually go about sharing it with others to see your work

sharing it with others to see your work well one option for this is actually

well one option for this is actually hosting your file online via something

hosting your file online via something like one drive which if you're paying

like one drive which if you're paying for a subscription of Microsoft service

for a subscription of Microsoft service you have access to one drive and you can

you have access to one drive and you can host your dashboard online all I need to

host your dashboard online all I need to do is navigate to One drive. live.com go

do is navigate to One drive. live.com go to this add new and files upload from

to this add new and files upload from there select my file that I actually

there select my file that I actually want to upload online and then we can go

want to upload online and then we can go to it and our file is actually uploaded

to it and our file is actually uploaded here which we can actually go through

here which we can actually go through and select something like data

and select something like data scientists and it will actually

scientists and it will actually calculate based on the changes we make

calculate based on the changes we make to it now one note the country chart

to it now one note the country chart inside of excel online doesn't work but

inside of excel online doesn't work but I have a fix for it and mainly it's to

I have a fix for it and mainly it's to just remove it you go into the review

just remove it you go into the review tab under protection and go to manage

tab under protection and go to manage protection and then you turn off sheet

protection and then you turn off sheet protection then from there you can

protection then from there you can delete it next all you need to do is

delete it next all you need to do is just take those charts and actually

just take those charts and actually extend them over so way they take up

extend them over so way they take up that extra space and then once you're

that extra space and then once you're complete with that turn back on the

complete with that turn back on the sheet protection and now you can go

sheet protection and now you can go about actually sharing this so here I'm

about actually sharing this so here I'm coming into share and you can add an

coming into share and you can add an email if you want or if you just want to

email if you want or if you just want to share it in general with a link you can

share it in general with a link you can come down here and fine-tune the control

come down here and fine-tune the control of a link to provide in this case I'm

of a link to provide in this case I'm selecting that I'm going to share with

selecting that I'm going to share with anyone they can edit it you could make

anyone they can edit it you could make it view but then they can't change the

it view but then they can't change the dropdowns so I recommend that you still

dropdowns so I recommend that you still leave it on edit you could set an

leave it on edit you could set an expiration and even password and then

expiration and even password and then from there click apply and now you have

from there click apply and now you have a link to your dashboard that works even

a link to your dashboard that works even if you don't have a Microsoft account so

if you don't have a Microsoft account so here I am in incognito mode within my

here I am in incognito mode within my browser so I'm not signed in at all and

browser so I'm not signed in at all and I can actually go in and access this

I can actually go in and access this dashboard and go through and select

dashboard and go through and select something and it updates in real time

something and it updates in real time and because I got that sheet protection

and because I got that sheet protection on they can't go through and change

on they can't go through and change anything except for these dropdowns

anything except for these dropdowns don't believe me you can check out my

don't believe me you can check out my project via the link below but what

project via the link below but what happens if we want to not only maybe

happens if we want to not only maybe share our file but also write up what we

share our file but also write up what we did the work we did with this and all

did the work we did with this and all the different skills that we used well

the different skills that we used well that's the case of using something like

that's the case of using something like GitHub GitHub provides a location to

GitHub GitHub provides a location to store Excel files like shown here along

store Excel files like shown here along with giving you the ability to go

with giving you the ability to go through and perform a write up detailing

through and perform a write up detailing all the different work that you did now

all the different work that you did now if you wanted to see this you could just

if you wanted to see this you could just navigate over to my project where you

navigate over to my project where you download all these files from on GitHub

download all these files from on GitHub navigate into that project

navigate into that project one-board and in here has our Excel file

one-board and in here has our Excel file and also this read me which then appears

and also this read me which then appears actually underneath here and details all

actually underneath here and details all the different work that we did for this

the different work that we did for this now getting this project onto GitHub if

now getting this project onto GitHub if you're not familiar with GitHub up is

you're not familiar with GitHub up is fairly complex we're actually going to

fairly complex we're actually going to be saving this for after project 2 and

be saving this for after project 2 and in that case navigating back to the

in that case navigating back to the project itself we'll not only be

project itself we'll not only be uploading project one we'll also be

uploading project one we'll also be uploading project two as well so after

uploading project two as well so after we finish the last chapter chapter 8 on

we finish the last chapter chapter 8 on power pivot we'll be getting into all of

power pivot we'll be getting into all of this and you'll be learning more about

this and you'll be learning more about git GitHub and how to manage a

projects now from what I found working in data science it's that the best way

in data science it's that the best way to share your work and your project and

to share your work and your project and potentially collaborate with others is

potentially collaborate with others is use something like LinkedIn a social

use something like LinkedIn a social media platform for networking in order

media platform for networking in order to share your project specifically here

to share your project specifically here I am on my profile right here and if we

I am on my profile right here and if we scroll on down they have a section in

scroll on down they have a section in your profile to basically show all your

your profile to basically show all your different projects that you've worked on

different projects that you've worked on and contributed to and adding a project

and contributed to and adding a project is super simple I got to do is click

is super simple I got to do is click this plus icon include a description in

this plus icon include a description in my case I was trying to help out job

my case I was trying to help out job Seekers inves salaries for their desired

Seekers inves salaries for their desired jobs put in a few skills up to five of

jobs put in a few skills up to five of Microsoft Excel data analysis or Excel

Microsoft Excel data analysis or Excel dashboards now for media they do have

dashboards now for media they do have options to add a link or media in the

options to add a link or media in the case of the media it doesn't support

case of the media it doesn't support Excel files and then if you try to

Excel files and then if you try to insert your one Drive Link I ran into

insert your one Drive Link I ran into errors so I find the best way to

errors so I find the best way to actually just share the link is to post

actually just share the link is to post it inside of the description from there

it inside of the description from there specify when you start and stopped on

specify when you start and stopped on this project anybody that contributed to

this project anybody that contributed to it this or anything that is associated

it this or anything that is associated with and then from there click save the

with and then from there click save the other option that I recommend is

other option that I recommend is actually just going in and making a post

actually just going in and making a post here I just write up a short little

here I just write up a short little description of what you did with your

description of what you did with your project and then if you want include

project and then if you want include something like an image or even

something like an image or even something like a gif which shows an

something like a gif which shows an overview of the project and then

overview of the project and then probably the most important thing is

probably the most important thing is actually sharing that link to your one

actually sharing that link to your one drive online you can also Post in the

drive online you can also Post in the comments and not include in the

comments and not include in the description it's really up to you anyway

description it's really up to you anyway go through there and then post

go through there and then post so bam that's how you share your project

so bam that's how you share your project as a reminder we will be going into

as a reminder we will be going into greater detail into how to share both

greater detail into how to share both this project and also the second project

this project and also the second project on GitHub using git and also use things

on GitHub using git and also use things like markdown in order to write about

like markdown in order to write about your project but that'll be included

your project but that'll be included after we go through all of the different

after we go through all of the different Excel content just wanted to have a

Excel content just wanted to have a quick way of you going through and

quick way of you going through and actually sharing what you've done so far

actually sharing what you've done so far cuz I know you're probably excited and

cuz I know you're probably excited and proud of it all right in the next videos

proud of it all right in the next videos we're going to be shifting gear into the

we're going to be shifting gear into the advanced chapters getting starting off

advanced chapters getting starting off first with pivot tables with that I'll

first with pivot tables with that I'll see you in

there all right welcome to the advanced chapter and because we're get into the

chapter and because we're get into the advanced section you know it's time for

advanced section you know it's time for a new

a new flannel and with this Advanced chapter

flannel and with this Advanced chapter we're going to be focusing on a few core

we're going to be focusing on a few core topics that I think is going to make

topics that I think is going to make your life a lot easier specifically

your life a lot easier specifically we're f focus on things like pivot

we're f focus on things like pivot tables power query and also power pivot

tables power query and also power pivot all of these are great at automating my

all of these are great at automating my Excel workflows to make it a lot easier

Excel workflows to make it a lot easier to do repetitive analytics that my boss

to do repetitive analytics that my boss may come to me back and back again for

may come to me back and back again for instead of with something like a formula

instead of with something like a formula where I have to go through and make and

where I have to go through and make and copy and paste that formula all over

copy and paste that formula all over again and rerun that whole analysis

again and rerun that whole analysis these Advanced chapters are going to

these Advanced chapters are going to make your life a lot easier anyway in

make your life a lot easier anyway in this chapter we're going to be focused

this chapter we're going to be focused on pivot tables this lesson specifically

on pivot tables this lesson specifically will be getting an intro into pivot

will be getting an intro into pivot tables how to make them how to

tables how to make them how to manipulate them how to even read them in

manipulate them how to even read them in the next lesson we'll be going into

the next lesson we'll be going into advanced pivot tables looking at things

advanced pivot tables looking at things like grouping and even aggregating such

like grouping and even aggregating such as getting percentages of grand totals

as getting percentages of grand totals and whatnot and then the final lesson in

and whatnot and then the final lesson in this chapter is on pivot charts which

this chapter is on pivot charts which allows us to basically take what we have

allows us to basically take what we have in our pivot tables and convert it into

in our pivot tables and convert it into a usable chart hence the name pivot

a usable chart hence the name pivot chart all right so let's actually get

chart all right so let's actually get into it and understanding why these

into it and understanding why these pivot tables are so

important so in the basics chapter we made this table right here which uses

made this table right here which uses hardcoded values for the different job

hardcoded values for the different job titles along with the different months

titles along with the different months and then from there uses formulas

and then from there uses formulas specifically some product along with

specifically some product along with some array calculations in order to

some array calculations in order to calculate how many job counts per month

calculate how many job counts per month this is cool and all but what happens if

this is cool and all but what happens if we wanted to add another job title so

we wanted to add another job title so say we have like some like business

say we have like some like business analyst or we have software developer

analyst or we have software developer we'd have to actually manipulate and

we'd have to actually manipulate and upgrade all these different formulas

upgrade all these different formulas that we have here well here's that same

that we have here well here's that same table but in a pivot table and by its

table but in a pivot table and by its name that's what they're great at

name that's what they're great at they're great at pivoting and thus

they're great at pivoting and thus aggregating data based on certain values

aggregating data based on certain values and whatnot so what is if we want to add

and whatnot so what is if we want to add more job title this well I can just come

more job title this well I can just come in here similar to how we manipulate a

in here similar to how we manipulate a table select this filter dropdown and

table select this filter dropdown and then go from there and select things

then go from there and select things like oh I want to include something like

like oh I want to include something like a business analyst and then the data

a business analyst and then the data automatically updates for this no

automatically updates for this no readjusting formulas makes it super

readjusting formulas makes it super simple I can even take this table a step

simple I can even take this table a step further and if I wanted to I can

further and if I wanted to I can actually filter by the job country in

actually filter by the job country in this case I'm filtering by the United

this case I'm filtering by the United States and we now have these values

States and we now have these values makes it super simple anyway we're

makes it super simple anyway we're getting ahead of ourselves we actually

getting ahead of ourselves we actually need to get into creating our first

need to get into creating our first pivot

table all right so for the advanced chapters it's going to be a little bit

chapters it's going to be a little bit different for what files you're going to

different for what files you're going to use for this the final results of this

use for this the final results of this lesson will be in the lesson title of

lesson will be in the lesson title of pivot table intro but what I want you to

pivot table intro but what I want you to do whenever you're going through or

do whenever you're going through or following me along in this lesson is

following me along in this lesson is actually revert back to the previous

actually revert back to the previous file of the last lesson in this case or

file of the last lesson in this case or the first lesson so we don't have one so

the first lesson so we don't have one so I have this one called zero of just

I have this one called zero of just pivot tables that's the one you want to

pivot tables that's the one you want to start with so in this case pivot tables

start with so in this case pivot tables itself just has the data tab of the data

itself just has the data tab of the data we want to work with and this sheet of

we want to work with and this sheet of the table that we've been familiar with

the table that we've been familiar with in Basics chapter which by the end of

in Basics chapter which by the end of this we're going to make a pivot table

this we're going to make a pivot table out of and when out of I mean actually

out of and when out of I mean actually of the core data itself anyway for the

of the core data itself anyway for the actual pivot table intro this will have

actual pivot table intro this will have also those similar tabs but then also

also those similar tabs but then also the lesson itself will have all the

the lesson itself will have all the different work that we've actually done

different work that we've actually done to complete what we need to do so feel

to complete what we need to do so feel free to just have both of these up

free to just have both of these up during a lesson so that way you can

during a lesson so that way you can consult back and forth in case you get

consult back and forth in case you get lost all right so let's get into our

lost all right so let's get into our first pivot table we're going to be

first pivot table we're going to be using the data that we previous been

using the data that we previous been using of all the salary data for those

using of all the salary data for those job titles anyway if I go into the

job titles anyway if I go into the insert tab up here in the top left hand

insert tab up here in the top left hand corner I have pivot tables but I also

corner I have pivot tables but I also have recommended pivot tables if I don't

have recommended pivot tables if I don't have an analysis in mind I could come

have an analysis in mind I could come into recommended pivot tables a Pan's

into recommended pivot tables a Pan's going to appear on the right hand side

going to appear on the right hand side and notice here that it actually

and notice here that it actually selected the data range I know that's

selected the data range I know that's the data range and it goes through and

the data range and it goes through and provides some recommended different

provides some recommended different pivot tables that you could put into

pivot tables that you could put into here whether you put it into a new sheet

here whether you put it into a new sheet or an existing sheet but I know what

or an existing sheet but I know what analysis I want to do specifically I

analysis I want to do specifically I want to do a count of the different job

want to do a count of the different job titles so data engineer I want to find

titles so data engineer I want to find the accounts of this senior data analyst

the accounts of this senior data analyst and so on right now it's not providing

and so on right now it's not providing any of that I don't typically find that

any of that I don't typically find that any time with recommended pivot tables

any time with recommended pivot tables that it provides me what I want so I

that it provides me what I want so I don't find myself using that often

don't find myself using that often instead I go directly into pivot tables

instead I go directly into pivot tables right here and then we have three

right here and then we have three options but we're really going to focus

options but we're really going to focus for this lesson and this chapter is from

for this lesson and this chapter is from table or range I'm selected inside of A4

table or range I'm selected inside of A4 right now but it automatically knows

right now but it automatically knows that this is the data range all the way

that this is the data range all the way down to the bottom the other thing it

down to the bottom the other thing it says is choose where you want the pivot

says is choose where you want the pivot tail to place you can either do a new

tail to place you can either do a new worksheet or you can do inside the

worksheet or you can do inside the existing worksheet but you have to

existing worksheet but you have to specify a location we don't want that I

specify a location we don't want that I typically like it in a new worksheet to

typically like it in a new worksheet to keep my analysis in one standard

keep my analysis in one standard location the last thing it asked is

location the last thing it asked is whether you want to analyze multiple

whether you want to analyze multiple tables specifically add this to the data

tables specifically add this to the data model we're going to be going into Data

model we're going to be going into Data models very heavily in the power pivot

models very heavily in the power pivot chapter or chapter eight or last chapter

chapter or chapter eight or last chapter this is a super powerful feature when

this is a super powerful feature when you have multiple tables you need to

you have multiple tables you need to combine it we're not doing it in this

combine it we're not doing it in this lesson or in this chapter so we're going

lesson or in this chapter so we're going to leave it unchecked so now I'm in this

to leave it unchecked so now I'm in this new sheet that I'm going to rename to

new sheet that I'm going to rename to job count and I'm also going to move it

job count and I'm also going to move it over here to the end anyway this pivot

over here to the end anyway this pivot table this pivot table 2 that is calling

table this pivot table 2 that is calling it is there's nothing in it right now

it is there's nothing in it right now and you notice there's a few things that

and you notice there's a few things that popped up first is the pivot table

popped up first is the pivot table analyze tab which is available with this

analyze tab which is available with this and also the design tab we'll be going

and also the design tab we'll be going into these in some upcoming examples

into these in some upcoming examples that we're going to get into we're

that we're going to get into we're however going to be focusing on for this

however going to be focusing on for this example example on the job count I'm

example example on the job count I'm going to close this out on this pivot

going to close this out on this pivot tabl Fields pane right here now the

tabl Fields pane right here now the layout of this you may see it's somewhat

layout of this you may see it's somewhat different is we have the columns over

different is we have the columns over here on the left so if you remember the

here on the left so if you remember the job tile short column job tile column

job tile short column job tile column job location and then these fields on

job location and then these fields on the right hand side are things for like

the right hand side are things for like filters row columns or values so I can

filters row columns or values so I can take the job title short column put into

take the job title short column put into something like the rows and get

something like the rows and get basically all the values in the rows now

basically all the values in the rows now your layout may be a little bit

your layout may be a little bit different if you come up and select the

different if you come up and select the tools icon right here you may be under

tools icon right here you may be under this Field section and area section

this Field section and area section stacked which has the feels down here on

stacked which has the feels down here on the bottom I personally don't really

the bottom I personally don't really like this because look how short my

like this because look how short my column titles are so I like having them

column titles are so I like having them like this instead anyway I think we

like this instead anyway I think we understand this columns area right here

understand this columns area right here but I don't think we understand these

but I don't think we understand these filters rows columns and values so let's

filters rows columns and values so let's explore this by calculating the counts

explore this by calculating the counts of these different job titles now

of these different job titles now anytime I add something to the rows or

anytime I add something to the rows or any of these columns I can either remove

any of these columns I can either remove it by grabbing it and pulling it off

it by grabbing it and pulling it off notice they have the x mark on it or

notice they have the x mark on it or similarly I can also just come in here

similarly I can also just come in here and click the uncheck Mark box that's

and click the uncheck Mark box that's more applicable if especially for having

more applicable if especially for having it in multiple different panes and want

it in multiple different panes and want to move it completely makes it simple

to move it completely makes it simple besides rows we also have columns and so

besides rows we also have columns and so instead of the job titles being in rows

instead of the job titles being in rows they're in the different columns I don't

they're in the different columns I don't really like this too much I typically

really like this too much I typically find myself using rows so we're trying

find myself using rows so we're trying to calculate what is the count of these

to calculate what is the count of these job title shorts so I'm just going to

job title shorts so I'm just going to take that job title short again and put

take that job title short again and put it into the values and it automatically

it into the values and it automatically Aggregates this by counts of that but

Aggregates this by counts of that but what happens if I don't want to do that

what happens if I don't want to do that count aggregation well one way is to

count aggregation well one way is to come back into that values right here

come back into that values right here and I'm going to just click it not right

and I'm going to just click it not right click it just normal click it and then

click it just normal click it and then go into value field settings and this

go into value field settings and this pop-up is going to come up first up is

pop-up is going to come up first up is the name of the column itself I actually

the name of the column itself I actually don't like this for of a name I'm just

don't like this for of a name I'm just going to rename this to job count under

going to rename this to job count under here under the summarized values by tab

here under the summarized values by tab you can select a lot of different

you can select a lot of different aggregation methods we're going to stay

aggregation methods we're going to stay with count you can also change how you

with count you can also change how you show value as basically if we wanted to

show value as basically if we wanted to do a percentage of some total or not

do a percentage of some total or not we're going to be jumping that in the

we're going to be jumping that in the advaned lesson so stand by for that the

advaned lesson so stand by for that the last thing to note with this is the

last thing to note with this is the number format so I can come in here and

number format so I can come in here and actually select in our case we have

actually select in our case we have thousand values so I like to use a th

thousand values so I like to use a th separator along with zero decimal places

separator along with zero decimal places and then clicking okay to apply this all

and then clicking okay to apply this all it updates the formatting and the name

it updates the formatting and the name so we've going over rows columns and

so we've going over rows columns and values what happens if we want to then

values what happens if we want to then filter let's say for only United States

filter let's say for only United States jobs well I could drag something like

jobs well I could drag something like the job country column into filters and

the job country column into filters and right now it's selecting all you have

right now it's selecting all you have you see this pan come up right here and

you see this pan come up right here and from there here I can actually go

from there here I can actually go through and select something like the

through and select something like the United States click okay and now the

United States click okay and now the values as you can see they reduced and

values as you can see they reduced and are only United States value other type

are only United States value other type of filterings I can do I can filter the

of filterings I can do I can filter the row itself so if I wanted to I could

row itself so if I wanted to I could select the different job titles that I

select the different job titles that I want to appear in this and click apply I

want to appear in this and click apply I could also do something where let's say

could also do something where let's say I wanted only job title so we're going

I wanted only job title so we're going to do a label filter and jobs that

to do a label filter and jobs that contain the word data so I could just

contain the word data so I could just type in here

type in here data and whenever I filter it I get all

data and whenever I filter it I get all the different jobs that contain data

the different jobs that contain data similarly I could also filter by this

similarly I could also filter by this job count here and that's by the values

job count here and that's by the values filter so I'm going to remove this label

filter so I'm going to remove this label filters to start with and we can go back

filters to start with and we can go back in here in the values filter and we

in here in the values filter and we could do something like hey we want to

could do something like hey we want to get jobs that are only greater than

get jobs that are only greater than let's see here Cloud Engineers 33 I

let's see here Cloud Engineers 33 I don't want to see that anymore I get to

don't want to see that anymore I get to greater than 100 and it filters down but

greater than 100 and it filters down but we're not going to use any filters right

we're not going to use any filters right now so I'm going to one clear this

now so I'm going to one clear this filter for the table and then also

filter for the table and then also remove this filter from filtering for

remove this filter from filtering for the United

States so let's get into taking this analysis of step further and we're going

analysis of step further and we're going to want to now analyze the average

to want to now analyze the average salary of these different job titles

salary of these different job titles while we're going through this we're

while we're going through this we're also going to be exploring the pivot

also going to be exploring the pivot table analyze tab so a quick tour of

table analyze tab so a quick tour of this tab first up over here on the left

this tab first up over here on the left is Pivot tables if I wanted to I could

is Pivot tables if I wanted to I could go through and rename this i' probably

go through and rename this i' probably name this typically something similar to

name this typically something similar to what is my sheet name itself this case I

what is my sheet name itself this case I named it job count additionally inside

named it job count additionally inside of here we have options which allows us

of here we have options which allows us to do a lot of detailed control of how

to do a lot of detailed control of how we're building our pivot tables it's a

we're building our pivot tables it's a very Advanced feature I don't find

very Advanced feature I don't find myself going into it quite often unless

myself going into it quite often unless I need to fine-tune the functionality of

I need to fine-tune the functionality of it active field so that tells us

it active field so that tells us basically what's the active field

basically what's the active field grouping is something we're going to go

grouping is something we're going to go into in the next lesson we actually go

into in the next lesson we actually go and Performing groups of different job

and Performing groups of different job titles slicers and timelines we're going

titles slicers and timelines we're going to be going into the last lesson on

to be going into the last lesson on pivot charts in order to basically use

pivot charts in order to basically use these slicers and timelines to filter

these slicers and timelines to filter data section is used to control our data

data section is used to control our data so I can click something like refresh or

so I can click something like refresh or refresh all it's going to refresh the

refresh all it's going to refresh the data that we have so in this case

data that we have so in this case remember business analyst is around

remember business analyst is around 1,1 so if I go back to our data itself

1,1 so if I go back to our data itself and I find this entry on business

and I find this entry on business analyst and then and let's say that

analyst and then and let's say that that's not correct and I delete that out

that's not correct and I delete that out of there whenever I come back to this

of there whenever I come back to this table itself it still says

table itself it still says 1,1 what I have to do is well we've

1,1 what I have to do is well we've updated the data so I have to well

updated the data so I have to well refresh it now that I refreshed it it's

refresh it now that I refreshed it it's down to 1,000 I actually don't want to

down to 1,000 I actually don't want to remove that entry so I'm going to just

remove that entry so I'm going to just press contrl Z and bring that right back

press contrl Z and bring that right back and then also click refresh to make sure

and then also click refresh to make sure it's up to date if I want to change the

it's up to date if I want to change the data source or maybe the range I could

data source or maybe the range I could go into something like this of change

go into something like this of change data source actions allow us to clear

data source actions allow us to clear select and even move a pivot table for

select and even move a pivot table for calculations they have things like

calculations they have things like calculated fields and items but we're

calculated fields and items but we're going to get into measures and I feel

going to get into measures and I feel they're way more powerful so we're not

they're way more powerful so we're not going to cover this much the last thing

going to cover this much the last thing to cover with this is over here on the

to cover with this is over here on the right hand side is the show sometimes

right hand side is the show sometimes whenever you're navigating you'll click

whenever you're navigating you'll click into your pivot table and that pivot

into your pivot table and that pivot table Fields pane won't pop up you can

table Fields pane won't pop up you can also pan it on and off by clicking this

also pan it on and off by clicking this field list and if you didn't want

field list and if you didn't want something like row labels at the top you

something like row labels at the top you could just remove the field headers as

could just remove the field headers as well so getting into that actual

well so getting into that actual analysis we want to analyze the salary

analysis we want to analyze the salary year average what is the average value

year average what is the average value now I can't see all the different values

now I can't see all the different values selected in here so I'm going to

selected in here so I'm going to actually going to go ahead and close

actually going to go ahead and close this paint up here to have a bigger view

this paint up here to have a bigger view anyway what it did was it did a sum of

anyway what it did was it did a sum of the salary year average we don't really

the salary year average we don't really want that we want to go to average and

want that we want to go to average and I'll change this column name to to

I'll change this column name to to average yearly salary now if you've been

average yearly salary now if you've been following along since the basic chapter

following along since the basic chapter you probably know that I prefer me

you probably know that I prefer me performing a median for this salary data

performing a median for this salary data over an average but if you actually go

over an average but if you actually go through this there's no median value for

through this there's no median value for this that doesn't mean you can't do

this that doesn't mean you can't do median in pivot tables you actually can

median in pivot tables you actually can you can actually do even more advanced

you can actually do even more advanced stuff which we're going to get to in

stuff which we're going to get to in chapter 8 and power pivot but for now

chapter 8 and power pivot but for now we're just going to stick to only

we're just going to stick to only performing average for this I'm going to

performing average for this I'm going to click okay so the formatting on this is

click okay so the formatting on this is all jacked up and we could go into that

all jacked up and we could go into that field settings and adjust that or I can

field settings and adjust that or I can actually go in as long as I have all the

actually go in as long as I have all the values selected here I can select hey I

values selected here I can select hey I want to convert this to a currency and

want to convert this to a currency and that I don't want any decimal places and

that I don't want any decimal places and it's going to format all the values and

it's going to format all the values and I feel this is a little bit easier

I feel this is a little bit easier because now actually if you go back and

because now actually if you go back and in exploring the value field settings

in exploring the value field settings inside of number format it actually

inside of number format it actually applied this custom formatting for me so

applied this custom formatting for me so it knows to apply that since I applied

it knows to apply that since I applied it to all the values that were visible

it to all the values that were visible now since this is so easy I could also

now since this is so easy I could also do something like get the average of the

do something like get the average of the hourly salary once again it's doing the

hourly salary once again it's doing the sum of that and I don't want that I want

sum of that and I don't want that I want the average itself and I can change that

the average itself and I can change that column Name by just going in here and

column Name by just going in here and typing in average hourly salary

typing in average hourly salary inspecting the value field setting it

inspecting the value field setting it also updates inside of here and I'm

also updates inside of here and I'm going to go ahead and adjust the

going to go ahead and adjust the formatting as well changes to a currency

formatting as well changes to a currency with two decimal

places so let's get into actually cleaning how this table looks up and we

cleaning how this table looks up and we can go and do this by going into the

can go and do this by going into the design tab now I'm going to start over

design tab now I'm going to start over here on the right in pivot table Styles

here on the right in pivot table Styles and we can actually change what it may

and we can actually change what it may look like in this case I sort of like

look like in this case I sort of like this one right here the simplistic look

this one right here the simplistic look I can also change things like column

I can also change things like column headers which I like the formatting on

headers which I like the formatting on it or whether I want banded rows or

it or whether I want banded rows or banded columns in my case I kind of like

banded columns in my case I kind of like the banded rows we'll go with that last

the banded rows we'll go with that last portion is around the layout if you

portion is around the layout if you notice down here we have this grand

notice down here we have this grand total over here this is a grand total

total over here this is a grand total based on well the column values it's

based on well the column values it's adding up all the values in the column

adding up all the values in the column so this is on for the column so if I

so this is on for the column so if I wanted to turn it off for rows and

wanted to turn it off for rows and columns I could come up here and

columns I could come up here and actually do that I kind of like this so

actually do that I kind of like this so we're going to leave it on I could also

we're going to leave it on I could also turn on on for the rows and columns but

turn on on for the rows and columns but in this case because we're doing

in this case because we're doing different aggregation method so a count

different aggregation method so a count here and an average here it's not

here and an average here it's not necessarily going to do anything over

necessarily going to do anything over here for the row grand total whereas for

here for the row grand total whereas for something like the columns gram total

something like the columns gram total that knows that hey for a job count I

that knows that hey for a job count I probably need the total count for the

probably need the total count for the average I probably need an average and

average I probably need an average and that's what it does for both of these

that's what it does for both of these there's some additional ones up here on

there's some additional ones up here on adjusting the report layout adjusting

adjusting the report layout adjusting for blank rolls and then also subtitles

for blank rolls and then also subtitles we'll be exploring that as we go along

we'll be exploring that as we go along as we build out more complex pivot

as we build out more complex pivot tables

so let's now get into that final analysis and we're going to be creating

analysis and we're going to be creating basically this pivot table that we did

basically this pivot table that we did previously with formulas and functions

previously with formulas and functions so what we'll need to do or think of

so what we'll need to do or think of right we're going to need the job title

right we're going to need the job title short in the rows and we're going to

short in the rows and we're going to need the month the job posted months in

need the month the job posted months in the columns and then we'll need to

the columns and then we'll need to aggregate this by count for the values

aggregate this by count for the values now I can navigate back to the data Tab

now I can navigate back to the data Tab and once again go to insert pivot table

and once again go to insert pivot table if you notice here it says from table or

if you notice here it says from table or range so that's the really good thing if

range so that's the really good thing if we actually convert this to a table

we actually convert this to a table we'll now be able to once we do this

we'll now be able to once we do this press okay and rename this to something

press okay and rename this to something like jobs now we can really be anywhere

like jobs now we can really be anywhere in this workbook in this case I created

in this workbook in this case I created a new sheet I go hey insert from table

a new sheet I go hey insert from table arrange specifically I want to do a

arrange specifically I want to do a table of jobs and we want to do this

table of jobs and we want to do this existing worksheet in A1 and all the

existing worksheet in A1 and all the values from that jobs table are now here

values from that jobs table are now here so we know we need the job title short

so we know we need the job title short along the rows but then we need the job

along the rows but then we need the job posted month across the top which right

posted month across the top which right now we have a date we could put the date

now we have a date we could put the date into the columns but we get this air

into the columns but we get this air Message hey you cannot place a field

Message hey you cannot place a field that has more than well 16,000 different

that has more than well 16,000 different values for it so we're not going to do

values for it so we're not going to do that also before we forget I'm going to

that also before we forget I'm going to rename the sheet to monthly count anyway

rename the sheet to monthly count anyway we need a monthly value here so what

we need a monthly value here so what going to have to do is good thing about

going to have to do is good thing about the table itself is now that we've

the table itself is now that we've created this as a table I know next to

created this as a table I know next to this job posted date colum I want to

this job posted date colum I want to insert in a column called job posted

insert in a column called job posted month and for this we'll just use that

month and for this we'll just use that text function that we already know using

text function that we already know using the value of job posted date and then

the value of job posted date and then for the format we know we want three

for the format we know we want three lowercase M to get the month itself it's

lowercase M to get the month itself it's going to fill all the way down okay so

going to fill all the way down okay so now we have job posted month going back

now we have job posted month going back to our pivot table itself remember we're

to our pivot table itself remember we're not going to see job posted month in

not going to see job posted month in here until we actually go back into

here until we actually go back into pivot table to analyze and click

pivot table to analyze and click refresh now job posted month is inside

refresh now job posted month is inside of here and conveniently it's also in

of here and conveniently it's also in the correct order now this thing is

the correct order now this thing is completely blank right now we need to

completely blank right now we need to actually add what values we want so I'm

actually add what values we want so I'm going to drag job title short into

going to drag job title short into values and it's going to do a count

values and it's going to do a count notice here we do have column value Val

notice here we do have column value Val which go up and down and then the row

which go up and down and then the row values itself so we can see what the

values itself so we can see what the count of business analyst is around 101

count of business analyst is around 101 I'm not really a fan of these things

I'm not really a fan of these things that say row and column labels I'm going

that say row and column labels I'm going so I'm going to toggle off field headers

so I'm going to toggle off field headers to make this look a little bit better

to make this look a little bit better and I'm also going to change the name of

and I'm also going to change the name of this to monthly job count so bam this is

this to monthly job count so bam this is looking good and we compare it to our

looking good and we compare it to our basically non-pa table just to make sure

basically non-pa table just to make sure that our values are correct we can see

that our values are correct we can see we have 982 for data analyst come over

we have 982 for data analyst come over over to data analyst we have 982 all the

over to data analyst we have 982 all the last thing we want to do is actually

last thing we want to do is actually filter this down and better sort our

filter this down and better sort our values specifically I'm curious about

values specifically I'm curious about roles in the United States so I'm going

roles in the United States so I'm going to drag that job country over here and

to drag that job country over here and select United States from here to apply

select United States from here to apply to it additionally I care about the most

to it additionally I care about the most important jobs at the top and the least

important jobs at the top and the least important at the bottom mainly by this

important at the bottom mainly by this grand total right here and so what I can

grand total right here and so what I can do is I can sort it by the grand total

do is I can sort it by the grand total but if you notice I remove that that

but if you notice I remove that that filter button right here whenever I

filter button right here whenever I actually remove the field headers so I

actually remove the field headers so I can also go in Instead rightclick This

can also go in Instead rightclick This Grand the value inside of grand total

Grand the value inside of grand total and I can say sort from in our case

and I can say sort from in our case largest to smallest so I feel like that

largest to smallest so I feel like that makes it a lot more convenient alsoo

makes it a lot more convenient alsoo sort additionally I'm noticing the

sort additionally I'm noticing the formatting isn't correct for this I'm

formatting isn't correct for this I'm going to put in that comma separator and

going to put in that comma separator and then remove the two decimal places

then remove the two decimal places similarly not only did we sort by the

similarly not only did we sort by the grand total let's say I only wanted

grand total let's say I only wanted maybe the top six of these right here I

maybe the top six of these right here I could rightclick any of these job titles

could rightclick any of these job titles right here and then go into filter in

right here and then go into filter in this case I'm going to go top 10 instead

this case I'm going to go top 10 instead I'm going to select top six press okay

I'm going to select top six press okay now that we have this all sorted I can

now that we have this all sorted I can once again go into that design tab

once again go into that design tab change the grand totals we're going to

change the grand totals we're going to turn it on for columns only and Bam now

turn it on for columns only and Bam now we have basically the same pivot table

we have basically the same pivot table that we had before with our values or

that we had before with our values or using formulas but instead now with

using formulas but instead now with pivot tables and this is a lot more

pivot tables and this is a lot more customizable all right all right it's

customizable all right all right it's your turn now to get your hands dirty

your turn now to get your hands dirty with some practice problems and

with some practice problems and exploring how to make some different

exploring how to make some different pivot tables in the next lesson we're

pivot tables in the next lesson we're going to go deeper with pivot tables

going to go deeper with pivot tables looking at things like grouping

looking at things like grouping hierarchy and how we can show different

hierarchy and how we can show different values as with that I'll see you in the

values as with that I'll see you in the next

one so let's get into some Advanced pivot table features and for this lesson

pivot table features and for this lesson and actually for everything in advanced

and actually for everything in advanced chapter we're going to be sticking with

chapter we're going to be sticking with that salary data set of over 30,000 rows

that salary data set of over 30,000 rows in order to actually analyze for this so

in order to actually analyze for this so I'm not going to be calling it out

I'm not going to be calling it out really any further into other lessons or

really any further into other lessons or chapters the first thing we're going to

chapters the first thing we're going to focus on is hierarchy which allows us to

focus on is hierarchy which allows us to look at things like we want to aggregate

look at things like we want to aggregate not only the job title itself but also

not only the job title itself but also by the country so what job titles are

by the country so what job titles are within a country and then look at

within a country and then look at specific values there for say like the

specific values there for say like the salary next we're going to move into

salary next we're going to move into grouping focusing first on automatic

grouping focusing first on automatic grouping basically using that job posted

grouping basically using that job posted date column to automatically aggregate

date column to automatically aggregate by year month and whatnot and from there

by year month and whatnot and from there we'll then shift into some manual

we'll then shift into some manual grouping we'll be able to create groups

grouping we'll be able to create groups of different job titles and basically

of different job titles and basically break out whether we want to look at

break out whether we want to look at maybe senior roles such as senior data

maybe senior roles such as senior data analyst senior data engineers and

analyst senior data engineers and compare them to just normal data nerd

compare them to just normal data nerd roles such as data analyst or data

roles such as data analyst or data Engineers with this we're also going to

Engineers with this we're also going to dive deep into understanding a deeper

dive deep into understanding a deeper method to analyze maybe percentages of

method to analyze maybe percentages of totals or percentages of grand totals

totals or percentages of grand totals when analyzing these type of groups for

when analyzing these type of groups for this you can continue working with that

this you can continue working with that workbook you were working with on the

workbook you were working with on the last lesson if you've did everything you

last lesson if you've did everything you did there or you can just open the pivot

did there or you can just open the pivot table intro for this lesson once again

table intro for this lesson once again as a reminder the solution is going to

as a reminder the solution is going to be in pivot table Advanced we don't want

be in pivot table Advanced we don't want to open that just yet because it could

to open that just yet because it could mess up what we're doing here if I could

mess up what we're doing here if I could it is so we have four different sheets

it is so we have four different sheets that we cre created with this I only

that we cre created with this I only really care about the data tab right now

really care about the data tab right now so I'm actually going to select all

so I'm actually going to select all these other ones by holding control and

these other ones by holding control and then right clicking it to hi

them so let's actually look what a hierarchy actually creates I'm going to

hierarchy actually creates I'm going to go in and insert a pivot table from

go in and insert a pivot table from table arrange remember we're using that

table arrange remember we're using that table of jobs you should have named the

table of jobs you should have named the table that in order for this to work and

table that in order for this to work and we're going to insert it in a new

we're going to insert it in a new worksheet I'm going to move this over

worksheet I'm going to move this over and I'm also going to create uh call

and I'm also going to create uh call this sheet hierarchy so for this we want

this sheet hierarchy so for this we want to look at the salaries for job titles

to look at the salaries for job titles in a certain country so we're going to

in a certain country so we're going to start by dragging that job country over

start by dragging that job country over to Rose and right now there's no

to Rose and right now there's no hierarchy but if I drag job title short

hierarchy but if I drag job title short into the rows as well when we close this

into the rows as well when we close this tab up here we can see that now we have

tab up here we can see that now we have two values in here and how we have

two values in here and how we have values underneath here we've now created

values underneath here we've now created a hierarchy so Albania is basically the

a hierarchy so Albania is basically the parent or the top of this and then we

parent or the top of this and then we have data analyst data scientist senior

have data analyst data scientist senior data scientist notice there's only three

data scientist notice there's only three values here and that's because an

values here and that's because an Albania sort of a smaller country they

Albania sort of a smaller country they only have three types of jobs there at

only have three types of jobs there at least in the data set now we want to

least in the data set now we want to look at salary for this so I'm going to

look at salary for this so I'm going to drag the salary your average into the

drag the salary your average into the values it's going to do a sum once again

values it's going to do a sum once again going into value field settings I'm

going into value field settings I'm going to change this to average rename

going to change this to average rename the title to salary year average and

the title to salary year average and then changing the number format to

then changing the number format to currency with zero decimal places

currency with zero decimal places pressing okay for all this bam now I'm

pressing okay for all this bam now I'm also curious by this how many jobs we

also curious by this how many jobs we actually have with a salary value this

actually have with a salary value this just sort of an add-on so I'm going to

just sort of an add-on so I'm going to drag that salary year average over going

drag that salary year average over going into the value field settings I'm going

into the value field settings I'm going to do a count of this and we'll call

to do a count of this and we'll call this job count click okay so now we get

this job count click okay so now we get more of a relative idea of how many jobs

more of a relative idea of how many jobs are so in Albania we have well only five

are so in Albania we have well only five job postings so now I want to get into

job postings so now I want to get into actually seeing what countries have the

actually seeing what countries have the highest pay now as a refresher you can

highest pay now as a refresher you can come in here and select the dropdown and

come in here and select the dropdown and we could either select how we're going

we could either select how we're going to filter the row labels or filter the

to filter the row labels or filter the value labels but remember we want to

value labels but remember we want to sort them and right now this is only the

sort them and right now this is only the or option to sort a toz or Za to a for

or option to sort a toz or Za to a for those row labels instead I can just

those row labels instead I can just click make sure I'm clicking the Sal

click make sure I'm clicking the Sal your average because that's where I care

your average because that's where I care about I can rightclick it and from there

about I can rightclick it and from there go to sort in this case sort large just

go to sort in this case sort large just the smallest and what it did is it

the smallest and what it did is it sorted the values well within each of

sorted the values well within each of these it still kept this kept the

these it still kept this kept the countries in alphabetic order instead

countries in alphabetic order instead what I can do is Select this cell for

what I can do is Select this cell for the countries because I want to sort the

the countries because I want to sort the country's highest to lowest and then I

country's highest to lowest and then I can sort largest to smallest as well now

can sort largest to smallest as well now this is pretty neat because now we can

this is pretty neat because now we can see things like Belarus Russia Bahamas I

see things like Belarus Russia Bahamas I got to go down there have some of the

got to go down there have some of the highest salaries by country and then

highest salaries by country and then what those are based on the different

what those are based on the different job titles there now some sometimes I

job titles there now some sometimes I find reading this somewhat difficult in

find reading this somewhat difficult in this manner that it's laid out here I'm

this manner that it's laid out here I'm going to show you how you can actually

going to show you how you can actually change this so going back into the

change this so going back into the design tab remember we had this reports

design tab remember we had this reports layout that we sort of breezed over last

layout that we sort of breezed over last right now it's in this show in compact

right now it's in this show in compact form we can actually change this to

form we can actually change this to something like show in outline form and

something like show in outline form and it will basically shift this over and

it will basically shift this over and have this hierarchy basically in two

have this hierarchy basically in two separate columns it also makes it nice

separate columns it also makes it nice that you can actually a little bit

that you can actually a little bit easier to sort with another method is

easier to sort with another method is show in tabular form so now it basically

show in tabular form so now it basically crunches it up and I actually like this

crunches it up and I actually like this one even better and it's still breaking

one even better and it's still breaking out the job country and job title short

out the job country and job title short into two different columns but now it's

into two different columns but now it's actually aggregated to less line so I

actually aggregated to less line so I can actually see more data on here now

can actually see more data on here now this is definitely a form that I'd like

this is definitely a form that I'd like if I want to hand over on boss and even

if I want to hand over on boss and even if I wanted to convert this even further

if I wanted to convert this even further to what is this repeat all item labels

to what is this repeat all item labels so now I could if I wanted to actually

so now I could if I wanted to actually copy and paste this into its own table

copy and paste this into its own table and analyze further at least now I have

and analyze further at least now I have like Bahamas with the software data

like Bahamas with the software data engineer not software data engineer I

engineer not software data engineer I mean software engineer or senior data

mean software engineer or senior data engineer anyway you may have noticed

engineer anyway you may have noticed there are some blank values in here and

there are some blank values in here and that's because it has an Associated

that's because it has an Associated hourly salary but not yearly what i'

hourly salary but not yearly what i' need to do is actually apply a value

need to do is actually apply a value filter because it's a value so I come in

filter because it's a value so I come in here and click to drop down go to Value

here and click to drop down go to Value F filters and then maybe put something

F filters and then maybe put something like greater than we'll put zero and now

like greater than we'll put zero and now those values will

disappear next analysis we're going to do is a count by the job month but we're

do is a count by the job month but we're not going to use the this job posted

not going to use the this job posted month column that we created in the last

month column that we created in the last lesson instead we're going to use

lesson instead we're going to use automatic grouping for this so we'll go

automatic grouping for this so we'll go ahead insert in a pivot table we'll

ahead insert in a pivot table we'll insert into a new sheet and we'll call

insert into a new sheet and we'll call this group automatic I'll go ahead and

this group automatic I'll go ahead and move that to the very end okay so what

move that to the very end okay so what I'm going to do is I'm going to take the

I'm going to do is I'm going to take the job posted date remember it's a bunch of

job posted date remember it's a bunch of dates and I'm going to throw it into the

dates and I'm going to throw it into the rows and this is going to get into some

rows and this is going to get into some aggregation it's going to take a little

aggregation it's going to take a little bit to load my computer's not even

bit to load my computer's not even loaded yet but it's about 15 seconds

loaded yet but it's about 15 seconds later and it is now available if you

later and it is now available if you notice now we have this hierarchy of

notice now we have this hierarchy of this grouping and I can now dive into in

this grouping and I can now dive into in this case January and then one Jan here

this case January and then one Jan here and then diving in further we can dive

and then diving in further we can dive into specific times of job postings

into specific times of job postings going to go ahead and close this up if

going to go ahead and close this up if we actually investigate over here inside

we actually investigate over here inside of here we can see that after I dragged

of here we can see that after I dragged that job posted date over it basically

that job posted date over it basically created a month days and then the date

created a month days and then the date itself which is actually a date time but

itself which is actually a date time but anyway three different values its own

anyway three different values its own hierarchy with this automatic grouping

hierarchy with this automatic grouping and so now I can go in and do something

and so now I can go in and do something like drag the job title short into here

like drag the job title short into here to get the job count I'm going to change

to get the job count I'm going to change this

this to job count also go in and actually

to job count also go in and actually adjust the formatting but now whenever

adjust the formatting but now whenever actually go into each one of these

actually go into each one of these hierarchies and look in we can see how

hierarchies and look in we can see how many job postings were having on a daily

many job postings were having on a daily bra basis and how many were happening at

bra basis and how many were happening at a certain date time so now let's say I

a certain date time so now let's say I wanted to dive deeper to understanding

wanted to dive deeper to understanding maybe why July had such a high number

maybe why July had such a high number compared to all the other months one I

compared to all the other months one I could double click it or I can just

could double click it or I can just rightclick it and go to show details

rightclick it and go to show details this is going to show well the details

this is going to show well the details and if we actually go over to the job

and if we actually go over to the job posted date column it's going to have

posted date column it's going to have all the values for July inside of here

all the values for July inside of here so this is a pretty unique way to get

so this is a pretty unique way to get into diving deep and showing the details

into diving deep and showing the details of what is the data being used to

of what is the data being used to perform these aggregations and also

perform these aggregations and also double check your

work now we're going to get into manual grouping specifically we're going to

grouping specifically we're going to create this where we actually go through

create this where we actually go through and aggregate based on the job titles

and aggregate based on the job titles itself assigning it into well a group so

itself assigning it into well a group so put data analyst scientists and data

put data analyst scientists and data Engineers into Data nerds senior RS into

Engineers into Data nerds senior RS into senior data nerds and then these guys

senior data nerds and then these guys into other data nerds so we're going to

into other data nerds so we're going to create a pivot table for this go in and

create a pivot table for this go in and select okay using the jobs table and

select okay using the jobs table and we're going to be grouping the job title

we're going to be grouping the job title short so I'll drag that into the rows

short so I'll drag that into the rows for the time being and we'll just start

for the time being and we'll just start by grouping just the data nerds so I'm

by grouping just the data nerds so I'm going to just select one of these and

going to just select one of these and then hold down control and then also

then hold down control and then also select data engineer and then also data

select data engineer and then also data scientist then I'm going to rightclick

scientist then I'm going to rightclick it and select group the other way I

it and select group the other way I could also do this is go into pivot

could also do this is go into pivot table analyze and select group selection

table analyze and select group selection the next one on want to group are senior

the next one on want to group are senior roles so I'm going to just select all

roles so I'm going to just select all the different senior roles conveniently

the different senior roles conveniently they're all right next to each other

they're all right next to each other then I'm going right click it and go to

then I'm going right click it and go to group so now they're the own group the

group so now they're the own group the only thing left is getting the rest of

only thing left is getting the rest of these I'm actually going have to control

these I'm actually going have to control these select these and then these as

these select these and then these as well and then from there we'll group

well and then from there we'll group that for group one I'm just going to

that for group one I'm just going to select it come up to the formula bar and

select it come up to the formula bar and type in data nerds name group two to

type in data nerds name group two to senior data nerds and then group three

senior data nerds and then group three to other data nerds also going to zoom

to other data nerds also going to zoom in a little bit to get a little bit

in a little bit to get a little bit closer

now that we have all these grouped let's actually dive into performing a

actually dive into performing a basically deeper anal analysis on this

basically deeper anal analysis on this to look at how or what percentages these

to look at how or what percentages these make up of all the job titles and also

make up of all the job titles and also of their respective groups specifically

of their respective groups specifically we're going to be looking at on going

we're going to be looking at on going job the job title short over here we're

job the job title short over here we're looking at the count and how the counts

looking at the count and how the counts of those jobs are going to be of the

of those jobs are going to be of the percentages anyway I'm going change this

percentages anyway I'm going change this to job count along with going through

to job count along with going through and updating the formatting to use a

and updating the formatting to use a comma and no decimal places so for this

comma and no decimal places so for this I still wanted to use that basically

I still wanted to use that basically count of the job title short so with

count of the job title short so with these counts we're going to do the

these counts we're going to do the percentages so I'm still going to use

percentages so I'm still going to use that job title short column going to

that job title short column going to drag it into the values we did a count

drag it into the values we did a count but now let's actually go in inside of

but now let's actually go in inside of the value field setting remember we got

the value field setting remember we got to that show value as and inside of here

to that show value as and inside of here we can have different values percent of

we can have different values percent of grand total percent of column total

grand total percent of column total percent of row total we're just going to

percent of row total we're just going to go percent of grand total to start press

go percent of grand total to start press okay and Bam this is now showing us the

okay and Bam this is now showing us the percent of the grand total now I'm not

percent of the grand total now I'm not liking how this is ordered right now I'm

liking how this is ordered right now I'm actually going to I'm going to sort this

actually going to I'm going to sort this selecting one of the values inside of

selecting one of the values inside of the job count from sort it from largest

the job count from sort it from largest to smallest and then also I want to do

to smallest and then also I want to do the actual grand total itself sort

the actual grand total itself sort largest to smallest anyway we updated

largest to smallest anyway we updated this to percent of grand total we need

this to percent of grand total we need to update the title to specify perent of

to update the title to specify perent of grand total and so we can see that data

grand total and so we can see that data nerds for their parent are taking up

nerds for their parent are taking up about 76% almost 34 of the jobs are that

about 76% almost 34 of the jobs are that and individually we can see that data

and individually we can see that data analysts are nearly 30% of that whereas

analysts are nearly 30% of that whereas we get down to the other data nerds

we get down to the other data nerds they're only taking up a very small

they're only taking up a very small percentage now what happens if we want

percentage now what happens if we want to see so what is data analyst of the

to see so what is data analyst of the actual parent or what is the cloud

actual parent or what is the cloud engineer of the parent other data nerds

engineer of the parent other data nerds well I can drag that job title short

well I can drag that job title short into the values again it's aggregating

into the values again it's aggregating by count but I can go in and this time

by count but I can go in and this time I'm actually just going to rightclick it

I'm actually just going to rightclick it and we can have this show value as I'm

and we can have this show value as I'm going to use that instead we can do that

going to use that instead we can do that percent of grand total but instead I'm

percent of grand total but instead I'm going to come down here to percent of

going to come down here to percent of parent total and in our case it's asking

parent total and in our case it's asking us what is the parent now you didn't we

us what is the parent now you didn't we haven't gone over this but it actually

haven't gone over this but it actually recreated that that grouping as job

recreated that that grouping as job title short two so I'm going to click

title short two so I'm going to click okay we don't want to do the job title

okay we don't want to do the job title short that's not the parent job child

short that's not the parent job child short to and that's you can see it

short to and that's you can see it actually down here job title short too

actually down here job title short too it created inside the rows but anyway

it created inside the rows but anyway getting back to the parent now it's

getting back to the parent now it's showing the percent that it takes to

showing the percent that it takes to make the parent and then obviously the

make the parent and then obviously the parent is at 100% so I'm going to rename

parent is at 100% so I'm going to rename this one percent of parent now we just

this one percent of parent now we just looked at percent of grand total and

looked at percent of grand total and percent of parent but the show value as

percent of parent but the show value as has a lot of different other ones you

has a lot of different other ones you can also do in here if I wanted to I can

can also do in here if I wanted to I can even do something like rank largest to

even do something like rank largest to smallest once again it's asking us do we

smallest once again it's asking us do we want to rank part of the parent or part

want to rank part of the parent or part of the job tile short I want to rank

of the job tile short I want to rank part of job tile short and it will show

part of job tile short and it will show its individual rankings underneath each

its individual rankings underneath each from highest to lowest I'm going to go

from highest to lowest I'm going to go ahead and undo this I don't want to know

ahead and undo this I don't want to know necessarily keep that one more note

necessarily keep that one more note before we go for those that purchase the

before we go for those that purchase the course practice problems and also note I

course practice problems and also note I also go into calculated items and field

also go into calculated items and field and have its own little worksheet for

and have its own little worksheet for you to follow along and try out

you to follow along and try out calculated items and field I didn't

calculated items and field I didn't necessarily include it in this lesson

necessarily include it in this lesson because I felt that it wasn't a very

because I felt that it wasn't a very powerful feature I instead use like

powerful feature I instead use like using measures instead which we going to

using measures instead which we going to cover in the power pivot chapter but if

cover in the power pivot chapter but if you're interested about it I have

you're interested about it I have content on it in our notes and those

content on it in our notes and those calculated field and items is underneath

calculated field and items is underneath that pivot table analyze tab in here on

that pivot table analyze tab in here on calculated field and items we're not

calculated field and items we're not going to be covering it outside of those

going to be covering it outside of those notes that you can follow along and do

notes that you can follow along and do your own self-study with it all right

your own self-study with it all right you have some practice problems now go

you have some practice problems now go through and get more and familiar with

through and get more and familiar with these Advanced features and pivot tables

these Advanced features and pivot tables because in the next lesson we're going

because in the next lesson we're going to be diving into actually making charts

to be diving into actually making charts out of these pivot tables using pivot

out of these pivot tables using pivot charts with that see you in the next one

moving now into pivot charts so we did a lot of work already in analyzing things

lot of work already in analyzing things with pivot tables we're going to take it

with pivot tables we're going to take it now to Next Level pivot charts

now to Next Level pivot charts specifically we're going to be looking

specifically we're going to be looking at first what is the average salary by a

at first what is the average salary by a job title next we'll be looking at which

job title next we'll be looking at which job has the highest percent of demand

job has the highest percent of demand and then finally lastly we'll be looking

and then finally lastly we'll be looking at how basically how are jobs trending

at how basically how are jobs trending over time we're going to be building all

over time we're going to be building all these charts using pivot tables

these charts using pivot tables additionally we're going to include the

additionally we're going to include the features of slicers and also timelines

features of slicers and also timelines based on what chart we're using in order

based on what chart we're using in order to be able to filter down and more

to be able to filter down and more easily make our graphs more interactive

easily make our graphs more interactive as usual in the advanced chapters I want

as usual in the advanced chapters I want you to starting with the Excel workbook

you to starting with the Excel workbook from the last lesson so pivot tables

from the last lesson so pivot tables advance and if you want to see the

advance and if you want to see the examples or the final answer you could

examples or the final answer you could go to Pivot charts for this we're not

go to Pivot charts for this we're not going to be using the hierarchy or that

going to be using the hierarchy or that show Det tail tab so I'm going to go

show Det tail tab so I'm going to go ahead and hide

those so let's create this first chart to analyze what is the top paying job in

to analyze what is the top paying job in data science for this I'm going to just

data science for this I'm going to just create a new pivot table for this using

create a new pivot table for this using that jobs table and we're going to be

that jobs table and we're going to be aggregating by job title short in the

aggregating by job title short in the rows and then the salary your average in

rows and then the salary your average in the values and for this we want to

the values and for this we want to summarize values we don't want to do the

summarize values we don't want to do the sum we're going to do the average I did

sum we're going to do the average I did this by right clicking it but we do to

this by right clicking it but we do to have these all formatted correctly in

have these all formatted correctly in currency with no decimal places and I'll

currency with no decimal places and I'll update the title as well to average

update the title as well to average yearly salary so in order to insert in

yearly salary so in order to insert in this pivot chart we're going to go to

this pivot chart we're going to go to the insert Tab and we're going to come

the insert Tab and we're going to come here to Pivot chart there's only one

here to Pivot chart there's only one option right now because we're selected

option right now because we're selected on a pivot table and that's a pivot

on a pivot table and that's a pivot chart itself so I'll go ahead and insert

chart itself so I'll go ahead and insert it with this there's no recommended

it with this there's no recommended charts but I know I want a column chart

charts but I know I want a column chart so we're going to go with that and if

so we're going to go with that and if charts aren't that different from

charts aren't that different from regular charts I can come up here select

regular charts I can come up here select this plus sign I can remove things like

this plus sign I can remove things like the legend I don't really need that and

the legend I don't really need that and then I can change things like the title

then I can change things like the title by just double clicking this to

by just double clicking this to something like what is the top paying

something like what is the top paying job in data science now you may notice

job in data science now you may notice these pivot charts are a little bit

these pivot charts are a little bit different as they have these field

different as they have these field buttons on here that basically allow you

buttons on here that basically allow you to with the chart itself go in and

to with the chart itself go in and filter it this is really convenient if

filter it this is really convenient if them say this chart was in a different

them say this chart was in a different page anyway I want to have these salary

page anyway I want to have these salary sorted from highest to lowest so I can

sorted from highest to lowest so I can come into here and you know we can go

come into here and you know we can go sort A to Z or Z to A and you can change

sort A to Z or Z to A and you can change it around we want to actually sort from

it around we want to actually sort from highest to lowest so I can come in here

highest to lowest so I can come in here under more sort options and I can change

under more sort options and I can change this from the job title short column to

this from the job title short column to that average yearly salary column and we

that average yearly salary column and we want it to be descending and we'll click

want it to be descending and we'll click okay so bam now we have our salary

okay so bam now we have our salary oriented from high to low with our

oriented from high to low with our values if you don't like these field

values if you don't like these field buttons right here you can come in and

buttons right here you can come in and right click it and go hide all field

right click it and go hide all field buttons if you want but if you want to

buttons if you want but if you want to get them back you have to come back

get them back you have to come back underneath the pivot chart analyze Tab

underneath the pivot chart analyze Tab and select field buttons and uncollect

and select field buttons and uncollect this hide

all the next thing to analyze is which job has the highest percentage of demand

job has the highest percentage of demand we're going to use that percentage of

we're going to use that percentage of grand total column before and we're

grand total column before and we're going to be adding a little twist with

going to be adding a little twist with this one as we're going to be also

this one as we're going to be also building in some slicers so we can slice

building in some slicers so we can slice the data for what we want so back inside

the data for what we want so back inside the work should you should be working in

the work should you should be working in so we want the percent of grand total

so we want the percent of grand total only so I'm going to move out count

only so I'm going to move out count percent of parent and also that rank

percent of parent and also that rank count to only have what we want next

count to only have what we want next move into getting a pivot chart Built

move into getting a pivot chart Built For This and once again I'm going to be

For This and once again I'm going to be using that column chart I'll go ahead

using that column chart I'll go ahead and insert that I'm going rename this to

and insert that I'm going rename this to which job has the highest percentage

which job has the highest percentage once again I don't really care about

once again I don't really care about that Legend now I want my basically

that Legend now I want my basically target audience whoever I give this to

target audience whoever I give this to to have control to be able to select

to have control to be able to select which group they can filter for whether

which group they can filter for whether that's data nerds senior data nerds or

that's data nerds senior data nerds or other data nerds so in order to control

other data nerds so in order to control that I'm going to first zoom out we're

that I'm going to first zoom out we're going to insert some slicers for this so

going to insert some slicers for this so if we come into the pivot chart analyze

if we come into the pivot chart analyze tab we can have with this chart selected

tab we can have with this chart selected I'm going to go into insert slicer and

I'm going to go into insert slicer and we're going to do it for remember that

we're going to do it for remember that that group from last time is actually

that group from last time is actually job title short 2 and also we're going

job title short 2 and also we're going to filter this one also by country I'm

to filter this one also by country I'm going to click okay they're going to pop

going to click okay they're going to pop up here on top of this I don't really

up here on top of this I don't really like this I'm going to drag it over and

like this I'm going to drag it over and I'm going to fix the formatting real

I'm going to fix the formatting real quick so now with these slicers I can

quick so now with these slicers I can make it a lot easier for somebody using

make it a lot easier for somebody using this to come in and say hey I only want

this to come in and say hey I only want to look at data nerds or I want to look

to look at data nerds or I want to look at other data nerds and see what their

at other data nerds and see what their appropriate percentage is when you click

appropriate percentage is when you click on a slicer you will notice that this

on a slicer you will notice that this slicer tab comes up there's some

slicer tab comes up there's some different formatting options the one

different formatting options the one thing that I Define myself do changing

thing that I Define myself do changing is the appropriate label or the slicer

is the appropriate label or the slicer caption in this case I would rename this

caption in this case I would rename this one to something like job group and then

one to something like job group and then for the job country I would just rename

for the job country I would just rename this to Country and you can see they

this to Country and you can see they update appropriately here for it as a

update appropriately here for it as a refresher right if you wanted to select

refresher right if you wanted to select multiple different op options I would

multiple different op options I would select this multi select right here and

select this multi select right here and then with that enabled I can then select

then with that enabled I can then select data nerds and also senior data

nerds the last visualization we're going to be building with this it's a line

to be building with this it's a line chart looking at how jobs are trending

chart looking at how jobs are trending out of time using that previous pivot

out of time using that previous pivot table we made on the job count for this

table we made on the job count for this one we're going to be using a timeline

one we're going to be using a timeline filter to be able to select down to

filter to be able to select down to maybe a certain quarter or month so back

maybe a certain quarter or month so back in the workbook that we're working in

in the workbook that we're working in I'm in this group automatic sheet we

I'm in this group automatic sheet we want to create a pivot chart so I go to

want to create a pivot chart so I go to insert and into pivot chart and for this

insert and into pivot chart and for this one we want a line so I'm going to go

one we want a line so I'm going to go ahead and insert that I'm going to give

ahead and insert that I'm going to give this appropriate title of how are jobs

this appropriate title of how are jobs trending over time additionally I'm

trending over time additionally I'm going to remove that Legend and I want

going to remove that Legend and I want to add a trend line to it now you notice

to add a trend line to it now you notice by this one the actual field values for

by this one the actual field values for this you have multiple different ones

this you have multiple different ones here remember it did that automatic

here remember it did that automatic grouping in the last lesson so you have

grouping in the last lesson so you have not only months to filter by days and

not only months to filter by days and also that job posted date so a lot more

also that job posted date so a lot more values here now to add a timeline for

values here now to add a timeline for this I'm going to go up to Pivot chart

this I'm going to go up to Pivot chart analyze and I'm going to go into insert

analyze and I'm going to go into insert timeline there's only one value that's

timeline there's only one value that's going to be available for this job

going to be available for this job posted date and right now if I expand

posted date and right now if I expand this all the way out we have all the

this all the way out we have all the different months that are available I'm

different months that are available I'm going go ahead and close this up right

going go ahead and close this up right below it so if I wanted to filter by a

below it so if I wanted to filter by a specific month I could be like hey I

specific month I could be like hey I want from February to November in this

want from February to November in this case October I actually need to select

case October I actually need to select February I'm holding down my key for

February I'm holding down my key for this and then dragging to November

this and then dragging to November anyway I can also change this with this

anyway I can also change this with this filter not only months but also quarters

filter not only months but also quarters and even something like years I prefer I

and even something like years I prefer I typically analyze things in quarters so

typically analyze things in quarters so we're going to do it that manner and I'm

we're going to do it that manner and I'm also going to shift it up here to the

also going to shift it up here to the right hand side similar to slicers if I

right hand side similar to slicers if I have the timeline selected I can come up

have the timeline selected I can come up here and actually change the name in

here and actually change the name in this case I'm going to change it to date

this case I'm going to change it to date I could also change thing like

I could also change thing like formatting or even things like color now

formatting or even things like color now one thing to note with this with what I

one thing to note with this with what I have selected here it's only going to

have selected here it's only going to filter what I have the chart set up to

filter what I have the chart set up to or what I actually created the timeline

or what I actually created the timeline while the pivot chart was selected so

while the pivot chart was selected so let's say I came into here and I wanted

let's say I came into here and I wanted to look at in our case just data nerds

to look at in our case just data nerds and then also go into looking at the

and then also go into looking at the counts themselves this isn't necessarily

counts themselves this isn't necessarily going to update for that those slicers

going to update for that those slicers aren't connected to other charts but you

aren't connected to other charts but you can change it to do that so in this case

can change it to do that so in this case I could select something like the pivot

I could select something like the pivot table itself going into pivot table

table itself going into pivot table analyze and then here under filters

analyze and then here under filters where you can create things like slicers

where you can create things like slicers and timelines which we did in the pivot

and timelines which we did in the pivot chart anyway they have this thing called

chart anyway they have this thing called filter connections and I'm going to

filter connections and I'm going to expand this out so we can actually see

expand this out so we can actually see it and right now we're saying that well

it and right now we're saying that well for pivot table 3 as we can see up here

for pivot table 3 as we can see up here probably need to give these even better

probably need to give these even better names only the date is actually

names only the date is actually connected to this if I wanted to connect

connected to this if I wanted to connect the other ones such as country or job

the other ones such as country or job group I'd have to select them and press

group I'd have to select them and press okay now I don't know if you noticed

okay now I don't know if you noticed that but it actually adjusted these

that but it actually adjusted these values actually decrease because I have

values actually decrease because I have less values selected here whereas if I

less values selected here whereas if I actually select more all of these going

actually select more all of these going on this is going to increase the values

on this is going to increase the values anyway that's sort of hard to see let's

anyway that's sort of hard to see let's actually show this by with uh sheet one

actually show this by with uh sheet one which actually should be something like

which actually should be something like top paying jobs and in this case I can

top paying jobs and in this case I can go into pivot chart analyze into filter

go into pivot chart analyze into filter connections and this is going to show us

connections and this is going to show us based on pivot table 7 which is this one

based on pivot table 7 which is this one right here I should have renamed these

right here I should have renamed these there's no different slicers or

there's no different slicers or timelines attached to it so I can

timelines attached to it so I can actually select all of these and apply

actually select all of these and apply it to this one and now when I go to our

it to this one and now when I go to our grouping right here right so we had all

grouping right here right so we had all of them selected if I want to just look

of them selected if I want to just look at data nerds here so I can see the

at data nerds here so I can see the percentages of data analyst dat engineer

percentages of data analyst dat engineer and data scientist I can see what their

and data scientist I can see what their salaries are for it and then also I can

salaries are for it and then also I can see their counts for those as well so

see their counts for those as well so this is definitely a useful feature if

this is definitely a useful feature if you're looking to link charts or

you're looking to link charts or specifically pivot tables that are not

specifically pivot tables that are not necessarily

necessarily connected all right now it's your turn

connected all right now it's your turn to get more familiar with using pivot

to get more familiar with using pivot charts we have some practice problems

charts we have some practice problems that you go through and actually

that you go through and actually understand more about how to use them

understand more about how to use them with that in the next lesson we're going

with that in the next lesson we're going to be jumping into well the next chapter

to be jumping into well the next chapter on Advanced Data analysis and using some

on Advanced Data analysis and using some pretty unique and pretty complicated

pretty unique and pretty complicated features in order to analyze data so

features in order to analyze data so with that I'll see you in that

one welcome to this chapter on Advanced Data analysis and this entire chapter is

Data analysis and this entire chapter is really focused on using addins which are

really focused on using addins which are basically programs that people have

basically programs that people have built to incorporate into Excel to do

built to incorporate into Excel to do very unique and specific tasks because

very unique and specific tasks because of that going from less lesson to lesson

of that going from less lesson to lesson we're not going to necessarily be

we're not going to necessarily be building on each other as we go through

building on each other as we go through these lessons every lesson is going to

these lessons every lesson is going to be sort of its own unique sort of

be sort of its own unique sort of Learning Journey about a specific

Learning Journey about a specific feature or features to start with this

feature or features to start with this lesson we're looking at just enabling

lesson we're looking at just enabling the add-ins and looking at some basic

the add-ins and looking at some basic ones such as what if analysis and we're

ones such as what if analysis and we're going to get more into it in a second

going to get more into it in a second but we're going to be focused on looking

but we're going to be focused on looking at if weed three different job offers

at if weed three different job offers which one should we actually take in the

which one should we actually take in the next lesson we're going to be continuing

next lesson we're going to be continuing on with what analysis focusing on data

on with what analysis focusing on data tables and this shows us how values are

tables and this shows us how values are going to be changing based on one or

going to be changing based on one or multiple variables and then finally the

multiple variables and then finally the third lesson is on an addin called

third lesson is on an addin called analysis tool pack that provides us

analysis tool pack that provides us access to a lot of different statistical

access to a lot of different statistical analysis that we can just easily select

analysis that we can just easily select what type of analysis want to perform

what type of analysis want to perform and it does all the analysis for for us

and it does all the analysis for for us and provides it in a sheet pretty neat

and provides it in a sheet pretty neat anyway getting into this lesson we're

anyway getting into this lesson we're going to start by first enabling these

going to start by first enabling these add-ins so that way you have it and then

add-ins so that way you have it and then from there we're going to move into our

from there we're going to move into our first somewhat simple example

first somewhat simple example forecasting what's going to happen into

forecasting what's going to happen into the future specifically we're going to

the future specifically we're going to look in at our past job postings and try

look in at our past job postings and try to predict what's going to happen in the

to predict what's going to happen in the future from there we're going to be

future from there we're going to be moving into what if analysis and for

moving into what if analysis and for this we're going to have a scenario

this we're going to have a scenario where we have three job offers and we're

where we have three job offers and we're trying to find what is the most optimal

trying to find what is the most optimal one we're going to use things like

one we're going to use things like scenario manager to go through and

scenario manager to go through and automatically calculate what it should

automatically calculate what it should be for those three different job offers

be for those three different job offers and then let's say we need to actually

and then let's say we need to actually negotiate one of those job offers and we

negotiate one of those job offers and we want to match another we can use solver

want to match another we can use solver or goalkeeper and both of these have

or goalkeeper and both of these have both unique different features of them

both unique different features of them that we're going to dive into to allow

that we're going to dive into to allow us to adjust what we could potentially

us to adjust what we could potentially negotiate for better job offers one

negotiate for better job offers one quick reminder on which versions of

quick reminder on which versions of excel will support this chapter on

excel will support this chapter on Advanced Data analysis all of them will

Advanced Data analysis all of them will with the exception of Microsoft online

with the exception of Microsoft online it doesn't have the ability to add in

it doesn't have the ability to add in these specific addins but you're on Mac

these specific addins but you're on Mac or the windows version you're going to

or the windows version you're going to be completely fine so for this we're

be completely fine so for this we're going to be working inside of the

going to be working inside of the analysis addins workbook I know it said

analysis addins workbook I know it said previously you need to work with the

previously you need to work with the previous workbook from the previous

previous workbook from the previous lesson but this chapter in general

lesson but this chapter in general doesn't build on anything it has

doesn't build on anything it has everything you need within the workbook

everything you need within the workbook so you're going to be fine with this

so you're going to be fine with this anyway we just need two sheets from this

anyway we just need two sheets from this forecast original and what if analysis

forecast original and what if analysis all the others are just the results that

all the others are just the results that we're going to be getting and feel free

we're going to be getting and feel free to go through and select the sheets that

to go through and select the sheets that we're not using so these four in this

we're not using so these four in this case and hide them so that way we only

case and hide them so that way we only have the two sheets of forecast original

have the two sheets of forecast original and what if

analysis so before we enable addins I think you need to know what are exactly

think you need to know what are exactly Excel addins here I am in perplexity a

Excel addins here I am in perplexity a and I asked the question and it goes

and I asked the question and it goes into to specify What It Is by saying

into to specify What It Is by saying that basically interacts with Excel

that basically interacts with Excel objects and data and it will add custom

objects and data and it will add custom ribbon buttons or menu items and thus

ribbon buttons or menu items and thus providing custom functions now this is a

providing custom functions now this is a little technical but there are three

little technical but there are three different type of addins they have web

different type of addins they have web Excel and com add-ins today we're going

Excel and com add-ins today we're going to be importing in Excel addins which

to be importing in Excel addins which are actually created using something

are actually created using something like VBA anyway the most popular Excel

like VBA anyway the most popular Excel add-ins are things like solver power

add-ins are things like solver power pivot power query you don't necessarily

pivot power query you don't necessarily have to add in unless it's not included

have to add in unless it's not included and then also things like analysis tool

and then also things like analysis tool pack which we're going to get to in that

pack which we're going to get to in that third lesson all right enough on the

third lesson all right enough on the history lesson let's actually get into

history lesson let's actually get into enabling your addins if you go to the

enabling your addins if you go to the data tab right now you'll probably see

data tab right now you'll probably see that you have this forecast section so

that you have this forecast section so you do have what if analysis available

you do have what if analysis available but you don't have anything ex else over

but you don't have anything ex else over here right now it's um well usually

here right now it's um well usually blank but we're going to add to it so

blank but we're going to add to it so I'm going to go into file and then from

I'm going to go into file and then from there it's hidden but under more I'm

there it's hidden but under more I'm going to go to options on the menu on

going to go to options on the menu on the left hand side I'm going to go into

the left hand side I'm going to go into addins and this menu right here tells

addins and this menu right here tells you what your active application addins

you what your active application addins are right now I have no active

are right now I have no active applications and then your inactive

applications and then your inactive application addins so I do have access

application addins so I do have access to all these different ones right here

to all these different ones right here so I want to enable them specifically I

so I want to enable them specifically I want this analysis tool pack and then

want this analysis tool pack and then well the one we're going to use in this

well the one we're going to use in this lesson solver so um on manage I have

lesson solver so um on manage I have Excel addins that's the one that I want

Excel addins that's the one that I want to actually use for this I'm going to

to actually use for this I'm going to click go and now we need to enable which

click go and now we need to enable which ones we're going to use so analysis tool

ones we're going to use so analysis tool pack for the third lesson and solver for

pack for the third lesson and solver for this one from there I'm going to click

this one from there I'm going to click okay and now over here on the right hand

okay and now over here on the right hand side we have analysis popup data

side we have analysis popup data analysis which is the analysis tool pack

analysis which is the analysis tool pack and then solver is the solver

added so let's actually get into forecasting specifically looking at what

forecasting specifically looking at what we expect job postings it to be next

we expect job postings it to be next year and right here in the forecast

year and right here in the forecast original sheet I have date and then also

original sheet I have date and then also the job count and this goes all the way

the job count and this goes all the way for or this is all the data for 2023

for or this is all the data for 2023 anyway this example is going to show the

anyway this example is going to show the custom features that we really can do

custom features that we really can do with some of these add-ins and also

with some of these add-ins and also built-in features so I can select the

built-in features so I can select the date and job count column and then for

date and job count column and then for this we're going to go into the forecast

this we're going to go into the forecast and specifically to forecast sheet in

and specifically to forecast sheet in this it plots in blue what are our

this it plots in blue what are our values that we currently have for

values that we currently have for basically 2023 and then from there it

basically 2023 and then from there it plots into the future using this orange

plots into the future using this orange I can toggle this between this a line

I can toggle this between this a line chart and also a column chart but I'm

chart and also a column chart but I'm not really finding the column chart that

not really finding the column chart that useful It's Time series data so I'm

useful It's Time series data so I'm going to go back to that line chart the

going to go back to that line chart the other major thing I control is the

other major thing I control is the forecast end date so if I wanted to only

forecast end date so if I wanted to only do maybe two months I could change this

do maybe two months I could change this instead to end in March additionally

instead to end in March additionally have hidden underneath this drop down of

have hidden underneath this drop down of options the ability to go in and

options the ability to go in and actually change other things like

actually change other things like confidence interval and seasonality and

confidence interval and seasonality and things like that right now it's

things like that right now it's automatic set it up to basically detect

automatic set it up to basically detect automatically and seasonality is as you

automatically and seasonality is as you notice in this data it goes up and down

notice in this data it goes up and down up and down up and down it has a

up and down up and down it has a seasonality to it basically every single

seasonality to it basically every single week there's more postings during the

week there's more postings during the week and on the weekend there's less as

week and on the weekend there's less as expected so this seasonality is carried

expected so this seasonality is carried out into the predicted data as you can

out into the predicted data as you can see here because it's still in the

see here because it's still in the orange actually goes up and down anyway

orange actually goes up and down anyway going to close this this is great I'm

going to close this this is great I'm going to click create in this new sheet

going to click create in this new sheet it automatically has this popup here

it automatically has this popup here that says this table contains a copy of

that says this table contains a copy of your data with additional forecast of

your data with additional forecast of values at the end you can manually edit

values at the end you can manually edit the forecasting formulas in the sheet or

the forecasting formulas in the sheet or return to the original data to create a

return to the original data to create a different forecast worksheet okay great

different forecast worksheet okay great got it I'm going to zoom out a little

got it I'm going to zoom out a little bit and what this table did is it still

bit and what this table did is it still kept that date and job count column but

kept that date and job count column but it also built out three other columns to

it also built out three other columns to actually look at scroll all the way down

actually look at scroll all the way down what the forecasted would be a lower

what the forecasted would be a lower confidence band and then an upper

confidence band and then an upper confidence band and then looking at the

confidence band and then looking at the actual chart that it provides we can see

actual chart that it provides we can see this where this darker orange color is

this where this darker orange color is what The Forecastle band is this is the

what The Forecastle band is this is the upper band and then this is the lower

upper band and then this is the lower band anyway that's pretty cool that I

band anyway that's pretty cool that I could generate this all by just clicking

could generate this all by just clicking a single button of forecast

sheet all right now we're going to move into wh if analysis and we click this wh

into wh if analysis and we click this wh if analysis we have three different

if analysis we have three different things here we have scenario manager

things here we have scenario manager goal seeker and data table

goal seeker and data table for this one we're going to start with

for this one we're going to start with scenario manager but let's first go over

scenario manager but let's first go over what the data is here in the sheet that

what the data is here in the sheet that we're trying to basically trying to

we're trying to basically trying to calculate first let's focus on these

calculate first let's focus on these columns B and C this is a if you will

columns B and C this is a if you will dashboard or calculator that I built so

dashboard or calculator that I built so I can put into here a base salary a

I can put into here a base salary a bonus rate and then an annual raise

bonus rate and then an annual raise amount and it will calculate it so let's

amount and it will calculate it so let's say our base salary is 12,000 I can put

say our base salary is 12,000 I can put that into here assuming the same 10% and

that into here assuming the same 10% and 1.5% it's going to automatically update

1.5% it's going to automatically update for this over here on the right hand

for this over here on the right hand side in E through H over here we have

side in E through H over here we have three different job offers that we

three different job offers that we received and they consist of the base

received and they consist of the base salary the bonus rate and the annual

salary the bonus rate and the annual raise underneath here this fourth or

raise underneath here this fourth or fifth row if you will this is

fifth row if you will this is constraints that we're going to use

constraints that we're going to use later on I would just ignore this right

later on I would just ignore this right now so what's going on down here in the

now so what's going on down here in the result cell well what we're doing is

result cell well what we're doing is we're

we're calculating what the expected salary is

calculating what the expected salary is for year zero all the way to year four

for year zero all the way to year four and then from there we're actually

and then from there we're actually getting a total so in this case this is

getting a total so in this case this is summing up all these values right here

summing up all these values right here so why am I doing four years why am I do

so why am I doing four years why am I do a total left for these four years well

a total left for these four years well the Bureau of Labor Statistics basically

the Bureau of Labor Statistics basically estimates that most people have the

estimates that most people have the average tenure at a company of four

average tenure at a company of four years so the idea with this calculator

years so the idea with this calculator that I've made is that we're able to

that I've made is that we're able to calculate based on a job offer we re

calculate based on a job offer we re what would we expect if we were to stay

what would we expect if we were to stay at the basically average amount or

at the basically average amount or median amount of time that a normal

median amount of time that a normal person stays at a job like just looking

person stays at a job like just looking at what's the first year because

at what's the first year because sometimes things like bonuses and annual

sometimes things like bonuses and annual raise may actually push us into higher

raise may actually push us into higher salaries even though the base salary is

salaries even though the base salary is lower than another salary so it

lower than another salary so it basically helps calculate this out and

basically helps calculate this out and even the playing field for these three

even the playing field for these three jobs that we're trying to calculate

jobs that we're trying to calculate anyway you can go through if you want to

anyway you can go through if you want to and and understand what formulas are

and and understand what formulas are going on behind the scenes here but

going on behind the scenes here but basically I'm just taking into account

basically I'm just taking into account these three parameters right here and

these three parameters right here and then every year basically starting with

then every year basically starting with that previous years and then adjusting

that previous years and then adjusting it for the annual raise and then giving

it for the annual raise and then giving it its appropriate bonus so as expected

it its appropriate bonus so as expected because there's an annual raise on each

because there's an annual raise on each one of these the salaries are going up

one of these the salaries are going up so with that what is going on here do I

so with that what is going on here do I need to actually go through and actually

need to actually go through and actually put in every single one of those jobs so

put in every single one of those jobs so I'll put in job one and get the 566,000

I'll put in job one and get the 566,000 and then now do the second job and third

and then now do the second job and third job no I can use scenario manager for

job no I can use scenario manager for this so going into what if analysis I

this so going into what if analysis I select scenario manager and we're going

select scenario manager and we're going to add three different scenarios so I'm

to add three different scenarios so I'm going to come up here and select add

going to come up here and select add this scenario name we're going to call

this scenario name we're going to call it job one next we're going to move into

it job one next we're going to move into what we're going to use for the changing

what we're going to use for the changing cells and I've labeled these basically

cells and I've labeled these basically or made these into an input format we're

or made these into an input format we're going to select these three right here

going to select these three right here so C3 through C5 we'll leave the comment

so C3 through C5 we'll leave the comment as is protection as prevent changes and

as is protection as prevent changes and go to okay now it's going to ask us what

go to okay now it's going to ask us what values we want to use for each in this

values we want to use for each in this case I use 100,000 10% and 1.5 it's

case I use 100,000 10% and 1.5 it's already filled in pre-filled in from

already filled in pre-filled in from there I'm going to click okay now we

there I'm going to click okay now we need to add job two for this I'm going

need to add job two for this I'm going to leave changing cells the same this

to leave changing cells the same this one I'm going to change to 880,000

one I'm going to change to 880,000 15% and then change this bottom one to

15% and then change this bottom one to 1.2%

1.2% then finally we need to add that job

then finally we need to add that job three one of the last steps we need to

three one of the last steps we need to do is now go into summary right here and

do is now go into summary right here and for this we need to figure out what we

for this we need to figure out what we want to actually have it provide for us

want to actually have it provide for us in our case we want the result cell of

in our case we want the result cell of C9 through c14 to be provided from there

C9 through c14 to be provided from there we click okay and bam we're going to get

we click okay and bam we're going to get this scenario summary sheet that goes

this scenario summary sheet that goes through in details based on job one job

through in details based on job one job two and job three for the value that we

two and job three for the value that we input into it and from there it's going

input into it and from there it's going to tell us what year zero is year 1 2 3

to tell us what year zero is year 1 2 3 all the way down to the total salary now

all the way down to the total salary now one thing to note is you see these names

one thing to note is you see these names of Base bonus raise year zero uh and

of Base bonus raise year zero uh and then total salary if I go back to what

then total salary if I go back to what if analysis I've actually gone through

if analysis I've actually gone through already for you and actually Nam this so

already for you and actually Nam this so in this case I'm selecting zero it's

in this case I'm selecting zero it's named year zero and total salary if I

named year zero and total salary if I were to use things that were maybe not

were to use things that were maybe not named it would just provide the cell so

named it would just provide the cell so if we're using the values here it would

if we're using the values here it would just going to be provide F6 and in that

just going to be provide F6 and in that case we would have saw F6 here also back

case we would have saw F6 here also back in the scenario summary you may not have

in the scenario summary you may not have ever saw this before but Excel allows

ever saw this before but Excel allows this sort of grouping if you will to

this sort of grouping if you will to basically manipulate the sheets and what

basically manipulate the sheets and what values are hidden or potentially shown

values are hidden or potentially shown here anyway pretty unique feature that

here anyway pretty unique feature that you may or may not have seen

before all right moving on to goal Seeker let's say we have the scenario

Seeker let's say we have the scenario now where we got the job offer for job

now where we got the job offer for job one in this case but we want to try to

one in this case but we want to try to match that of job three specifically if

match that of job three specifically if I go back to that scenario summary sheet

I go back to that scenario summary sheet we can see that job one is at around

we can see that job one is at around 566,000 but job three is at 640,000

566,000 but job three is at 640,000 we'll say we have some Insider

we'll say we have some Insider information that human resources told us

information that human resources told us hey we can't adjust the base or the

hey we can't adjust the base or the bonus but we can adjust the raise what

bonus but we can adjust the raise what raise you get every year and so you

raise you get every year and so you could potentially ask for a higher Rays

could potentially ask for a higher Rays what Rays would you need to basically

what Rays would you need to basically put into here to get equal to that job

put into here to get equal to that job three so the first thing I'm going to do

three so the first thing I'm going to do is go in and make sure that we have

is go in and make sure that we have inside of our formula input in the job

inside of our formula input in the job one actual statistics of it so 100,000

one actual statistics of it so 100,000 10% and 1.5% for the annual raise now I

10% and 1.5% for the annual raise now I could go through there so I type 1.7%

could go through there so I type 1.7% and then 1.8% and just keep on going up

and then 1.8% and just keep on going up until I actually find what it is or

until I actually find what it is or instead we can just actually use this

instead we can just actually use this goal seeker and for this we're going to

goal seeker and for this we're going to be setting a cell specifically cell

be setting a cell specifically cell c14 to that 640,000 that we want to get

c14 to that 640,000 that we want to get to and we need to provide what cell

to and we need to provide what cell we're going to actually change in this C

we're going to actually change in this C case we're going to change cell

case we're going to change cell C5 which is the annual raise no for this

C5 which is the annual raise no for this we can only change one option we're

we can only change one option we're going to be able to change M multiple

going to be able to change M multiple the next scenario but not in this one of

the next scenario but not in this one of goal Seeker so from there I'll go ahead

goal Seeker so from there I'll go ahead and click okay and Bam automatically

and click okay and Bam automatically goes through I don't know if you saw

goes through I don't know if you saw that it Ste through it and it went up to

that it Ste through it and it went up to 7.6% and that's what we'll need in order

7.6% and that's what we'll need in order to get to that 640,000 and it even

to get to that 640,000 and it even provides an old nice dialogue box saying

provides an old nice dialogue box saying that hey it did find a solution

that hey it did find a solution sometimes you may put a goal in that's

sometimes you may put a goal in that's not achievable and in this case it would

not achievable and in this case it would it would tell

you so 7.76% is a pretty high raise let's say

7.76% is a pretty high raise let's say we get further information from HR

we get further information from HR saying hey we can actually change not

saying hey we can actually change not only the annual raise but also your

only the annual raise but also your bonus we still have the same scenario

bonus we still have the same scenario you can't change the base salary needs

you can't change the base salary needs to stay at 100,000 for that first year

to stay at 100,000 for that first year so we have multiple parameters now that

so we have multiple parameters now that are changing this is when we're going to

are changing this is when we're going to shift from using this goal Seeker now

shift from using this goal Seeker now over to solver one thing before we start

over to solver one thing before we start we need to actually reset these values

we need to actually reset these values in here I'm going to change this back to

in here I'm going to change this back to 1.5% both of these Step Up in value so

1.5% both of these Step Up in value so you want to reset it before you go so

you want to reset it before you go so opening up solver I'm going to set the

opening up solver I'm going to set the objective as before that c14 of that

objective as before that c14 of that total salary and we want to get it to a

total salary and we want to get it to a salary of 640,000 and we want to do this

salary of 640,000 and we want to do this by like we said we can change two things

by like we said we can change two things in this case the bonus and the annual

in this case the bonus and the annual raise we can also add constraints which

raise we can also add constraints which we'll do in a second after we just run

we'll do in a second after we just run through this one but I want to actually

through this one but I want to actually just go through and solve it first and

just go through and solve it first and the last thing we need to look at is

the last thing we need to look at is select a solving method we're going to

select a solving method we're going to just leave it here I really like this

just leave it here I really like this grg nonlinear we'll leave it that for

grg nonlinear we'll leave it that for the time being and we'll go ahead and

the time being and we'll go ahead and click solve now for this it says solver

click solve now for this it says solver found a solution all constraints and

found a solution all constraints and optionality conditions are satisfied as

optionality conditions are satisfied as we can see it increased the bonus and

we can see it increased the bonus and then also the annual raise and we got to

then also the annual raise and we got to that 640,000 inside of this popup box we

that 640,000 inside of this popup box we can have it output certain reports so

can have it output certain reports so I'm going to just hold control and

I'm going to just hold control and select multiple different reports along

select multiple different reports along with clicking this for outline reports

with clicking this for outline reports that's it's going to actually print to

that's it's going to actually print to different sheets and from there click

different sheets and from there click okay anyway the most important of these

okay anyway the most important of these three different reports that it gave to

three different reports that it gave to us feels the answer report basically

us feels the answer report basically tells us hey what was the original

tells us hey what was the original values put in for the D bonus and raise

values put in for the D bonus and raise and then what are the final values in

and then what are the final values in order to get to that final value of 6

order to get to that final value of 6 40,000 they also have these two other

40,000 they also have these two other reports one on sensitivity analysis and

reports one on sensitivity analysis and the other one evaluating the limits

the other one evaluating the limits which we're going to get to um but these

which we're going to get to um but these I don't find as important so now with

I don't find as important so now with this with solver we found that we can

this with solver we found that we can input more than one different input now

input more than one different input now we can also specify constraints if I

we can also specify constraints if I come back up to solver and it says Hey

come back up to solver and it says Hey in this dialogue box subject to the

in this dialogue box subject to the constraint right now the annual raise is

constraint right now the annual raise is sort of low still at 2.1% but that bonus

sort of low still at 2.1% but that bonus skyrocketed it was previously at 10% and

skyrocketed it was previously at 10% and it went all the way up to 23% so we

it went all the way up to 23% so we could actually put some constraints in

could actually put some constraints in by clicking add and we'll say hey the

by clicking add and we'll say hey the bonus we're not going to let that exceed

bonus we're not going to let that exceed 15% we'll click add for that and then

15% we'll click add for that and then for the next one we don't want the

for the next one we don't want the annual raise to exceed we'll say 4% and

annual raise to exceed we'll say 4% and we'll click okay remember I did name

we'll click okay remember I did name these cells so that's why it pops up

these cells so that's why it pops up automatically as B and raise makes it

automatically as B and raise makes it super easy whenever you name cells all

super easy whenever you name cells all right let's go ahead and click solve so

right let's go ahead and click solve so look at this solver could not find a

look at this solver could not find a feasible solution with these constraints

feasible solution with these constraints basically maxed out the bonus and maxed

basically maxed out the bonus and maxed out that annual raise and we didn't get

out that annual raise and we didn't get to that 640,000 so what I can do is I

to that 640,000 so what I can do is I can return to the solver parameters

can return to the solver parameters dialogue click okay and in this case

dialogue click okay and in this case I'll change the bonus to we'll say 20%

I'll change the bonus to we'll say 20% now and then for the raise we'll change

now and then for the raise we'll change this to 5% click okay and then try to

this to 5% click okay and then try to solve again and we found a solution we

solve again and we found a solution we have 17% and

have 17% and 4.4% and for this I'm going to Output

4.4% and for this I'm going to Output the answers I'll click outline reports

the answers I'll click outline reports to export it click okay close this out

to export it click okay close this out and then go to the report we can see

and then go to the report we can see what our finally values are along with

what our finally values are along with how we got to our 640,000 final value

how we got to our 640,000 final value all right you got some practice problem

all right you got some practice problem problem to now go through and try these

problem to now go through and try these different features out of scenario

different features out of scenario manager and goal seeker and also solver

manager and goal seeker and also solver and I think once you play around with

and I think once you play around with them more you can find out which one is

them more you can find out which one is more applicable to which scenario with

more applicable to which scenario with that I'll see you in the next section

that I'll see you in the next section where we're going be going into deeper

where we're going be going into deeper into what if analysis specifically on

into what if analysis specifically on data tables one my favorite features of

data tables one my favorite features of what if analysis with that see you

there let's now get wrapped up on what if analysis by focusing on data tables

if analysis by focusing on data tables we're going to be focusing on building

we're going to be focusing on building one input and also two input data tables

one input and also two input data tables for the first one on one input we're

for the first one on one input we're going to be continuing on with that

going to be continuing on with that exercise from last lesson looking into

exercise from last lesson looking into that job offer one and seeing how we

that job offer one and seeing how we could change the annual rays in order to

could change the annual rays in order to thus affect different salaries at our

thus affect different salaries at our 4-year point and mainly the total salary

4-year point and mainly the total salary at this point and from there we're going

at this point and from there we're going to shift into building two input data

to shift into building two input data tables where we're not only analyzing

tables where we're not only analyzing that annual raise increase but also a

that annual raise increase but also a change in the bonus rate to see what the

change in the bonus rate to see what the different salaries are for that final

different salaries are for that final total amount of those four years so for

total amount of those four years so for this lesson and also for this chapter

this lesson and also for this chapter we're going to be starting with the

we're going to be starting with the actual workbook of the name of the

actual workbook of the name of the chapter in this case data tables and

chapter in this case data tables and we're going to be working this original

we're going to be working this original sheet but I want to jump into that one

sheet but I want to jump into that one input to basically show you what we're

input to basically show you what we're going to be building

we're going to be inputting into here the annual raise percentage we're going

the annual raise percentage we're going to put it in increments of. 5% and then

to put it in increments of. 5% and then along the top in the row we're going to

along the top in the row we're going to be inputting the values from over here

be inputting the values from over here um and these values right here across

um and these values right here across the top and then the data table itself

the top and then the data table itself is going to fill this in with the

is going to fill this in with the expected result so in this case year

expected result so in this case year three at 2% s uh 2% increase in arrays

three at 2% s uh 2% increase in arrays it's going to get around

it's going to get around 116,000 we also do for coloring at the

116,000 we also do for coloring at the end uh the data tables don't do that

end uh the data tables don't do that that's done with conditional formatting

that's done with conditional formatting so here we are back in the original

so here we are back in the original sheet first thing we need to do is get

sheet first thing we need to do is get the annual Rays put up here remember we

the annual Rays put up here remember we want to go in we'll say. 5% increment so

want to go in we'll say. 5% increment so I'll do zero

0.5% and then for the rest of these I'll just drag them down I end up messing up

just drag them down I end up messing up the formatting so I'm just clear the

the formatting so I'm just clear the borders and then put a border back

borders and then put a border back around the outside now for the salaries

around the outside now for the salaries I want that to be for what year zero

I want that to be for what year zero then year 1 I'll drag this on over for

then year 1 I'll drag this on over for these and then we'll put a total so for

these and then we'll put a total so for this I want to enter in that year zero

this I want to enter in that year zero we're going to be doing this for all the

we're going to be doing this for all the different values right there I'm going

different values right there I'm going go ahead and put it in if you notice it

go ahead and put it in if you notice it has this line through it and I actually

has this line through it and I actually click it and then from here whenever I

click it and then from here whenever I look into it it provides the error of

look into it it provides the error of stale value you may or may not see this

stale value you may or may not see this but I'm going I show you how to fix this

but I'm going I show you how to fix this if you are experienced this you can go

if you are experienced this you can go into file and then into more under

into file and then into more under options and what happens is under

options and what happens is under formulas my workbook calculations went

formulas my workbook calculations went from basically automatically calculating

from basically automatically calculating to manually where under manually if I

to manually where under manually if I look at this little icon right here they

look at this little icon right here they can be manually calculated by pressing

can be manually calculated by pressing F9 or going to formulas calculate now

F9 or going to formulas calculate now anyway there's nothing wrong with having

anyway there's nothing wrong with having automatic calculations that's actually

automatic calculations that's actually what I want all the time somehow my

what I want all the time somehow my thing switched into this manual if yours

thing switched into this manual if yours does switch it back to automatic click

does switch it back to automatic click okay bam we're good to go and we'll

okay bam we're good to go and we'll continue on now it's important for up

continue on now it's important for up here at the top that we have them equal

here at the top that we have them equal to the formulas here because this is

to the formulas here because this is what's going to be ultimately getting

what's going to be ultimately getting changed and manipulated so I wouldn't

changed and manipulated so I wouldn't want to go through and actually manually

want to go through and actually manually fill this in with a 110,000 it needs to

fill this in with a 110,000 it needs to be connected to the formula that

be connected to the formula that actually is getting calculated so

actually is getting calculated so building our data table now I'm going to

building our data table now I'm going to select this entire range right here E3

select this entire range right here E3 all the way down to K12 go to the data

all the way down to K12 go to the data Tab and select data table now this

Tab and select data table now this provides us two inputs a row input cell

provides us two inputs a row input cell and a column input cell we're only doing

and a column input cell we're only doing a one input data table so we only need

a one input data table so we only need to fill in one of these specifically

to fill in one of these specifically we're looking for the input either into

we're looking for the input either into the row or the input into the column in

the row or the input into the column in this case we're going to be subbing in

this case we're going to be subbing in this this column this e column right

this this column this e column right here we're going to be subbing it into

here we're going to be subbing it into the formula here and it wants to know

the formula here and it wants to know what is the input cell for in this case

what is the input cell for in this case the column so I'm going to go ahead and

the column so I'm going to go ahead and select it it's C5 I'm gonna go ahead and

select it it's C5 I'm gonna go ahead and click okay and it's going to

click okay and it's going to automatically fill it in now what's

automatically fill it in now what's unique about this is I could also go in

unique about this is I could also go in here if I wanted to and maybe change

here if I wanted to and maybe change this to something like 10% and it will

this to something like 10% and it will update this entire data table with that

update this entire data table with that new value I'm actually going to change

new value I'm actually going to change that back to 3% but pretty unique anyway

that back to 3% but pretty unique anyway if I wanted to I can come in also and

if I wanted to I can come in also and I'll so go in and to conditional format

I'll so go in and to conditional format it I'm only going to select Euro 0

it I'm only going to select Euro 0 through four and I'm going to do a white

through four and I'm going to do a white to green and then for the total I'm

to green and then for the total I'm going to do its own because it's almost

going to do its own because it's almost in its own bracket here right it's a a

in its own bracket here right it's a a sum of all those different values so I'm

sum of all those different values so I'm also going to do the same thing of the

also going to do the same thing of the white to green and then you know me I

white to green and then you know me I don't really really like green so I'm

don't really really like green so I'm going to go ahead and select this and

going to go ahead and select this and I'm going to end up changing this by

I'm going to end up changing this by going into manage rules and conditional

going into manage rules and conditional formatting selecting on this one

formatting selecting on this one adjusting the color to Blue and also

adjusting the color to Blue and also selecting this one and changing this one

selecting this one and changing this one to Blue as well click apply and then

to Blue as well click apply and then okay and

Bam so with that example complete let's move into a two input data table and

move into a two input data table and let's look at the final example for this

let's look at the final example for this for this we're going to have as we had

for this we're going to have as we had before the annual rays in the column but

before the annual rays in the column but this time we're going to have the bonus

this time we're going to have the bonus up on that top row and for this we're

up on that top row and for this we're going to be calculating as we click here

going to be calculating as we click here it's going to be calculating

it's going to be calculating c14 which is the total salary we're not

c14 which is the total salary we're not going to be calculating that 0 1 through

going to be calculating that 0 1 through 4 anymore and it's going to go through

4 anymore and it's going to go through and calculate it for all of these

and calculate it for all of these different scenarios if you will all

different scenarios if you will all right to do this I'm going to go back to

right to do this I'm going to go back to that original sheet I'm going to

that original sheet I'm going to actually duplicate this by saying copy

actually duplicate this by saying copy it create a copy and click okay okay so

it create a copy and click okay okay so now we have original two so I'm going to

now we have original two so I'm going to name original to one input and then

name original to one input and then rename or two to two input now for this

rename or two to two input now for this one I'm going to end up just clearing

one I'm going to end up just clearing the contents from here I'll go to

the contents from here I'll go to editing clear and I'll just select clear

editing clear and I'll just select clear contents and now thinking about it I

contents and now thinking about it I want to also clear any of the formatting

want to also clear any of the formatting that's in here cuz we're going to be

that's in here cuz we're going to be doing something different with it I can

doing something different with it I can go into clear rules I can go clear rules

go into clear rules I can go clear rules from entire sheet all right so we're

from entire sheet all right so we're have the Rays and the rows and now we

have the Rays and the rows and now we need the actual bonus in the columns for

need the actual bonus in the columns for this we'll go from 0% to

this we'll go from 0% to 5% and I need to actually change this

5% and I need to actually change this formatting to actually be a percentage

formatting to actually be a percentage and then drag this all the way through

and then drag this all the way through along with fixing this formatting so now

along with fixing this formatting so now a two input data table is a little bit

a two input data table is a little bit different in that we need in the upper

different in that we need in the upper left hand corner what we actually want

left hand corner what we actually want to change whereas the one input put we

to change whereas the one input put we did across in in our case we did across

did across in in our case we did across the rows in this case we just want to

the rows in this case we just want to have in the upper left hand corner there

have in the upper left hand corner there it is I sort of grayed it out you can

it is I sort of grayed it out you can make it a little bit darker if if you

make it a little bit darker if if you want to but I would just want to make it

want to but I would just want to make it known that hey we're not necessarily

known that hey we're not necessarily using it so similarly we're actually

using it so similarly we're actually going to get into creating it we're

going to get into creating it we're going to select the entire data table go

going to select the entire data table go to the data tab what if analysis data

to the data tab what if analysis data table for the row input cell so this row

table for the row input cell so this row up here what are we wanting to

up here what are we wanting to substitute these values into well we

substitute these values into well we want to sub it into the bonus and then

want to sub it into the bonus and then similarly for the column input same as

similarly for the column input same as last time that's the annual raise so

last time that's the annual raise so we're going to want to sub that into C5

we're going to want to sub that into C5 going go ahead and click okay so I'm

going go ahead and click okay so I'm going to dress this up a little bit I'm

going to dress this up a little bit I'm going to bold the header right here also

going to bold the header right here also I'm going to merge and center this all

I'm going to merge and center this all so we can put inside of here bonus and

so we can put inside of here bonus and then finally I'm going to conditionally

then finally I'm going to conditionally format it like we did last time using

format it like we did last time using that white to green and then changing

that white to green and then changing that green to a blue to get it more of

that green to a blue to get it more of what I want so bam now we have a two

what I want so bam now we have a two input table and we can see what it's

input table and we can see what it's going to be across all these things also

going to be across all these things also with this if you remember from our last

with this if you remember from our last lesson right we were looking at finding

lesson right we were looking at finding what is the value we'd want to be to get

what is the value we'd want to be to get around 640,000

around 640,000 now we have a few different values we

now we have a few different values we can actually look at for this and we can

can actually look at for this and we can tell from this well we going to need to

tell from this well we going to need to be above a bonus rate of 15% to even be

be above a bonus rate of 15% to even be considered to get up to 640,000 so

considered to get up to 640,000 so sometimes I like this visually better

sometimes I like this visually better than going in and doing something like

than going in and doing something like goal Seeker or even things like solver

goal Seeker or even things like solver because now I have multiple different

because now I have multiple different variables I can look at and analyze and

variables I can look at and analyze and try to adjust on my own all right so you

try to adjust on my own all right so you now have some practice problems to go

now have some practice problems to go through and get familiar with data

through and get familiar with data tables I found when I first started with

tables I found when I first started with data tables got really confused on the

data tables got really confused on the row input and also the column input

row input and also the column input cells but really understanding how those

cells but really understanding how those are being applied into the original

are being applied into the original formula helps you figure that out all

formula helps you figure that out all right with that I'll see in the next one

right with that I'll see in the next one where we're going going into the

where we're going going into the analysis tool pack and diving into a lot

analysis tool pack and diving into a lot of different statistical analysis you

of different statistical analysis you can do with Excel so with that see you

there all right this is the last lesson in this chapter on Advanced ad analysis

in this chapter on Advanced ad analysis and specifically we're going to be

and specifically we're going to be focusing on that analysis tool pack

focusing on that analysis tool pack addin now this addin is packed full of

addin now this addin is packed full of features and I can make a whole tutorial

features and I can make a whole tutorial just on this addin alone but we're only

just on this addin alone but we're only going to be focusing on four core things

going to be focusing on four core things of it that it does that I use from time

of it that it does that I use from time to time on our job posting salary data

to time on our job posting salary data set of over 30,000 rows first we're

set of over 30,000 rows first we're going to look at how we can get

going to look at how we can get descriptive statistics of something like

descriptive statistics of something like a salary column so we don't have to go

a salary column so we don't have to go through and use formulas to get all the

through and use formulas to get all the different statistics for it second we're

different statistics for it second we're going to investigate how to make

going to investigate how to make histograms but these are a little bit

histograms but these are a little bit with a Twist in that I feel like they're

with a Twist in that I feel like they're more customizable than the previous

more customizable than the previous histograms we can make third we'll get

histograms we can make third we'll get into ranking and assigning a percentile

into ranking and assigning a percentile for our salary data so we can understand

for our salary data so we can understand where it actually ranks for percentiles

where it actually ranks for percentiles and then finally we're going to be

and then finally we're going to be moving into looking at at a moving

moving into looking at at a moving average if you remember our job posting

average if you remember our job posting data set had all the seasonality in it

data set had all the seasonality in it basically went up and down a lot

basically went up and down a lot depending on where it was posted during

depending on where it was posted during the week well we can remove those

the week well we can remove those fluctuations by a moving average for

fluctuations by a moving average for this we're going to be working in the

this we're going to be working in the analysis tool pack workbook and all the

analysis tool pack workbook and all the answers in there so you can feel free to

answers in there so you can feel free to go ahead and actually select all the

go ahead and actually select all the different sheets in here and go ahead

different sheets in here and go ahead and hide them so we only have the data

and hide them so we only have the data tab in there and we'll be working with

tab in there and we'll be working with this

so as a refresher this is the data analysis tool pack you should have gone

analysis tool pack you should have gone through in that first lesson and

through in that first lesson and actually enabled it by going into

actually enabled it by going into options into the addins itself and it

options into the addins itself and it should now be under the active addins if

should now be under the active addins if you didn't do that remember you all you

you didn't do that remember you all you have to do is just go into go into here

have to do is just go into go into here and select it all right so let's open

and select it all right so let's open this bad boy up and if I click that

this bad boy up and if I click that analysis it's going to pop up here and

analysis it's going to pop up here and this dialogue box allows us to select

this dialogue box allows us to select like I said from a variety of different

like I said from a variety of different tests that we can actually perform

tests that we can actually perform there's a lot of different statistical

there's a lot of different statistical tests in here such as regression and

tests in here such as regression and sampling and then even things like

sampling and then even things like correlation Co variance and whatnot so

correlation Co variance and whatnot so let's start with the one that I find

let's start with the one that I find myself using the most and that's

myself using the most and that's descriptive statistics when I want to

descriptive statistics when I want to perform Eda or exploratory analysis this

perform Eda or exploratory analysis this is the first thing I want to do now the

is the first thing I want to do now the thing about this is we need to provide a

thing about this is we need to provide a column that has numerical values in it

column that has numerical values in it so we could do the date column but what

so we could do the date column but what we're going to do is we're going to to

we're going to do is we're going to to provide the salary year average column

provide the salary year average column go ahead and press enter for this we do

go ahead and press enter for this we do have labels in the first row so I need

have labels in the first row so I need to click this here for output options we

to click this here for output options we want to go to a new worksheet so that's

want to go to a new worksheet so that's what we'll leave for this and with this

what we'll leave for this and with this we do want the summary statistics you

we do want the summary statistics you can go in and also specify things like

can go in and also specify things like confidence level and the cith largest

confidence level and the cith largest and kith smth but we're going to leave

and kith smth but we're going to leave those default for the time being and

those default for the time being and click okay now it's popped up in this

click okay now it's popped up in this new sheet called cheap one and diving

new sheet called cheap one and diving into it I'm actually going to expand

into it I'm actually going to expand this out and then format all these

this out and then format all these numbers real quick so that's much more

numbers real quick so that's much more readable so now we have all the key

readable so now we have all the key statistics from it we don't have to go

statistics from it we don't have to go through and calculate a formula for mean

through and calculate a formula for mean median mode standard deviation the

median mode standard deviation the minimum maximum sum

whatnot all right next up is histogram and previously remember we could just

and previously remember we could just select something like the M column go

select something like the M column go into insert here and actually insert a

into insert here and actually insert a histogram now the one problem I have

histogram now the one problem I have with this is the formatting of the rows

with this is the formatting of the rows or the X values down here it basically

or the X values down here it basically provides this range this is a lot of

provides this range this is a lot of data right there and there's it's really

data right there and there's it's really hard to format this so let's look at an

hard to format this so let's look at an alternate option for this using the data

alternate option for this using the data analysis tool pack specifically we're to

analysis tool pack specifically we're to come in here to histogram for the input

come in here to histogram for the input range once again I'm going to go ahead

range once again I'm going to go ahead and just select that column M press

and just select that column M press enter it does have labels for bin range

enter it does have labels for bin range I'm going to leave m I'm not going to

I'm going to leave m I'm not going to specify a width of the histogram or the

specify a width of the histogram or the bin I'm going to leave it just default

bin I'm going to leave it just default for the output I'm going to leave it as

for the output I'm going to leave it as the new worksheet ply I don't want

the new worksheet ply I don't want either of these the parto or the

either of these the parto or the cumulative percentage instead I just

cumulative percentage instead I just want the chart output of this press okay

want the chart output of this press okay and here we have the histogram it's

and here we have the histogram it's honestly not too special it's a little

honestly not too special it's a little hard to read based on the size of these

hard to read based on the size of these bins as you can see basically the

bins as you can see basically the difference between these is around it

difference between these is around it looks like they're doing basically an

looks like they're doing basically an thousand increments so the increments

thousand increments so the increments are way too small we need to adjust the

are way too small we need to adjust the bin anyway the one good thing is along

bin anyway the one good thing is along this xais it's only one value now so a

this xais it's only one value now so a lot easier to read so now let's go in

lot easier to read so now let's go in and adjust that bin size so if I go back

and adjust that bin size so if I go back to data analysis into histogram and

to data analysis into histogram and click okay for the bin range it wants me

click okay for the bin range it wants me to actually put in a range or a

to actually put in a range or a selection so we need to actually

selection so we need to actually pre-fill out what range or bins we want

pre-fill out what range or bins we want for this so I'm going to copy this

for this so I'm going to copy this header up here cuz we're going to keep

header up here cuz we're going to keep the bin in frequency start a new sheet

the bin in frequency start a new sheet paste it in here and I want to go in

paste it in here and I want to go in we'll say 50,000 increments so 0

we'll say 50,000 increments so 0 50,000 and I want it to go to basically

50,000 and I want it to go to basically 400,000 so now going into Data analysis

400,000 so now going into Data analysis again histogram opening it back up still

again histogram opening it back up still has the input range selected correctly

has the input range selected correctly now for the bin range I'll select A2 to

now for the bin range I'll select A2 to A10 select the output range to I

A10 select the output range to I basically want it to be inside of of

basically want it to be inside of of this notebook so I'm going to select up

this notebook so I'm going to select up here on D1 we'll just start there and we

here on D1 we'll just start there and we want a chart output on this page okay

want a chart output on this page okay I'll click okay and I'm getting this

I'll click okay and I'm getting this error message that the input range must

error message that the input range must contain at least one data point right

contain at least one data point right now this Elm is not referring back to

now this Elm is not referring back to the correct sheet it needs to look at so

the correct sheet it needs to look at so actually I'm going to select right here

actually I'm going to select right here you can see it selected that other sheet

you can see it selected that other sheet I actually want to select the M column

I actually want to select the M column of the data tab now we'll press okay so

of the data tab now we'll press okay so now I love this because wanted output

now I love this because wanted output this I didn't apparently need to do this

this I didn't apparently need to do this frequency thing I got confused anyway we

frequency thing I got confused anyway we can actually go in and format this to

can actually go in and format this to remove the legend and then update the

remove the legend and then update the axess title for salary and then we'll

axess title for salary and then we'll update this one for frequency anyway I

update this one for frequency anyway I really like this because now look at

really like this because now look at this control we were able to minimize it

this control we were able to minimize it not to go past 40,000 and have all these

not to go past 40,000 and have all these outliers and everything else that has

outliers and everything else that has past 40,000 is put into this basically

past 40,000 is put into this basically more value you anyway this is my

more value you anyway this is my preferred method for making histograms

preferred method for making histograms especially whenever I need to control

especially whenever I need to control that

xais next up is Rank and percentile and with this one we're going to be doing a

with this one we're going to be doing a rank and percentile of that salary year

rank and percentile of that salary year average column once again now this one

average column once again now this one depending on the size of your computer

depending on the size of your computer may take up it may even crash your

may take up it may even crash your computer so if you're concerned that

computer so if you're concerned that this is not going to be able to

this is not going to be able to performed on your computer don't run it

performed on your computer don't run it just look at my example and understand

just look at my example and understand what get out of it anyway I selected

what get out of it anyway I selected rank in percentile and then for the

rank in percentile and then for the input range once again I'll select that

input range once again I'll select that column M and then we'll output it to a

column M and then we'll output it to a new worksheet ply and I can do something

new worksheet ply and I can do something like even name it in this case calling

like even name it in this case calling it Rank and percentile of the sheet that

it Rank and percentile of the sheet that it's going to go to so clicking okay it

it's going to go to so clicking okay it says Rank and percentile input range

says Rank and percentile input range contains non-numeric data basically I

contains non-numeric data basically I forgot to click this of labels in the

forgot to click this of labels in the first row clicking again it's thinking

first row clicking again it's thinking how long is it going to take all right

how long is it going to take all right so Excel just on me maybe that wasn't a

so Excel just on me maybe that wasn't a great idea let's try that again using

great idea let's try that again using Rank and percentile this time instead of

Rank and percentile this time instead of selecting the whole column I think

selecting the whole column I think because it had some blank value

because it had some blank value especially down to a million rows sort

especially down to a million rows sort of crashed it instead what I'm going to

of crashed it instead what I'm going to do is I'm going to just select A1 and

do is I'm going to just select A1 and then select down all the way to the

then select down all the way to the bottom I don't know why it changed it

bottom I don't know why it changed it over to column F but the main point of

over to column F but the main point of me to doing this is that way we select

me to doing this is that way we select column M and also I need to remove this

column M and also I need to remove this A1 at the beginning okay and also need

A1 at the beginning okay and also need to update this to be starting the second

to update this to be starting the second cell and we're going to try this again I

cell and we're going to try this again I gave it the name of rank percentile I

gave it the name of rank percentile I didn't have the labels in first row

didn't have the labels in first row selected because we're going from the

selected because we're going from the second cell how long is it going to take

second cell how long is it going to take this time all right so that was a lot

this time all right so that was a lot quicker this time and we have our now in

quicker this time and we have our now in this Rank and percentile sheet our

this Rank and percentile sheet our actual data it did take about a minute

actual data it did take about a minute to do so once again if you have a

to do so once again if you have a computer that's not necessarily that

computer that's not necessarily that fast don't try this at home all right so

fast don't try this at home all right so some key statistics about this it

some key statistics about this it provides a point which is the row number

provides a point which is the row number it's itself and then from there what is

it's itself and then from there what is the value that's the column the rank and

the value that's the column the rank and then the percentile what's cool about

then the percentile what's cool about this because of provided point we could

this because of provided point we could do something like the index function and

do something like the index function and you provided an array and then the row

you provided an array and then the row number in this case that's the row

number in this case that's the row number so if I wanted to find out what

number so if I wanted to find out what the job title is I could select column B

the job title is I could select column B and then from there for the row number

and then from there for the row number go back to rank and percentile and

go back to rank and percentile and select this value right here then close

select this value right here then close parenthesis press enter looks like it's

parenthesis press enter looks like it's a clinical NLP data scientist and I can

a clinical NLP data scientist and I can actually autofill this all the way down

actually autofill this all the way down anyway let's make sure this is actually

anyway let's make sure this is actually correct okay yeah just double checking

correct okay yeah just double checking the row number at 25589 is clinical NLP

the row number at 25589 is clinical NLP data scientist so we have it correct

data scientist so we have it correct anyway I could go through now and I did

anyway I could go through now and I did this for the job title itself but you

this for the job title itself but you could imagine you could pull out things

could imagine you could pull out things like the job country job tile short all

like the job country job tile short all sorts of other key information and get

sorts of other key information and get this in a list of what it's rank is

this in a list of what it's rank is along with its

percentile our last feature to look at is moving average and this is what we're

is moving average and this is what we're going to be calculating here the Blue

going to be calculating here the Blue Line already is data we already have of

Line already is data we already have of what are the job postings over time but

what are the job postings over time but that orange line is the moving average

that orange line is the moving average we can use this analysis tool pack in

we can use this analysis tool pack in order to calculate this and as you can

order to calculate this and as you can see it removes a lot of these fluctu

see it removes a lot of these fluctu these weekly fluctuations if you will

these weekly fluctuations if you will from it and makes it a lot more are

from it and makes it a lot more are basically readable to see where actual

basically readable to see where actual the Peaks and the troughs are now in

the Peaks and the troughs are now in order to do this I can't necessarily

order to do this I can't necessarily just put in that job posted date into it

just put in that job posted date into it I have to actually get a count of the

I have to actually get a count of the dates and also what are the counts of

dates and also what are the counts of the job postings per date so we need to

the job postings per date so we need to create a pivot table so we go in insert

create a pivot table so we go in insert pivot table from table we're going to do

pivot table from table we're going to do it from this table which is named jobs

it from this table which is named jobs and we're going to insert it into a new

and we're going to insert it into a new sheet similar before we're going to put

sheet similar before we're going to put that job posted date into the rows and

that job posted date into the rows and I'm actually going to take out you can

I'm actually going to take out you can see it aggregated by month I'm going to

see it aggregated by month I'm going to take out the month from there so it does

take out the month from there so it does by days and now I'm going to throw into

by days and now I'm going to throw into the values here it's going to do a count

the values here it's going to do a count so I'm just change this to job count and

so I'm just change this to job count and we can actually visualize this by itself

we can actually visualize this by itself by going to insert pivot charts

by going to insert pivot charts inserting in a pivot chart we want a

inserting in a pivot chart we want a line and that's what we saw before with

line and that's what we saw before with our Blue Line before that showed how it

our Blue Line before that showed how it basically went across uh went through

basically went across uh went through time

time all right so goes ahead and I'm going to

all right so goes ahead and I'm going to delete this chart because we're going to

delete this chart because we're going to be making it and once again we're going

be making it and once again we're going to that data tab into Data analysis and

to that data tab into Data analysis and we're going to be forming moving average

we're going to be forming moving average for the input range I'm going to select

for the input range I'm going to select B4 and then select all the way to the

B4 and then select all the way to the Bottom now this grand total went into it

Bottom now this grand total went into it so actually I'm going to back up one and

so actually I'm going to back up one and change this to 368 we didn't select any

change this to 368 we didn't select any labels in the front row so I'm going to

labels in the front row so I'm going to leave that on blank in the interval I'm

leave that on blank in the interval I'm going to just set it something like

going to just set it something like seven for the time being for the output

seven for the time being for the output range I want it to go right next to my

range I want it to go right next to my chart so I'm going to copy this above

chart so I'm going to copy this above and paste it below and change these B's

and paste it below and change these B's into C's so it's C values right next to

into C's so it's C values right next to it and we want a chart output along with

it and we want a chart output along with standard errors I'm going to go ahead

standard errors I'm going to go ahead and click okay now this chart is not

and click okay now this chart is not correct um we made a little bit of a

correct um we made a little bit of a mistake but I did want to show you real

mistake but I did want to show you real quick this moving average we can see

quick this moving average we can see that it starts 7 days later right here

that it starts 7 days later right here and so that's what's happening in this C

and so that's what's happening in this C column here that's the actual moving

column here that's the actual moving average and then the actual error itself

average and then the actual error itself is right next to it it's pretty

is right next to it it's pretty consistent around 30 to 40 anyway we

consistent around 30 to 40 anyway we need to fix this we need to take this

need to fix this we need to take this entire value if you will and move it out

entire value if you will and move it out of a pivot chart so I'm going to select

of a pivot chart so I'm going to select this all the way down to the bottom and

this all the way down to the bottom and copy it then inside of a new sheet I'm

copy it then inside of a new sheet I'm going to come in and paste it I'm going

going to come in and paste it I'm going to just paste looks like a pasting with

to just paste looks like a pasting with the pivot table formatting I'm going to

the pivot table formatting I'm going to paste uh the values only and change this

paste uh the values only and change this to job date so let's try this again

to job date so let's try this again using data analysis going to moving

using data analysis going to moving average for the input range we're going

average for the input range we're going to select B2 and then all the way down

to select B2 and then all the way down to the bottom remember this has a grand

to the bottom remember this has a grand total so I actually need to change that

total so I actually need to change that to minus one for the interval I'm going

to minus one for the interval I'm going to adjust it a little bit I'm going to

to adjust it a little bit I'm going to actually change this now to a 21-day

actually change this now to a 21-day moving average and then for the output

moving average and then for the output range this actually needs to be adjusted

range this actually needs to be adjusted to match what the input range is but for

to match what the input range is but for b or c sorry anyway go go ahead leave

b or c sorry anyway go go ahead leave everything else checked click okay and

everything else checked click okay and Bam now we have blue and also orange if

Bam now we have blue and also orange if you will for the actual and the forecast

you will for the actual and the forecast now one thing I'm noticing with this

now one thing I'm noticing with this chart is well the markers are pretty

chart is well the markers are pretty heinous they're making they're clogging

heinous they're making they're clogging up this chart so what I can do is Select

up this chart so what I can do is Select something like this orange line right

something like this orange line right here I can rightclick it go to format

here I can rightclick it go to format data series and then here underneath

data series and then here underneath this fill and line go into markers and

this fill and line go into markers and then for the marker options just

then for the marker options just basically do none we just want to have a

basically do none we just want to have a line instead additionally we can just go

line instead additionally we can just go ahead and click that blue the blue line

ahead and click that blue the blue line and for the markers there we can do none

and for the markers there we can do none as well okay sensory overloads gone now

as well okay sensory overloads gone now looks a lot more readable with the

looks a lot more readable with the exception of down here for some reason

exception of down here for some reason it didn't pick up the dates on mine and

it didn't pick up the dates on mine and we can adjust that by right clicking

we can adjust that by right clicking that and going to select data underneath

that and going to select data underneath the horizontal ax labels I'm going to go

the horizontal ax labels I'm going to go ahead and edit this I'm going like from

ahead and edit this I'm going like from A2 all the way down minus one we don't

A2 all the way down minus one we don't to do grand total click okay that

to do grand total click okay that changed the names let's see if that

changed the names let's see if that updated the chart and Bam it did now I'm

updated the chart and Bam it did now I'm going to do some minor cleanup I'm going

going to do some minor cleanup I'm going to remove that Legend from there and

to remove that Legend from there and that looks a lot better so now we have a

that looks a lot better so now we have a graph of our moving average of the job

graph of our moving average of the job postings and as we sort of suspected in

postings and as we sort of suspected in August we had a peak along with January

August we had a peak along with January seemed sort of high then went down a

seemed sort of high then went down a little bit but then up again in August

little bit but then up again in August so we see a lot more Trends and then

so we see a lot more Trends and then tapering out towards the end of the year

tapering out towards the end of the year all right now it's your turn to go

all right now it's your turn to go through and practice with those practice

through and practice with those practice problems and exploring some of these

problems and exploring some of these features in the analysis tool pack add

features in the analysis tool pack add in with that we're going to be wrapping

in with that we're going to be wrapping up this chapter and in the next one

up this chapter and in the next one we're be jumping into Power query which

we're be jumping into Power query which I'm super excited about in order how to

I'm super excited about in order how to clean up our data and load it in in the

clean up our data and load it in in the format that we want easily all right

format that we want easily all right with that see you

there welcome to this chapter on power query and no pun intended but this is

query and no pun intended but this is one of the most powerful tools within

one of the most powerful tools within Excel it allows us to perform ETL

Excel it allows us to perform ETL processes or extract transform and load

processes or extract transform and load which just some fancy data engineering

which just some fancy data engineering talk for connecting to a data source and

talk for connecting to a data source and loading it in after you clean it up

loading it in after you clean it up anyway in this chapter we have five

anyway in this chapter we have five lessons specifically in this one we're

lessons specifically in this one we're going to have an intro to power query

going to have an intro to power query what it's all about how to actually

what it's all about how to actually connect to a data source in the next one

connect to a data source in the next one we'll be moving into the power query

we'll be moving into the power query editor and we'll be covering that for

editor and we'll be covering that for three lessons in order to go in how to

three lessons in order to go in how to actually clean up your data and get it

actually clean up your data and get it prepared to a format that you want in

prepared to a format that you want in the last lesson we'll be diving into the

the last lesson we'll be diving into the M language which is powering power query

M language which is powering power query don't worry we're not going to do any

don't worry we're not going to do any in-depth coding or anything like that

in-depth coding or anything like that just want you to have some familiarity

just want you to have some familiarity with you so we have more experience with

with you so we have more experience with using power

query so what's this lesson about well in order to understand that we have to

in order to understand that we have to understand is what is power query and

understand is what is power query and here on Microsoft's learning platform

here on Microsoft's learning platform they have this fancy Dancy diagram that

they have this fancy Dancy diagram that basically shows this what power query

basically shows this what power query does it allows us to connect to

does it allows us to connect to different data sources it could be

different data sources it could be something like a database a text file or

something like a database a text file or even something on the cloud from there

even something on the cloud from there power query will then pipe it in to a

power query will then pipe it in to a bunch of different products they have

bunch of different products they have and we're going to be using it for

and we're going to be using it for Microsoft Excel but it's also famously

Microsoft Excel but it's also famously also in powerbi now if you have a

also in powerbi now if you have a Windows version of excel power query is

Windows version of excel power query is going to work just fine on the Mac

going to work just fine on the Mac versions it is available however it's

versions it is available however it's very limited so a lot of the stuff we're

very limited so a lot of the stuff we're going to do within this lesson you're

going to do within this lesson you're not going to be able to do and also

not going to be able to do and also Microsoft online is just completely not

Microsoft online is just completely not available so as a reminder power query

available so as a reminder power query is an ETL tool or extract transform load

is an ETL tool or extract transform load and we can connect to as a data source

and we can connect to as a data source such as this here's a Wikipedia page on

such as this here's a Wikipedia page on the list of S&P 500 companies and it has

the list of S&P 500 companies and it has all the different 500 companies that are

all the different 500 companies that are part of the S&P 500 anyway let's say I

part of the S&P 500 anyway let's say I want this table I could go through and

want this table I could go through and try I mean as you can see I'm trying to

try I mean as you can see I'm trying to select it right now and it's like

select it right now and it's like selecting the whole page it's a whole

selecting the whole page it's a whole mess if I'm trying to get this but we

mess if I'm trying to get this but we can actually use power query to extract

can actually use power query to extract all this components out all I have to do

all this components out all I have to do is go in and provide the web address of

is go in and provide the web address of this which I know it's located right

this which I know it's located right here I'll then select which of the

here I'll then select which of the tables I want out of the web page which

tables I want out of the web page which is this one right here and then I just

is this one right here and then I just load it in and here it is in our

load it in and here it is in our workbook now don't worry I sort of ran

workbook now don't worry I sort of ran through that example real quick we're

through that example real quick we're going to go more in depth and Detail in

going to go more in depth and Detail in the last example in this lesson but I

the last example in this lesson but I just wanted to show the power of this

just wanted to show the power of this and how we can actually get data even

and how we can actually get data even from online into our workbook so easily

from online into our workbook so easily so why do we need to use power query

so why do we need to use power query well we're going to find that out as we

well we're going to find that out as we go along but I'm going to give you the

go along but I'm going to give you the tidbits right now of One it automates

tidbits right now of One it automates the ETL process so I don't have to do

the ETL process so I don't have to do that annoying task of going to a sheet

that annoying task of going to a sheet and copying it over every time I get new

and copying it over every time I get new data I can just get power query to do it

data I can just get power query to do it for me additionally with that sometimes

for me additionally with that sometimes I may have mistakes I'm copy and paste

I may have mistakes I'm copy and paste and sheets over therefore I have

and sheets over therefore I have reproducibility and then finally with

reproducibility and then finally with this I'm now allowed to bring data in

this I'm now allowed to bring data in that potentially exceeds that 1 million

that potentially exceeds that 1 million row limit of Excel which we'll show how

row limit of Excel which we'll show how we can deal with that in a bit so let's

we can deal with that in a bit so let's actually get into performing our first

actually get into performing our first example of loading in a simple data set

example of loading in a simple data set specifically from another Excel sheet

specifically from another Excel sheet like I talked about the beginning of the

like I talked about the beginning of the advanced chapters you're not going to be

advanced chapters you're not going to be able to actually work inside of the

able to actually work inside of the workbooks that I have given so in this

workbooks that I have given so in this case power query intro has the final

case power query intro has the final results but I don't want you working in

results but I don't want you working in that I'll tell you what works you need

that I'll tell you what works you need to be working with as we go through this

to be working with as we go through this which you're probably getting the

which you're probably getting the security warning of external data

security warning of external data connections have been disabled and we'll

connections have been disabled and we'll get to troubleshoot shooting that at the

get to troubleshoot shooting that at the end so instead we're going to be

end so instead we're going to be starting with a new blank workbook I'm

starting with a new blank workbook I'm going to go to navigate over here to the

going to go to navigate over here to the data tab this is where power query is

data tab this is where power query is located specifically under this get and

located specifically under this get and transform data it doesn't really say

transform data it doesn't really say power query but that's where power query

power query but that's where power query is hidden now anytime I'm importing any

is hidden now anytime I'm importing any data I typically go to this get data and

data I typically go to this get data and then from there I navigate Down Deeper

then from there I navigate Down Deeper depending on it's file database from

depending on it's file database from fabric and power platforms or from even

fabric and power platforms or from even other sources they do have for all these

other sources they do have for all these for it here they also have smaller icons

for it here they also have smaller icons right next to it that you can navigate

right next to it that you can navigate over and basically highlight okay this

over and basically highlight okay this is from web and then this is from a

is from web and then this is from a table of range and whatnot we're going

table of range and whatnot we're going to be going over multiple examples in

to be going over multiple examples in this video so don't worry if you're not

this video so don't worry if you're not following along with which data sources

following along with which data sources you can actually import I think you'll

you can actually import I think you'll have a good idea by the end of

this so what are we going to import first well if you navigate into our

first well if you navigate into our course folder under resources under dat

course folder under resources under dat ass sets and then data jobs monthly we

ass sets and then data jobs monthly we have Excel files for every single month

have Excel files for every single month we're going to start by just importing

we're going to start by just importing one Excel file to start and then in the

one Excel file to start and then in the next exercise we'll go into how to

next exercise we'll go into how to import all these at once anyway we're

import all these at once anyway we're going to start simple first with just

going to start simple first with just this Excel file so for this I'm going to

this Excel file so for this I'm going to go to get data and it's a file

go to get data and it's a file specifically it's from an Excel workbook

specifically it's from an Excel workbook inside the course folder I'm going to

inside the course folder I'm going to then navigate to the data set going to

then navigate to the data set going to resources data sets monthly and then

resources data sets monthly and then select that January data set and click

select that January data set and click import with power query you're going to

import with power query you're going to find that it has this Navigator window

find that it has this Navigator window pop up and from there it will show you

pop up and from there it will show you what is actually importing in in this

what is actually importing in in this case January data jobs the Excel sheet

case January data jobs the Excel sheet and then if it had one or multiple

and then if it had one or multiple sheets it will appear there underneath

sheets it will appear there underneath it whenever I select sheet one it then

it whenever I select sheet one it then shows me to the right hand side a

shows me to the right hand side a snapshot or a preview of all the

snapshot or a preview of all the different data in there it doesn't show

different data in there it doesn't show all the columns but a snapshot of it at

all the columns but a snapshot of it at the bottom there's a few options to load

the bottom there's a few options to load or load to and then also transform we're

or load to and then also transform we're going to keep it simple for the time

going to keep it simple for the time being and we're just going to load so

being and we're just going to load so I'll go ahead and click it so we just

I'll go ahead and click it so we just imported in this data set from another

imported in this data set from another worksh sheet it's already in its own

worksh sheet it's already in its own table and because it also was sheet one

table and because it also was sheet one it's naming the sheet sheet one

it's naming the sheet sheet one parenthesis 2 to signify as the second

parenthesis 2 to signify as the second one so congratulations we just completed

one so congratulations we just completed our first ETL process of actually

our first ETL process of actually extracting transforming and loading an

extracting transforming and loading an Excel workbook into another

workbook so we loaded this table in but how do we actually go about using it

how do we actually go about using it well in this portion we're going to be

well in this portion we're going to be demonstrating how we can manipulate it

demonstrating how we can manipulate it with a pivot table and how to basically

with a pivot table and how to basically control all our different queries if you

control all our different queries if you notice we had over on the right hand

notice we had over on the right hand pane this queries and connections now if

pane this queries and connections now if it's not popping up you can go up here

it's not popping up you can go up here to the data Tab and then you see queries

to the data Tab and then you see queries and connections you can navigate it on

and connections you can navigate it on and off by clicking this button power

and off by clicking this button power query sets up these queries and in this

query sets up these queries and in this case it named it sheet one after the

case it named it sheet one after the sheet one in that workbook that we

sheet one in that workbook that we exported in I'm sorry that we imported

exported in I'm sorry that we imported in and if we hover over it we can get

in and if we hover over it we can get some details about the columns when it

some details about the columns when it was last refreshed it's load status and

was last refreshed it's load status and even data source now connections over

even data source now connections over here on the right right now we have zero

here on the right right now we have zero connections that's actually what's

connections that's actually what's controlled by power pivot which we're

controlled by power pivot which we're going to be going over in the next

going to be going over in the next chapter on power pivot but anyway back

chapter on power pivot but anyway back to Power queries itself right now we see

to Power queries itself right now we see with sheet one that 3,000 rows are

with sheet one that 3,000 rows are loaded and if necessary we go through

loaded and if necessary we go through and refresh the data set as showing it

and refresh the data set as showing it loaded the data and 3,000 rows are

loaded the data and 3,000 rows are loaded again pretty quick so let's

loaded again pretty quick so let's actually get into manipulating this well

actually get into manipulating this well it says that 3,000 rows are loaded but I

it says that 3,000 rows are loaded but I actually I can go in and delete this tab

actually I can go in and delete this tab and it's going to give you this warming

and it's going to give you this warming that's going to per delete the sheet do

that's going to per delete the sheet do you want to continue yes I do and

you want to continue yes I do and whenever I do that since the data is no

whenever I do that since the data is no longer loaded it now displays that it's

longer loaded it now displays that it's connection only so we can actually

connection only so we can actually change where we load our data to if you

change where we load our data to if you will and I can get to this by right

will and I can get to this by right clicking it and then going into here and

clicking it and then going into here and we'll be exploring all these other

we'll be exploring all these other options as we go through but I'm only

options as we go through but I'm only want to focus right now on this load to

want to focus right now on this load to and they have a few different options in

and they have a few different options in here let's actually explore them right

here let's actually explore them right now it has only create connection so

now it has only create connection so right now it only has a connection if we

right now it only has a connection if we go back to that table and click okay it

go back to that table and click okay it once again loads it into that table if

once again loads it into that table if we want to actually get into a pivot

we want to actually get into a pivot table we'll select this on pivot table

table we'll select this on pivot table report we can also do a pivot chart and

report we can also do a pivot chart and it asks whether we want to put it in the

it asks whether we want to put it in the existing worksheet or a new worksheet

existing worksheet or a new worksheet and then finally it has ADD this data to

and then finally it has ADD this data to the data model you've seen this one

the data model you've seen this one before and once again we're going to be

before and once again we're going to be going over data models more in depth in

going over data models more in depth in chapter eight on power pivot so we're

chapter eight on power pivot so we're not going to be enabling this checkbox

not going to be enabling this checkbox just yet anyway I went in the existing

just yet anyway I went in the existing worksheet I don't need that table there

worksheet I don't need that table there so I'm going to click okay and it says

so I'm going to click okay and it says hey there's possible data loss because

hey there's possible data loss because we're going to be basically getting rid

we're going to be basically getting rid of that table and replacing it with a

of that table and replacing it with a pivot table do I want to continue yeah

pivot table do I want to continue yeah and now like we did before in the pivot

and now like we did before in the pivot table chapter we're now using a pivot

table chapter we're now using a pivot table and so we can put things like job

table and so we can put things like job title short and analyze it for the count

title short and analyze it for the count of different jobs that it has within it

of different jobs that it has within it there's no change whatsoever in

there's no change whatsoever in everything we learn in pivot tables

everything we learn in pivot tables still same application that we're using

still same application that we're using it here

for so now let's actually get into importing multiple different Excel files

importing multiple different Excel files we're going to specifically be importing

we're going to specifically be importing all 12 of these of January through

all 12 of these of January through December this time whenever I go into

December this time whenever I go into the data tab under get data and we want

the data tab under get data and we want to get it from a file but I'm not going

to get it from a file but I'm not going to select an Excel workbook instead what

to select an Excel workbook instead what I'm going to do is select a folder

I'm going to do is select a folder because all those Excel files are in the

because all those Excel files are in the same folder inside my course I'll

same folder inside my course I'll navigate into resources data sets and

navigate into resources data sets and then I'm going to select the folder

then I'm going to select the folder itself and select open now you may

itself and select open now you may notice the Navigator window looks a

notice the Navigator window looks a little bit different and that's because

little bit different and that's because now it contains the metadata of these

now it contains the metadata of these Excel files itself such as the name data

Excel files itself such as the name data access modified created and whatnot and

access modified created and whatnot and with this one before we had that load

with this one before we had that load and load to along with transform data

and load to along with transform data we're just going to go into combining

we're just going to go into combining this data set so I'm going to go ahead

this data set so I'm going to go ahead and click that and specifically we're

and click that and specifically we're going to use combine and load now we

going to use combine and load now we navigate to a window we're more familiar

navigate to a window we're more familiar with of combined files and what this is

with of combined files and what this is doing is showing is how it's going to

doing is showing is how it's going to actually combine the files in that we

actually combine the files in that we need to make sure one that they're all

need to make sure one that they're all the same format but if I actually click

the same format but if I actually click sheet one of which the sample file is

sheet one of which the sample file is looking at is the first file this is

looking at is the first file this is what it looks like and we know this

what it looks like and we know this already because we looked at the January

already because we looked at the January file anyway if you wanted to you could

file anyway if you wanted to you could also change this to a specific file I'm

also change this to a specific file I'm fine with just using first file

fine with just using first file selecting a sheet if I was having errors

selecting a sheet if I was having errors I would do skip files with errors but

I would do skip files with errors but I'm not worried about that just yet I'm

I'm not worried about that just yet I'm going go ahead and click okay and Bam

going go ahead and click okay and Bam now we have that once again that table

now we have that once again that table loaded into here and this has all the

loaded into here and this has all the data so I expect it to have around

data so I expect it to have around 30,000 results similar to what we've

30,000 results similar to what we've been working with before and it looks

been working with before and it looks like it does and if you notice we have

like it does and if you notice we have this new column right here on Source

this new column right here on Source name which tells which Excel file each

name which tells which Excel file each of these comes through and just doing a

of these comes through and just doing a cursory check it looks like all the

cursory check it looks like all the different months are in there now onto

different months are in there now onto this queries and connections paint up

this queries and connections paint up here I'm going to actually make this

here I'm going to actually make this smaller so I can actually see it all

smaller so I can actually see it all previously we only had our sheet one

previously we only had our sheet one query but now we have also this data

query but now we have also this data jobs monthly query and with that up here

jobs monthly query and with that up here at the top because we're connecting

at the top because we're connecting multiple different files we have these

multiple different files we have these helper queries that were created during

helper queries that were created during the process so you can navigate over

the process so you can navigate over these and basically see that hey it used

these and basically see that hey it used the September file as a sample and this

the September file as a sample and this is the steps it took or this is what the

is the steps it took or this is what the sample file actually looks like anyway

sample file actually looks like anyway I'm not too concerned with those helper

I'm not too concerned with those helper queries right there or with anything

queries right there or with anything underneath this transform from files I

underneath this transform from files I mainly care about what's under those

mainly care about what's under those other queries so we have sheet one and

other queries so we have sheet one and data jobs monthly speaking of which

data jobs monthly speaking of which sheet one is a really bad name for this

sheet one is a really bad name for this so I'm going to rename this to data jobs

so I'm going to rename this to data jobs January I also rename the sheet so just

January I also rename the sheet so just to prove with the data jobs monthly that

to prove with the data jobs monthly that we actually imported it all in we're

we actually imported it all in we're going to go in and load to and we're

going to go in and load to and we're going to do this time a pivot chart

going to do this time a pivot chart going to go ahead and click okay we're

going to go ahead and click okay we're doing the existing sheet with the table

doing the existing sheet with the table I don't care if I get rid of that table

I don't care if I get rid of that table so I'll click okay and similar four I'm

so I'll click okay and similar four I'm going to put that job title short this

going to put that job title short this we're going to put in the Axis or the

we're going to put in the Axis or the rows and then we're going to want a

rows and then we're going to want a count of that as well and then I'll just

count of that as well and then I'll just organize this in descending order based

organize this in descending order based on the count of job title short so bam

on the count of job title short so bam we now connected with power query to

we now connected with power query to multiple Excel files and imported in at

multiple Excel files and imported in at once I hope you realize that now this

once I hope you realize that now this unlocks a lot of potentials because say

unlocks a lot of potentials because say you get January of next year's data you

you get January of next year's data you could just put it into this folder here

could just put it into this folder here and then just all you need to do is go

and then just all you need to do is go back into the data tab click refresh

back into the data tab click refresh it's going to go through and refresh all

it's going to go through and refresh all that data set and pull those new numbers

in all right in this example you're not going to follow along I'm just want to

going to follow along I'm just want to show the power a power query okay the

show the power a power query okay the pun's getting old by now anyway I have

pun's getting old by now anyway I have this CSV pile or comma separated values

this CSV pile or comma separated values basically it has comma separating

basically it has comma separating everything I looked at this is in VSS

everything I looked at this is in VSS code don't worry about any of this stuff

code don't worry about any of this stuff like I said you're not doing it the main

like I said you're not doing it the main point is to show this data set itself

point is to show this data set itself right here it's starting at the top row

right here it's starting at the top row of one and if I scroll all the way down

of one and if I scroll all the way down we get to the last entry and that's

we get to the last entry and that's 2.7 million jobs that I have here in

2.7 million jobs that I have here in this data set we can actually import

this data set we can actually import this into Excel now if you recall if you

this into Excel now if you recall if you scroll all the way down to the bottom of

scroll all the way down to the bottom of excel it only includes about 1 million

excel it only includes about 1 million rows so how the heck are we going to do

rows so how the heck are we going to do this with power query so this is a CSV

this with power query so this is a CSV file I'm going to go to data get data

file I'm going to go to data get data from file specifically it's a text or

from file specifically it's a text or CSV and I'm going to import in this data

CSV and I'm going to import in this data jobs large file that I have reminder

jobs large file that I have reminder again you don't have access to this file

again you don't have access to this file it's just too big to even get onto

it's just too big to even get onto GitHub so that's why this is a demo only

GitHub so that's why this is a demo only this is the data set itself so I'm going

this is the data set itself so I'm going to go in and actually go and look load

to go in and actually go and look load it now this has taken a little bit of

it now this has taken a little bit of time as you can see it's loading around

time as you can see it's loading around 100,000 rows as it goes through also it

100,000 rows as it goes through also it had well it has three errors now in here

had well it has three errors now in here this usually appears whenever it has a

this usually appears whenever it has a row of data that doesn't necessarily

row of data that doesn't necessarily make sense for what it's supposed to

make sense for what it's supposed to import it alert you there's an error so

import it alert you there's an error so the 2.7 million rows are loaded but I

the 2.7 million rows are loaded but I get this error message the query

get this error message the query returned more data that will fit on a

returned more data that will fit on a worksheet remember it automatically by

worksheet remember it automatically by default tries to load it into a table

default tries to load it into a table into Excel and it's telling me that hey

into Excel and it's telling me that hey it's not going to fit so I'll click okay

it's not going to fit so I'll click okay now it's still going to try to load that

now it's still going to try to load that table but it's going to cut it off at

table but it's going to cut it off at that 1.5 million but this doesn't mean

that 1.5 million but this doesn't mean we can't analyze it if I scroll over

we can't analyze it if I scroll over this query it reminds me that the

this query it reminds me that the results of this query is too large to be

results of this query is too large to be loaded to the specified location

loaded to the specified location worksheets have a limit of 1 million

worksheets have a limit of 1 million rows sure instead what I'm going to do

rows sure instead what I'm going to do is go and load to and I'm going to load

is go and load to and I'm going to load to a pivot table click okay and it's

to a pivot table click okay and it's going to warn me again about the table

going to warn me again about the table loss yeah I know so once it loaded like

loss yeah I know so once it loaded like a hot minute to do that I can actually

a hot minute to do that I can actually go through and now analyze these 2.7

go through and now analyze these 2.7 million rows so if I do something like

million rows so if I do something like put the job posted date into the rows

put the job posted date into the rows and we also want and we want to get a

and we also want and we want to get a count of this so I'm going to put the

count of this so I'm going to put the job poster date also into the values so

job poster date also into the values so we get this counts anyway reformatting

we get this counts anyway reformatting it with commas to actually be able to

it with commas to actually be able to read this now we can see that we did

read this now we can see that we did actually get in 2.7 million different

actually get in 2.7 million different data points for this and as a side note

data points for this and as a side note this is all the data that I've collected

this is all the data that I've collected since I started in 2022 doing this so

since I started in 2022 doing this so there's a lot of different jobs so Excel

there's a lot of different jobs so Excel is not necessarily limited to just

is not necessarily limited to just analyzing 1 million rows of

data all right so let's finally get into that last example of importing in this

that last example of importing in this list of S&P 500 companies feel free you

list of S&P 500 companies feel free you don't necessarily have to do this table

don't necessarily have to do this table from Wikipedia but I'll drop a link

from Wikipedia but I'll drop a link below on where this table is located and

below on where this table is located and you can use that if you want so I copied

you can use that if you want so I copied the web page of that table then I'm

the web page of that table then I'm going to come in here and select like

going to come in here and select like this of from web you can do basic or

this of from web you can do basic or Advanced with Wikipedia it's perfectly

Advanced with Wikipedia it's perfectly fine to do the basic version putting in

fine to do the basic version putting in that URL clicking okay we get into that

that URL clicking okay we get into that Navigator window and there's actually

Navigator window and there's actually multiple tables inside of here one is

multiple tables inside of here one is the list of 500 companies and the second

the list of 500 companies and the second one is a list of companies that have

one is a list of companies that have been added and also removed from there

been added and also removed from there they also just have random tables in

they also just have random tables in there as well just because in the

there as well just because in the internet you're going to have random

internet you're going to have random tables like this one of main menu

tables like this one of main menu contents tools appearances not

contents tools appearances not applicable anyway we want to do table

applicable anyway we want to do table one I'm going to go ahead and click load

one I'm going to go ahead and click load and now that we have it in here anytime

and now that we have it in here anytime we do this probably need to rename it

we do this probably need to rename it appropriately from something like table

appropriately from something like table one to S&P 500 in this case and Bam

one to S&P 500 in this case and Bam scrolling down we can see that we have

scrolling down we can see that we have um should be 500 oh a little bit more

um should be 500 oh a little bit more than 500 apparently the list has been

than 500 apparently the list has been updated to clear a little bit more I

updated to clear a little bit more I don't know why that is but got all the

don't know why that is but got all the DAT

nonetheless now quick note on if you want to actually navigate into any of

want to actually navigate into any of the files and see what I've done

the files and see what I've done whenever you go to open it so in this

whenever you go to open it so in this case I want to open power query intro

case I want to open power query intro I'm going to open it up you're going to

I'm going to open it up you're going to get this of external data connections

get this of external data connections have been disabled do you want to enable

have been disabled do you want to enable content in this case yes you want to

content in this case yes you want to enable all that now the problem you now

enable all that now the problem you now may also have is that it may give you a

may also have is that it may give you a warning that your data source settings

warning that your data source settings aren't correct and what do I mean by

aren't correct and what do I mean by that if I go into data and then under

that if I go into data and then under get data we're going to see this thing

get data we're going to see this thing here for data source settings and it's

here for data source settings and it's managing settings for your data sources

managing settings for your data sources anyway you're going to see these

anyway you're going to see these locations here these are file locations

locations here these are file locations of the data sets and they reference the

of the data sets and they reference the files that are on my computer that's not

files that are on my computer that's not going to be the same for your computer

going to be the same for your computer it's probably going to be in a different

it's probably going to be in a different location with a different name so here I

location with a different name so here I know that this is the data jobs monthly

know that this is the data jobs monthly folder if I wanted to actually go in and

folder if I wanted to actually go in and update it with the actual location for

update it with the actual location for where it is I would go down here select

where it is I would go down here select change source and then from there select

change source and then from there select browse to navigate to it you're going to

browse to navigate to it you're going to once again navigate to your course of

once again navigate to your course of excel. analytics into resources data

excel. analytics into resources data sets and then there's that data jobs

sets and then there's that data jobs monthly click open and okay and then

monthly click open and okay and then it's going to update you're going to

it's going to update you're going to have to do that for this file and all

have to do that for this file and all the files within a power query and also

the files within a power query and also power pivot because your file locations

power pivot because your file locations are not the same as my file locations

are not the same as my file locations then after you do that all it should go

then after you do that all it should go through and refresh but if it doesn't

through and refresh but if it doesn't you can manually refresh it underneath

you can manually refresh it underneath the data tab by clicking refresh

all the last item to call out is the options menu we're going to be going

options menu we're going to be going into the query editor in the next video

into the query editor in the next video so we're going to save that for that one

so we're going to save that for that one anyway query option has a lot of

anyway query option has a lot of advanced details in controlling power

advanced details in controlling power query in this case of showing the query

query in this case of showing the query Peak when hovering on a query in the

Peak when hovering on a query in the query's task pane that's sort of

query's task pane that's sort of annoying to me it pops up every now and

annoying to me it pops up every now and then I'm going to go ahead and unclick

then I'm going to go ahead and unclick it but they also have different

it but they also have different behaviors you contr control for data

behaviors you contr control for data load for the power qu editor the

load for the power qu editor the security privacy and even Diagnostics so

security privacy and even Diagnostics so feel free to go through this and

feel free to go through this and navigate and see what is available to

navigate and see what is available to actually customize with this I'm going

actually customize with this I'm going to go ahead and click my changes of okay

to go ahead and click my changes of okay and now whenever I go to the queries and

and now whenever I go to the queries and connections and actually hover over

connections and actually hover over something like data jobs Jan doesn't

something like data jobs Jan doesn't just pop up on the screen and sort of

just pop up on the screen and sort of catch me off guard so I sort of like

catch me off guard so I sort of like that all right we now got some practice

that all right we now got some practice problems for you to go through and get

problems for you to go through and get more familiar with performing Bally ETL

more familiar with performing Bally ETL with power query and loading in some

with power query and loading in some different data sources with it with that

different data sources with it with that we'll see you in the next one we're

we'll see you in the next one we're going to get into the power query editor

going to get into the power query editor anyway nothing to be intimidated by as a

anyway nothing to be intimidated by as a lot of the core principles we've learned

lot of the core principles we've learned already in Excel are going to be applied

already in Excel are going to be applied to this new window so you're going to

to this new window so you're going to pick it right up on it all right with

pick it right up on it all right with that I'll see you in the next

that I'll see you in the next [Music]

one in this lesson we're going to be continuing on with power query focusing

continuing on with power query focusing on specifically getting you introduced

on specifically getting you introduced to this power query editor and in order

to this power query editor and in order to facilitate this we're going to be

to facilitate this we're going to be going through or walking through

going through or walking through actually importing and cleaning up our

actually importing and cleaning up our data science job posting data set that

data science job posting data set that has over 30,000 rows of data we're going

has over 30,000 rows of data we're going to be automating a lot of the steps

to be automating a lot of the steps using power query that previously we had

using power query that previously we had to use functions and formulas for so

to use functions and formulas for so it's going to be saving us a lot of

it's going to be saving us a lot of times in order to actually automate this

times in order to actually automate this data in

justest for this we're going to be starting out with a blank workbook so I

starting out with a blank workbook so I know we do have this power query editor

know we do have this power query editor but I don't want you actually editing

but I don't want you actually editing from that that's more for a reference

from that that's more for a reference now if you do open this file in order to

now if you do open this file in order to reference it as we go along this

reference it as we go along this remember you're going to have issues or

remember you're going to have issues or an error saying hey data source isn't

an error saying hey data source isn't there remember you need to go in and

there remember you need to go in and actually select where this data set is

actually select where this data set is so under the data tab get data and then

so under the data tab get data and then under data source settings you're going

under data source settings you're going to need to update this link or this

to need to update this link or this address right here of where you're

address right here of where you're actually accessing the data job salary

actually accessing the data job salary all Excel file this is my location not

all Excel file this is my location not yours got to update it anyway like I

yours got to update it anyway like I said we're not going to be using this so

said we're not going to be using this so I'm going to open up a new notebook and

I'm going to open up a new notebook and like before we're going to be importing

like before we're going to be importing in that data set so we'll go to get data

in that data set so we'll go to get data from file from Excel workbook you'll

from file from Excel workbook you'll navigate to the course itself under

navigate to the course itself under resource under data sets and then we're

resource under data sets and then we're going to be using this data jobs salary

going to be using this data jobs salary all Microsoft Excel file go ahead and

all Microsoft Excel file go ahead and import this in we're going to select

import this in we're going to select that sheet one and this time instead of

that sheet one and this time instead of doing load or even the load two we're

doing load or even the load two we're actually going to go into transform data

actually going to go into transform data and this is now going to pop open the

and this is now going to pop open the power query editor and this is where all

power query editor and this is where all the magic happens behind the scenes in

the magic happens behind the scenes in order to get our data cleaned up so

order to get our data cleaned up so let's go over a quick overview of the

let's go over a quick overview of the window itself it's very similar to laid

window itself it's very similar to laid out to excel up at the top we have a

out to excel up at the top we have a ribbon with four different tabs of Home

ribbon with four different tabs of Home transform add columns and view we'll be

transform add columns and view we'll be walking through each one of these as we

walking through each one of these as we go through this lesson underneath here

go through this lesson underneath here on the Le hand side we have which query

on the Le hand side we have which query we're selected to once we're building

we're selected to once we're building multiple queries they'll start popping

multiple queries they'll start popping up underneath each other we can close

up underneath each other we can close this if we want and make more room is

this if we want and make more room is right here in the middle is what the

right here in the middle is what the current step or what the current status

current step or what the current status is is of our data set now yours may look

is is of our data set now yours may look a little bit different right now

a little bit different right now specifically I have this column

specifically I have this column distribution enabled underneath the view

distribution enabled underneath the view tab which I'm going to go to more in a

tab which I'm going to go to more in a second but anyway it basically outlines

second but anyway it basically outlines all the different columns or where we're

all the different columns or where we're at with the data set itself before we

at with the data set itself before we finally loaded in now right above this

finally loaded in now right above this area is a Formula bar just like similar

area is a Formula bar just like similar again to the Excel UI and this has all

again to the Excel UI and this has all the steps or all the code the M language

the steps or all the code the M language done in this current step if you will of

done in this current step if you will of actually cleaning up this data set and

actually cleaning up this data set and you're like step like what step well

you're like step like what step well over here on the right hand side we have

over here on the right hand side we have our query settings and in it we have the

our query settings and in it we have the name of our query and then we have the

name of our query and then we have the applied steps this lists all the

applied steps this lists all the different Transformations that we've

different Transformations that we've walked through so just a brief walkr the

walked through so just a brief walkr the first step is source and if I look at

first step is source and if I look at the formula bar basically what it's

the formula bar basically what it's doing is it's connecting to that Excel

doing is it's connecting to that Excel file with the file path that it has in

file with the file path that it has in the next step of navigation it's

the next step of navigation it's basically selecting hey out of that

basically selecting hey out of that Excel file actually select sheet one

Excel file actually select sheet one from there to actually load in then from

from there to actually load in then from there we can see that the headers are

there we can see that the headers are actually in the first row and not up at

actually in the first row and not up at the top so the next or third step is the

the top so the next or third step is the promote the headers up to the top and

promote the headers up to the top and then finally the last step is change

then finally the last step is change type it actually goes through and

type it actually goes through and assigns for each of these what data type

assigns for each of these what data type it is so in this case job title short it

it is so in this case job title short it assigns to type text whereas something

assigns to type text whereas something like job posted date it assigns to type

like job posted date it assigns to type number which needs to be a date which we

number which needs to be a date which we going to fix that in a little bit down

going to fix that in a little bit down at the bottom there's a few statistics

at the bottom there's a few statistics on this specifically talks about 16

on this specifically talks about 16 columns and over 999 rows and it tells

columns and over 999 rows and it tells you when the last preview is downloaded

you when the last preview is downloaded anyway if I just wanted to stop here

anyway if I just wanted to stop here with this data transformation if you

with this data transformation if you will I would just come up into home go

will I would just come up into home go into close and load we're just going to

into close and load we're just going to do close and load two and in this case

do close and load two and in this case like I'm just going to put in a pivot

like I'm just going to put in a pivot table

table specifically analyzing for job title

specifically analyzing for job title short specifically how many different

short specifically how many different counts or that we have of this we can

counts or that we have of this we can see totaling it all up have around

see totaling it all up have around 32,000 anyway that's a quick overview

32,000 anyway that's a quick overview let's actually get into exploring each

let's actually get into exploring each one of those tabs in the power query

one of those tabs in the power query editor so we're going to go back to data

editor so we're going to go back to data get data and from there you can just

get data and from there you can just select this of launch powerquery editor

select this of launch powerquery editor similarly you can also use a shortcut of

similarly you can also use a shortcut of just alt F12 I'm on a Mac so I have to

just alt F12 I'm on a Mac so I have to press option

press option but actually launching this up boom it

but actually launching this up boom it has it with just a shortcut anytime you

has it with just a shortcut anytime you launch it it may be grayed out here so

launch it it may be grayed out here so we need to make sure that we go in and

we need to make sure that we go in and actually select a query that we want to

actually select a query that we want to analyze and

transform for this overview we're going to start with the view tab because

to start with the view tab because mainly I want to get into actually how

mainly I want to get into actually how we can use the power query editor for

we can use the power query editor for Eda and thus save us a lot of time of

Eda and thus save us a lot of time of actually having to analyze it in Excel

actually having to analyze it in Excel in the spreadsheets itself instead we

in the spreadsheets itself instead we can do it right here so going through

can do it right here so going through this first thing is you can toggle on

this first thing is you can toggle on and off the formula bar I always leave

and off the formula bar I always leave the form on so I don't know why that's

the form on so I don't know why that's an option next is the data preview I can

an option next is the data preview I can change the font type I can also CH the

change the font type I can also CH the column quality so this is telling us if

column quality so this is telling us if there would be a potential error in here

there would be a potential error in here or if in this case of job location if

or if in this case of job location if there's empty values you typically have

there's empty values you typically have error values whenever the data type

error values whenever the data type isn't being being understood correctly

isn't being being understood correctly so in this case job tile short is text

so in this case job tile short is text everything in there is a text column if

everything in there is a text column if I were to change this to number press

I were to change this to number press enter to run I'm going to get errors all

enter to run I'm going to get errors all the way through here because well that

the way through here because well that was text and can't convert text to

was text and can't convert text to numbers also not sure why but it should

numbers also not sure why but it should say 100% error but it's not anyway they

say 100% error but it's not anyway they also have this green bar up at the top

also have this green bar up at the top and you can use this that's what I

and you can use this that's what I actually prefer so I'm going to unclick

actually prefer so I'm going to unclick on The View and changes from the con

on The View and changes from the con quality because you can actually look up

quality because you can actually look up here and see and then also togg it so in

here and see and then also togg it so in this case for salary or average it looks

this case for salary or average it looks like there's 60% of them are valid and

like there's 60% of them are valid and 40% are empty now remember this is only

40% are empty now remember this is only doing the data sets around 30,000 or

doing the data sets around 30,000 or 32,000 rows but it's only profiling so

32,000 rows but it's only profiling so down here on the bottom column profiling

down here on the bottom column profiling based on the top 1,000 rows so that's

based on the top 1,000 rows so that's all we're seeing right here if I wanted

all we're seeing right here if I wanted to see all of the data itself now

to see all of the data itself now depending on how big it is we may not

depending on how big it is we may not want to do this I can select this at the

want to do this I can select this at the bottom and column profiling based on

bottom and column profiling based on entire data set and it's going to reload

entire data set and it's going to reload back into here not sure how long it's

back into here not sure how long it's going to take now going over I can see

going to take now going over I can see there's 22,000 data sets of for data

there's 22,000 data sets of for data points of the salary year where 10,000

points of the salary year where 10,000 are empty the other thing that you may

are empty the other thing that you may have enabled by now is that column

have enabled by now is that column distribution to be able to see what are

distribution to be able to see what are the what is the breakdown of distinct

the what is the breakdown of distinct and also unique values investigating

and also unique values investigating what actually distinct unique means I

what actually distinct unique means I went back to the job tile short looks

went back to the job tile short looks like now it's actually picking up on all

like now it's actually picking up on all the different errors I'm going to

the different errors I'm going to actually change this back we don't want

actually change this back we don't want this to be number for job tile short

this to be number for job tile short we're going to change this back to text

we're going to change this back to text and I'm also going to refresh the

and I'm also going to refresh the preview by going to that Home tab

preview by going to that Home tab basically refreshing it to get it all

basically refreshing it to get it all cleaned up anyway if we recall from our

cleaned up anyway if we recall from our previous analysis there's 10 different

previous analysis there's 10 different job titles of sat senior data scientist

job titles of sat senior data scientist data engineers and whatnot and so that

data engineers and whatnot and so that is the 10 distinct values they're

is the 10 distinct values they're distinct because they have repetitive

distinct because they have repetitive values in here like right in here in six

values in here like right in here in six and 7 data engineer appears more than

and 7 data engineer appears more than once now if we go over to something like

once now if we go over to something like job country they have 111 distinct so

job country they have 111 distinct so meaning 111 countries that have multiple

meaning 111 countries that have multiple different countries and only 12

different countries and only 12 countries that have one value for it or

countries that have one value for it or one unique value all right the last

one unique value all right the last thing in data preview is column profile

thing in data preview is column profile and this is pretty neat right now I'm

and this is pretty neat right now I'm selected on the job tile short column

selected on the job tile short column it provides one on the left- hand side

it provides one on the left- hand side key statistics about the column and then

key statistics about the column and then two it actually shows a breakdown of the

two it actually shows a breakdown of the value distribution of it so this is

value distribution of it so this is really helpful in performing Eda if I

really helpful in performing Eda if I wanted to go through here and actually

wanted to go through here and actually see something so I can easily go in and

see something so I can easily go in and even see something like job country and

even see something like job country and see how United States has the majority

see how United States has the majority of the values and then how the different

of the values and then how the different other countries Fall underneath that now

other countries Fall underneath that now this takes up a lot of room and sort of

this takes up a lot of room and sort of valuable real estate so I find myself

valuable real estate so I find myself togging Ling this column profile on and

togging Ling this column profile on and off all right last few sections in this

off all right last few sections in this view tab go to column if you have a

view tab go to column if you have a large data set with a ton of columns you

large data set with a ton of columns you can just come down here select the

can just come down here select the column you want to go to and then it

column you want to go to and then it will navigate you to it parameters this

will navigate you to it parameters this is beyond the scope of this course we're

is beyond the scope of this course we're not going to be enabling parameters or

not going to be enabling parameters or even using them so we'll call This na

even using them so we'll call This na next is the advanced editor which allows

next is the advanced editor which allows us access to basically the behind the

us access to basically the behind the scenes of our am uh M language which

scenes of our am uh M language which we're going to be breaking down further

we're going to be breaking down further in an upcoming lesson so we're going to

in an upcoming lesson so we're going to save that but you can also access that

save that but you can also access that from the home menu in advanced editor as

from the home menu in advanced editor as well lastly is query dependencies

well lastly is query dependencies whenever it gets into complicated ways

whenever it gets into complicated ways that you're actually building your

that you're actually building your different queries and how they're

different queries and how they're connected to each other this is going to

connected to each other this is going to come in handy and this case we're

come in handy and this case we're showing that hey we connected to that

showing that hey we connected to that Excel file on my MacBook and we loaded

Excel file on my MacBook and we loaded it into a pivot

table all right next up is query settings I'm actually going to go ahead

settings I'm actually going to go ahead and close this out for queries over here

and close this out for queries over here anyway with the query settings we can

anyway with the query settings we can actually change the name of the query if

actually change the name of the query if we want to in this case is named sheet

we want to in this case is named sheet one I don't really like that I'm going

one I don't really like that I'm going to name it something like J jobs and I

to name it something like J jobs and I know it has salary data in it so I'm

know it has salary data in it so I'm going to have salary down here on the

going to have salary down here on the applied steps like we mentioned this is

applied steps like we mentioned this is a step through walkth through of each of

a step through walkth through of each of the individual steps that power query

the individual steps that power query has taken to actually clean up our data

has taken to actually clean up our data set now one thing I will call out in

set now one thing I will call out in this if I need to modify anything so in

this if I need to modify anything so in this case if I wanted to modify the data

this case if I wanted to modify the data source here I could come inside of here

source here I could come inside of here into the formula bar and edit it I would

into the formula bar and edit it I would encourage you if you're not familiar

encourage you if you're not familiar with the phone of the bar with using

with the phone of the bar with using that or comfortable using it instead

that or comfortable using it instead click click this settings icon over here

click click this settings icon over here on the right hand side and then

on the right hand side and then typically a window will pop up and allow

typically a window will pop up and allow you to edit it so I could technically

you to edit it so I could technically change the location of this or change

change the location of this or change what type of file it is the same for

what type of file it is the same for navigation as well I can basically pull

navigation as well I can basically pull back up that navigation window that I

back up that navigation window that I had before and change the sheet I wanted

had before and change the sheet I wanted to for the change type this doesn't

to for the change type this doesn't really have a gear icon next to it for

really have a gear icon next to it for us to edit so we're about to go through

us to edit so we're about to go through and actually change it but if we inspect

and actually change it but if we inspect the job posted date we'll see that here

the job posted date we'll see that here one it has it underneath the type number

one it has it underneath the type number but then actually looking at the column

but then actually looking at the column itself it's a number value because

itself it's a number value because remember Excel stores ex uh dates as

remember Excel stores ex uh dates as number values behind the scene well we

number values behind the scene well we could convert this to a date by typing

could convert this to a date by typing in date here but you may not be

in date here but you may not be comfortable doing that just yet anyway

comfortable doing that just yet anyway with that that's a great segue into the

with that that's a great segue into the Home tab into how actually we can change

Home tab into how actually we can change something like a data

type with the home typ we've already seen a lot of things already right we

seen a lot of things already right we saw the close and load too we also saw

saw the close and load too we also saw that I can go through and actually

that I can go through and actually refresh my query query to make sure that

refresh my query query to make sure that it's fully loaded and up to date if I

it's fully loaded and up to date if I have multiple queries I can not only do

have multiple queries I can not only do this refresh pery I can go to this

this refresh pery I can go to this refresh all and it does refresh of all

refresh all and it does refresh of all queries we've already seen Advanced

queries we've already seen Advanced edited before properties just allows us

edited before properties just allows us to actually go in and change the name of

to actually go in and change the name of this query if you want to and manage is

this query if you want to and manage is more advanced we'll be dive in that in a

more advanced we'll be dive in that in a little bit similar to Under The View tab

little bit similar to Under The View tab with goto column we also have this

with goto column we also have this option of choose column and go do column

option of choose column and go do column we can also just actually select a

we can also just actually select a column if you will so if I wanted to

column if you will so if I wanted to actually select job post to date or even

actually select job post to date or even more than that I can just do that and

more than that I can just do that and it's going to select it and it's going

it's going to select it and it's going to actually remove all the other columns

to actually remove all the other columns so which is not what we want to do which

so which is not what we want to do which brings us a good point if we want to get

brings us a good point if we want to get mid rid of a step all we have to do is

mid rid of a step all we have to do is come over to the applied steps and

come over to the applied steps and there's a red x mark that will appear

there's a red x mark that will appear over any step that you do so I'm just

over any step that you do so I'm just going to go ahead and click X here and

going to go ahead and click X here and it's going to remove anything that I've

it's going to remove anything that I've done moving on to remove columns which I

done moving on to remove columns which I think is pretty self-explanatory if you

think is pretty self-explanatory if you want to remove a column you just select

want to remove a column you just select it and you select remove column

it and you select remove column additionally if I want to remove all

additionally if I want to remove all other columns so in this case job title

other columns so in this case job title let's say I want to keep that I could

let's say I want to keep that I could select remove all other columns and it

select remove all other columns and it would do that I want to cancel this step

would do that I want to cancel this step so I'll click X similarly to remove

so I'll click X similarly to remove columns we have well keep rows and also

columns we have well keep rows and also remove rows and then we have options for

remove rows and then we have options for also sorting our values if we want to

also sorting our values if we want to sort them from a to z or Z to A

sort them from a to z or Z to A depending on a column so back to job

depending on a column so back to job post to date maybe I wanted them in

post to date maybe I wanted them in numerical order I could just click A to

numerical order I could just click A to Z and it would go through and actually

Z and it would go through and actually sort it anyway I don't really want to do

sort it anyway I don't really want to do this I'm going to clear this step as

this I'm going to clear this step as well this brings us actually into what

well this brings us actually into what we want to do of we want to change this

we want to do of we want to change this job posted date to a date time and

job posted date to a date time and that's we're going to use underneath

that's we're going to use underneath this transform section in the Home tab

this transform section in the Home tab right now this data type as I'm

right now this data type as I'm selecting this job posted dat it notices

selecting this job posted dat it notices that it's a decimal number I go to

that it's a decimal number I go to something like search location it

something like search location it changes to text so what I want to do is

changes to text so what I want to do is change this data type of decimal number

change this data type of decimal number to specifically a date time because

to specifically a date time because that's what we have in here we have date

that's what we have in here we have date and time now this popup is going to come

and time now this popup is going to come up if you're doing this underneath the

up if you're doing this underneath the step that has changed type already what

step that has changed type already what it's noticing is that the selected

it's noticing is that the selected column has an existing type conversion

column has an existing type conversion would you like to replace the existing

would you like to replace the existing conversion or basically preserve that as

conversion or basically preserve that as a number and add a separate step I'm

a number and add a separate step I'm just going to go ahead we're going to do

just going to go ahead we're going to do replace current but I just want to show

replace current but I just want to show what it looks like of adding another

what it looks like of adding another step in this case I converted it in this

step in this case I converted it in this step to a number and then the next step

step to a number and then the next step I converted it to a date time I don't

I converted it to a date time I don't like having a bunch of steps I want to

like having a bunch of steps I want to make this as concise as possible so I'm

make this as concise as possible so I'm going to clear that step instead and

going to clear that step instead and instead this time whenever we go through

instead this time whenever we go through it and select date time I'm going to say

it and select date time I'm going to say hey replace current now underneath here

hey replace current now underneath here it updated that job post to date type to

it updated that job post to date type to date time and it's all within one step

date time and it's all within one step love this similarly to that date time I

love this similarly to that date time I also want to convert the salary or

also want to convert the salary or average and the salary hour average

average and the salary hour average columns right now they're decimal

columns right now they're decimal numbers which is nothing wrong with that

numbers which is nothing wrong with that but I actually have the option to change

but I actually have the option to change it to something like a currency in this

it to something like a currency in this case once again I want to replace the

case once again I want to replace the current step for that I'm going to do

current step for that I'm going to do the same for salary hour average and

the same for salary hour average and change that to a currency as well for

change that to a currency as well for replace current covering briefly these

replace current covering briefly these other sections in the Home tab first up

other sections in the Home tab first up is merge and append we're going to be

is merge and append we're going to be covering an entire lesson on this and

covering an entire lesson on this and how we can actually take different Excel

how we can actually take different Excel files and different queries and combine

files and different queries and combine them together with this manage

them together with this manage parameters is outside the scope of this

parameters is outside the scope of this course I don't find myself ever really

course I don't find myself ever really doing this so not something we need to

doing this so not something we need to worry about data source settings similar

worry about data source settings similar to what we saw outside of the power qu

to what we saw outside of the power qu in Excel basically the same popup is

in Excel basically the same popup is going to come here to allow you to

going to come here to allow you to change where your data source is and

change where your data source is and then down here at the very end if we

then down here at the very end if we have wanted to put in a new query I

have wanted to put in a new query I wouldn't necessarily have to back out of

wouldn't necessarily have to back out of the power query editor I could just come

the power query editor I could just come in here and select a new source a file

in here and select a new source a file or database or other source and then

or database or other source and then work through actually importing it in in

work through actually importing it in in a query sometimes I find myself also

a query sometimes I find myself also using this one of enter data say I had a

using this one of enter data say I had a simple table that I wanted to input into

simple table that I wanted to input into Power query to have I could go through

Power query to have I could go through and just create that

table all right next up is the transform Tab and this one I feel is maybe

Tab and this one I feel is maybe actually although it looks like a lot of

actually although it looks like a lot of options it's probably one of the most

options it's probably one of the most simplest as you can see we have things

simplest as you can see we have things like text column number column date and

like text column number column date and time columns structured columns

time columns structured columns basically if we have a data type of this

basically if we have a data type of this we're going to go to you can go to if I

we're going to go to you can go to if I have a number column I want to go to

have a number column I want to go to this and see what things I could do to

this and see what things I could do to it such if I could do statistics to it I

it such if I could do statistics to it I could do rounding to it or I could even

could do rounding to it or I could even get information out of it if it's even

get information out of it if it's even or odd I also have this section on any

or odd I also have this section on any column that basically applies to any

column that basically applies to any column this is allows us to one like we

column this is allows us to one like we saw in the Home tab actually convert the

saw in the Home tab actually convert the data type of something but also even

data type of something but also even more advanced Transformations such as

more advanced Transformations such as pivoting and unpivoting columns which

pivoting and unpivoting columns which we're going to be diving deeper into in

we're going to be diving deeper into in the next lesson on Advanced

the next lesson on Advanced Transformations and finally we have this

Transformations and finally we have this section on tables which just does more

section on tables which just does more of generic things to this data set such

of generic things to this data set such as if I wanted to actually go through

as if I wanted to actually go through and count the rows on this could and I

and count the rows on this could and I find out I have 32,000 different rows on

find out I have 32,000 different rows on this anyway I actually want to transform

this anyway I actually want to transform a column of this specifically this job

a column of this specifically this job via column as you notice from here that

via column as you notice from here that all these different job platforms have

all these different job platforms have via and then a space right at the

via and then a space right at the beginning of it I want to actually

beginning of it I want to actually remove that so in order to do this I

remove that so in order to do this I make sure that one job via column is

make sure that one job via column is selected I notice up here in the any

selected I notice up here in the any columns it has the data type of text now

columns it has the data type of text now there are a few options in underneath

there are a few options in underneath the text column section for like

the text column section for like splitting columns I could split it by

splitting columns I could split it by this half and then delete that via but I

this half and then delete that via but I find actually the easiest way to do this

find actually the easiest way to do this is just go through this replace values

is just go through this replace values and we're not going to do replace errors

and we're not going to do replace errors we're going to just do replace values

we're going to just do replace values itself and we find a value in here in

itself and we find a value in here in this case we want to find VIA with a

this case we want to find VIA with a space and we want to replace it with

space and we want to replace it with well nothing if I wanted to go into

well nothing if I wanted to go into advanced options and I have a few

advanced options and I have a few different selections available but

different selections available but neither of these applicable does so

neither of these applicable does so we're going to just go ahead and click

we're going to just go ahead and click okay and Bam now we have these job

okay and Bam now we have these job platforms cleared up now we've been

platforms cleared up now we've been going through this and keeping the names

going through this and keeping the names of these steps the same but sometimes I

of these steps the same but sometimes I like to be more descriptive in when it's

like to be more descriptive in when it's not a general tyag now it named this new

not a general tyag now it named this new Step replaced values I may actually do

Step replaced values I may actually do that a few times and I want to be able

that a few times and I want to be able to whenever I go back to this actually

to whenever I go back to this actually be able to identify what steps did what

be able to identify what steps did what in this case change type promoted

in this case change type promoted headers navigation Source those are all

headers navigation Source those are all only usually typically done once so I

only usually typically done once so I know what that means however however for

know what that means however however for this one I don't know so I'm going to

this one I don't know so I'm going to right click it and go to rename and I'll

right click it and go to rename and I'll say this is replaced via in job via

say this is replaced via in job via which is much more descriptive in my

opinion all right only one more tab to cover and that is the add column with

cover and that is the add column with transform we transformed a current

transform we transformed a current column with ADD column we're adding

column with ADD column we're adding additional column to this similar

additional column to this similar transform it has these options for text

transform it has these options for text number and also date and time so very

number and also date and time so very familiar features with this so let's say

familiar features with this so let's say I wanted to extract the month and the

I wanted to extract the month and the year out of the job posted date column

year out of the job posted date column basically I want to Callum for month and

basically I want to Callum for month and I want to Callum for Year anyway

I want to Callum for Year anyway previously we learned with that

previously we learned with that transform tab if I were to come into

transform tab if I were to come into here under date time and then select

here under date time and then select something like month it's going to

something like month it's going to transform this tab so it's going to get

transform this tab so it's going to get rid of the contents of the job posted

rid of the contents of the job posted date is not necessarily what I want I

date is not necessarily what I want I want a new column so I'm going to

want a new column so I'm going to actually get rid of this Stu so with ADD

actually get rid of this Stu so with ADD column what this does is with that job

column what this does is with that job posted date column selected I select

posted date column selected I select date in this case I want month I could

date in this case I want month I could do start a month end of month day of

do start a month end of month day of month whatever I just want the month

month whatever I just want the month itself and then inserted month is pretty

itself and then inserted month is pretty descriptive I however don't like the

descriptive I however don't like the name of this so I could come in here

name of this so I could come in here this is an option and change I double

this is an option and change I double clicked on this and name this job posted

clicked on this and name this job posted month and then press enter now with this

month and then press enter now with this I'm going to get a renamed columns here

I'm going to get a renamed columns here so now I have two steps of this month

so now I have two steps of this month was inserted into this and then we

was inserted into this and then we rename the column I would encourage you

rename the column I would encourage you to minimize the amount of steps you have

to minimize the amount of steps you have because these queries can get quite long

because these queries can get quite long in this case I'm going to delete this

in this case I'm going to delete this rename column go back to this inserted

rename column go back to this inserted month if we actually re read this you

month if we actually re read this you don't actually need to understand what's

don't actually need to understand what's going on much in here but I can see

going on much in here but I can see basically that we have this month in

basically that we have this month in quotation marks and this is named month

quotation marks and this is named month so I basically can reason that this is

so I basically can reason that this is probably the new column title of this so

probably the new column title of this so instead of using month I'm just going to

instead of using month I'm just going to edit this in the formula bar to job

edit this in the formula bar to job posted month then I'm going to click at

posted month then I'm going to click at the end and press enter and now all

the end and press enter and now all within one step I inserted that month

within one step I inserted that month and renamed it as well if you're not

and renamed it as well if you're not comfortable doing that feel free to go

comfortable doing that feel free to go through that next step of actually

through that next step of actually double clicking this and actually

double clicking this and actually changing it but I would encourage you if

changing it but I would encourage you if you can actually try to mess around with

you can actually try to mess around with the formula if you make a mistake it's

the formula if you make a mistake it's pretty simple to just X out of that step

pretty simple to just X out of that step and then redo it again so there's no

and then redo it again so there's no harm to your actual data set now

harm to your actual data set now similarly if I wanted to create that job

similarly if I wanted to create that job posted year column I could just go

posted year column I could just go through here select year whether I want

through here select year whether I want start year end of year year itself once

start year end of year year itself once again it inserts year and then I would

again it inserts year and then I would want to change the name of this and

want to change the name of this and change this to job posted year and then

change this to job posted year and then click enter and Bam now we have it I

click enter and Bam now we have it I don't actually need this all these are

don't actually need this all these are from 2023 I don't actually this is not

from 2023 I don't actually this is not going to provide any useful data for me

going to provide any useful data for me so I'm actually going to delete this

Stu all right I want to do one last transformation before we actually load

transformation before we actually load this and going to actually visualize

this and going to actually visualize this so we have our salary year average

this so we have our salary year average column and then also want to compare

column and then also want to compare this to the salary hour average column

this to the salary hour average column but right this is on a yearly basis this

but right this is on a yearly basis this is on an hourly basis what we could do

is on an hourly basis what we could do is do a conversion to our salary hour

is do a conversion to our salary hour average column to get it to an equal

average column to get it to an equal value or comparable value to our yearly

value or comparable value to our yearly value meaning we could put the number of

value meaning we could put the number of hours in a year multiply it times this

hours in a year multiply it times this value and from there get what would be

value and from there get what would be the expected yearly salary for this hour

the expected yearly salary for this hour data so I could do this via the

data so I could do this via the transform tab right going into that

transform tab right going into that number column under standard we want to

number column under standard we want to actually multiply and then there's 2080

actually multiply and then there's 2080 hours in a year working hours for 40

hours in a year working hours for 40 hours of work week I could go through

hours of work week I could go through and actually do that and that's going to

and actually do that and that's going to update this column itself but remember

update this column itself but remember we probably want its own column so I'm

we probably want its own column so I'm not going to use that instead we'll go

not going to use that instead we'll go to add column with this

to add column with this hour average column selected select

hour average column selected select standard multiply put in those hours of

standard multiply put in those hours of 2080 and then click okay once again I'm

2080 and then click okay once again I'm going to rename this I can see that this

going to rename this I can see that this multiplication column is titled this via

multiplication column is titled this via in this step right here so I'm going to

in this step right here so I'm going to rename it to salary hour adjusted and in

rename it to salary hour adjusted and in this case I'm going to also rename this

this case I'm going to also rename this step to adjusted hourly salary to yearly

step to adjusted hourly salary to yearly now I'm sort of a stickler for keeping

now I'm sort of a stickler for keeping my data set in order right now I have

my data set in order right now I have this job posted month and it's sort of

this job posted month and it's sort of right away from it's pretty far away

right away from it's pretty far away from my job posted date I would actually

from my job posted date I would actually want to move it right next to it so

want to move it right next to it so there's a couple options I can do to

there's a couple options I can do to move it I can select the column and then

move it I can select the column and then come up here to the transform Tab and

come up here to the transform Tab and move go left right to beginning to end

move go left right to beginning to end or I can actually just take it and then

or I can actually just take it and then drag it and this is taking forever it's

drag it and this is taking forever it's like paint dry but find where I want it

like paint dry but find where I want it boom plant it in and then inserted the

boom plant it in and then inserted the step of reordered columns I'm going to

step of reordered columns I'm going to do the same thing with salary hour

do the same thing with salary hour adjusted and put it right next to salary

adjusted and put it right next to salary hour average and both of these done with

hour average and both of these done with one step of reordered columns so I'm

one step of reordered columns so I'm fine with

that so now let's actually get into analyzing this specifically I want to be

analyzing this specifically I want to be able to analyze and compare this salary

able to analyze and compare this salary hour adjusted column that we just

hour adjusted column that we just created compared to the salary year

created compared to the salary year average so going back to home I'm going

average so going back to home I'm going to close and load this in we have this

to close and load this in we have this previous analysis that we did before

previous analysis that we did before doing Eda on the jobs actually want to

doing Eda on the jobs actually want to create my own from scratch all right so

create my own from scratch all right so back on sheet one we can see our queries

back on sheet one we can see our queries connection specifically that data job

connection specifically that data job salary remember the data tab you can go

salary remember the data tab you can go into that and it can toggle on all that

into that and it can toggle on all that queries and connections anyway we want

queries and connections anyway we want to insert I want to analyze that hourly

to insert I want to analyze that hourly adjusted salary so I'm going to come in

adjusted salary so I'm going to come in to create a pivot chart we also do pivot

to create a pivot chart we also do pivot chart and pivot table at the same time

chart and pivot table at the same time anyway when this pops up for pivot table

anyway when this pops up for pivot table or pivot charts we want to we're not

or pivot charts we want to we're not going to select a table AR range because

going to select a table AR range because this is a power query connection if you

this is a power query connection if you will we're going to use this external

will we're going to use this external data source and we're going to say

data source and we're going to say choose connection what connection do we

choose connection what connection do we want to use for this specifically I want

want to use for this specifically I want to use that DOA job salary so go ahead

to use that DOA job salary so go ahead and click that and open and we're going

and click that and open and we're going to insert it into the existing worksheet

to insert it into the existing worksheet so now the pivot table set up for us go

so now the pivot table set up for us go forward to do one quick note you may be

forward to do one quick note you may be tempted say if we went back to jobs Eda

tempted say if we went back to jobs Eda to rightclick this and then go load to

to rightclick this and then go load to and let's say hey I wanted to create a

and let's say hey I wanted to create a new pivot chart well the problem is is

new pivot chart well the problem is is going to then get rid of this pivot

going to then get rid of this pivot table that we previously created so you

table that we previously created so you don't want to necessarily if you want to

don't want to necessarily if you want to keep this you don't want to actually do

keep this you don't want to actually do that back to the pivot table itself

that back to the pivot table itself you'll notice now because we have these

you'll notice now because we have these queries and connections but you can

queries and connections but you can toggle between the two over here on the

toggle between the two over here on the right hand side anyway what I want to

right hand side anyway what I want to compare is that salary hour adjusted to

compare is that salary hour adjusted to that salary year average right now it's

that salary year average right now it's doing sums we don't want that we do

doing sums we don't want that we do eventually we're go to Value fail

eventually we're go to Value fail settings we're going to do average here

settings we're going to do average here we're eventually going to do median I

we're eventually going to do median I promise you but we're going to STi for

promise you but we're going to STi for average for the time being I'll adjust

average for the time being I'll adjust both of these to be of average then I'm

both of these to be of average then I'm not really liking the formatting here I

not really liking the formatting here I know we adjusted it as currency back in

know we adjusted it as currency back in the the power query but this is the one

the the power query but this is the one data type that I find doesn't actually

data type that I find doesn't actually follow through in actually making into

follow through in actually making into the correct data type when you import it

the correct data type when you import it into Excel so you do need to go back

into Excel so you do need to go back still and actually convert it into the

still and actually convert it into the correct thing anyway we're seeing that

correct thing anyway we're seeing that the hourly salary is much less than the

the hourly salary is much less than the yearly salary and moving this over we

yearly salary and moving this over we can also see this via visualization this

can also see this via visualization this doesn't really show as much I would

doesn't really show as much I would rather look at this when compared to job

rather look at this when compared to job type

type so I'm going to go ahead and grab job

so I'm going to go ahead and grab job title short and throw it into the axis

title short and throw it into the axis now closing out of this and then closing

now closing out of this and then closing out of this on the side we can now get a

out of this on the side we can now get a better view of this I'm not liking the

better view of this I'm not liking the format of this pivot chart specifically

format of this pivot chart specifically I'm going to go in here design under

I'm going to go in here design under change chart type and change this to a

change chart type and change this to a bar chart I feel like it's going to be

bar chart I feel like it's going to be easier to read yeah it's a lot easier to

easier to read yeah it's a lot easier to read also for these visualizations I'm

read also for these visualizations I'm going to rightclick this and I'm going

going to rightclick this and I'm going to say hide all field button so that

to say hide all field button so that make this easier to view and I'm going

make this easier to view and I'm going to go ahead and stick The Legend at the

to go ahead and stick The Legend at the bottom okay we're off to a good start

bottom okay we're off to a good start other things I want to do to clean this

other things I want to do to clean this up is oh my goodness this is so long I'm

up is oh my goodness this is so long I'm going to change these column titles to

going to change these column titles to hourly adjusted salary and then yearly

hourly adjusted salary and then yearly salary additionally I want to sort this

salary additionally I want to sort this a little bit better specifically from

a little bit better specifically from high to low so under sort options more

high to low so under sort options more sort options I'm going to go into

sort options I'm going to go into sorting this as sending based on the

sorting this as sending based on the year L salary from high to low sorry

year L salary from high to low sorry that's actually descending selecting

that's actually descending selecting year salary clicking okay no it was

year salary clicking okay no it was right the first time it's ascending okay

right the first time it's ascending okay this is looking good you know also I

this is looking good you know also I don't like having different colors I

don't like having different colors I like actually going with a consistent

like actually going with a consistent theme so going into design change colors

theme so going into design change colors I'll change this to this monochromatic

I'll change this to this monochromatic pallette 8 and Bam we now have our final

pallette 8 and Bam we now have our final visualization that we use power query to

visualization that we use power query to basically ingest all our data in clean

basically ingest all our data in clean it up create this new column of hourly

it up create this new column of hourly adjusted salary perform an analysis in

adjusted salary perform an analysis in Excel to average it and we can see that

Excel to average it and we can see that consistently the hourly salary is well

consistently the hourly salary is well below that of the yearly salary so I

below that of the yearly salary so I guess it pays to have a salary job all

guess it pays to have a salary job all right we have some practice problems for

right we have some practice problems for you to now go through and test out all

you to now go through and test out all these different features and get more

these different features and get more familiar with the power query editor in

familiar with the power query editor in the next lesson we're going to be going

the next lesson we're going to be going into advanced Transformations and Diving

into advanced Transformations and Diving deeper specifically in analyzing skills

deeper specifically in analyzing skills and using power query to actually clean

and using power query to actually clean it up so where we can actually analyze

it up so where we can actually analyze skills with that see you in that

one all right welcome to this lesson we're going to continue on with power

we're going to continue on with power query specifically focusing on using

query specifically focusing on using more advanced Transformations and for

more advanced Transformations and for this we're actually going to get into

this we're actually going to get into analyzing those skills and being able to

analyzing those skills and being able to put them on a graph and actually

put them on a graph and actually visualize what are the top skills of

visualize what are the top skills of data nerds now if you recall way back in

data nerds now if you recall way back in the functions and formulas chapter when

the functions and formulas chapter when we went over text functions we did a

we went over text functions we did a little bit of text cleanup to clean up

little bit of text cleanup to clean up this column and then plot it but we were

this column and then plot it but we were only able to do that with around 20 rows

only able to do that with around 20 rows now with the power of power query we're

now with the power of power query we're actually going to be able to clean up

actually going to be able to clean up all these values and be able to

all these values and be able to visualize it for all 30,000 job post

visualize it for all 30,000 job post so let's jump in if you want to you can

so let's jump in if you want to you can continue on from that worksheet that we

continue on from that worksheet that we used in the previous lesson and just

used in the previous lesson and just make sure that you do go through and

make sure that you do go through and actually save it before you continue on

actually save it before you continue on however if you got lost in the way or

however if you got lost in the way or you just don't have that file anymore

you just don't have that file anymore feel free to use the lesson or the file

feel free to use the lesson or the file from the last lesson of power query Eder

from the last lesson of power query Eder once again you don't want to be using

once again you don't want to be using the actual one working cuz that has the

the actual one working cuz that has the final results we're going to want to

final results we're going to want to work with that one and this has all the

work with that one and this has all the different work that we did it also has

different work that we did it also has some some additional analysis whenever I

some some additional analysis whenever I looked at plotting it over time to see

looked at plotting it over time to see if how the salary of yearly versus

if how the salary of yearly versus hourly

compared anyway let's get into editing this and we can get to the power query

this and we can get to the power query editor by going up to get data launch

editor by going up to get data launch power query or pressing alt F12 once it

power query or pressing alt F12 once it loads and need to click on the query

loads and need to click on the query that I actually want to look at and I'm

that I actually want to look at and I'm going to close this or minimize this the

going to close this or minimize this the first thing that I want to do is start

first thing that I want to do is start an index column on this data set because

an index column on this data set because in general whenever you have a source

in general whenever you have a source data set or a fact table like this is

data set or a fact table like this is you want to have an index associated

you want to have an index associated with it yeah these row numbers are good

with it yeah these row numbers are good but that's not good enough and we'll be

but that's not good enough and we'll be using it more in the power pivot chapter

using it more in the power pivot chapter but it's good practice to start it now

but it's good practice to start it now so moving over to the add column tab I'm

so moving over to the add column tab I'm going to go to index column it allows us

going to go to index column it allows us to start from either zero or one I'm a

to start from either zero or one I'm a coder so I like from zero now Pro tip I

coder so I like from zero now Pro tip I want this index at the front now I could

want this index at the front now I could go to to transform and then move and

go to to transform and then move and then move this to the beginning but

then move this to the beginning but remember we did this reordered columns

remember we did this reordered columns right here so what I'm actually going to

right here so what I'm actually going to do is take this added index put it

do is take this added index put it before reordered columns now that the

before reordered columns now that the reordered columns is right there

reordered columns is right there whenever I select this index and move

whenever I select this index and move this over to beginning it's going to be

this over to beginning it's going to be included in part of this step of all of

included in part of this step of all of our column reord so I don't have once

our column reord so I don't have once again multiple different reordered

again multiple different reordered columns

all right in order to clean up this job skills column we're going to end up

skills column we're going to end up being putting this uh these skills right

being putting this uh these skills right now they're separated by column inside

now they're separated by column inside of this list we're going to be breaking

of this list we're going to be breaking them up into their own individual rows

them up into their own individual rows and because we're breaking this up into

and because we're breaking this up into different rows this now is going to put

different rows this now is going to put for this Row one value here this is

for this Row one value here this is going to make 1 2 3 4 5 6 7 this is

going to make 1 2 3 4 5 6 7 this is going to make seven different rows of

going to make seven different rows of data this is going to mess up anytime we

data this is going to mess up anytime we want to analyze anything because imagine

want to analyze anything because imagine if you have like a salary data it's then

if you have like a salary data it's then going to appear seven times so the main

going to appear seven times so the main point of explaining that is we want a

point of explaining that is we want a new query to actually populate and

new query to actually populate and actually break these skills out into

actually break these skills out into their own separate rows so in order to

their own separate rows so in order to create a query or another query right

create a query or another query right now we have queries one to create

now we have queries one to create another query from this we have two

another query from this we have two options and that's underneath Home tab

options and that's underneath Home tab they have manage and we can either

they have manage and we can either delete a query which we're not going to

delete a query which we're not going to do we can either duplicate it or

do we can either duplicate it or reference it I can also get to this by

reference it I can also get to this by just right-clicking the query and it

just right-clicking the query and it also has these of duplicate and

also has these of duplicate and reference let's actually look at both of

reference let's actually look at both of those starting with duplicate first so

those starting with duplicate first so I've created my duplicate query and as

I've created my duplicate query and as you can see it basically has a duplicate

you can see it basically has a duplicate of the original query nothing really has

of the original query nothing really has changed from it now this is cool if I

changed from it now this is cool if I want to walk through all the different

want to walk through all the different steps again and I wanted to have it in

steps again and I wanted to have it in this new query but I actually like this

this new query but I actually like this other option so I'm going to go to data

other option so I'm going to go to data job salary this CL I'm going to go down

job salary this CL I'm going to go down select reference okay this query this

select reference okay this query this one named three is referencing data job

one named three is referencing data job seller and it only has one applied step

seller and it only has one applied step if we look at the applied step all it is

if we look at the applied step all it is doing is referencing the data jobs

doing is referencing the data jobs salary so this first query right now and

salary so this first query right now and populating it for us and this is really

populating it for us and this is really good because say now I make changes to

good because say now I make changes to the original query such as say I want to

the original query such as say I want to go through and I don't want any any more

go through and I don't want any any more of the hourly data in here I only want

of the hourly data in here I only want the yearly data so I filter down to only

the yearly data so I filter down to only have the yearly data so now it's

have the yearly data so now it's filtered these rows for the yearly data

filtered these rows for the yearly data don't worry we're actually not going to

don't worry we're actually not going to do this I'm going to delete this Stu but

do this I'm going to delete this Stu but anyway if I go to that duplicated query

anyway if I go to that duplicated query the one with the three at the end this

the one with the three at the end this one only has year values in it this I

one only has year values in it this I can verify is 100% yearly by looking

can verify is 100% yearly by looking either the column distribution or the

either the column distribution or the column profile everything is your anyway

column profile everything is your anyway we don't actually want to do that step

we don't actually want to do that step so I'm going to go back to this original

so I'm going to go back to this original query clear the filtered rows and once

query clear the filtered rows and once again it's going to just clean this back

again it's going to just clean this back up to have two distinct values so

up to have two distinct values so compare checking the S rate yearly and

compare checking the S rate yearly and also hourly okay so we like the

also hourly okay so we like the reference for our case cuz I like we may

reference for our case cuz I like we may make changes to the original one so I'm

make changes to the original one so I'm going to delete this number two because

going to delete this number two because remember that was the duplicate and

remember that was the duplicate and we're going to keep the number three one

we're going to keep the number three one which was the reference we're also going

which was the reference we're also going to be doing all our alterations on the

to be doing all our alterations on the skills on this one so I'm going to to

skills on this one so I'm going to to rename this one data jobs

skills so with this new query data jobs skills let's actually get into cleaning

skills let's actually get into cleaning up this column of data of job skills

up this column of data of job skills specifically we're going to be

specifically we're going to be separating this into each of these

separating this into each of these skills into the new rows by this comma

skills into the new rows by this comma delimiter but we need to remove a few

delimiter but we need to remove a few things from this specifically this has

things from this specifically this has brackets around it and it also has

brackets around it and it also has single quotes we don't need any of that

single quotes we don't need any of that we need to remove it so going to that

we need to remove it so going to that transform tab we're going to go into

transform tab we're going to go into replace values and we've done this

replace values and we've done this before so for the value defin I'm going

before so for the value defin I'm going to just start with the first square

to just start with the first square bracket we want to replace with nothing

bracket we want to replace with nothing I'm going to click okay additionally we

I'm going to click okay additionally we want to replace the other bracket as

want to replace the other bracket as well replace it with a blank and then

well replace it with a blank and then finally we want to replace that single

finally we want to replace that single quote as well also I'm going to just

quote as well also I'm going to just rename these all next thing we going to

rename these all next thing we going to do is actually split these columns on

do is actually split these columns on this delimiter of a comma so under

this delimiter of a comma so under transform we can go here to split column

transform we can go here to split column it has a few different options by

it has a few different options by delimiter number of characters by

delimiter number of characters by positions we can go to by delimiter I'm

positions we can go to by delimiter I'm going to select that for this we're

going to select that for this we're going to use a comma delimiter because

going to use a comma delimiter because there's multiple different options you

there's multiple different options you could potentially use for this we want

could potentially use for this we want to split at not just the leftmost but we

to split at not just the leftmost but we want to split at each occurrence there's

want to split at each occurrence there's no quote characters in here we removed

no quote characters in here we removed all the quote characters so I'm going to

all the quote characters so I'm going to click none and then click okay so now we

click none and then click okay so now we just split these skills into let's see

just split these skills into let's see how many different columns we have here

how many different columns we have here looks like we have up to 24 skills for

looks like we have up to 24 skills for all these different skills that we have

all these different skills that we have so now what we need to do to get all of

so now what we need to do to get all of these if you will skills within a single

these if you will skills within a single column we need to unpivot them but the

column we need to unpivot them but the one issue right now so I have all these

one issue right now so I have all these skills right here but we also have all

skills right here but we also have all these other columns right here I don't

these other columns right here I don't really care about all them just I don't

really care about all them just I don't really care about around too much I want

really care about around too much I want to mainly just analyze job title short

to mainly just analyze job title short and indexed so what I'm going to do to

and indexed so what I'm going to do to make this easier because I need to

make this easier because I need to basically select which columns I want to

basically select which columns I want to remove or which ones I don't want to

remove or which ones I don't want to remove in this case so what I'm going to

remove in this case so what I'm going to do is go back to source and this one has

do is go back to source and this one has before we actually broken up the job

before we actually broken up the job skills so I'm going to select job skills

skills so I'm going to select job skills hold down control and then from there

hold down control and then from there select job title short and also index

select job title short and also index and then underneath the Home tab we're

and then underneath the Home tab we're going to go to remove call s what we're

going to go to remove call s what we're going to do remove other columns

going to do remove other columns basically going to keep those three

basically going to keep those three columns that we have now we are doing

columns that we have now we are doing this in the applied steps after that

this in the applied steps after that first step of source so it's asking hey

first step of source so it's asking hey do we want to insert this step yes we do

do we want to insert this step yes we do and so now we've limited it down to

and so now we've limited it down to those three columns and Bam now whenever

those three columns and Bam now whenever we go down here down to that last step

we go down here down to that last step of change type we can see that we have

of change type we can see that we have all our different job skills and then

all our different job skills and then over on the right hand side we have our

over on the right hand side we have our index and our job tile short which I

index and our job tile short which I don't really like the order of this I'm

don't really like the order of this I'm actually going to go back to reorder

actually going to go back to reorder this over here I'm going to just take

this over here I'm going to just take these column values and then put them in

these column values and then put them in this order of index job title short and

this order of index job title short and job skills so now we actually get into

job skills so now we actually get into unpivoting these job skills columns

unpivoting these job skills columns basically making all these job skills

basically making all these job skills into one column so I'm going to select

into one column so I'm going to select instead of selecting all the job skills

instead of selecting all the job skills column I'm actually going to select the

column I'm actually going to select the opposite holding control select the

opposite holding control select the index and job title short and I'm going

index and job title short and I'm going to go into to transform tab into unpivot

to go into to transform tab into unpivot columns and for this one once again

columns and for this one once again we're going to use the other we want to

we're going to use the other we want to unpivot other columns and go ahead and

unpivot other columns and go ahead and do this all right so what we do here we

do this all right so what we do here we now have this new column of attribute

now have this new column of attribute and value attribute if we go back that

and value attribute if we go back that is just the name of the column that was

is just the name of the column that was created previously and then the value is

created previously and then the value is what was in the cell itself and that's

what was in the cell itself and that's filled with all the skills so personally

filled with all the skills so personally I don't really care for use of this

I don't really care for use of this attribute so I'm going to go ahead and

attribute so I'm going to go ahead and just remove this column by right

just remove this column by right clicking and selecting it additionally

clicking and selecting it additionally I'm going to go back up here and I don't

I'm going to go back up here and I don't want this to be named value so I can go

want this to be named value so I can go in and inspect this under unpivot other

in and inspect this under unpivot other columns I can see in here that it

columns I can see in here that it renames these columns attribute and

renames these columns attribute and value in this case I don't want to be

value in this case I don't want to be value like I said I want to be job

value like I said I want to be job skills clicking enter boom renamed it to

skills clicking enter boom renamed it to job skills and then in here it is job

job skills and then in here it is job skills

skills now one thing that's bothering me real

now one thing that's bothering me real quick before we continue on to actually

quick before we continue on to actually visualizing this data is this column

visualizing this data is this column here typically I like to name things

here typically I like to name things something like job uncore whatever it is

something like job uncore whatever it is in this case index I want to Name jobor

in this case index I want to Name jobor ID but if you recall back we created

ID but if you recall back we created this back in this data jobs salary

this back in this data jobs salary portion especially here under the step

portion especially here under the step of added index I want to change this

of added index I want to change this from index as we've done before going in

from index as we've done before going in and renaming it to job ID however

and renaming it to job ID however whenever I do this press enter this is

whenever I do this press enter this is going to break my queries and this is

going to break my queries and this is going to happen to you anytime you're

going to happen to you anytime you're manipulating it so I think we need to

manipulating it so I think we need to get familiar with it so if I go to the

get familiar with it so if I go to the next step of reorder columns we're going

next step of reorder columns we're going to have this expression error the column

to have this expression error the column index of the table wasn't found duh

index of the table wasn't found duh because we named it job ID in the

because we named it job ID in the previous step instead of index but this

previous step instead of index but this step is still the same so what I can do

step is still the same so what I can do is come in here change index to job ID

is come in here change index to job ID press enter and Bam that updates but

press enter and Bam that updates but then now going to data job skills we're

then now going to data job skills we're going to have the same thing you're

going to have the same thing you're going to notice with this one right the

going to notice with this one right the column index the tail wasn't found index

column index the tail wasn't found index so same error message what we want to do

so same error message what we want to do you can do is go to error it's going to

you can do is go to error it's going to go to the first occurrence of that error

go to the first occurrence of that error in this is trying to reference index we

in this is trying to reference index we if you call back from if we go to the

if you call back from if we go to the first step of source we expect it to be

first step of source we expect it to be called job ID now because we renamed it

called job ID now because we renamed it right so I'm going to change this to job

right so I'm going to change this to job ID and then scrolling through the

ID and then scrolling through the applied steps to see whenever we get to

applied steps to see whenever we get to our next error if there is an error and

our next error if there is an error and that's unpivot other columns

that's unpivot other columns specifically they have job title short

specifically they have job title short and index I don't want index here I want

and index I don't want index here I want job ID and now bam now we have it

job ID and now bam now we have it cleaned so I should have done that job

cleaned so I should have done that job ID but that was actually good

ID but that was actually good troubleshooting to walk through that you

troubleshooting to walk through that you may

encounter so let's actually get into visualizing this so we're going to go to

visualizing this so we're going to go to home and we're going to close and we're

home and we're going to close and we're going to close and load

going to close and load now it's popping up as a table but we

now it's popping up as a table but we actually want to analyze this I don't

actually want to analyze this I don't really care to have it as a table so I'm

really care to have it as a table so I'm going to right click it and I'm going

going to right click it and I'm going click load to specifically we're going

click load to specifically we're going to go to a pivot chart and we'll insert

to go to a pivot chart and we'll insert in the existing worksheet because we're

in the existing worksheet because we're going to get rid of that data yes

going to get rid of that data yes there's going to be possible data loss

there's going to be possible data loss we understand that so I'm going move

we understand that so I'm going move this chart off to the side select inside

this chart off to the side select inside the pivot table and we want to analyze

the pivot table and we want to analyze the job skills so I'm going to take the

the job skills so I'm going to take the job skills put them in rows and then the

job skills put them in rows and then the job skills also in the values to to

job skills also in the values to to count up the values then also I'm going

count up the values then also I'm going to sort them I want to sound them from

to sort them I want to sound them from high to low so I went to more sort

high to low so I went to more sort options um we're doing a descending

options um we're doing a descending order count of job skills so now there's

order count of job skills so now there's a ton of different skills in here but

a ton of different skills in here but want you to inspect this if you notice

want you to inspect this if you notice one these skills have sometimes have

one these skills have sometimes have spaces in the front of them basically we

spaces in the front of them basically we didn't do a full cleanup of this so

didn't do a full cleanup of this so that's why we have python twice in here

that's why we have python twice in here is cuz this one has a space of it so

is cuz this one has a space of it so opening up the power query editor by

opening up the power query editor by playing by pressing alt F12 so

playing by pressing alt F12 so underneath the data job skills query I'm

underneath the data job skills query I'm going to go ahead and we want to do a

going to go ahead and we want to do a text

text transformation specifically if we look

transformation specifically if we look underneath this underneath for format we

underneath this underneath for format we can change this to lower case upload

can change this to lower case upload case capitalize each word we're going to

case capitalize each word we're going to do trim which removes leading and

do trim which removes leading and trailing white space from each of the

trailing white space from each of the cells in the selected cell from there

cells in the selected cell from there we'll go back to home close and load

we'll go back to home close and load this and now it's going to be reloading

this and now it's going to be reloading the data and those duplicate values are

the data and those duplicate values are now going to be removed now there's a

now going to be removed now there's a lot of skills here so I really only want

lot of skills here so I really only want to see the top 10 so I'm going to put a

to see the top 10 so I'm going to put a filter on here go into value filters and

filter on here go into value filters and top one specifically want to see the top

top one specifically want to see the top 10 items by count of job skills also I'm

10 items by count of job skills also I'm going to rename this to skill count and

going to rename this to skill count and because these are text values down here

because these are text values down here I'm actually going to change this from a

I'm actually going to change this from a column chart going to change chart type

column chart going to change chart type into a bar chart instead clicking okay

into a bar chart instead clicking okay boom and then with this obviously it's

boom and then with this obviously it's not sorted from high to low that's how I

not sorted from high to low that's how I want actually to sort it so I'm going to

want actually to sort it so I'm going to go in here back underneath our more sort

go in here back underneath our more sort options Chang this from descending to

options Chang this from descending to ascending and the good thing about this

ascending and the good thing about this is we still have that top 10 filter on

is we still have that top 10 filter on it so it's still going to apply this and

it so it's still going to apply this and have the top 10 values on there first

have the top 10 values on there first last little clean up I'm going to hide

last little clean up I'm going to hide all field buttons I'm going to get rid

all field buttons I'm going to get rid of this Legend right here and and then

of this Legend right here and and then I'm going to rename this to what are the

I'm going to rename this to what are the top skills of data

nerds now let's say that I'm frequently referencing the top 10 skills as we have

referencing the top 10 skills as we have right here and instead of having to

right here and instead of having to populate this every single time I want

populate this every single time I want to actually create a own or create a

to actually create a own or create a query for this so opening power query

query for this so opening power query going to alt F12 I could do the same

going to alt F12 I could do the same analysis inside of power query query and

analysis inside of power query query and get this into its own table to be reused

get this into its own table to be reused but for this I don't want to use this

but for this I don't want to use this data job skills query instead like we

data job skills query instead like we did before I'm going to create a new

did before I'm going to create a new query we're not going to duplicate this

query we're not going to duplicate this instead we're going to reference it so

instead we're going to reference it so now it's Unique and distinct and I'll

now it's Unique and distinct and I'll rename this data jobs skill count

rename this data jobs skill count because we're get the top 10 and their

because we're get the top 10 and their Associated count so in order to do this

Associated count so in order to do this analysis to find what is the count of

analysis to find what is the count of all these different skills we want to do

all these different skills we want to do a group buy and it's right here under

a group buy and it's right here under transform form under that Home tab and I

transform form under that Home tab and I can do group by which group rows in the

can do group by which group rows in the table based on the values in the

table based on the values in the currently selected column we're going to

currently selected column we're going to be forming a basic Group by we're using

be forming a basic Group by we're using that job skills column I could change it

that job skills column I could change it to another column if I wanted to and

to another column if I wanted to and that new column name is going to be

that new column name is going to be skill count operation we're going to be

skill count operation we're going to be counting the rows we could do any other

counting the rows we could do any other type of aggregation as well if we had

type of aggregation as well if we had numerical data we could do average

numerical data we could do average median min max whatnot go ahead and

median min max whatnot go ahead and click okay so we've done this

click okay so we've done this aggregation now the next thing is I just

aggregation now the next thing is I just want to get the top 10 values but before

want to get the top 10 values but before to do that I need to actually sort this

to do that I need to actually sort this in descending order right now I can tell

in descending order right now I can tell looking into the numbers this isn't

looking into the numbers this isn't necessar although it looks like it isn't

necessar although it looks like it isn't right so clicking the arrow up at the

right so clicking the arrow up at the top I'm just going to say hey sort

top I'm just going to say hey sort descending and then we want the top 10

descending and then we want the top 10 values so underneath the Home tab under

values so underneath the Home tab under keep rows I'm going to have keep top

keep rows I'm going to have keep top rows and it's going to prop me how many

rows and it's going to prop me how many number of rows do I want to keep 10 in

number of rows do I want to keep 10 in this case I want the 10 values and now

this case I want the 10 values and now from here all I got to do is close and

from here all I got to do is close and load this into its own separate query

load this into its own separate query and Bam here we have it and so if I

and Bam here we have it and so if I needed to reference the top 10 skills

needed to reference the top 10 skills any time all I would have to do is just

any time all I would have to do is just reference this query and I wouldn't have

reference this query and I wouldn't have to like we did last time go through this

to like we did last time go through this full analysis so power of query is

full analysis so power of query is really great at automating some

really great at automating some repetitive analysis and having it just

repetitive analysis and having it just ready for

you all right last little cleanup if we look at these skilled names they're not

look at these skilled names they're not formatted correctly specifically if I

formatted correctly specifically if I look at something like SQL I expect to

look at something like SQL I expect to be all capital letters SQL capital

be all capital letters SQL capital letters python I expected to be Capital

letters python I expected to be Capital At the beginning python so we're going

At the beginning python so we're going to go through and actually fix this so

to go through and actually fix this so that way whenever we present our data to

that way whenever we present our data to someone it doesn't look like a hot mess

someone it doesn't look like a hot mess so opening up the power query menu by

so opening up the power query menu by pressing alt F12 we're going to go into

pressing alt F12 we're going to go into the data jobs skills query specifically

the data jobs skills query specifically on that last step on and we're want to

on that last step on and we're want to alter the job skills column so the first

alter the job skills column so the first thing I want to do with this text

thing I want to do with this text cleanup the easiest thing looking at

cleanup the easiest thing looking at this is we just need to capitalize the

this is we just need to capitalize the first letter of every single word and

first letter of every single word and then from there we'll go through and

then from there we'll go through and actually fine-tune it to capitalize in

actually fine-tune it to capitalize in case of SQL capitalize all letters we'll

case of SQL capitalize all letters we'll have to put in special case for this

have to put in special case for this anyway if you recall from before we have

anyway if you recall from before we have that transform format and they have this

that transform format and they have this capitalize each word we're going to do

capitalize each word we're going to do that the next thing though the more

that the next thing though the more complicated one is we're going to go

complicated one is we're going to go into add column and we're going to add a

into add column and we're going to add a conditional column so what we're going

conditional column so what we're going to do is go through we're going to keep

to do is go through we're going to keep the the name of custom column cuz we're

the the name of custom column cuz we're technically going to be since we're

technically going to be since we're adding a column we're going to have to

adding a column we're going to have to go and delete this job skills column

go and delete this job skills column once create this new one I don't want to

once create this new one I don't want to name a job skills right now going to

name a job skills right now going to call MK anyway what we want to do is we

call MK anyway what we want to do is we want to select the column that we want

want to select the column that we want so if job skills equals in this case we

so if job skills equals in this case we expect to equal something like SQL we

expect to equal something like SQL we want the output to equal SQL then if we

want the output to equal SQL then if we want to add more conditions or Clauses

want to add more conditions or Clauses to it we go to add Clause once again I'm

to it we go to add Clause once again I'm going to select job skills and I'm going

going to select job skills and I'm going to put something like

to put something like powerbi it had a lowercase ey at the end

powerbi it had a lowercase ey at the end I want the powerbi to be fully

I want the powerbi to be fully capitalized at the end I also went

capitalized at the end I also went through and added some other ones such

through and added some other ones such as AWS gcp no SQL and SAS most all these

as AWS gcp no SQL and SAS most all these required them to just capitalize fully

required them to just capitalize fully except for the no SQL one then what do

except for the no SQL one then what do we want it to be if it's not any of

we want it to be if it's not any of these conditions well we'll add this

these conditions well we'll add this else clause and we want it to be

else clause and we want it to be basically the results of an entire

basically the results of an entire column we want it to be whatever it is

column we want it to be whatever it is already in the job skills column I'm

already in the job skills column I'm going to go ahead and click okay so now

going to go ahead and click okay so now we have this cleaned up data set as well

we have this cleaned up data set as well with nice looking names now if you want

with nice looking names now if you want to if you're going through and finding

to if you're going through and finding anything in here that you want to clean

anything in here that you want to clean up feel free to add to that conditional

up feel free to add to that conditional column statement those are the ones I'm

column statement those are the ones I'm just going to go for right now anyway

just going to go for right now anyway because we added this new column and I

because we added this new column and I don't really know an easy way to do this

don't really know an easy way to do this without actually creating this new

without actually creating this new column we need to now go ahead and

column we need to now go ahead and remove job skills and rename custom so

remove job skills and rename custom so going to the Home tab I'm going to

going to the Home tab I'm going to remove column I'm going to remove the

remove column I'm going to remove the one that's selected and I'm going to

one that's selected and I'm going to renames custom to job skills and

renames custom to job skills and conveniently because we're using that

conveniently because we're using that same name and just replacing it if I go

same name and just replacing it if I go to the data jobs skill count that one

to the data jobs skill count that one because it references this one will also

because it references this one will also get updated and all those values in

get updated and all those values in there are updated as well anyway let's

there are updated as well anyway let's go ahead and close and load and inspect

go ahead and close and load and inspect this is our previous pivot table and

this is our previous pivot table and pivot chart that we analyzed it's now

pivot chart that we analyzed it's now going through and loading all the data

going through and loading all the data and now we have it updated with all that

and now we have it updated with all that correct formatting for those different

correct formatting for those different data points one last thing before we go

data points one last thing before we go this is generic these top skills of data

this is generic these top skills of data nerds tall data nerds and that is using

nerds tall data nerds and that is using the data job skills query which has the

the data job skills query which has the job title short column in it so we can

job title short column in it so we can actually visualize this for a certain

actually visualize this for a certain job by going into pivot chart analyze

job by going into pivot chart analyze I'm going to go into insert slicer

I'm going to go into insert slicer specifically we're going to look at job

specifically we're going to look at job title short I'm going to put it over

title short I'm going to put it over here and then as usual I'm going to

here and then as usual I'm going to rename it real quick to job title and

rename it real quick to job title and now let's say we want to analyze

now let's say we want to analyze something like data analyst we can see

something like data analyst we can see that SQL is the top skill but Excel is

that SQL is the top skill but Excel is in second place followed by python

in second place followed by python Tableau and SAS what about for business

Tableau and SAS what about for business analysts very similar in that sqls top

analysts very similar in that sqls top and then Excel is in that second place

and then Excel is in that second place so really unique and showing the

so really unique and showing the importance of excel Within These skills

importance of excel Within These skills and pretty meta that we used Excel to

and pretty meta that we used Excel to find this out all right now it's your

find this out all right now it's your turn to give it a shot you have some

turn to give it a shot you have some practice problems to go through and get

practice problems to go through and get more familiar with doing these Advanced

more familiar with doing these Advanced Transformations specifically pivoting

Transformations specifically pivoting unpivoting and then also Group by all

unpivoting and then also Group by all right with that I'll see you in the next

right with that I'll see you in the next one we're going to be diving into append

one we're going to be diving into append and merging queries specifically going

and merging queries specifically going to be doing this with that skill query

to be doing this with that skill query that we did previously all right see you

that we did previously all right see you there

let's now get into how to perform a pend and also merges and so the first portion

and also merges and so the first portion of this lesson the easiest portion of my

of this lesson the easiest portion of my opinion is going to be a pend

opinion is going to be a pend specifically going back to that Excel

specifically going back to that Excel sheet where we had all those different

sheet where we had all those different uh sheets for the months of the year and

uh sheets for the months of the year and they're job posting on each because all

they're job posting on each because all these data sets are of the same format I

these data sets are of the same format I have the same columns we're going to be

have the same columns we're going to be able to append all these together and

able to append all these together and get what is our final data set of all

get what is our final data set of all 30,000 rows if you recall each month had

30,000 rows if you recall each month had around 3,000 postings so that's how we

around 3,000 postings so that's how we get to that value from there the primary

get to that value from there the primary focus of this lesson will then shift to

focus of this lesson will then shift to merge for this we're going to be

merge for this we're going to be combining our two queries that we built

combining our two queries that we built previously one which was our original

previously one which was our original data set so we titled that one data jobs

data set so we titled that one data jobs salary and then that new query that we

salary and then that new query that we created in the last lesson on the skills

created in the last lesson on the skills so data job skills we're going to be

so data job skills we're going to be merging those two together

merging those two together and this will allow us to do some pretty

and this will allow us to do some pretty interesting analysis specifically now

interesting analysis specifically now that we've merged those we'll be able to

that we've merged those we'll be able to see based on a skill what is the

see based on a skill what is the expected salary and we're going to build

expected salary and we're going to build a visualization for that for the top 10

a visualization for that for the top 10 skills now merge unlike a pend is a very

skills now merge unlike a pend is a very complex operation mainly because there's

complex operation mainly because there's a lot of different types of merges

a lot of different types of merges specifically there's six type of merges

specifically there's six type of merges in Microsoft alone so we're going to be

in Microsoft alone so we're going to be walking through each one of those so you

walking through each one of those so you understand the differences and know

understand the differences and know which one to use when for this first

which one to use when for this first append example we're going to be using

append example we're going to be using this data job salary monthly data set

this data job salary monthly data set and just as a refresher this contains

and just as a refresher this contains everything for in this case I'm selected

everything for in this case I'm selected on the January sheet down here and this

on the January sheet down here and this has all the January data which has

has all the January data which has around 3,100 rows for this and we have

around 3,100 rows for this and we have each one of the months for the year

here anyway let's use power query to append all these together because

append all these together because previously before you knew about this

previously before you knew about this you'd have to go through and actually

you'd have to go through and actually copy and paste all these different

copy and paste all these different options right here and then put it into

options right here and then put it into a new sheet doing this 12 times is a hot

a new sheet doing this 12 times is a hot mess so since this is only a simple

mess so since this is only a simple example that we're not going to use

example that we're not going to use later on I recommend just opening up a

later on I recommend just opening up a new workbook for this now coming into

new workbook for this now coming into the data tab I can come down to get data

the data tab I can come down to get data and they do have this option right here

and they do have this option right here for Combined queries merge and also

for Combined queries merge and also append but this is for append two

append but this is for append two queries from within in this workbook

queries from within in this workbook it's basically assuming you've already

it's basically assuming you've already imported it in so instead what we need

imported it in so instead what we need to do is actually go to from file and

to do is actually go to from file and actually start our first query of

actually start our first query of connecting to that Excel workbook with

connecting to that Excel workbook with all those different sheets navigating to

all those different sheets navigating to the course underneath resources data

the course underneath resources data sets and then here down on data job

sets and then here down on data job salary monthly I'll select that select

salary monthly I'll select that select Import in the Navigator we can see all

Import in the Navigator we can see all the different sheets that are available

the different sheets that are available we want to actually do enable this of

we want to actually do enable this of select multiple items and then go

select multiple items and then go through and select all the items with

through and select all the items with all these loaded we're going to then

all these loaded we're going to then shift into not just loading it we want

shift into not just loading it we want to actually go into the power query

to actually go into the power query editor so I'm going to select transform

editor so I'm going to select transform data and it's going to start by loading

data and it's going to start by loading each one of those sheets and just going

each one of those sheets and just going to be naming each one of the queries

to be naming each one of the queries respectively after those sheets with

respectively after those sheets with power query editor launched we can see

power query editor launched we can see over here in the left hand pan all 12 of

over here in the left hand pan all 12 of those queries for each of the months so

those queries for each of the months so these are all their separate own queries

these are all their separate own queries because of that we need to now move into

because of that we need to now move into actually appending them and make it one

actually appending them and make it one final query that we can actually export

final query that we can actually export into or import into Excel so underneath

into or import into Excel so underneath the Home tab they have the option for

the Home tab they have the option for combine append queries they have appen

combine append queries they have appen queries and append queries is new with

queries and append queries is new with the January query selected I'm going to

the January query selected I'm going to go to append queries and for this I can

go to append queries and for this I can say either do two tables and specify the

say either do two tables and specify the table I want to do we're going to do

table I want to do we're going to do three or more cuz we want to do all of

three or more cuz we want to do all of them with them all selected I'll now go

them with them all selected I'll now go through and click okay to append now

through and click okay to append now this inserted a step of appended queries

this inserted a step of appended queries inside inside of that January query so

inside inside of that January query so now that January query is all those

now that January query is all those different data sets so I just want to

different data sets so I just want to verify that I got all the data in here

verify that I got all the data in here right now if we scroll down well I'm

right now if we scroll down well I'm just going to show it right here we're

just going to show it right here we're only showing column profile based on the

only showing column profile based on the top 1,000 the fastest way to actually

top 1,000 the fastest way to actually find this out is just go to the

find this out is just go to the transform Tab and go to count rows which

transform Tab and go to count rows which it tells me there's 36,000 rows which

it tells me there's 36,000 rows which it's a few thousand too many and if I go

it's a few thousand too many and if I go back into the appended query option and

back into the appended query option and actually look into it I can see in the

actually look into it I can see in the formula bar we have August in here I

formula bar we have August in here I accidentally selected it twice so I'll

accidentally selected it twice so I'll go ahead and delete it and then look at

go ahead and delete it and then look at the counted rows that's actually what I

the counted rows that's actually what I expect the value to be around 32,000

expect the value to be around 32,000 anyway that was just to count the rows

anyway that was just to count the rows additionally I don't want the append

additionally I don't want the append query to be inside of that January query

query to be inside of that January query so I'm going to delete this step as well

so I'm going to delete this step as well instead with the January query selected

instead with the January query selected I'll go back to that home append queries

I'll go back to that home append queries and then select append queries as new

and then select append queries as new this is going to create a completely new

this is going to create a completely new query once again we want to do three or

query once again we want to do three or more tables this time I'm going to hold

more tables this time I'm going to hold control and select all of them and then

control and select all of them and then move them over at once make sure we

move them over at once make sure we don't have duplicates this time so this

don't have duplicates this time so this now starts a new query right now it's

now starts a new query right now it's called aend one I would probably name it

called aend one I would probably name it something like data jobs all and then

something like data jobs all and then pressing enter it then loads in here but

pressing enter it then loads in here but you can see these queries like imagine

you can see these queries like imagine the case where I right now we have 13

the case where I right now we have 13 queries I want to organize these a

queries I want to organize these a little bit better so we can actually

little bit better so we can actually group these specifically we can group

group these specifically we can group these monthly ones I selected April and

these monthly ones I selected April and then holding control selecting all the

then holding control selecting all the other queries as well then right clicked

other queries as well then right clicked it and I'm going to select this option

it and I'm going to select this option to move to group we need to have a new

to move to group we need to have a new group and I'll call this real uniquely

group and I'll call this real uniquely data jobs

data jobs monthly and click okay so now we have

monthly and click okay so now we have these two folders one with data jobs

these two folders one with data jobs monthly I'm going to close that down and

monthly I'm going to close that down and then there other queries which we've

then there other queries which we've seen before and there's one query inside

seen before and there's one query inside of this of data jobs all this cleans it

of this of data jobs all this cleans it up also you may get this disclaimer up

up also you may get this disclaimer up here the preview may be up to 33 days

here the preview may be up to 33 days old feel free to refresh it if you've

old feel free to refresh it if you've been getting that should have no effect

been getting that should have no effect on your data then if we wanted to we

on your data then if we wanted to we could go through and actually Analyze

could go through and actually Analyze This by pressing close and load to I

This by pressing close and load to I pretty maturely selected close and load

pretty maturely selected close and load I recommend you select close and load to

I recommend you select close and load to anyway nonetheless I'll go to the data

anyway nonetheless I'll go to the data jobs all we'll go to load to

jobs all we'll go to load to specifically I want to look at a pivot

specifically I want to look at a pivot table I know there's going to be some

table I know there's going to be some data loss because it's going to remove

data loss because it's going to remove the data in the sheet and then I can

the data in the sheet and then I can inspect that job posted date

inspect that job posted date specifically for the account dragging

specifically for the account dragging job post date into the rows and then

job post date into the rows and then also dragging job posted date into

also dragging job posted date into values and once again this is why we

values and once again this is why we double check it this time it looks like

double check it this time it looks like I accidentally imported in January twice

I accidentally imported in January twice with this as we can see that it's

with this as we can see that it's 35,000 anyway opening up that power

35,000 anyway opening up that power query editor going to the data jobs all

query editor going to the data jobs all query and updating it to remove that

query and updating it to remove that second January that I should have caught

second January that I should have caught from before and then close and loading

from before and then close and loading it and now it should refresh and update

it and now it should refresh and update for these these correct values boom so

for these these correct values boom so now it's actually aligned with what I

now it's actually aligned with what I expect to see this why we always double

expect to see this why we always double check any type of query or analysis you

check any type of query or analysis you do this double check of the work is

do this double check of the work is going to save your

butt all right let's now get into the bulk of this lesson I'm moving into

bulk of this lesson I'm moving into merge for this feel free to continue

merge for this feel free to continue working with that workbook that you were

working with that workbook that you were working with in the last lesson if you

working with in the last lesson if you didn't Happ to save it or you got lost

didn't Happ to save it or you got lost you can use the advanced transform

you can use the advanced transform workbook from the last lesson that'll

workbook from the last lesson that'll pick right right back up where we left

pick right right back up where we left off and then as usual the append and the

off and then as usual the append and the merge are the final examples that you're

merge are the final examples that you're going to see at the end of this which

going to see at the end of this which specifically for append you've already

specifically for append you've already saw so let's actually get into merging

saw so let's actually get into merging those queries for this I want to press

those queries for this I want to press alt F12 and right now we have three

alt F12 and right now we have three queries in here the data job salary

queries in here the data job salary which is basically like our fact table

which is basically like our fact table this includes all of our data going into

this includes all of our data going into transform and count rows we have as

transform and count rows we have as expected around 32 data point points I'm

expected around 32 data point points I'm going go ahead and delete that Stu

going go ahead and delete that Stu similarly we have this data jobs skills

similarly we have this data jobs skills which has all of our skills in it let's

which has all of our skills in it let's see how many rows are in this by going

see how many rows are in this by going up to transform and to count rows and

up to transform and to count rows and this has

this has 167,000 now it's important to understand

167,000 now it's important to understand these numbers because we're going to be

these numbers because we're going to be using them or need to understand them

using them or need to understand them whenever we actually get into the joins

whenever we actually get into the joins to see when we have missing or more data

to see when we have missing or more data so I'm going go ahead and delete the

so I'm going go ahead and delete the step of counted rows as well we don't

step of counted rows as well we don't need it then we have also this final

need it then we have also this final query of data job skills count this was

query of data job skills count this was made as an example only we're not going

made as an example only we're not going to use this any further into the future

to use this any further into the future so I'm actually going to go ahead and

so I'm actually going to go ahead and just delete this to minimize my queries

just delete this to minimize my queries it's going to ask them I'm sure want to

it's going to ask them I'm sure want to delete it yep so let's get into merging

delete it yep so let's get into merging these queries I have data job salary

these queries I have data job salary selected come up to the Home tab under

selected come up to the Home tab under merge queries we're going to have merge

merge queries we're going to have merge queries and merge queries as new like we

queries and merge queries as new like we learned from the append of appen queries

learned from the append of appen queries and appen queries is new we're going to

and appen queries is new we're going to want a new query so that way we still

want a new query so that way we still have these Source queries so I'm going

have these Source queries so I'm going to go merge queries as new with this

to go merge queries as new with this this merge window pops up and it says

this merge window pops up and it says select the tables and matching columns

select the tables and matching columns to create a merge table specifically we

to create a merge table specifically we want to go with the data jobs salary and

want to go with the data jobs salary and we want to merge it on the job ID that's

we want to merge it on the job ID that's why we created that a few lessons ago

why we created that a few lessons ago we're trying to connect to the data jobs

we're trying to connect to the data jobs skills on also that job ID now down here

skills on also that job ID now down here underneath this there's a join kind and

underneath this there's a join kind and there's six different options from this

there's six different options from this of left outer right outer full outer

of left outer right outer full outer inner left anti and right anti now Kelly

inner left anti and right anti now Kelly put together this fancy chart that shows

put together this fancy chart that shows visually what is happening with these

visually what is happening with these merges and we're going to be walking

merges and we're going to be walking through all of these briefly in order to

through all of these briefly in order to understand which type of join you should

understand which type of join you should be choosing depending on which scenario

be choosing depending on which scenario you're in as a quick overview these

you're in as a quick overview these circles are signifying the two different

circles are signifying the two different tables so in this case table a and table

tables so in this case table a and table B and the Shaded Blue Area shows what

B and the Shaded Blue Area shows what portion of the contents from those

portion of the contents from those tables will be included in the final

tables will be included in the final table first up is a left outer join and

table first up is a left outer join and with this join what's showing here is

with this join what's showing here is that all rows from table a will be

that all rows from table a will be included in the final table and then

included in the final table and then from that Center portion right there

from that Center portion right there where A and B overlap this signifies

where A and B overlap this signifies that it's only going to keep items from

that it's only going to keep items from table B that are in table a or match

table B that are in table a or match with table a so what does it actually

with table a so what does it actually mean so if we go here into join kind and

mean so if we go here into join kind and select left outer and then what we get

select left outer and then what we get told based on this next to this check

told based on this next to this check mark is the selection matches 29,000 of

mark is the selection matches 29,000 of 32,000 rows from the first table so what

32,000 rows from the first table so what are those missing jobs well basically

are those missing jobs well basically there's some jobs that don't have a

there's some jobs that don't have a skill now this isn't necessarily a bad

skill now this isn't necessarily a bad thing although we're not going to go

thing although we're not going to go with this join this could be an option

with this join this could be an option we could use I'm going to click okay to

we could use I'm going to click okay to load it in so right now we have it under

load it in so right now we have it under this query called merge one and as you

this query called merge one and as you can see there's not repeating any job

can see there's not repeating any job IDs basically we have the original dat

IDs basically we have the original dat jobs salary table and then we scroll all

jobs salary table and then we scroll all the way to the right we have the data

the way to the right we have the data job skills over here and if you see each

job skills over here and if you see each one of these items is a table if I click

one of these items is a table if I click on it and expand it to see hey what's in

on it and expand it to see hey what's in this table we can see that for this one

this table we can see that for this one there job posting or job ID of 10,000

there job posting or job ID of 10,000 And1 this is the table associated with

And1 this is the table associated with it so I'm going to go ahead and actually

it so I'm going to go ahead and actually delete out of this step and go back to

delete out of this step and go back to it so what we could do is expand it out

it so what we could do is expand it out and there's this icon up in the top

and there's this icon up in the top right hand corner I'm going to go ahead

right hand corner I'm going to go ahead and click it and it's going to ask me

and click it and it's going to ask me how it wants to basically expand out and

how it wants to basically expand out and in this case I already have the job ID I

in this case I already have the job ID I already have job title short I would

already have job title short I would expand it by job skills so now seeing

expand it by job skills so now seeing how these skills are broken over I can

how these skills are broken over I can actually scroll all the way over and see

actually scroll all the way over and see that now 10,000 And1 ID is duplicated

that now 10,000 And1 ID is duplicated multiple times and if actually looked at

multiple times and if actually looked at the number of rows within this data set

the number of rows within this data set this new data set we have 170,000 rows

this new data set we have 170,000 rows now technically this merge has exactly

now technically this merge has exactly what we want but we still need to go

what we want but we still need to go through those other merge examples to

through those other merge examples to understand them so we're going to show

understand them so we're going to show them as well now for this I want to go

them as well now for this I want to go back to that merge window and I'm going

back to that merge window and I'm going to click the settings icon I need to get

to click the settings icon I need to get rid of the step we're going to be trying

rid of the step we're going to be trying out different types of merges so I'm

out different types of merges so I'm going to xit out and then go in here and

going to xit out and then go in here and click the gear icon now it's popping

click the gear icon now it's popping back up we did left outer next thing

back up we did left outer next thing we're going to look at is Right outer

we're going to look at is Right outer for right outer this takes all of the

for right outer this takes all of the rows out of table B and then from there

rows out of table B and then from there any that match those rows in table a are

any that match those rows in table a are included now this one when we look down

included now this one when we look down here it says Hey the selection

here it says Hey the selection matches

matches 167,000 of 167,000 rows from the second

167,000 of 167,000 rows from the second table if you recall back from that left

table if you recall back from that left outer we had

outer we had 170,000 so 3,000 higher why is that well

170,000 so 3,000 higher why is that well that table a or data job salary has

that table a or data job salary has 3,000 roles in here that don't have any

3,000 roles in here that don't have any skills listed hence why 3000 is less

skills listed hence why 3000 is less this provides a similar type of merge

this provides a similar type of merge that we did before where we need to

that we did before where we need to actually go over to that data job skills

actually go over to that data job skills and expand it out selecting the job

and expand it out selecting the job skills column and with this table we can

skills column and with this table we can just check that we have 167,000 rows

just check that we have 167,000 rows which bam we confirm all right I'm going

which bam we confirm all right I'm going to get rid of these two steps we're

to get rid of these two steps we're going to move into the next merge next

going to move into the next merge next is inner join and this provides only

is inner join and this provides only matching rows from table a and matching

matching rows from table a and matching rows from table B so depending how

rows from table B so depending how you're join it there could be missing

you're join it there could be missing data on both A and B for this one it's

data on both A and B for this one it's saying hey the selection matches about

saying hey the selection matches about 29,000 of 32,000 rows from the first

29,000 of 32,000 rows from the first table which what we expect and then

table which what we expect and then basically all of the rows from the

basically all of the rows from the second table so this one if actually go

second table so this one if actually go into it and then expand out those data

into it and then expand out those data job skills looking only at the job

job skills looking only at the job skills column with it expanded out

skills column with it expanded out actually counting the rows we have once

actually counting the rows we have once again 167,000 so missing that 3,000 of

again 167,000 so missing that 3,000 of jobs that don't have skills next is left

jobs that don't have skills next is left anti and in this case it checks to see

anti and in this case it checks to see what matches it doesn't have and Returns

what matches it doesn't have and Returns the value for that specifically for

the value for that specifically for table a whichever values don't have a

table a whichever values don't have a match it's going to return that so in

match it's going to return that so in this case it says the selection excludes

this case it says the selection excludes 29,000 out of the 32,000 when I go to

29,000 out of the 32,000 when I go to load it I get the rows from table a or

load it I get the rows from table a or data jobs salary and it still has the

data jobs salary and it still has the data job skills but actually if I looked

data job skills but actually if I looked into here right we should be matching on

into here right we should be matching on things that don't match or don't have a

things that don't match or don't have a value specifically there shouldn't be

value specifically there shouldn't be inside anything in this table that I'm

inside anything in this table that I'm clicking on and as expected they're null

clicking on and as expected they're null values because it doesn't have skills so

values because it doesn't have skills so exiting out of navigation going back to

exiting out of navigation going back to Source counting these rows we can see

Source counting these rows we can see that we have 3,000 jobs basically with

that we have 3,000 jobs basically with no skills for right anti this gets rows

no skills for right anti this gets rows from the right table that do not have

from the right table that do not have matches in the left table and for this

matches in the left table and for this with right anti- selected this selection

with right anti- selected this selection excludes 167,000 out of 167 rows from

excludes 167,000 out of 167 rows from the second table so basically everything

the second table so basically everything from this table is included we're not

from this table is included we're not going to walk through this in the power

going to walk through this in the power query cuz this is also not what we want

query cuz this is also not what we want the final one we're going to actually

the final one we're going to actually use is a full out join from this it

use is a full out join from this it takes all rows from table a and all rows

takes all rows from table a and all rows from table B and if there's a match it

from table B and if there's a match it will join those two if there's no

will join those two if there's no matches it's still going to return them

matches it's still going to return them in the table it will just be a null

in the table it will just be a null value for where it doesn't match up and

value for where it doesn't match up and this talks about how basically selection

this talks about how basically selection matches 29,000 of 32,000 rows from the

matches 29,000 of 32,000 rows from the first table and all the rows from the

first table and all the rows from the second table loading this in once again

second table loading this in once again we have data job skills we need to

we have data job skills we need to expand out and we only want to expand

expand out and we only want to expand out those job skills and then from there

out those job skills and then from there just going to do a double check I'm I'm

just going to do a double check I'm I'm going to do count rows and this has

going to do count rows and this has 170,000 rows in it so similar to our

170,000 rows in it so similar to our left outer we could have done either of

left outer we could have done either of these these are one the twos that we

these these are one the twos that we want but I'm going to stick with this

want but I'm going to stick with this one of the full outer because I have all

one of the full outer because I have all the work here any I'm going to close out

the work here any I'm going to close out the step and I think that's a great

the step and I think that's a great example of sometimes there may be

example of sometimes there may be multiple joins that fit the example it's

multiple joins that fit the example it's important that you go through and

important that you go through and actually count the rows and understand

actually count the rows and understand the data set to figure out which one you

the data set to figure out which one you need to use and for what purpose anyway

need to use and for what purpose anyway one thing I glossed over real quick

one thing I glossed over real quick going back to source and that gear icon

going back to source and that gear icon is right underneath this underneath the

is right underneath this underneath the join kind they have used fuzzy matching

join kind they have used fuzzy matching to perform the merge right now we're

to perform the merge right now we're doing basically exact matching as the

doing basically exact matching as the job ID of 10,1 we're matching up exactly

job ID of 10,1 we're matching up exactly with the 10,1 from the other table fuzzy

with the 10,1 from the other table fuzzy matching allows you to connect to tables

matching allows you to connect to tables that have basically non-exact matches so

that have basically non-exact matches so in this case we have table a with a

in this case we have table a with a student ID and a student's name and only

student ID and a student's name and only their first name but then in table B we

their first name but then in table B we have the student name full so first and

have the student name full so first and last name and the grade with the fuzzy

last name and the grade with the fuzzy matching we could merge table A and B

matching we could merge table A and B based on that student name First Column

based on that student name First Column and the student name full column now

and the student name full column now what happens if we get to where we have

what happens if we get to where we have students with multiple similar first

students with multiple similar first names it's going to create a hot mess so

names it's going to create a hot mess so I don't always recommend using this

I don't always recommend using this unless you know the data and you know

unless you know the data and you know you're going to cause complications with

you're going to cause complications with it so that was a quick overview of of

it so that was a quick overview of of the different joins within power query

the different joins within power query if you want a more indepth tutorial for

if you want a more indepth tutorial for how this is done then and you can check

how this is done then and you can check out my SQL tutorial where I go through

out my SQL tutorial where I go through it with all the different SQL analysis

it with all the different SQL analysis that we do in that course and break it

that we do in that course and break it down step by step I'll include a link to

down step by step I'll include a link to that video right here for you to go and

that video right here for you to go and see

it all right so we have the final table that we actually want for this remember

that we actually want for this remember these do have duplicate values in it so

these do have duplicate values in it so you have to keep that in mind anytime

you have to keep that in mind anytime you're doing analysis I'm going to

you're doing analysis I'm going to rename this as data jobs merged one last

rename this as data jobs merged one last thing for close and load we have this

thing for close and load we have this job skills column which is sort of

job skills column which is sort of redundant right now because we actually

redundant right now because we actually have the data job skills not job skills

have the data job skills not job skills the actual skills itself so I need to

the actual skills itself so I need to get rid of this column I actually want

get rid of this column I actually want to do this I'm going to do this in the

to do this I'm going to do this in the source step before we even break this

source step before we even break this out so I'm going to select job skills

out so I'm going to select job skills and select remove columns it's going to

and select remove columns it's going to ask if I want to insert the step which I

ask if I want to insert the step which I do and then after we remove the columns

do and then after we remove the columns we go into expanding it out and because

we go into expanding it out and because we did it in that order I can actually

we did it in that order I can actually come in here instead of renaming it here

come in here instead of renaming it here I can just rename it via the formula

I can just rename it via the formula inside of expanded skills and just

inside of expanded skills and just change it to job skills and Bam now I

change it to job skills and Bam now I only added two steps Vice one all right

only added two steps Vice one all right go ahead now we're going to close and

go ahead now we're going to close and load two I'm going to want a pivot table

load two I'm going to want a pivot table and also pivot chart so I'm going to

and also pivot chart so I'm going to select the pivot chart option here and

select the pivot chart option here and underneath quers and connections it's

underneath quers and connections it's going to show that it's loading this in

going to show that it's loading this in here under data jobs merged so let me

here under data jobs merged so let me show you what we're going to be creating

show you what we're going to be creating with this I want to build this

with this I want to build this visualization that's showing what is the

visualization that's showing what is the salary of the top 10 skills top 10

salary of the top 10 skills top 10 skills by count for data nerds and this

skills by count for data nerds and this is a combo chart we're going to have not

is a combo chart we're going to have not only the salary or the average salary

only the salary or the average salary for a skill but also for this line

for a skill but also for this line portion we're going to have the

portion we're going to have the associated count for the number of

associated count for the number of skills that appears or how many jobs it

skills that appears or how many jobs it appears in all right so I'm going to go

appears in all right so I'm going to go ahead and move this pivot chart out of

ahead and move this pivot chart out of the way and select the pivot table

the way and select the pivot table remember we want to use the job skills

remember we want to use the job skills we're going to be analyzing that so I'm

we're going to be analyzing that so I'm going to throw in the rows the first

going to throw in the rows the first thing I'm going to look at is the

thing I'm going to look at is the easiest is the count of these job skills

easiest is the count of these job skills and I'm going to rename this to job

and I'm going to rename this to job count along with changing the value

count along with changing the value field settings going to number format I

field settings going to number format I want to change the number specifically I

want to change the number specifically I want to use a thand separator with zero

want to use a thand separator with zero decimal places I'll go ahead and press

decimal places I'll go ahead and press okay so we have a count now we want the

okay so we have a count now we want the average salary so I'm going to take

average salary so I'm going to take salary your average drag it into the

salary your average drag it into the values right now it's doing a sum so

values right now it's doing a sum so I'll go into value field settings select

I'll go into value field settings select average and then for number format we're

average and then for number format we're going to do currency with zero decimal

going to do currency with zero decimal places click okay and okay again and I'm

places click okay and okay again and I'm going to change this one to average

going to change this one to average salary and then specify the units of USD

salary and then specify the units of USD all right so now xing out of this and

all right so now xing out of this and xing out of this now our pivot chart is

xing out of this now our pivot chart is sort of all jacked up well it is jacked

sort of all jacked up well it is jacked up mainly it's trying to PR this as like

up mainly it's trying to PR this as like a dual column chart and that's not what

a dual column chart and that's not what we want so we're going to change this

we want so we're going to change this design of it going to design change

design of it going to design change chart type I'm going to go over to combo

chart type I'm going to go over to combo and then underneath here for the combo

and then underneath here for the combo for the job count I want that to be a

for the job count I want that to be a line so I'm going to go up here and

line so I'm going to go up here and select line and for the average salary I

select line and for the average salary I actually want that to be the column now

actually want that to be the column now I want the job count on a secondary axis

I want the job count on a secondary axis I don't want the same axis as the salary

I don't want the same axis as the salary itself because they're just not

itself because they're just not proportional I'm going to go ahead and

proportional I'm going to go ahead and click okay I want to clean this up a

click okay I want to clean this up a little bit further by removing the

little bit further by removing the legend and then also right clicking here

legend and then also right clicking here and hiding all field buttons on this

and hiding all field buttons on this okay there's now there's still too many

okay there's now there's still too many skills on here remember we want the top

skills on here remember we want the top 10 skills so going into the pivot table

10 skills so going into the pivot table itself I'm going to come up into the

itself I'm going to come up into the filter into value filters and top one

filter into value filters and top one we're going to do top 10 items by job

we're going to do top 10 items by job count all right this is getting a lot

count all right this is getting a lot more readable now because I have the top

more readable now because I have the top 10 by job count I want to order this

10 by job count I want to order this from high to low by salary so I'm going

from high to low by salary so I'm going to go to more sort options and we're

to go to more sort options and we're going to do descending on average salary

going to do descending on average salary I'll click okay and Bam now we're

I'll click okay and Bam now we're getting somewhere so we're seeing things

getting somewhere so we're seeing things like spark and AWS have the highest and

like spark and AWS have the highest and Excel did make the top 10 so it's on

Excel did make the top 10 so it's on there at 100,000 other things I'm going

there at 100,000 other things I'm going to change selecting on this pivot chart

to change selecting on this pivot chart is the actual design itself you know how

is the actual design itself you know how I am about colors so we're going to

I am about colors so we're going to change the colors I'm going to use this

change the colors I'm going to use this monochrom MAAC palette 8 I want the line

monochrom MAAC palette 8 I want the line to be a lighter color than the actual

to be a lighter color than the actual bars itself I'm going to go ahead and

bars itself I'm going to go ahead and add access titles for primary vertical

add access titles for primary vertical and secondary vertical for this I'm

and secondary vertical for this I'm going just select the box go into the

going just select the box go into the formula bar and say hey for this one

formula bar and say hey for this one make it equal to average yearly salary

make it equal to average yearly salary for this one selecting the Box going

for this one selecting the Box going into the formula bar pressing equal I'm

into the formula bar pressing equal I'm going to make it equal to job count I'm

going to make it equal to job count I'm also going to add a title to this I'm

also going to add a title to this I'm going toall this of what is the salary

going toall this of what is the salary of the top 10 skill of data nerds and

of the top 10 skill of data nerds and remember this is for all data nerds so I

remember this is for all data nerds so I want to be able to actually what's the

want to be able to actually what's the great thing about this of joining these

great thing about this of joining these tables now we not only get salary data

tables now we not only get salary data but we can get job title information so

but we can get job title information so I'm going to add a slicer now but going

I'm going to add a slicer now but going in pivot chart analyze insert slicer add

in pivot chart analyze insert slicer add in that job title short only going to

in that job title short only going to move that out of the way now I'm going

move that out of the way now I'm going to go to slicer I'm going to rename this

to go to slicer I'm going to rename this to a more friendly title of job title

to a more friendly title of job title and now now let's actually look at it

and now now let's actually look at it for data analyst so with this looks like

for data analyst so with this looks like python arlor the highest Excel still

python arlor the highest Excel still makes that top 10 and for data analysts

makes that top 10 and for data analysts at

at 86,000 it's also if we look at this it's

86,000 it's also if we look at this it's the second most important skill behind

the second most important skill behind SQL which has a value of 96,000 let's

SQL which has a value of 96,000 let's see what it is for a business analyst

see what it is for a business analyst once again SQL and Excel are two of the

once again SQL and Excel are two of the highest and for business analysts Excel

highest and for business analysts Excel is paying 87,000

is paying 87,000 so bam we just showed the power of well

so bam we just showed the power of well append but also more specifically merge

append but also more specifically merge we can now take this analysis to another

we can now take this analysis to another level analyzing skills to other data

level analyzing skills to other data points from our main fact table or that

points from our main fact table or that data jobs salary table that has all of

data jobs salary table that has all of the data in it so now you have some

the data in it so now you have some practice problems to go through and get

practice problems to go through and get more familiar with using both a pend and

more familiar with using both a pend and also merge after that we'll be jumping

also merge after that we'll be jumping into the last lesson of power query

into the last lesson of power query focusing on the M language as I warned

focusing on the M language as I warned at the beginning don't worry if you

at the beginning don't worry if you don't have coding experience or anything

don't have coding experience or anything like that we're going to be taking it

like that we're going to be taking it nice and easy and you're going to be

nice and easy and you're going to be able to follow along and fill it out

able to follow along and fill it out pretty easily we're going to be doing

pretty easily we're going to be doing some final prep before we finally send

some final prep before we finally send this data set on over to power pivot

this data set on over to power pivot which we're going to cover in the next

which we're going to cover in the next chapter all right with that I'll see you

there welcome to this final lesson on the M language and we're going to be

the M language and we're going to be going into some pretty Advanced

going into some pretty Advanced Techniques and understanding how to read

Techniques and understanding how to read and better utilize the M language in

and better utilize the M language in building your power query queries anyway

building your power query queries anyway nothing in this lesson is going to be

nothing in this lesson is going to be used that we actually go through and do

used that we actually go through and do used to build on our project so if any

used to build on our project so if any time you're not following along or

time you're not following along or you're not able to do anything don't

you're not able to do anything don't worry too much nothing's actually be

worry too much nothing's actually be used it's more to inform you about the M

used it's more to inform you about the M language so you get more familiar with

language so you get more familiar with it as a disclaimer you will not be an

it as a disclaimer you will not be an expert on M language you not be able to

expert on M language you not be able to code in M language after this mainly

code in M language after this mainly you'll just be able to look look at it

you'll just be able to look look at it understand what's going on there from

understand what's going on there from there and make slight adjustments if

there and make slight adjustments if necessary feel free to continue working

necessary feel free to continue working on in that worksheet that you've been

on in that worksheet that you've been using previously where we just

using previously where we just calculated in the last lesson looking at

calculated in the last lesson looking at the top 10 skills and what the salary is

the top 10 skills and what the salary is for them however if you got lost or

for them however if you got lost or wasn't able to follow along or just

wasn't able to follow along or just starting over feel free to use this

starting over feel free to use this merge notebook don't use once again that

merge notebook don't use once again that M language one that one's going to be

M language one that one's going to be what is going to be done at the end of

what is going to be done at the end of this lesson so what are we going to be

this lesson so what are we going to be covering in this lesson well if you open

covering in this lesson well if you open up the power query editor we can

up the power query editor we can navigate into it we're going to be

navigate into it we're going to be covering three main things first is the

covering three main things first is the Z Advan editor actually walking through

Z Advan editor actually walking through a previous query and understanding how

a previous query and understanding how to read it and then from there under add

to read it and then from there under add column tab we're going to go into these

column tab we're going to go into these different examples on creating custom

different examples on creating custom columns and also custom

functions so what exactly is this m language well if we dive in

language well if we dive in documentation we can see that the power

documentation we can see that the power query engine uses a scripting language

query engine uses a scripting language behind the scenes for all power query

behind the scenes for all power query Transformations the power query M formul

Transformations the power query M formul language also known as M so although

language also known as M so although we're doing all these edits inside of

we're doing all these edits inside of this power query editor behind the

this power query editor behind the scenes if we navigates something like

scenes if we navigates something like the advanced editor it's actually using

the advanced editor it's actually using this m language right here to carry out

this m language right here to carry out all the Transformations and it goes on

all the Transformations and it goes on to say if you want to do Advanced

to say if you want to do Advanced Transformations using the power query

Transformations using the power query engine you can use the advanced Editor

engine you can use the advanced Editor to access the script of the query and

to access the script of the query and modify it as you want it even goes on to

modify it as you want it even goes on to discuss that if you're not finding what

discuss that if you're not finding what you need in the actual GUI or the

you need in the actual GUI or the graphical unit user interface of the

graphical unit user interface of the power query editor you can use the M

power query editor you can use the M language editing it in the advanced

language editing it in the advanced editor for

this so let's go into breaking down this m language more by going to that data

m language more by going to that data jobs merge and entering the advanced

jobs merge and entering the advanced editor and we're going to be just

editor and we're going to be just breaking down this simple query right

breaking down this simple query right here up here on the right hand side

here up here on the right hand side there's a few different options display

there's a few different options display options I'm going to do this render Whit

options I'm going to do this render Whit space basically it shows me the

space basically it shows me the indentation that's going on here right

indentation that's going on here right now I'm seeing that there's four spaces

now I'm seeing that there's four spaces in here anyway the key thing here is

in here anyway the key thing here is we've have first have this let keyword

we've have first have this let keyword and then in keyword this Begins the

and then in keyword this Begins the basically definition block if you will

basically definition block if you will this whole portion right here for

this whole portion right here for defining different variables and

defining different variables and specifically different tasks if we look

specifically different tasks if we look we have things like source expanded data

we have things like source expanded data job skills sorted rows remove column

job skills sorted rows remove column remove columns if I go ahead and move

remove columns if I go ahead and move this over to the right those applied

this over to the right those applied steps are the same thing those are the

steps are the same thing those are the variables itself I currently have enable

variables itself I currently have enable word wrap enabled and I'm not liking the

word wrap enabled and I'm not liking the format and how it looks I'm going to go

format and how it looks I'm going to go ahead and unclick that finally we have

ahead and unclick that finally we have the in keyword and then this displays

the in keyword and then this displays the final value that we want to appear

the final value that we want to appear for our query so in this case we want

for our query so in this case we want the final value of rename columns or the

the final value of rename columns or the last applied step to be what appears now

last applied step to be what appears now this Advanced ER I'm going to expand it

this Advanced ER I'm going to expand it back out again is also a syntax Checker

back out again is also a syntax Checker so in this case let's say I deleted this

so in this case let's say I deleted this quotations at the end of this rename

quotations at the end of this rename columns it's going to one it's going to

columns it's going to one it's going to give me these red squiggly lines to say

give me these red squiggly lines to say that hey there's something wrong here

that hey there's something wrong here and two it's going to actually give you

and two it's going to actually give you an error of invalid identifier and so we

an error of invalid identifier and so we would probably know that we probably

would probably know that we probably need to fix this so we're not going to

need to fix this so we're not going to be breaking down much more of the

be breaking down much more of the formulas here but I do want you to spot

formulas here but I do want you to spot two main things from this the first

two main things from this the first thing is this column names column names

thing is this column names column names are always put in quotes in here and

are always put in quotes in here and conveniently they're also highlighted in

conveniently they're also highlighted in here so if you needed to do any changes

here so if you needed to do any changes to column names or see what's happening

to column names or see what's happening that's one quick way to identify it the

that's one quick way to identify it the next thing is this every step that is

next thing is this every step that is taken refers to the previous one what do

taken refers to the previous one what do I mean by this so this first step is

I mean by this so this first step is assign the valuable variable of source

assign the valuable variable of source and I know it's assign this variable

and I know it's assign this variable because it has an equal sign right next

because it has an equal sign right next to it

to it and then whenever we go to the next line

and then whenever we go to the next line of expanded data job skills inside this

of expanded data job skills inside this function of table expanded table column

function of table expanded table column it references source which if I scroll

it references source which if I scroll over it I can see that it's giving me

over it I can see that it's giving me the same formula for source which is

the same formula for source which is right above it so basically it's

right above it so basically it's plugging right into it similarly this

plugging right into it similarly this expanded data job skills is going to be

expanded data job skills is going to be located in the next one below it on

located in the next one below it on sorted rows and it's going to be the

sorted rows and it's going to be the first value in here for this table

first value in here for this table sorted and if you're curious about what

sorted and if you're curious about what these different functions are doing you

these different functions are doing you can just scroll over it as well in this

can just scroll over it as well in this case table. sort sorts the table using

case table. sort sorts the table using one or more Columns of names and

one or more Columns of names and comparison criteria and it tells us via

comparison criteria and it tells us via the syntax inside the parentheses that

the syntax inside the parentheses that the first parameter is table is table so

the first parameter is table is table so it takes that previous variable which is

it takes that previous variable which is a table anyway one minor last thing

a table anyway one minor last thing about this if you notice these are

about this if you notice these are surrounded by these variables have a

surrounded by these variables have a hashtag and then double quotes on each

hashtag and then double quotes on each side and that's because they have white

side and that's because they have white space in the actual names that we're

space in the actual names that we're doing for this in the case of source

doing for this in the case of source there's no white space it's only one

there's no white space it's only one value with no white space so it doesn't

value with no white space so it doesn't need to have this around it anyway why

need to have this around it anyway why am I yaen about all this stuff if you

am I yaen about all this stuff if you need to understand this m language

need to understand this m language anyway we're going to actually create

anyway we're going to actually create this data jobs merge query I'm going to

this data jobs merge query I'm going to select it all press contrl C to copy it

select it all press contrl C to copy it then from there I'm going to close out

then from there I'm going to close out of it we're going to now create a new

of it we're going to now create a new query so underneath the Home tab I'm

query so underneath the Home tab I'm going to go to new source I'm and then

going to go to new source I'm and then under that other source and I'm just

under that other source and I'm just going to go into blank query okay right

going to go into blank query okay right now this is completely blank but I can

now this is completely blank but I can go into that advanced error of query 1

go into that advanced error of query 1 and it has the let and instill and

and it has the let and instill and obviously nothing going on here what I

obviously nothing going on here what I can do is just highlight this all and

can do is just highlight this all and then using contrl V paste all of that

then using contrl V paste all of that other query into this now when I press

other query into this now when I press done it goes through and actually

done it goes through and actually creates that same exact query from data

creates that same exact query from data jobs merged now it could could have gone

jobs merged now it could could have gone through and right click data jobs merged

through and right click data jobs merged and click duplicate but this is more of

and click duplicate but this is more of to show that you can actually go in copy

to show that you can actually go in copy queries or copy portions of queries and

queries or copy portions of queries and thus paste it into other ones which

thus paste it into other ones which we're going to do in a little

bit so let's get into more of learning about the M Language by actually

about the M Language by actually cleaning up this query one that we just

cleaning up this query one that we just created by using this column from

created by using this column from example first thing though I do want to

example first thing though I do want to rename this query one this is the one

rename this query one this is the one we're be working with for the remainder

we're be working with for the remainder of this lesson and I'm going to call it

of this lesson and I'm going to call it data jobs clean because that's what

data jobs clean because that's what we're going to do we're going to clean

we're going to do we're going to clean it up so we have four major tasks that

it up so we have four major tasks that we're going to do with this the first is

we're going to do with this the first is for job schedule type I just want to

for job schedule type I just want to extract out the first value out of here

extract out the first value out of here that's full-time out of it additionally

that's full-time out of it additionally we're going to be using the date and

we're going to be using the date and date time columns to extract the weekday

date time columns to extract the weekday and also the hour of the job postings

and also the hour of the job postings and then finally we're going to do some

and then finally we're going to do some data cleanup on this job title column

data cleanup on this job title column that frankly is a mess specifically

that frankly is a mess specifically we're going to move job postings that

we're going to move job postings that have this parentheses remote around it

have this parentheses remote around it anyway let's start with this first one

anyway let's start with this first one of this job schedule type if I go into

of this job schedule type if I go into view and then look at the column profile

view and then look at the column profile it looks like we have that full-time

it looks like we have that full-time contractor part-time and whatnot but we

contractor part-time and whatnot but we have a lot of combines of full-time and

have a lot of combines of full-time and part-time contractor and temp work

part-time contractor and temp work full-time parttime and internship I

full-time parttime and internship I basically want to go through and just

basically want to go through and just extract out what is the first value that

extract out what is the first value that appears in here so in the case of this

appears in here so in the case of this full-time and parttime just want to

full-time and parttime just want to extract full-time contractor and temp n

extract full-time contractor and temp n work only contractor so under add column

work only contractor so under add column and then column from example we'll do

and then column from example we'll do from selection and this appears at the

from selection and this appears at the top of add column from examples enter

top of add column from examples enter sample values to create a new column

sample values to create a new column control enter to apply so I'll first go

control enter to apply so I'll first go by entering fulltime and it's already

by entering fulltime and it's already picking it up I'm just going to type it

picking it up I'm just going to type it in first okay and then I'm going to

in first okay and then I'm going to scroll down but in this case I'm going

scroll down but in this case I'm going to put in hey I want full time for this

to put in hey I want full time for this one this is the example remember so now

one this is the example remember so now it's cleaning up that let's scroll down

it's cleaning up that let's scroll down further if it's done this fully for even

further if it's done this fully for even more okay it's getting the first of

more okay it's getting the first of these and you might think that this is

these and you might think that this is correct but the problem we're running

correct but the problem we're running into now is if we go down to this one

into now is if we go down to this one where it says contractor it's only

where it says contractor it's only contract do and just looking at the

contract do and just looking at the formula this is the formula it's

formula this is the formula it's generated so far it's doing teex start

generated so far it's doing teex start and nine I don't really know too much

and nine I don't really know too much what's going on here but I'm assuming

what's going on here but I'm assuming that it's taking the first nine values

that it's taking the first nine values that's not I want so inside this

that's not I want so inside this contractor one I'm going to type in

contractor one I'm going to type in contractor with an R so that way it

contractor with an R so that way it hopefully fixes this so this is good and

hopefully fixes this so this is good and now it has text before delimiter and a

now it has text before delimiter and a space so I'm going to go ahead and click

space so I'm going to go ahead and click okay to load this in so let's scroll

okay to load this in so let's scroll down to just inspect it to make sure

down to just inspect it to make sure that we have this correct and an easier

that we have this correct and an easier way instead of scrolling down and trying

way instead of scrolling down and trying to find something I can just use this

to find something I can just use this drop down right here and look in here

drop down right here and look in here and it looks like we're good

and it looks like we're good except for we now have a comma here

except for we now have a comma here specifically I have a fulltime and then

specifically I have a fulltime and then a full-time comma so what's going on

a full-time comma so what's going on here well for values that have more than

here well for values that have more than two so three they actually insert a

two so three they actually insert a comma in there and when we inspect our

comma in there and when we inspect our formula opening up the formula bar here

formula opening up the formula bar here it's only checking for a space so the

it's only checking for a space so the easiest way to fix this is actually just

easiest way to fix this is actually just like we did before we're pretty familiar

like we did before we're pretty familiar with it let's go to the trans form Tab

with it let's go to the trans form Tab and then under replace values we want to

and then under replace values we want to go to replace values specifically we

go to replace values specifically we want to find commas we want to replace

want to find commas we want to replace it with a blank bam so now pulling down

it with a blank bam so now pulling down that drop down we don't have multiple

that drop down we don't have multiple different full times we just have that

different full times we just have that single one without the comma we have

single one without the comma we have what we want all right we're going to

what we want all right we're going to rename this and I can just go ahead and

rename this and I can just go ahead and double click this and rename it but I'm

double click this and rename it but I'm actually going to do something first I

actually going to do something first I see that I have the step already for

see that I have the step already for renamed columns so I'm going to take

renamed columns so I'm going to take that and I'm going to drag it to the

that and I'm going to drag it to the Bottom now with rename columns as the

Bottom now with rename columns as the last step I'll then rename it to job

last step I'll then rename it to job schedule type first press enter and then

schedule type first press enter and then it inserts it into that current step as

it inserts it into that current step as we can see from here cuz we're now

we can see from here cuz we're now familiar with it and we don't have

familiar with it and we don't have multiple rename columns in there and

multiple rename columns in there and then finally you know how I get about

then finally you know how I get about column ordering this job schedule type

column ordering this job schedule type first I want it next to the job schedule

first I want it next to the job schedule type so I'm going to drag this on over

type so I'm going to drag this on over here see how long it takes and we've

here see how long it takes and we've moved it over and we now have this new

moved it over and we now have this new step of reordered columns all right

step of reordered columns all right let's look at some other quick examples

let's look at some other quick examples for column from examples for this we're

for column from examples for this we're going to be using the job posted date

going to be using the job posted date for this using column from example I'm

for this using column from example I'm going to select from selection now with

going to select from selection now with some of these things whenever I type in

some of these things whenever I type in this box I want to get let's say the

this box I want to get let's say the year in this case if I were to type in

year in this case if I were to type in four one it would pop up that hey with

four one it would pop up that hey with all these different options we can do

all these different options we can do and so this provides a lot of different

and so this provides a lot of different options as far as okay I do know if I

options as far as okay I do know if I wanted to do the month I could do that

wanted to do the month I could do that and pressing enter it's going to copy it

and pressing enter it's going to copy it all the way down that's not what I

all the way down that's not what I wanted this case though I'm going to

wanted this case though I'm going to double click it again go

double click it again go 2023 and scrolling down and looking

2023 and scrolling down and looking through this this option here of year

through this this option here of year from job post to date so we're going to

from job post to date so we're going to go with that then press enter and

go with that then press enter and looking at the transform we can see what

looking at the transform we can see what is the m language code that it used for

is the m language code that it used for this it used the date and year function

this it used the date and year function putting in job posted date this is what

putting in job posted date this is what we want we'll click okay you know I I'm

we want we'll click okay you know I I'm with naming so we're not going to keep

with naming so we're not going to keep this named year so I'm going to modify

this named year so I'm going to modify this m language to be job post posted

this m language to be job post posted year with that renamed let's actually

year with that renamed let's actually move over to our other example

move over to our other example extracting out the hour for this we're

extracting out the hour for this we're going to be using that job posted

going to be using that job posted datetime column column from example from

datetime column column from example from selection in this case I want the hour

selection in this case I want the hour out of it so I'm just going to put

out of it so I'm just going to put something like nine and we can see that

something like nine and we can see that we also have this here for hours from

we also have this here for hours from job post to date time I want that one

job post to date time I want that one press enter again inspecting the M

press enter again inspecting the M language formula it's extracting the

language formula it's extracting the hour out of this one I'm good with it

hour out of this one I'm good with it I'm also seeing the other values are

I'm also seeing the other values are updating correctly I'll click okay and

updating correctly I'll click okay and we have our new column called hour which

we have our new column called hour which you know me we're going to fix this an

you know me we're going to fix this an updated hour to job posted hour press

updated hour to job posted hour press enter all right now we got it so you're

enter all right now we got it so you're probably like look I already know how to

probably like look I already know how to go something like the transform Tab and

go something like the transform Tab and already extract out that information

already extract out that information using these functions that we used

using these functions that we used before well that was mainly as a primer

before well that was mainly as a primer for this next example we're going to be

for this next example we're going to be doing and that's that with this job

doing and that's that with this job title column there's some job titles in

title column there's some job titles in here that have a lot of sort of

here that have a lot of sort of frivolous information that we don't need

frivolous information that we don't need like in this case supervisor information

like in this case supervisor information technology specialist and then

technology specialist and then parentheses it has associate director I

parentheses it has associate director I don't need anything in parenthesis

don't need anything in parenthesis similarly for this for the senior data

similarly for this for the senior data engineer I don't need this remote in

engineer I don't need this remote in here so let's select this job title go

here so let's select this job title go into add column column from example and

into add column column from example and from selection for this first one with

from selection for this first one with the associate director I'm going to

the associate director I'm going to select it so it appears below and then

select it so it appears below and then just highlight what I want press contrl

just highlight what I want press contrl C and then paste it in here then

C and then paste it in here then scrolling here through here to do a

scrolling here through here to do a cursor check so I'm seeing that senior

cursor check so I'm seeing that senior data engineer remotes in here I could

data engineer remotes in here I could select it and copy this down here

select it and copy this down here another option is I just go in here

another option is I just go in here double click it since it's now

double click it since it's now populating and delete out that remote

populating and delete out that remote press enter and it looks like it's doing

press enter and it looks like it's doing this it's getting the text before the

this it's getting the text before the limiter job title specifically before

limiter job title specifically before the parenthesis and looks like in this

the parenthesis and looks like in this case University grad data scientist PhD

case University grad data scientist PhD only now hiring it removed all that okay

only now hiring it removed all that okay so this is now doing what we want click

so this is now doing what we want click okay and I don't want I want to call

okay and I don't want I want to call this column text for delimiter I want to

this column text for delimiter I want to call this job title clean pressing enter

call this job title clean pressing enter all right so last thing I want to now

all right so last thing I want to now clean up these columns and you know how

clean up these columns and you know how I get I want the year an hour to be next

I get I want the year an hour to be next to the date time the job tile clean be

to the date time the job tile clean be next to the job tiles I could drag and

next to the job tiles I could drag and drop these I'm going to show you

drop these I'm going to show you something else this reordered column

something else this reordered column step we're going to be modifying the M

step we're going to be modifying the M language for this and I don't want

language for this and I don't want reordered columns to appear more than

reordered columns to appear more than once so I'm going to take it once again

once so I'm going to take it once again and drag it to the very end now what I

and drag it to the very end now what I can do is take and modify this m

can do is take and modify this m language that we have in here now if we

language that we have in here now if we actually inspect this reordered columns

actually inspect this reordered columns it may do this or may not in my case it

it may do this or may not in my case it didn't add anything after job skills it

didn't add anything after job skills it basically let any new columns just fall

basically let any new columns just fall towards the end so this job skills all

towards the end so this job skills all these other columns after it aren't

these other columns after it aren't included which not a big deal so what I

included which not a big deal so what I want to do is I want to move this year

want to do is I want to move this year and hour to near job posted date and job

and hour to near job posted date and job posted month so I'll enter inside of

posted month so I'll enter inside of here put in job posted year and also job

here put in job posted year and also job posted hour make sure we're putting

posted hour make sure we're putting commas after both of those then I'm

commas after both of those then I'm going to run this to make sure there's

going to run this to make sure there's no issues with it and it looks like it

no issues with it and it looks like it moved it over inspecting next to job

moved it over inspecting next to job post a date we have our month and also

post a date we have our month and also year and hour all right the last one is

year and hour all right the last one is this job title clean and I want this to

this job title clean and I want this to be right after job title so I'll go

be right after job title so I'll go ahead and put that in right here making

ahead and put that in right here making sure to put a comma after that and then

sure to put a comma after that and then from there press ing this check mark up

from there press ing this check mark up here to move it inspecting over we have

here to move it inspecting over we have job title clean right next to

it our next to look at is custom column we'll go ahead and actually just select

we'll go ahead and actually just select this and whenever we pull this up this

this and whenever we pull this up this tells us this allows us to add a column

tells us this allows us to add a column that's computed from the other column

that's computed from the other column provides a box to basically put in the

provides a box to basically put in the new column name but right here this is

new column name but right here this is where we put in the custom column

where we put in the custom column formula or the M language to maybe clean

formula or the M language to maybe clean it up now let's start with something

it up now let's start with something simple let's say I just wanted to repeat

simple let's say I just wanted to repeat the job ID column I would come over here

the job ID column I would come over here select job ID click insert it's going to

select job ID click insert it's going to put it in notice that the variable

put it in notice that the variable itself is inside of brackets and I'm

itself is inside of brackets and I'm going to rename this job ID repeat down

going to rename this job ID repeat down at the bottom it's telling me that no

at the bottom it's telling me that no syntax errors have been detected I'll

syntax errors have been detected I'll click okay and then I get this new step

click okay and then I get this new step for added custom and we can see hey it's

for added custom and we can see hey it's job ID repeat scrolling over yep it

job ID repeat scrolling over yep it repeated it if I want to go back in to

repeated it if I want to go back in to edit it I'll press that settings icon

edit it I'll press that settings icon and it's going to pull this back up so

and it's going to pull this back up so let's do something a little bit more

let's do something a little bit more complex now and it going to involve the

complex now and it going to involve the salary year average column and that

salary year average column and that salary hour adjusted column go ahead and

salary hour adjusted column go ahead and cancel out of this what I want is to

cancel out of this what I want is to create a new column that if there's a

create a new column that if there's a salary year average value it will

salary year average value it will basically be in that new column and then

basically be in that new column and then if there's a salary hour adjusted value

if there's a salary hour adjusted value it will be in that column instead

it will be in that column instead just as for warning anytime salary year

just as for warning anytime salary year average is null there's always a value

average is null there's always a value for salary hour adjusted and vice versa

for salary hour adjusted and vice versa so like I said we're not going to

so like I said we're not going to becoming coding experts with this so I

becoming coding experts with this so I recommend taking use of chat Bots like

recommend taking use of chat Bots like chat gbt gemini or whatnot lots of free

chat gbt gemini or whatnot lots of free options available out there anyway we

options available out there anyway we have this prompt of generate a power

have this prompt of generate a power query formula for a custom column on

query formula for a custom column on building make the column salary your

building make the column salary your average if it's not blank otherwise it

average if it's not blank otherwise it is salary hour adjusted now it's giving

is salary hour adjusted now it's giving do the entire M language right this is

do the entire M language right this is what we providing to the advanced editor

what we providing to the advanced editor providing that previous step name what

providing that previous step name what column we're using everything like that

column we're using everything like that I care about really this formula right

I care about really this formula right here specifically everything after the

here specifically everything after the each I'm going to copy this from if all

each I'm going to copy this from if all the way to the end that's the actual

the way to the end that's the actual code right here going back to the custom

code right here going back to the custom column I'm going to delete that job ID

column I'm going to delete that job ID out of there I want to make sure that

out of there I want to make sure that there's an equal sign still there and

there's an equal sign still there and I'm going to paste this in

I'm going to paste this in and you can see from this this is just

and you can see from this this is just basically an if formula it's doing if

basically an if formula it's doing if salary year average is not equal to null

salary year average is not equal to null then salary year average else perform

then salary year average else perform salary hour adjusted down at the bottom

salary hour adjusted down at the bottom we can see that no syntax errors have

we can see that no syntax errors have been detected so I'm going to go ahead

been detected so I'm going to go ahead and click okay so bam we now have this I

and click okay so bam we now have this I did in that jav ID repeat value here so

did in that jav ID repeat value here so we're going to actually change that to

we're going to actually change that to rename that value to salary year

rename that value to salary year combined and then clicking the check

combined and then clicking the check mark in order to to rerun that formula

mark in order to to rerun that formula to update the column and you know I like

to update the column and you know I like have my steps in order so I'm going to

have my steps in order so I'm going to grab reordered column and I'm going to

grab reordered column and I'm going to drag it to the very end and for this one

drag it to the very end and for this one I'm just going to drag it over to salary

I'm just going to drag it over to salary hour adjusted right after it to salary

hour adjusted right after it to salary year combined so now scrolling down just

year combined so now scrolling down just to double check it it looks like we got

to double check it it looks like we got 140,000 here 140,000 82,000 82,000 there

140,000 here 140,000 82,000 82,000 there so the formula filled out

correctly so let's get into our final task so we've been working this data

task so we've been working this data jobs clean data set we made this salary

jobs clean data set we made this salary year combined which is pretty useful

year combined which is pretty useful actually what happens now if we want it

actually what happens now if we want it in something like data jobs merged what

in something like data jobs merged what do we need to do to actually add it into

do we need to do to actually add it into here because we have everything we need

here because we have everything we need for it specifically we have that salary

for it specifically we have that salary year average and we have the salary hour

year average and we have the salary hour adjusted columns well we could recreate

adjusted columns well we could recreate it in here going through all those steps

it in here going through all those steps creating that if statement or we could

creating that if statement or we could just copy it out of the advanced error

just copy it out of the advanced error and bring it in here so I'm going to go

and bring it in here so I'm going to go back to data jobs cleaned and then under

back to data jobs cleaned and then under home Advanced editor I'm going to go and

home Advanced editor I'm going to go and find the step that's in here

find the step that's in here specifically it was this of added column

specifically it was this of added column and I'm going to copy it because I can

and I'm going to copy it because I can see that hey it has the salary year

see that hey it has the salary year combined in it I'm going to copy it all

combined in it I'm going to copy it all the way the the end and I'm going to

the way the the end and I'm going to copy it by pressing contrl C okay go and

copy it by pressing contrl C okay go and close out of this one and then bring

close out of this one and then bring over to data jobs merged go into the

over to data jobs merged go into the advanced editor and I want to insert it

advanced editor and I want to insert it in right at the end so I'm going to go

in right at the end so I'm going to go to at the end of this block of this let

to at the end of this block of this let block going to press enter and then from

block going to press enter and then from there press contrl + V to paste it in

there press contrl + V to paste it in now I'm already getting an error message

now I'm already getting an error message and it's saying hey token comma un

and it's saying hey token comma un basically expected and it's not getting

basically expected and it's not getting it if I scroll over I can see these

it if I scroll over I can see these squiggly lines right here basically

squiggly lines right here basically there's not if we can see there's commas

there's not if we can see there's commas after every one of these variable

after every one of these variable definitions so I need to come up here

definitions so I need to come up here put a comma in there next is this a

put a comma in there next is this a comma cannot proceed an in so if we

comma cannot proceed an in so if we scroll over we can see this is red

scroll over we can see this is red highlighted probably wrong not to have a

highlighted probably wrong not to have a comma here so we'll get rid of it now

comma here so we'll get rid of it now we're not done it's going to say there's

we're not done it's going to say there's no syntax errors but we didn't complete

no syntax errors but we didn't complete this remember you have to have the name

this remember you have to have the name of the it's got to reference the

of the it's got to reference the previous name here in it so if I tried

previous name here in it so if I tried to even though it says no syntax errors

to even though it says no syntax errors if I try to click done and go to load it

if I try to click done and go to load it I'm basically getting an error I can see

I'm basically getting an error I can see this by this basically air Bo at the top

this by this basically air Bo at the top of each one of these columns also

of each one of these columns also there's only one applied step and it's

there's only one applied step and it's calling it data job

calling it data job merged of the actual title itself but we

merged of the actual title itself but we need to fix this query and actually get

need to fix this query and actually get it back to where it had multiple

it back to where it had multiple different applied steps so I'm going to

different applied steps so I'm going to go back to the advanced editor we're

go back to the advanced editor we're going to show what we did wrong here and

going to show what we did wrong here and that has to deal with remember we had

that has to deal with remember we had before where we had something like

before where we had something like remove columns you reference the

remove columns you reference the previous column in it so in this case

previous column in it so in this case remove columns right there well rename

remove columns right there well rename columns is the last one we had I'm going

columns is the last one we had I'm going to go ahead and copy this by control

to go ahead and copy this by control cing it but yet we have inex inserted

cing it but yet we have inex inserted text before delimiter one which is not

text before delimiter one which is not correct so I'm going to select all of

correct so I'm going to select all of that and replace it by pressing crl +v

that and replace it by pressing crl +v so we have the rename columns now one

so we have the rename columns now one other thing we have to do this last

other thing we have to do this last statement or and the in portion needs to

statement or and the in portion needs to be referencing that last variable of

be referencing that last variable of added custom so I'm going to go ahead

added custom so I'm going to go ahead and copy this contrl C and then pasting

and copy this contrl C and then pasting it in control V click done and now

it in control V click done and now scrolling all the way over we can see

scrolling all the way over we can see that we have that salary year combined

that we have that salary year combined column that we created in the last query

column that we created in the last query it's at the end we do need to move it

it's at the end we do need to move it over but it's in there nonetheless so it

over but it's in there nonetheless so it helps with understanding these queries

helps with understanding these queries now one quick thing before we go we've

now one quick thing before we go we've gone through basically every single

gone through basically every single thing in this chapter on power query up

thing in this chapter on power query up to this point with the exception of this

to this point with the exception of this invoke custom functions this basically

invoke custom functions this basically invokes a custom function defined in the

invokes a custom function defined in the file for each row of this table this is

file for each row of this table this is more advanced and Beyond the scope of

more advanced and Beyond the scope of this course we're not going to be

this course we're not going to be covering it but is available for you to

covering it but is available for you to dive into say you're doing a lot of

dive into say you're doing a lot of different Imports and you need to

different Imports and you need to automate the Imports that you do this

automate the Imports that you do this would be a path you would go but for

would be a path you would go but for beginners like us I'm going to say stick

beginners like us I'm going to say stick away from it for the time being so this

away from it for the time being so this now wraps up on the M language and that

now wraps up on the M language and that was really a crash course and

was really a crash course and understanding how to use it by no means

understanding how to use it by no means do you need be a professional or be an

do you need be a professional or be an expert coder and codeing the M language

expert coder and codeing the M language if you got lost at any point in the way

if you got lost at any point in the way nothing to feel ashamed about this is a

nothing to feel ashamed about this is a very pretty complex topic if you would

very pretty complex topic if you would like to learn more I do recommend this

like to learn more I do recommend this book which is M is for data monkey it's

book which is M is for data monkey it's a good little read talking about not

a good little read talking about not only Power query but also how to

only Power query but also how to manipulate the M language I'll include a

manipulate the M language I'll include a link in the description below anyway

link in the description below anyway power query in my opinion is one of the

power query in my opinion is one of the most important features the most

most important features the most powerful tools within Excel and also

powerful tools within Excel and also powerbi and so it's worth your time

powerbi and so it's worth your time investing and learning it and so this

investing and learning it and so this all culminates and we're now finalized

all culminates and we're now finalized covering power query in this chapter in

covering power query in this chapter in the next chapter we're going be jumping

the next chapter we're going be jumping into Power pivot and that's going to

into Power pivot and that's going to jumping into actually data modeling but

jumping into actually data modeling but before that for those that purchase C

before that for those that purchase C practice problems you have some practice

practice problems you have some practice problems to go through and get more

problems to go through and get more familiar with that M language for

familiar with that M language for proceeding forward all right with that

proceeding forward all right with that see you in the next

one welcome to this chapter on power pivot and this chapter consists of four

pivot and this chapter consists of four different lessons where we're going to

different lessons where we're going to go an intro into Power pivot and over

go an intro into Power pivot and over the wind window that it actually

the wind window that it actually provides then from there looking into

provides then from there looking into Dax or data analytical Expressions which

Dax or data analytical Expressions which is a Formula language very similar to

is a Formula language very similar to excel formulas but before we actually

excel formulas but before we actually jump into this lesson and going over

jump into this lesson and going over what we're going for it we're going to

what we're going for it we're going to focus on what exactly is power

pivot so here I am in Excel and this is meant for me to just go through and

meant for me to just go through and quickly explain what is the power power

quickly explain what is the power power of power pivot I know that pun is

of power pivot I know that pun is getting sort of old by now but it really

getting sort of old by now but it really is powerful if you're curious of looking

is powerful if you're curious of looking at it it's in the workbook of power

at it it's in the workbook of power pivot intro part one part two is what

pivot intro part one part two is what we're going to be using for the actual

we're going to be using for the actual lesson so in power query in the last

lesson so in power query in the last chapter we end up clearing up our data

chapter we end up clearing up our data set to have these two main tables versus

set to have these two main tables versus data job salary which has the complete

data job salary which has the complete data set on all the data science job

data set on all the data science job postings and then data job skills which

postings and then data job skills which is unique to the skills for a job we

is unique to the skills for a job we also created a data jobs merge table but

also created a data jobs merge table but that table is actually going to be well

that table is actually going to be well it's pretty much Obsolete and power

it's pretty much Obsolete and power pivot is going to help replace that and

pivot is going to help replace that and for good reason so what exactly is power

for good reason so what exactly is power pivot well it's an addin we're going to

pivot well it's an addin we're going to get to adding it in and it has a few

get to adding it in and it has a few different features that you can do

different features that you can do within it such as accessing the data

within it such as accessing the data model adding measures kpis and whatnot

model adding measures kpis and whatnot this lesson is going to be going over

this lesson is going to be going over this tab as a quick refresher power

this tab as a quick refresher power pivot is going to be available in

pivot is going to be available in basically any version of Windows for

basically any version of Windows for Microsoft past

Microsoft past 2010 but it's completely not available

2010 but it's completely not available in either the Mac version or the

in either the Mac version or the Microsoft online version so you won't be

Microsoft online version so you won't be able to do this chapter if you have

able to do this chapter if you have those versions or the final project

those versions or the final project anyway the core portion of power pivot

anyway the core portion of power pivot is actually managing a data model and

is actually managing a data model and what's a data model well a data model

what's a data model well a data model defines how data is basically structured

defines how data is basically structured stored and also related in this case we

stored and also related in this case we have the data jobs salary table right

have the data jobs salary table right here and we have the data jobs skill

here and we have the data jobs skill table what we can do with power pivot

table what we can do with power pivot besides modeling these tables and

besides modeling these tables and showing how they're structured is the

showing how they're structured is the more important thing of creating a

more important thing of creating a relationship in this case I created a

relationship in this case I created a relationship between the job ID of data

relationship between the job ID of data job salary and that of data job skills

job salary and that of data job skills and because I created this relationship

and because I created this relationship I can look at things like the job title

I can look at things like the job title shot short column see how many jobs it

shot short column see how many jobs it has with it but also I can query across

has with it but also I can query across a table over to the job skills and see

a table over to the job skills and see how many skills has with it in fact

how many skills has with it in fact let's actually do that real quick here I

let's actually do that real quick here I have my data model itself I have my two

have my data model itself I have my two tables which are shown anyway I can look

tables which are shown anyway I can look at things like what are the count of the

at things like what are the count of the different job titles themselves I'm

different job titles themselves I'm going to do that on job ID and like

going to do that on job ID and like we've done plenty of times before here's

we've done plenty of times before here's the job count with a little clean up of

the job count with a little clean up of the actual text here but now with power

the actual text here but now with power pivot I can actually reach across to

pivot I can actually reach across to that other table of data job skills and

that other table of data job skills and drag the job skills into here and this

drag the job skills into here and this is telling us obviously the count of the

is telling us obviously the count of the skills based on the job title pretty

skills based on the job title pretty cool that we can reach across the tables

cool that we can reach across the tables and do this now the other cool thing

and do this now the other cool thing that power pivot unlocks is Dax or data

that power pivot unlocks is Dax or data analytical Expressions recall previously

analytical Expressions recall previously that we were using the average of the

that we were using the average of the salaries and like we learned way back

salaries and like we learned way back earlier in this Excel course we prefer

earlier in this Excel course we prefer actually a median salary but

actually a median salary but unfortunately looking at the value fied

unfortunately looking at the value fied settings window here there is no option

settings window here there is no option to actually pick median from this and

to actually pick median from this and that's where where Dax comes to the

that's where where Dax comes to the rescue with this I can go to something

rescue with this I can go to something like the power pivot Tab and now create

like the power pivot Tab and now create a measure which is where you actually

a measure which is where you actually insert in your Dax and I can create a

insert in your Dax and I can create a new one called median salary and we're

new one called median salary and we're going to be using this Dax formula in

going to be using this Dax formula in this case I'm going to use the median

this case I'm going to use the median formula very similar to the Excel

formula very similar to the Excel formula and I can do it on the entire

formula and I can do it on the entire salary year average column here I'm

salary year average column here I'm going to format it real quick and then

going to format it real quick and then press enter anyway bam now we have

press enter anyway bam now we have because of the power of Dax we have the

because of the power of Dax we have the ability to get the median salary and

ability to get the median salary and those Dax things can do some pretty

those Dax things can do some pretty complicated calculations so in the case

complicated calculations so in the case of here we have this job count and count

of here we have this job count and count of skills and we want to see what were

of skills and we want to see what were the skills per job specifically in this

the skills per job specifically in this case what is something like C2 / B2 and

case what is something like C2 / B2 and then dragging all the way down and

then dragging all the way down and filling it for all these this provides a

filling it for all these this provides a much better analysis of what's going on

much better analysis of what's going on with these values of counts and skills

with these values of counts and skills here when we get this proportionality we

here when we get this proportionality we can create this with measures as shown

can create this with measures as shown in this final pivot table that we're

in this final pivot table that we're going to be creating coming up in the

going to be creating coming up in the third lesson of this chapter so in

third lesson of this chapter so in summary power pivot provides us the

summary power pivot provides us the opportunity to now model our data which

opportunity to now model our data which allows us to one create relationships

allows us to one create relationships and two allows us on unlocks these

and two allows us on unlocks these measures that we can create using

Dax all right so let's get into this lesson what we're going to be focused on

lesson what we're going to be focused on for well first thing is we're going to

for well first thing is we're going to enable the power power pivot plugin and

enable the power power pivot plugin and then from there actually getting in to

then from there actually getting in to data modeling or modeling our data that

data modeling or modeling our data that we imported through Power query after we

we imported through Power query after we have everything set up with our data

have everything set up with our data model we're going to then move into

model we're going to then move into performing our first analysis analyzing

performing our first analysis analyzing based on a job title how many different

based on a job title how many different skills they have associated with it like

skills they have associated with it like I said we'll eventually get to that

I said we'll eventually get to that skills per job in an upcoming lesson so

skills per job in an upcoming lesson so for this you can continue to work in

for this you can continue to work in that workbook that we were working with

that workbook that we were working with in the last chapter EMP power query

in the last chapter EMP power query we're going to continue work on that

we're going to continue work on that because we want to use those queries

because we want to use those queries that we built if you got lost dur in the

that we built if you got lost dur in the way and just want to start back up we're

way and just want to start back up we're going to be starting from that M

going to be starting from that M language workbook back in the power

language workbook back in the power query chapter as a reminder these

query chapter as a reminder these lessons or workbooks are what are the

lessons or workbooks are what are the completed workbooks at the end of the

completed workbooks at the end of the lesson specifically for this lesson part

lesson specifically for this lesson part one was just that intro part two is what

one was just that intro part two is what will be done at the end of this lesson

anyway here I am in the M language workbook we need to get into enabling

workbook we need to get into enabling power pivot right now you probably don't

power pivot right now you probably don't see Power pivot up at the top of the

see Power pivot up at the top of the tabs so I'm going to go into file and

tabs so I'm going to go into file and then go down to options from here I'm

then go down to options from here I'm going to select add-ins like we did

going to select add-ins like we did before and instead of excel addins we're

before and instead of excel addins we're actually going to be using those Comm

actually going to be using those Comm addins I'm going click go and they have

addins I'm going click go and they have three different ones available data

three different ones available data streamer power map and power pivot we

streamer power map and power pivot we want Power pivot I'm go ahead and click

want Power pivot I'm go ahead and click okay now power pivot should appear up at

okay now power pivot should appear up at the top all the way on the right hand

the top all the way on the right hand side and should look something like this

side and should look something like this quick little overview of this tab manage

quick little overview of this tab manage here pops up the power pivot window

here pops up the power pivot window which we're going to be doing a deep

which we're going to be doing a deep dive on this in the next lesson we're

dive on this in the next lesson we're going to use it a little bit in this

going to use it a little bit in this lesson but anyway that's one way you can

lesson but anyway that's one way you can actually access it you can also go to

actually access it you can also go to the data Tab and then here under data

the data Tab and then here under data tools you should see it also and you'll

tools you should see it also and you'll be able to manage your data model and

be able to manage your data model and once again it will pop up the window

once again it will pop up the window additionally on this tab you have the

additionally on this tab you have the ability to create measures and kpis

ability to create measures and kpis which going to be diving deep into in

which going to be diving deep into in the third and fourth lesson if you have

the third and fourth lesson if you have a table within your worksheets you can

a table within your worksheets you can add it to your dat model you can also go

add it to your dat model you can also go about detecting relationships although I

about detecting relationships although I don't find that this feature works that

don't find that this feature works that well and then finally they have settings

well and then finally they have settings and settings I don't really touch that

and settings I don't really touch that much nor does it have much control

here so let's actually get into EMB boarding some data into our data model

boarding some data into our data model we're going to do a simple example first

we're going to do a simple example first here I created a new sheet made three

here I created a new sheet made three columns of ID name salary and then

columns of ID name salary and then different values associated with it one

different values associated with it one way I can add to the data model is if I

way I can add to the data model is if I have data in a table is to do this

have data in a table is to do this feature of add to data model in this my

feature of add to data model in this my table has headers I'll go ahead and

table has headers I'll go ahead and continue and then it will pop open power

continue and then it will pop open power pivot a similar like environment will

pivot a similar like environment will exist with Excel I can't actually edit

exist with Excel I can't actually edit any numbers in here this is just how

any numbers in here this is just how you're modeling your data if you needed

you're modeling your data if you needed to actually edit it I have to go back to

to actually edit it I have to go back to the sheets and like I said this isn't a

the sheets and like I said this isn't a method I typically use typically have

method I typically use typically have bigger data sets not located in tables

bigger data sets not located in tables so I'm going to go ahead and rightclick

so I'm going to go ahead and rightclick this down at the bottom this table name

this down at the bottom this table name of table two click delete it's going to

of table two click delete it's going to say hey do you sure you want to delete

say hey do you sure you want to delete this table and Bam it's gone all right

this table and Bam it's gone all right so now there's nothing in our data model

so now there's nothing in our data model right now here we are still inside the

right now here we are still inside the power pivot window and if you've noticed

power pivot window and if you've noticed from this in the Home tab right here it

from this in the Home tab right here it has the option to get external data they

has the option to get external data they have options for you to actually connect

have options for you to actually connect Direct ly with power pivot to things

Direct ly with power pivot to things like a SQL Server Microsoft Access you

like a SQL Server Microsoft Access you could also get it from some sort of data

could also get it from some sort of data feed and then this option would be more

feed and then this option would be more probably useful in that it has a lot of

probably useful in that it has a lot of different sources you could use such as

different sources you could use such as other Excel files text files such as

other Excel files text files such as csvs and whatnot now you may be asking

csvs and whatnot now you may be asking yourself I'm going to close out of this

yourself I'm going to close out of this power pivot why would I import of that

power pivot why would I import of that whenever we just went through with power

whenever we just went through with power query to get data via this when which

query to get data via this when which time should I use which well it's very

time should I use which well it's very important to remember the purpose of the

important to remember the purpose of the tool that you're using power query is an

tool that you're using power query is an ETL tool extract transform and load we

ETL tool extract transform and load we did a lot of Transformations with our

did a lot of Transformations with our data set and so that's really the power

data set and so that's really the power of power query and then it loads it in

of power query and then it loads it in power pivot strengths is not in ETL or

power pivot strengths is not in ETL or data cleaning instead it's in data

data cleaning instead it's in data modeling creating these relationships

modeling creating these relationships and Dax now now you may be tempted to

and Dax now now you may be tempted to come inside of existing connections and

come inside of existing connections and try to connect to specifically that

try to connect to specifically that salary and skills and if we went through

salary and skills and if we went through like in the salary case and try to click

like in the salary case and try to click open we're going to get an error message

open we're going to get an error message and I'll be honest this is really

and I'll be honest this is really confusing because we have this workbook

confusing because we have this workbook connections why isn't this working well

connections why isn't this working well it really just comes down to naming

it really just comes down to naming conventions and that the fact that power

conventions and that the fact that power query connections are not the same as

query connections are not the same as power pivot connections but we have a

power pivot connections but we have a fix for this we just need to exit out of

fix for this we just need to exit out of the power pivot window here inside of

the power pivot window here inside of queries and connections remember you can

queries and connections remember you can get to that by going to the data Tab and

get to that by going to the data Tab and going to queries and connections we can

going to queries and connections we can go to something like data job salary

go to something like data job salary which right now is a connection only

which right now is a connection only rightclick it and go to load to right

rightclick it and go to load to right now it's only under only create

now it's only under only create connection but we need to check this

connection but we need to check this check mark of add this data to the data

check mark of add this data to the data model I'm going to click okay it's going

model I'm going to click okay it's going to go through this process of loading

to go through this process of loading the data and now it talks about the rows

the data and now it talks about the rows are loaded but mainly if I go to the

are loaded but mainly if I go to the connection it has this new connection

connection it has this new connection now of this workbook data model which if

now of this workbook data model which if I go to and actually open up or manage

I go to and actually open up or manage our data model we can see that it's

our data model we can see that it's inside of here we have this basically

inside of here we have this basically sheet for the table itself of data job

sheet for the table itself of data job salary inside power pivot inside the

salary inside power pivot inside the data model now we do need to get that

data model now we do need to get that other pivot table or other table into

other pivot table or other table into there as well so I'm going go to queries

there as well so I'm going go to queries data job skills s right click this load

data job skills s right click this load to and also add this to the data model

to and also add this to the data model okay it talks about 167,000 rows are

okay it talks about 167,000 rows are loaded and another connections still

loaded and another connections still it's only going to be one connection

it's only going to be one connection because we only have one data model in

because we only have one data model in this case and now when I go to manage

this case and now when I go to manage the data model I have two basically

the data model I have two basically sheets down here but two tables and now

sheets down here but two tables and now we have the data job skills in

here anyway I want to do some cleanup real quick I'm going to clean up power

real quick I'm going to clean up power pivot but this data jobs merged and this

pivot but this data jobs merged and this data jobs cleaned it's going to be very

data jobs cleaned it's going to be very confusing like I said we're not using

confusing like I said we're not using this mainly for the fact that we have

this mainly for the fact that we have duplicate values in here for senior data

duplicate values in here for senior data scientists in this case and then for the

scientists in this case and then for the salaries and so if we don't manipulate

salaries and so if we don't manipulate this in a correct manner we're going to

this in a correct manner we're going to get the wrong results so we're just

get the wrong results so we're just going to get rid of these so for data

going to get rid of these so for data jobs merge I'm going to write click and

jobs merge I'm going to write click and select delete and it's going to say hey

select delete and it's going to say hey should you want to delete data jobs

should you want to delete data jobs merge yes I do and then I'm going to do

merge yes I do and then I'm going to do the same thing with data jobs clean

the same thing with data jobs clean right click it and select delete also if

right click it and select delete also if you have these tabs down here for data

you have these tabs down here for data jobs clean or merge you can go ahead and

jobs clean or merge you can go ahead and delete those as well with our models now

delete those as well with our models now cleaned up let's actually get into going

cleaned up let's actually get into going over really briefly this power pivot

over really briefly this power pivot window with this we have three main tabs

window with this we have three main tabs of Home Design and advanced advanced

of Home Design and advanced advanced we're not going to go into a lot of

we're not going to go into a lot of things inside of this if any at all it's

things inside of this if any at all it's beyond the scope of the course we're

beyond the scope of the course we're going to be focusing mostly on the home

going to be focusing mostly on the home and the design t tab so with this tab

and the design t tab so with this tab we've already gone over get external

we've already gone over get external data but we can do things like refresh

data but we can do things like refresh our data if we know that it's updated in

our data if we know that it's updated in power query generate pivot tables and

power query generate pivot tables and pivot charts based on our data model

pivot charts based on our data model itself change the formatting of a

itself change the formatting of a particular column in this case is

particular column in this case is noticing as text if we go to the data

noticing as text if we go to the data jobs salary data we can actually scroll

jobs salary data we can actually scroll over and see that for the salary your

over and see that for the salary your average column it knows that it's a

average column it knows that it's a currency we did a lot of this cleanup

currency we did a lot of this cleanup right in power query and setting these

right in power query and setting these different data types so this saves a lot

different data types so this saves a lot of steps here in power pivot if it

of steps here in power pivot if it wasn't done now we have options

wasn't done now we have options displaying the table below that we can

displaying the table below that we can actually sort it we can filter it or

actually sort it we can filter it or sort by a certain column they also

sort by a certain column they also provide options to find a specific value

provide options to find a specific value within here and then these features for

within here and then these features for calculations I don't find myself using

calculations I don't find myself using that much as far as the auto so anyway

that much as far as the auto so anyway over on the right the most important

over on the right the most important thing I find is allows you to toggle on

thing I find is allows you to toggle on the different views of your data set so

the different views of your data set so right now this is the data View and if I

right now this is the data View and if I scroll over here this is the diagram

scroll over here this is the diagram View and this is going to show our two

View and this is going to show our two different tables side by side I'm going

different tables side by side I'm going to move them over and actually expand

to move them over and actually expand this one out to show all the different

this one out to show all the different columns and then the data job skills now

columns and then the data job skills now back on that data view clicking that we

back on that data view clicking that we have data view but also below this we

have data view but also below this we have this calculation area which I can

have this calculation area which I can toggle on and off calculation areas are

toggle on and off calculation areas are where we're going to be storing our

where we're going to be storing our different measures that we build with

different measures that we build with dacks and so they'll be appearing

dacks and so they'll be appearing underneath here here if we have any

underneath here here if we have any hidden columns we'll be able to toggle

hidden columns we'll be able to toggle them on and off right now I don't have

them on and off right now I don't have any hidden columns now one thing to note

any hidden columns now one thing to note with this data cleanup some of that we

with this data cleanup some of that we did before with formatting stuff some of

did before with formatting stuff some of it's going to be quite limiting you may

it's going to be quite limiting you may not be able to do like in the case of

not be able to do like in the case of this so data job skills has this job

this so data job skills has this job title short column and actually if we

title short column and actually if we look at the data jobs salary data set we

look at the data jobs salary data set we have the same repeated column in it so

have the same repeated column in it so data job skills this job title short

data job skills this job title short right here is unnecessary now I could

right here is unnecessary now I could rightclick it and try to delete the

rightclick it and try to delete the column

column and ask me if I want to delete it it's

and ask me if I want to delete it it's going to tell me it's not going to be

going to tell me it's not going to be able to do it because it was created by

able to do it because it was created by a query I.E through Power query and

a query I.E through Power query and instead I should actually update it

instead I should actually update it through Power query which I would

through Power query which I would actually argue as best practice anyway

actually argue as best practice anyway so I could exit out a power pivot launch

so I could exit out a power pivot launch power query by pressing alt F12 then go

power query by pressing alt F12 then go into the data jobs skills query and if I

into the data jobs skills query and if I want I can just select this column and

want I can just select this column and select remove columns but you know how I

select remove columns but you know how I am I like to actually clean up the

am I like to actually clean up the applied steps because it could depending

applied steps because it could depending on how large your power query query is

on how large your power query query is it could take a long time to load it and

it could take a long time to load it and unload it necessary so if I go to this

unload it necessary so if I go to this remove other colums that's the first

remove other colums that's the first time that it appears in it I can remove

time that it appears in it I can remove this by deleting it out of there then

this by deleting it out of there then pressing enter we may get an error

pressing enter we may get an error message we may not I'm not sure going to

message we may not I'm not sure going to the last step in here I notice there one

the last step in here I notice there one thing of the table wasn't found

thing of the table wasn't found specifically here it's appearing job

specifically here it's appearing job title short in here so I can go ahead

title short in here so I can go ahead and delete job title short along with

and delete job title short along with with that comma and Bam we now have this

with that comma and Bam we now have this Final Table just to lean for those two

Final Table just to lean for those two steps I'm going to go ahead and close

steps I'm going to go ahead and close and load this and now going back in to

and load this and now going back in to look at our data model and power pivot I

look at our data model and power pivot I can see that it updated for data job

skills all right moving into this design tab within power pivot this has a few

tab within power pivot this has a few different options within it for adding

different options within it for adding columns freezing columns just messing

columns freezing columns just messing with the columns they also have

with the columns they also have different options for creating

different options for creating calculations concerning columns we'll be

calculations concerning columns we'll be getting into calculating columns more in

getting into calculating columns more in the next lesson so stay tuned for that

the next lesson so stay tuned for that right the main thing that we're actually

right the main thing that we're actually going to be doing in this portion of the

going to be doing in this portion of the video is actually setting up

video is actually setting up relationships and that is we could go

relationships and that is we could go about creating a relationship here and

about creating a relationship here and right now I have data job skills and I

right now I have data job skills and I could relate it with the job ID by

could relate it with the job ID by pulling the drop down to the data jobs

pulling the drop down to the data jobs salary table on that job ID now that's a

salary table on that job ID now that's a way I can do it I'm actually not going

way I can do it I'm actually not going to do it this way I actually prefer

to do it this way I actually prefer going to the diagram View and then from

going to the diagram View and then from there just dragging and dropping the job

there just dragging and dropping the job IDs across each other and then it

IDs across each other and then it establish this connection which we can

establish this connection which we can see through this line through here now

see through this line through here now there's a few different things that we

there's a few different things that we need to notice from this line here one

need to notice from this line here one this Arrow it's going to come to bite Us

this Arrow it's going to come to bite Us in the butt later and that's that that

in the butt later and that's that that Arrow only allows data flow in One

Arrow only allows data flow in One Direction and by data flow I mean

Direction and by data flow I mean filtering if I try to filter something

filtering if I try to filter something in the data job skills table this arrow

in the data job skills table this arrow is only pointing in One Direction I

is only pointing in One Direction I won't be able to filter it back we'll

won't be able to filter it back we'll encounter those problems in a little bit

encounter those problems in a little bit and we'll talk about strategies how to

and we'll talk about strategies how to actually offset it the other thing to

actually offset it the other thing to note with this relationship here is you

note with this relationship here is you notice right here it says one and over

notice right here it says one and over here it says star in this case this is a

here it says star in this case this is a one to many relationship and what does

one to many relationship and what does this mean well going to our data view

this mean well going to our data view for data job salary we only have one

for data job salary we only have one unique ID for each job whereas in the

unique ID for each job whereas in the data jobs skills we have multiple

data jobs skills we have multiple different job IDs or many job IDs now if

different job IDs or many job IDs now if we only had one job ID in there and we

we only had one job ID in there and we actually looked that diagram view for

actually looked that diagram view for this relationship we'd have a one to one

this relationship we'd have a one to one relationship but we have multiple skills

relationship but we have multiple skills in there so that's not possible now it's

in there so that's not possible now it's also possible to have a basically as to

also possible to have a basically as to ASIS or many to many relationship but

ASIS or many to many relationship but that causes a mess slows down your data

that causes a mess slows down your data model and I don't recommend it so you

model and I don't recommend it so you should typically see either a one to one

should typically see either a one to one or a one to many last little wrap up

or a one to many last little wrap up before we actually analyze and use this

before we actually analyze and use this relationship we have the options for

relationship we have the options for table properties which we're not going

table properties which we're not going to be able to look at because this was

to be able to look at because this was created the a power query for this

created the a power query for this connection and then we have options to

connection and then we have options to create date tables underneath calendars

create date tables underneath calendars which we're going to be exploring in an

which we're going to be exploring in an upcoming lesson and like always you have

upcoming lesson and like always you have a undo and redo anyway let's actually

a undo and redo anyway let's actually get into analyzing and putting this

get into analyzing and putting this actual relationship to the test so what

actual relationship to the test so what we're going to do is inside the Home tab

we're going to do is inside the Home tab go to pivot table CU we're want to

go to pivot table CU we're want to create a pivot table with this we're

create a pivot table with this we're going to insert a pivot table and we'll

going to insert a pivot table and we'll have it insert into a new worksheet

have it insert into a new worksheet selecting inside the pivot table it's

selecting inside the pivot table it's not having the field list come up so

not having the field list come up so I'll select it under pivot table analyze

I'll select it under pivot table analyze anyway we want to query across this

anyway we want to query across this table to show the power of the

table to show the power of the relationships so what I'm going to do is

relationships so what I'm going to do is from the data jobs salary table I'm

from the data jobs salary table I'm going to take that job title short throw

going to take that job title short throw it into the r those and then from there

it into the r those and then from there going to come down to the data jobs

going to come down to the data jobs skills table and I'm going to throw the

skills table and I'm going to throw the job skills into the values it should be

job skills into the values it should be performing a count and then I'm going to

performing a count and then I'm going to organize this real quick from largest to

organize this real quick from largest to smallest and it looks like data

smallest and it looks like data Engineers have the most so this is

Engineers have the most so this is pretty neat we're able now to query

pretty neat we're able now to query across tables going back into that power

across tables going back into that power pivot window this connection allows us

pivot window this connection allows us to do that I'm going to just show you

to do that I'm going to just show you something real quick by clicking this

something real quick by clicking this Rel ship right clicking it and deleting

Rel ship right clicking it and deleting it want to delete for model and I want

it want to delete for model and I want to show you how these values are

to show you how these values are basically going to change inside our

basically going to change inside our pivot table basically to the fact that

pivot table basically to the fact that they're going to have it to where

they're going to have it to where they're all the same value and that's

they're all the same value and that's how you know that your relationship is

how you know that your relationship is not set up correctly whenever you have

not set up correctly whenever you have multiple repeating values and you expect

multiple repeating values and you expect them not to be anyway sometimes you'll

them not to be anyway sometimes you'll see this popup come up of relationships

see this popup come up of relationships between tables may be needed

between tables may be needed autodetect and sometimes it works

autodetect and sometimes it works sometimes it doesn't um in this case it

sometimes it doesn't um in this case it looked like it worked so we're going to

looked like it worked so we're going to go with it and just double- checking it

go with it and just double- checking it in power pivot it is set up

correctly so for this final analysis we're going to be looking at building

we're going to be looking at building this visualization right here analyzing

this visualization right here analyzing what are the top skills of data nerds

what are the top skills of data nerds we're basically remaking what we did in

we're basically remaking what we did in the power query chapter now that we have

the power query chapter now that we have that updated data model anyway we're

that updated data model anyway we're going to build this out to see where the

going to build this out to see where the skills counts for each of these and also

skills counts for each of these and also provide filters for job country so back

provide filters for job country so back inside the workbook that we're

inside the workbook that we're previously working with if I would

previously working with if I would actually remember we did make that sort

actually remember we did make that sort of similar visualization that I talked

of similar visualization that I talked about but however if I go to data and

about but however if I go to data and actually refresh the data it's going to

actually refresh the data it's going to give me this error message because once

give me this error message because once again we deleted dat jobs merged anyway

again we deleted dat jobs merged anyway I thought this was actually going to go

I thought this was actually going to go away it didn't it is not what we want

away it didn't it is not what we want we're going to delete this one and then

we're going to delete this one and then we're going to do a little bit of

we're going to do a little bit of cleanup so that one that we created the

cleanup so that one that we created the job analysis on I'm going to actually

job analysis on I'm going to actually just rename that quick to job analysis

just rename that quick to job analysis and then now in this new sheet we're

and then now in this new sheet we're going to do we're going to name this one

going to do we're going to name this one skill job analysis anyway let's insert a

skill job analysis anyway let's insert a pivot table in here so we go to insert

pivot table in here so we go to insert pivot table and now what we have the

pivot table and now what we have the option for is from data model and it's

option for is from data model and it's ask if I want to put it in the existing

ask if I want to put it in the existing worksheet yes I do remember we want to

worksheet yes I do remember we want to analyze the skills and specifically how

analyze the skills and specifically how many counts they have associated with it

many counts they have associated with it or how many jobs they have associated

or how many jobs they have associated with it so I'm put the skills into into

with it so I'm put the skills into into the rows and then from there I want to

the rows and then from there I want to count how many jobs are associated with

count how many jobs are associated with it so I'm just going to drag that job ID

it so I'm just going to drag that job ID into the values right now it's doing a

into the values right now it's doing a sum going click on it go to Value field

sum going click on it go to Value field settings change this to count now you

settings change this to count now you may be like Luke could we use the job

may be like Luke could we use the job skills count and we can which has the

skills count and we can which has the same exact values but actually closing

same exact values but actually closing this out and taking out job skills

this out and taking out job skills you're probably more interested in why

you're probably more interested in why can't I use something like the job ID

can't I use something like the job ID from the data job salary table well if

from the data job salary table well if drag that over and then I change this

drag that over and then I change this value field setting to account count and

value field setting to account count and click okay you notice it says

click okay you notice it says 32672 which is coincidentally the same

32672 which is coincidentally the same number of rows of that data set and this

number of rows of that data set and this gets into the point of filter Direction

gets into the point of filter Direction what do I mean by that let's go back to

what do I mean by that let's go back to the data model itself looking at it in

the data model itself looking at it in diagram view remember the arrow is

diagram view remember the arrow is pointed towards the data job skill table

pointed towards the data job skill table right now I have job skills in the rows

right now I have job skills in the rows and I'm trying to filter for data job

and I'm trying to filter for data job salary based on the count of the job IDs

salary based on the count of the job IDs but the arrow doesn't flow in that

but the arrow doesn't flow in that direction we can't do it now in

direction we can't do it now in something like powerbi you can actually

something like powerbi you can actually rightclick this edit the relationship

rightclick this edit the relationship and change the direction that's not

and change the direction that's not possible within Excel unfortunately

possible within Excel unfortunately anyway we're going to be using Dax to

anyway we're going to be using Dax to fix this in the future for the time

fix this in the future for the time being we're just going to go about using

being we're just going to go about using in this case for this analysis the same

in this case for this analysis the same values in the same table I'm going to

values in the same table I'm going to remove this other job ID from the other

remove this other job ID from the other table anyway we're going to sort these

table anyway we're going to sort these values from largest to smallest then

values from largest to smallest then additionally I only want to show the top

additionally I only want to show the top 10 skills so I'll go to Value filters

10 skills so I'll go to Value filters and then top one dot dot dot top 10

and then top one dot dot dot top 10 items by count of job ID is what I want

items by count of job ID is what I want and so now we have this so now we have

and so now we have this so now we have the values we want to visualize I'll go

the values we want to visualize I'll go in and actually insert a pivot chart for

in and actually insert a pivot chart for this I like the bar because it makes it

this I like the bar because it makes it easier to read the different skills that

easier to read the different skills that it has right there and I'm realizing now

it has right there and I'm realizing now the sword order is actually back

the sword order is actually back backwards in this I want it from

backwards in this I want it from smallest to largest I'm also going to

smallest to largest I'm also going to right click and hide all field buttons

right click and hide all field buttons we're also going to be adding access

we're also going to be adding access titles for the primary horizontal and

titles for the primary horizontal and then removing that Legend we'll update

then removing that Legend we'll update this title to what are the top skills of

this title to what are the top skills of data nerds and then the y- axis is

data nerds and then the y- axis is self-explanatory but for the x-axis

self-explanatory but for the x-axis we'll label this skill count in job

we'll label this skill count in job postings okay the last thing we need to

postings okay the last thing we need to do now is actually add some slicers to

do now is actually add some slicers to this so we can actually control it

this so we can actually control it better so selecting the table itself

better so selecting the table itself going to insert slicers I'm going to

going to insert slicers I'm going to select the job title short and also we

select the job title short and also we want job country right here which each

want job country right here which each of these slicers I'm going to rename

of these slicers I'm going to rename them also this one job title short I'm

them also this one job title short I'm going to rename to job title and then

going to rename to job title and then job country I'm going to rename to

job country I'm going to rename to Country now when I go through I can

Country now when I go through I can actually select something like data

actually select something like data analyst and it will filter down and

analyst and it will filter down and actually see the associated skills I

actually see the associated skills I could also do something like like look

could also do something like like look at those in the United States

at those in the United States specifically for their counts and we see

specifically for their counts and we see that SQL Excel and Tableau are the three

that SQL Excel and Tableau are the three top skills now you may be scratching

top skills now you may be scratching your head on like okay I thought we were

your head on like okay I thought we were trying earlier to actually aggregate

trying earlier to actually aggregate something in the pivot table and it

something in the pivot table and it didn't work well remember this arrow is

didn't work well remember this arrow is pointing to the filter Direction so in

pointing to the filter Direction so in our case we have a job title short

our case we have a job title short slicer because this arrows in the

slicer because this arrows in the direction back to the data job skills

direction back to the data job skills table we can filter in that direction

table we can filter in that direction but we cannot conversely filter in the

but we cannot conversely filter in the other direction that's why we can't get

other direction that's why we can't get the counts from these tables little

the counts from these tables little confusing I know but I promise you we

confusing I know but I promise you we will work out as we go through this

will work out as we go through this entire chapter in power pivot so bam we

entire chapter in power pivot so bam we just completed our first analysis for

just completed our first analysis for our final project we have a few more

our final project we have a few more analysis coming up in the next lessons

analysis coming up in the next lessons you do have some practice problems

you do have some practice problems though to go through and get yourself

though to go through and get yourself more familiar with power pivot and

more familiar with power pivot and understanding what's going on with these

understanding what's going on with these relationships the one to many and

relationships the one to many and whatnot all right with that I'll see you

whatnot all right with that I'll see you in the next one which we're going to do

in the next one which we're going to do a deeper dive on looking into that power

a deeper dive on looking into that power pivot window that I'll see you

there all right let's now dive further into Power pivot and we're going to be

into Power pivot and we're going to be focusing on the power pivot window for

focusing on the power pivot window for this we're going to be looking at some

this we're going to be looking at some major aspects of it for this we're going

major aspects of it for this we're going to get into using a little bit of Dax to

to get into using a little bit of Dax to create our first measure and with those

create our first measure and with those measures we're also going to be

measures we're also going to be exploring the difference between

exploring the difference between implicit and explicit measures don't

implicit and explicit measures don't worry we'll cover that in a bit from

worry we'll cover that in a bit from there we're going to move into a feature

there we're going to move into a feature that's related to measures called

that's related to measures called calculated columns and it's going to

calculated columns and it's going to allow us to inside of our data model

allow us to inside of our data model create different values such in this

create different values such in this case we can actually create a date colum

case we can actually create a date colum from our date time value the last thing

from our date time value the last thing we'll explore are date tables which

we'll explore are date tables which power pivot gives with a click of a

power pivot gives with a click of a button and allows us to connect these

button and allows us to connect these data tables of these date tables to our

data tables of these date tables to our original data source and then filter it

original data source and then filter it by a lot of different data and so we'll

by a lot of different data and so we'll wrap this all up with a final analysis

wrap this all up with a final analysis where we're looking at job postings

where we're looking at job postings based on a day of week using this date

based on a day of week using this date table anyway jumping into Excel for this

table anyway jumping into Excel for this we're not going to be using any of the

we're not going to be using any of the work that we've done previously instead

work that we've done previously instead we're going to open up a completely new

we're going to open up a completely new workbook and be working out of this

workbook and be working out of this instead and the reason is all the work

instead and the reason is all the work that we're going to be doing within this

that we're going to be doing within this lesson we're not going to be carrying it

lesson we're not going to be carrying it on to our project that we're going using

on to our project that we're going using this is more this lesson is more to get

this is more this lesson is more to get us more familiar with the powers power

us more familiar with the powers power pivot oh gosh this pun's killing me and

pivot oh gosh this pun's killing me and so we'll eventually incorporate some of

so we'll eventually incorporate some of the stuff into our final project but

the stuff into our final project but like I said we're going to be starting

like I said we're going to be starting with a blank notebook or workbook for

with a blank notebook or workbook for this as always if you want to see what

this as always if you want to see what the results are at the end of this

the results are at the end of this lesson you can just go to Power pivot

lesson you can just go to Power pivot window and it will have

it all right so let's actually get some data into here to start working with and

data into here to start working with and like I said we're not going to use power

like I said we're not going to use power query at all for this we're going to use

query at all for this we're going to use power pivot so I'm going to open up the

power pivot so I'm going to open up the goto to the manage the power pivot data

goto to the manage the power pivot data model and we want to get this external

model and we want to get this external data specifically we want to get that

data specifically we want to get that Excel workbook that we've been working

Excel workbook that we've been working with of data jobs salary all so

with of data jobs salary all so underneath the Home tab I'm going to go

underneath the Home tab I'm going to go to get external data and it's going to

to get external data and it's going to be from other sources we scroll all down

be from other sources we scroll all down we could look at how we can import it

we could look at how we can import it from different databases or whatnot

from different databases or whatnot we're going to be doing it from an Excel

we're going to be doing it from an Excel file then from there we're going to

file then from there we're going to browse the connections navigating into

browse the connections navigating into that data set folder I'm going select

that data set folder I'm going select data jobs salary all it PR me if I want

data jobs salary all it PR me if I want to use the first row as column headers I

to use the first row as column headers I do if I wanted to I could go in and test

do if I wanted to I could go in and test the connection to make sure it's it's

the connection to make sure it's it's going to succeed and it does so we'll go

going to succeed and it does so we'll go from there to next it sees that it has

from there to next it sees that it has one sheet within the workbook that's the

one sheet within the workbook that's the one that I want I'll click finish next

one that I want I'll click finish next it'll go through the import looks like

it'll go through the import looks like it completed it has a success got 32,000

it completed it has a success got 32,000 rows I'll click close now let's go

rows I'll click close now let's go through and actually clean this data set

through and actually clean this data set up using power pivot now I know in the

up using power pivot now I know in the last lesson I talked about hey we're

last lesson I talked about hey we're using power query for ETL and that's

using power query for ETL and that's true but let's say you have a quick data

true but let's say you have a quick data set you need to connect to and model

set you need to connect to and model quickly in that case you would do some

quickly in that case you would do some of the stuff that I'm going to do here

of the stuff that I'm going to do here in order to quickly model it if I wanted

in order to quickly model it if I wanted to rename it I'd come down to this

to rename it I'd come down to this basically sheet tab down here it's

basically sheet tab down here it's called sheet one after where it's at

called sheet one after where it's at I'll rename it and we'll keep a similar

I'll rename it and we'll keep a similar naming Convention of Jatt jobs salary go

naming Convention of Jatt jobs salary go ahead and click enter so let's say for

ahead and click enter so let's say for this quick analysis that we're trying to

this quick analysis that we're trying to do in this lesson I'm trying to analyze

do in this lesson I'm trying to analyze only the yearly salary data I don't care

only the yearly salary data I don't care care about the salary uh hourly data and

care about the salary uh hourly data and I don't even want the data entries in

I don't even want the data entries in here well I can get rid of that salary

here well I can get rid of that salary hour average row by just deleting this

hour average row by just deleting this column by right clicking it it's asking

column by right clicking it it's asking me if I want to delete it yes and now

me if I want to delete it yes and now there's still blank values in here right

there's still blank values in here right so I need to get rid of this salary rate

so I need to get rid of this salary rate values that are equal to hour so I'm

values that are equal to hour so I'm going to click the filter here unclick

going to click the filter here unclick next to hour and click okay so now we

next to hour and click okay so now we have that out the other thing I want to

have that out the other thing I want to do is actually clean up the format of

do is actually clean up the format of the salary and I'm going to change that

the salary and I'm going to change that instead to a currency and this talks

instead to a currency and this talks about how the data is going to be a

about how the data is going to be a changed when where it's stored yeah I

changed when where it's stored yeah I don't really care about that no doubt

don't really care about that no doubt that I care about will be lost it'll all

that I care about will be lost it'll all be here still and then I'm going to

be here still and then I'm going to reduce the decimal places by two the

reduce the decimal places by two the other thing I can do if I wanted to is

other thing I can do if I wanted to is actually sort this based on that job

actually sort this based on that job posted date could come up here and sort

posted date could come up here and sort from newest to oldest and then it's in

from newest to oldest and then it's in order sorry actually want it oldest to

order sorry actually want it oldest to newest got confused on that one so bam

newest got confused on that one so bam just did some quick clean up to our data

just did some quick clean up to our data set and now we're ready to proceed

forward so let's actually get into building our first measure or measures

building our first measure or measures specifically I want to analyze this to

specifically I want to analyze this to understand what are the different the

understand what are the different the the amount of jobs in here and then also

the amount of jobs in here and then also what is the average and then also more

what is the average and then also more importantly the median salary well

importantly the median salary well there's a few different ways we can do

there's a few different ways we can do this we're going to do this first within

this we're going to do this first within this power pivot window so in order to

this power pivot window so in order to do this I'm going to first first I want

do this I'm going to first first I want to do a count so we're going to just run

to do a count so we're going to just run this on this job title short column and

this on this job title short column and here underneath on the Home tab under

here underneath on the Home tab under calculations we have this Auto sum I

calculations we have this Auto sum I don't frequently use this I use it every

don't frequently use this I use it every now and then but I can run things on

now and then but I can run things on this like count or distinct count I'm

this like count or distinct count I'm going to do count in this case and this

going to do count in this case and this is going to create our first measure

is going to create our first measure down here remember down below this area

down here remember down below this area is our calculation area I can toggle it

is our calculation area I can toggle it on and off by clicking calculation area

on and off by clicking calculation area up here anyway I can also make this

up here anyway I can also make this column slightly bigger and what's cool

column slightly bigger and what's cool about this keep on scrolling over is now

about this keep on scrolling over is now it tells us the name of this measure

it tells us the name of this measure count of job tile short and that there's

count of job tile short and that there's 22,000 remember there's normally around

22,000 remember there's normally around 30,000 but because we've taken out that

30,000 but because we've taken out that hourly data we're down to 22,000 now I

hourly data we're down to 22,000 now I can also edit this measure if you notice

can also edit this measure if you notice it appears right up here similarly they

it appears right up here similarly they have a formula bar in power pivot and to

have a formula bar in power pivot and to the left hand side it tells you what is

the left hand side it tells you what is actually selected job title short column

actually selected job title short column and then the actual measure itself in

and then the actual measure itself in here now one quick note there is

here now one quick note there is basically a colon and then an equal sign

basically a colon and then an equal sign that's how we're going to know that

that's how we're going to know that we're doing measures and we'll get to

we're doing measures and we'll get to calculate columns in a little bit and it

calculate columns in a little bit and it will only be the equal sign but this is

will only be the equal sign but this is Microsoft's way of signifying that this

Microsoft's way of signifying that this we're using a measure so that way you

we're using a measure so that way you don't confuse with anything else anyway

don't confuse with anything else anyway I can edit this the actual title in this

I can edit this the actual title in this case and I can change this something to

case and I can change this something to more more descriptive to job count

more more descriptive to job count pressing enter it now runs it and it's a

pressing enter it now runs it and it's a lot shorter additionally if I want to

lot shorter additionally if I want to actually format it I can have the

actually format it I can have the measure selected come up here select

measure selected come up here select comma and then it formats it with the

comma and then it formats it with the comma and then I don't want two decimal

comma and then I don't want two decimal places I'll go ahead and remove it next

places I'll go ahead and remove it next let's get into analyzing that salary

let's get into analyzing that salary column with this once again we can click

column with this once again we can click this I could use that auto sum and do

this I could use that auto sum and do something like average here clicking

something like average here clicking average and below it it generates that

average and below it it generates that average

average of salary or average 123,000 and I can

of salary or average 123,000 and I can change it if I want to average salary

change it if I want to average salary but if I wanted to calculate something

but if I wanted to calculate something like the median instead I would have to

like the median instead I would have to actually manually type out this

actually manually type out this calculation so selecting right below

calculation so selecting right below average salary and then coming into the

average salary and then coming into the formula bar I can type in something like

formula bar I can type in something like median salary remember we want to create

median salary remember we want to create a measure so it's going to be a colon

a measure so it's going to be a colon and then an equal to and then for this

and then an equal to and then for this we want to use the median function now a

we want to use the median function now a lot of these functions that are Dax

lot of these functions that are Dax functions are very similar to what we

functions are very similar to what we use in Excel so they have a lot of

use in Excel so they have a lot of different similarities but with this

different similarities but with this like we talked about before this allows

like we talked about before this allows us to now put in basically an entire

us to now put in basically an entire column into it and then perform that

column into it and then perform that entire aggregation on it in this case I

entire aggregation on it in this case I want to do it all on salary year average

want to do it all on salary year average making sure I put a close parenthesis to

making sure I put a close parenthesis to close out that function and Bam right

close out that function and Bam right next to average salary we have this

next to average salary we have this median salary now which needs to be

median salary now which needs to be formatted so I'll format it as English

formatted so I'll format it as English United States stes USD and remove the

United States stes USD and remove the decimal places now what happens if I

decimal places now what happens if I didn't enter that colon equal sign so

didn't enter that colon equal sign so here I am selected below median salary

here I am selected below median salary we'll go ahead and paste in that formula

we'll go ahead and paste in that formula and we'll delete that colon I haven't

and we'll delete that colon I haven't run this yet now I'm going to run I'm

run this yet now I'm going to run I'm going to press enter and as you notice

going to press enter and as you notice by this it's not actually calculating a

by this it's not actually calculating a value it actually just converts this to

value it actually just converts this to text so this is not what we want that's

text so this is not what we want that's why we have to do the colon equal to

why we have to do the colon equal to sign for entering in the formula bar

sign for entering in the formula bar there

so with measures it's important to understand implicit vers explicit

understand implicit vers explicit measures so let's close out the power

measures so let's close out the power pivot window and actually getting into

pivot window and actually getting into exploring these different measures by

exploring these different measures by creating a pivot table of that median

creating a pivot table of that median salary we just created so I'm going to

salary we just created so I'm going to go to insert pivot table from data model

go to insert pivot table from data model we're going to insert it into the

we're going to insert it into the existing sheet here we have our table of

existing sheet here we have our table of data job salary I'm going to analyze the

data job salary I'm going to analyze the salary based on the job title short

salary based on the job title short column so I'll put job title short into

column so I'll put job title short into the rows and then look we scroll down at

the rows and then look we scroll down at the very bottom you'll notice that the

the very bottom you'll notice that the measures that we created have this F ofx

measures that we created have this F ofx basically it shows us an equation that

basically it shows us an equation that it is a measure so I can take these

it is a measure so I can take these measures this median salary and in this

measures this median salary and in this case drag it into the values and now

case drag it into the values and now unlike power pivot where it did in that

unlike power pivot where it did in that same column we're now filtering down to

same column we're now filtering down to do it by well the appropriate job titles

do it by well the appropriate job titles now we could also do something like drag

now we could also do something like drag the the job count into the values as

the the job count into the values as well and actually see the job count

well and actually see the job count there now both of these measures are

there now both of these measures are explicit measures because we explicitly

explicit measures because we explicitly defined it we despine defined what job

defined it we despine defined what job count is and what median salary is so

count is and what median salary is so what is an implicit measure well you

what is an implicit measure well you actually created this before so in

actually created this before so in regards to that job count we're doing a

regards to that job count we're doing a count of the job title short column if I

count of the job title short column if I were to drag that down into here you can

were to drag that down into here you can see it says say count of job title short

see it says say count of job title short this is an implicit measure these are

this is an implicit measure these are great for quick short analysis as we

great for quick short analysis as we demonstrated before you can quickly

demonstrated before you can quickly throw something in and generate it and

throw something in and generate it and you didn't even know your us the

you didn't even know your us the measures and you were similarly with the

measures and you were similarly with the salary year average if I drag that in

salary year average if I drag that in down here we previously well changing

down here we previously well changing this up to actually perform an average

this up to actually perform an average mov to average from there that was also

mov to average from there that was also an implicit measure so I think you get

an implicit measure so I think you get the point but we're going to see the

the point but we're going to see the power of this as we go through this when

power of this as we go through this when we start to make newer measures that are

we start to make newer measures that are actually going to use our explicit

actually going to use our explicit measures specifically we're going to be

measures specifically we're going to be using our job count in other

using our job count in other calculations and so these explicit

calculations and so these explicit measures are going to save our butt and

measures are going to save our butt and save us so much time and ensure we're

save us so much time and ensure we're doing the correct

calculations so let's get into our first calculated column and we're going to be

calculated column and we're going to be going back into the power pivot window

going back into the power pivot window for this we're going to be creating a

for this we're going to be creating a column that will convert the salary year

column that will convert the salary year average values into Euro values so

average values into Euro values so there's a couple ways we can do this or

there's a couple ways we can do this or add these columns we can go under design

add these columns we can go under design and right here under columns we can

and right here under columns we can click add to add a column additionally

click add to add a column additionally without that that unselected selecting

without that that unselected selecting back in into again you see this add

back in into again you see this add column up here we can just go right in

column up here we can just go right in and add a column I feel that's actually

and add a column I feel that's actually easier anyway in this case in order to

easier anyway in this case in order to get the Euros value of what it is for

get the Euros value of what it is for Sal year average we need to multiply by

Sal year average we need to multiply by a conversion rate so inside of here I'm

a conversion rate so inside of here I'm going to put the equal sign and we see

going to put the equal sign and we see it's popping up here in the formula bar

it's popping up here in the formula bar from there I'm going to use the value in

from there I'm going to use the value in salary year average I just selected one

salary year average I just selected one of the values and it popped right in

of the values and it popped right in then from there similar to how we wrote

then from there similar to how we wrote formulas before I'm going to put times

formulas before I'm going to put times 0.9 enter now notice from this one I

0.9 enter now notice from this one I didn't use the colon equal sign right

didn't use the colon equal sign right because is not a measure it's a

because is not a measure it's a calculated column and it still knew that

calculated column and it still knew that this was a currency although I don't

this was a currency although I don't like it it has two decimal places so

like it it has two decimal places so I'll remove it and to me it knows it's a

I'll remove it and to me it knows it's a currency but it doesn't know that it's a

currency but it doesn't know that it's a Euro so I'm actually going to convert it

Euro so I'm actually going to convert it over to Euro and then remove the two

over to Euro and then remove the two decimal places additionally I'm going to

decimal places additionally I'm going to rename this from calculated column one

rename this from calculated column one to salary year Euro you can identify

to salary year Euro you can identify calculated columns because Normal

calculated columns because Normal columns are green the calculated columns

columns are green the calculated columns are black also if I go to the DI diagram

are black also if I go to the DI diagram view we can see that well you can't

view we can see that well you can't really tell that we have the calculate

really tell that we have the calculate column C Euro but you can see your

column C Euro but you can see your different measures that you've created

different measures that you've created all right so back to the data view even

all right so back to the data view even though we have this calculated column we

though we have this calculated column we could also create a measure on this

could also create a measure on this calculated column clicking in the box

calculated column clicking in the box below here and then typing in here I

below here and then typing in here I could do something like median salary

could do something like median salary Euro and then put in that median

Euro and then put in that median function for salary year Euro and then

function for salary year Euro and then close the parenthesis and Bam now we

close the parenthesis and Bam now we have it I'm going to spread it out to

have it I'm going to spread it out to actually see we have the value of €

actually see we have the value of € 103 now going back into here we can take

103 now going back into here we can take this and actually if we wanted to we

this and actually if we wanted to we could put the salary year euro into

could put the salary year euro into there that column it's going to

there that column it's going to aggregate it appropriately right now

aggregate it appropriately right now it's doing a sum so if I wanted to I

it's doing a sum so if I wanted to I could get a average of this of these

could get a average of this of these values or we could actually go to that

values or we could actually go to that measure that we created That explicit

measure that we created That explicit measure throw it in here and we get the

measure throw it in here and we get the explicit value of the median salary

Euro all right so let's shift our focus on this analysis let's say we wanted to

on this analysis let's say we wanted to analyze more around the date

analyze more around the date specifically the day of the weeks for

specifically the day of the weeks for when job postings are occurring well

when job postings are occurring well let's go back into Power pivot and

let's go back into Power pivot and manage to open up the power pivot window

manage to open up the power pivot window right now investigating our the diagram

right now investigating our the diagram view of our data model we only have one

view of our data model we only have one table in here data jobs salary well if

table in here data jobs salary well if we go under the design tab talked about

we go under the design tab talked about in the last lesson we can actually

in the last lesson we can actually create a date table I could also

create a date table I could also potentially mark this table of do job

potentially mark this table of do job salaries a it's not a date table so we

salaries a it's not a date table so we actually need to create one and you'll

actually need to create one and you'll see what it looks like after that and

see what it looks like after that and with that I did click new on this anyway

with that I did click new on this anyway it created this new table called

it created this new table called calendar and expecting all of the

calendar and expecting all of the different values in here well let's

different values in here well let's actually just get out of this view let's

actually just get out of this view let's actually go to the data view one which

actually go to the data view one which is pretty cool with it with it what it

is pretty cool with it with it what it created it created it based on the dates

created it created it based on the dates it knew what was in our original table

it knew what was in our original table so from the first of 2023 all the way to

so from the first of 2023 all the way to the last day of 2023 and with this it

the last day of 2023 and with this it has a year column month day of week and

has a year column month day of week and day of week number so a lot of great

day of week number so a lot of great values from it now we need to actually

values from it now we need to actually connect these two there's no

connect these two there's no relationship between the two if we go to

relationship between the two if we go to that data jobs salary so selecting it

that data jobs salary so selecting it here here we only have this job posted

here here we only have this job posted date column which is a date and a time

date column which is a date and a time so we need only a date so because this

so we need only a date so because this column is named inappropriately I'm

column is named inappropriately I'm going to change it to J job posted date

going to change it to J job posted date time so now let's create that new column

time so now let's create that new column with that job posted date time this time

with that job posted date time this time though instead of clicking add column

though instead of clicking add column we're going to go to insert function and

we're going to go to insert function and this is pretty neat because it allows us

this is pretty neat because it allows us to actually look under different things

to actually look under different things in this case we wanted sort of a text

in this case we wanted sort of a text function and we can look and explore

function and we can look and explore different one specifically I know we

different one specifically I know we want this one a format converts a value

want this one a format converts a value and text to the specified number format

and text to the specified number format so I'm going to click okay and it

so I'm going to click okay and it automatically fills it in with this

automatically fills it in with this colon and equal sign of format equal to

colon and equal sign of format equal to from there I'll select the job posted

from there I'll select the job posted date time column that's the value and

date time column that's the value and then what do we want for the format well

then what do we want for the format well I know we want in the format of

I know we want in the format of basically the year first then two months

basically the year first then two months or two M's and then two D's for month

or two M's and then two D's for month and date in order to match close that

and date in order to match close that double quote because that's the actual

double quote because that's the actual format we're using that's all we need so

format we're using that's all we need so we'll close the parentheses and press

we'll close the parentheses and press enter and then I'm going to take this

enter and then I'm going to take this calculated column one drag it over here

calculated column one drag it over here and then I can see that it did convert

and then I can see that it did convert it correctly so I'm also going to go now

it correctly so I'm also going to go now and rename this appropriately to job

and rename this appropriately to job posted date press enter so now let's

posted date press enter so now let's create a relationship between the two

create a relationship between the two remember we can go to that diagram view

remember we can go to that diagram view or I can use this of create relationship

or I can use this of create relationship go to calendar to match on the date

go to calendar to match on the date itself let's see what it looks like in

itself let's see what it looks like in that actual diagram view we always want

that actual diagram view we always want to inspect it to make sure we have this

to inspect it to make sure we have this right one to many or one to one anytime

right one to many or one to one anytime we have many to many you need to start

we have many to many you need to start questioning it depending on what the

questioning it depending on what the data is anyway we now have a

data is anyway we now have a relationship established with

this so let's actually get into analyzing this with our calendar based

analyzing this with our calendar based on this day of the week and seeing what

on this day of the week and seeing what is the prop portion that they're turning

is the prop portion that they're turning out during the week for job postings so

out during the week for job postings so closing out the power pivot window I'm

closing out the power pivot window I'm going to go in and create a new sheet

going to go in and create a new sheet from there I'm going to go go insert

from there I'm going to go go insert pivot table from data model we're going

pivot table from data model we're going to do it in the existing worksheet

to do it in the existing worksheet underneath calendar Underneath more

underneath calendar Underneath more Fields I'm going to drag in day of week

Fields I'm going to drag in day of week into the rows so it has Sunday all the

into the rows so it has Sunday all the way to Saturday then from there remember

way to Saturday then from there remember we created that job count already so I'm

we created that job count already so I'm going to take that and drag that into

going to take that and drag that into the values so looking at this I can see

the values so looking at this I can see that I think our relationship is not set

that I think our relationship is not set up properly cuz we have basically the

up properly cuz we have basically the blanks at 32,000 I think I know what's

blanks at 32,000 I think I know what's going on with this let's go back into

going on with this let's go back into the power pivot window in calendar when

the power pivot window in calendar when we select the date it's of the time data

we select the date it's of the time data type date it also has this format of

type date it also has this format of date and time I don't that really

date and time I don't that really matters too much but if we go into Data

matters too much but if we go into Data job salary and we go to that job post to

job salary and we go to that job post to date because we use that format function

date because we use that format function right now the data type is auto of text

right now the data type is auto of text we need it to be of date and this now

we need it to be of date and this now looks a lot more similar to what does on

looks a lot more similar to what does on the calendar now when I close out of

the calendar now when I close out of this bam all the values pop up here so

this bam all the values pop up here so don't forget about your data types and

don't forget about your data types and making sure they're match within the

making sure they're match within the data model so let's actually visualize

data model so let's actually visualize this by inserting a pivot chart and Bam

this by inserting a pivot chart and Bam we get this bad boy which we'll rename

we get this bad boy which we'll rename to to when are most jobs posted during

to to when are most jobs posted during the week and it looks like we have well

the week and it looks like we have well on Saturday Sunday or the lowest

on Saturday Sunday or the lowest obviously during the week it's the

obviously during the week it's the highest with a basically a higher amount

highest with a basically a higher amount on Wednesday so pretty cool analysis

on Wednesday so pretty cool analysis that we were able to do based on the day

that we were able to do based on the day of the week we didn't have to create any

of the week we didn't have to create any additional things and additionally we

additional things and additionally we can evaluate based on this calendar

can evaluate based on this calendar table created we can do other analysis

table created we can do other analysis such as by the year month day of the

such as by the year month day of the week and whatnot all right so that's a

week and whatnot all right so that's a brief intro into measures and also

brief intro into measures and also calculated columns don't worry too much

calculated columns don't worry too much if you're not feeling too confident with

if you're not feeling too confident with them just yet as one you have some

them just yet as one you have some practice problems to go through to get

practice problems to go through to get more familiar with it but the next

more familiar with it but the next lesson will be and the next two lessons

lesson will be and the next two lessons will be on Dax and Dax advance in order

will be on Dax and Dax advance in order to explore different formulas that you

to explore different formulas that you can also use inside of your measures and

can also use inside of your measures and also calculated columns all right with

also calculated columns all right with that I'll see you in the next one where

that I'll see you in the next one where we're getting into deck see you there

welcome to this lesson on Dax or data analytical Expressions we' used it a few

analytical Expressions we' used it a few times before in the previous lesson but

times before in the previous lesson but now we're going to go much more in depth

now we're going to go much more in depth and actually understanding the basics of

and actually understanding the basics of it now as we've learned Dax can be used

it now as we've learned Dax can be used within measures or even calculated

within measures or even calculated columns for the purpose of what we we

columns for the purpose of what we we going through in the project we're not

going through in the project we're not going to create any calculated columns

going to create any calculated columns but we will be using it for measures for

but we will be using it for measures for this we're going to be focusing on three

this we're going to be focusing on three major types of functions in this lesson

major types of functions in this lesson specifically around aggregation

specifically around aggregation statistics and also filter these

statistics and also filter these functions you're going to notice are

functions you're going to notice are very similar to your Excel functions

very similar to your Excel functions that we did back in Chapter 2 so a lot

that we did back in Chapter 2 so a lot of those similarities and concept we've

of those similarities and concept we've learned already are going to be able to

learned already are going to be able to be applied to this so we'll be able to

be applied to this so we'll be able to move pretty quick now we're going to be

move pretty quick now we're going to be answering two major questions regarding

answering two major questions regarding our final project the first one involves

our final project the first one involves calculating the number of skills

calculating the number of skills required per job title we're going to

required per job title we're going to use Dax in order to calculate this and

use Dax in order to calculate this and then we're even going to go on to

then we're even going to go on to actually graph this to show how it

actually graph this to show how it correlates with median salary spoil

correlates with median salary spoil alert the more skills you have the

alert the more skills you have the higher median salary you can expect from

higher median salary you can expect from there we're going to go into a deeper

there we're going to go into a deeper analysis of salar specifically looking

analysis of salar specifically looking at the median salary and specifically

at the median salary and specifically being able to compare it from your home

being able to compare it from your home country to the US and also non us

country to the US and also non us countries so we're going to use filter

countries so we're going to use filter function in order to be able to view

function in order to be able to view these things within a pivot table now

these things within a pivot table now jumping right into Excel for this you

jumping right into Excel for this you can continue working in the Excel file

can continue working in the Excel file that you have from that first lesson on

that you have from that first lesson on power pivot intro where we created this

power pivot intro where we created this visualization right here which analyzes

visualization right here which analyzes top skills of data nerds and has some

top skills of data nerds and has some filters for job title and Country if you

filters for job title and Country if you don't happen to have that file anymore

don't happen to have that file anymore or you got lost along the way you can

or you got lost along the way you can just use the power pivot intro part two

just use the power pivot intro part two file and you can start from there now if

file and you can start from there now if you're loading it via the power pivot

you're loading it via the power pivot intro part two file you're going to have

intro part two file you're going to have two sheets in there one skill job

two sheets in there one skill job analysis and then also the skill

analysis and then also the skill analysis we're not actually going to be

analysis we're not actually going to be using the skill analysis so you can feel

using the skill analysis so you can feel free to delete this or conversely if

free to delete this or conversely if you're working from the files that

you're working from the files that you've been building up during this and

you've been building up during this and didn't necessarily load from the power

didn't necessarily load from the power pivot intro part two file you may have

pivot intro part two file you may have multiple tabs in there once again I only

multiple tabs in there once again I only care about this skill jobs analysis

care about this skill jobs analysis where we have this this is what we're

where we have this this is what we're going to keep for the final project the

going to keep for the final project the job analysis and and also this other one

job analysis and and also this other one that we created back in the power query

that we created back in the power query lesson we're actually going to be

lesson we're actually going to be recreating it with power pivot so both

recreating it with power pivot so both of these I can just delete or anything

of these I can just delete or anything else you have in there you can f it free

else you have in there you can f it free to delete after holding control and

to delete after holding control and selecting both of those I'm just going

selecting both of those I'm just going to delete

them all right so we're going to be looking at aggregation functions first

looking at aggregation functions first conveniently Microsoft has some

conveniently Microsoft has some documentation around the Dax functions

documentation around the Dax functions and also statements that they have so

and also statements that they have so I'm going to dive right into the link

I'm going to dive right into the link that's provided on the screen underneath

that's provided on the screen underneath Dax functions specifically I'm going to

Dax functions specifically I'm going to go into the aggregation functions they

go into the aggregation functions they have this page here on aggregation

have this page here on aggregation functions overview and it shows a lot of

functions overview and it shows a lot of the different functions they have for

the different functions they have for this average count Max Min sum let's

this average count Max Min sum let's look at count real quick count is pretty

look at count real quick count is pretty simple all we're going to do is use the

simple all we're going to do is use the following syntax count and inside of it

following syntax count and inside of it you provide a column and for this it

you provide a column and for this it says Hey the column that contains the

says Hey the column that contains the values to be counted so pretty simple

values to be counted so pretty simple function to use similarly we have

function to use similarly we have distinct count which has the similar

distinct count which has the similar syntax of you provide distinct count and

syntax of you provide distinct count and the column and the column that contains

the column and the column that contains the values counted and it will return

the values counted and it will return the number of distinct values in columns

the number of distinct values in columns we're going to use this so what we're

we're going to use this so what we're going to be calculating with those

going to be calculating with those functions that we just went over is

functions that we just went over is trying to find out how many skills per

trying to find out how many skills per job we're going to first go through

job we're going to first go through based on a job title and find not only

based on a job title and find not only the skill count but also the job count

the skill count but also the job count and then we're going to take both these

and then we're going to take both these values and divide them to get the skills

values and divide them to get the skills per job so I'm going to create a new

per job so I'm going to create a new sheet for this and inside of here I'm

sheet for this and inside of here I'm going to insert in a pivot table from

going to insert in a pivot table from our data model we're going to do in the

our data model we're going to do in the existing worksheet for the rows we're

existing worksheet for the rows we're going to go through the do data job

going to go through the do data job salary table and we're going to put that

salary table and we're going to put that job title short into the rows and then

job title short into the rows and then now we need the skill count remember we

now we need the skill count remember we could go in and do something and create

could go in and do something and create an implicit measure by throwing job

an implicit measure by throwing job skills and the values we want an

skills and the values we want an explicit measure because we're actually

explicit measure because we're actually going to be using the skill count in a

going to be using the skill count in a later calculation to find that skill for

later calculation to find that skill for job anyway how do we do this well we can

job anyway how do we do this well we can also not only create a measure by going

also not only create a measure by going to power pivot and underneath here going

to power pivot and underneath here going to new measure you can also just select

to new measure you can also just select in here which table you want to use in

in here which table you want to use in this case I'm doing a skill count so I

this case I'm doing a skill count so I want to contain it in the data jobs

want to contain it in the data jobs skills table doesn't really matter which

skills table doesn't really matter which table I'll put it in but I just go by my

table I'll put it in but I just go by my memory of which one I'm going to know to

memory of which one I'm going to know to go look at for which in there it auto

go look at for which in there it auto selects that table of data jobs skills

selects that table of data jobs skills the measure name is going to be skill

the measure name is going to be skill count and then for the formula itself we

count and then for the formula itself we want to do a count of the job skills

want to do a count of the job skills column from the job skills table make

column from the job skills table make sure it's not from the job salary table

sure it's not from the job salary table okay I'm going to put a closing

okay I'm going to put a closing parenthesis on this and then for this we

parenthesis on this and then for this we do want to format it to use a th

do want to format it to use a th separator and zero click okay and now in

separator and zero click okay and now in the data job skills table we have this

the data job skills table we have this explicit measure can drag it right next

explicit measure can drag it right next to it same values are getting created as

to it same values are getting created as the implicit measure so I'm going to

the implicit measure so I'm going to take out that implicit measure next

take out that implicit measure next thing you want to calculate is that job

thing you want to calculate is that job count we're going to be counting it

count we're going to be counting it based on the distinct values of the job

based on the distinct values of the job ID so I'm going go to add measure we're

ID so I'm going go to add measure we're going to call this one job count and

going to call this one job count and we'll do a distinct count of we want to

we'll do a distinct count of we want to do it of the job ID column and for this

do it of the job ID column and for this one we want to make sure that we're

one we want to make sure that we're actually doing it from the salary or

actually doing it from the salary or data jobs salary table because this has

data jobs salary table because this has all the job IDs in it once again we're

all the job IDs in it once again we're going to format as a number with 1,000

going to format as a number with 1,000 separator and click okay and then I'm

separator and click okay and then I'm going to drag at the bottom the measure

going to drag at the bottom the measure is going to appear I'm going to drag it

is going to appear I'm going to drag it into here so now we want to get how many

into here so now we want to get how many skills per job so we want to take the

skills per job so we want to take the skill count column and divide it by the

skill count column and divide it by the job count column this one doesn't really

job count column this one doesn't really matter too much because it contains both

matter too much because it contains both of them but I'm going to put this in the

of them but I'm going to put this in the data jobs skills table I'm going to call

data jobs skills table I'm going to call this skills per job now what's great

this skills per job now what's great about these explicit measures that we

about these explicit measures that we just created is I can go hey I want to

just created is I can go hey I want to do this skill count and I want to divide

do this skill count and I want to divide divided by the job count and it's right

divided by the job count and it's right there so you don't have to necessarily

there so you don't have to necessarily write out every single time okay I want

write out every single time okay I want to do a count of the job skills column

to do a count of the job skills column and then divided by a count of the job

and then divided by a count of the job ID column which actually needs to be a

ID column which actually needs to be a distinct count anyway this is where we

distinct count anyway this is where we run into errors that's why the explicit

run into errors that's why the explicit meas are so measures are so great all

meas are so measures are so great all right so I have skill count divided by

right so I have skill count divided by job count I'm going to create it as a

job count I'm going to create it as a number and I want one decimal place for

number and I want one decimal place for this go ahead and click okay and then

this go ahead and click okay and then we're going to add this skills per job

we're going to add this skills per job two here now I'm actually going to

two here now I'm actually going to recommend although we just use the

recommend although we just use the division sign I'm going to actually

division sign I'm going to actually recommend this divide function with it

recommend this divide function with it which is a ma math function and what

which is a ma math function and what would you do in this case is you would

would you do in this case is you would provide divide and you list a numerator

provide divide and you list a numerator and a denominator and the reason why I

and a denominator and the reason why I like this is because it fixes any type

like this is because it fixes any type or catches any error specifically it

or catches any error specifically it performs Division and returns alternate

performs Division and returns alternate results or or blank on division by zero

results or or blank on division by zero so we're not going to necessar error out

so we're not going to necessar error out if we have a division by Z zero issue

if we have a division by Z zero issue and you can actually provide as shown

and you can actually provide as shown down here in the alternate result the

down here in the alternate result the value return When division by zero

value return When division by zero results in an error so you could

results in an error so you could actually catch that any so I'm go going

actually catch that any so I'm go going to go back into that skills per job and

to go back into that skills per job and I'm going to go to edit measure I'm

I'm going to go to edit measure I'm going to change this to divide specify

going to change this to divide specify the first and second parameter with a

the first and second parameter with a comma and then click okay okay overall

comma and then click okay okay overall no real change here but just a best

no real change here but just a best practice to know about

so now with this skills per job I want to actually get in and comparing this to

to actually get in and comparing this to median salary this is what we're going

median salary this is what we're going to be building right here we're going to

to be building right here we're going to be comparing it to median salary and

be comparing it to median salary and then graphing it in a scatter chart in

then graphing it in a scatter chart in order to see how these different job

order to see how these different job titles correlate to each other so first

titles correlate to each other so first so to know what the final analysis is

so to know what the final analysis is going to be of this I'm going to rename

going to be of this I'm going to rename this sheet appropriately specifically

this sheet appropriately specifically calling it salary vers skills and this

calling it salary vers skills and this pivot table here we don't need

pivot table here we don't need necessarily the skill count or the job

necessarily the skill count or the job count we just need the skills per job

count we just need the skills per job okay we're going to calculate now the

okay we're going to calculate now the median salary and median is a

median salary and median is a statistical function which is

statistical function which is encountered underneath here but there's

encountered underneath here but there's a lot of different options underneath

a lot of different options underneath here such as Med median finding the

here such as Med median finding the different percentiles like we did back

different percentiles like we did back in the formulas looking at things like

in the formulas looking at things like standard deviation and whatnot so a lot

standard deviation and whatnot so a lot of good statistical functions that you

of good statistical functions that you have access to Via Dax so for this

have access to Via Dax so for this measure I'm just going to come up here

measure I'm just going to come up here to power pivot go under measures and

to power pivot go under measures and select new measure I do want this in the

select new measure I do want this in the data job salary table and we're going to

data job salary table and we're going to call this median salary for this we're

call this median salary for this we're going to be using the median function

going to be using the median function and we need to provide it a column

and we need to provide it a column specifically that salary year average

specifically that salary year average value for formatting we're going to

value for formatting we're going to format it as a currency with zero

format it as a currency with zero decimal places since it's a salary so

decimal places since it's a salary so now we have median salary here I

now we have median salary here I actually want it to appear on the Y AIS

actually want it to appear on the Y AIS so I'm going to throw it over here on

so I'm going to throw it over here on the First Column so now we have the

the First Column so now we have the median salary and skills per job I'm

median salary and skills per job I'm just going to rate these or sort these

just going to rate these or sort these from highest to lowest to see if I can

from highest to lowest to see if I can see visually if there's anything going

see visually if there's anything going on with a correlation right now I am

on with a correlation right now I am seeing some higher skills than uh with a

seeing some higher skills than uh with a higher salary but let's actually

higher salary but let's actually visualize this so I'm going to insert

visualize this so I'm going to insert pivot chart and select PIV pivot chart

pivot chart and select PIV pivot chart for this we want to enter a scatter plot

for this we want to enter a scatter plot and if you remember back from our charts

and if you remember back from our charts lecture we're going to have issues with

lecture we're going to have issues with this you can't create this chart with

this you can't create this chart with the data inside the pivot table doesn't

the data inside the pivot table doesn't natively support creating Scatter Plots

natively support creating Scatter Plots kind of annoying if you ask me anyway

kind of annoying if you ask me anyway let's X out of this and for this what

let's X out of this and for this what we're going to do is we're just going to

we're going to do is we're just going to set this area starting up here we're

set this area starting up here we're going to set it equal to this entire

going to set it equal to this entire table right here I'm not going to

table right here I'm not going to capture the grand total at the bottom

capture the grand total at the bottom because we're not going to be plotting

because we're not going to be plotting that now with these values I'm going to

that now with these values I'm going to select the contents in that this column

select the contents in that this column f and g and then from there go insert a

f and g and then from there go insert a scatter plot specifically this one right

scatter plot specifically this one right here I can see it already looks pretty

here I can see it already looks pretty good you can't actually add the data

good you can't actually add the data labels in whenever you create this chart

labels in whenever you create this chart we actually have to go about doing that

we actually have to go about doing that somewhat manually specifically we have

somewhat manually specifically we have to select on the data points and then

to select on the data points and then rightclick it and we have to select add

rightclick it and we have to select add data labels okay now it's giving us

data labels okay now it's giving us points which bar which actually

points which bar which actually correlate to the skills per job point

correlate to the skills per job point it's not what we want we want to include

it's not what we want we want to include the job title we're going to add that so

the job title we're going to add that so we're going to do is select one of those

we're going to do is select one of those values and just rightclick it and then

values and just rightclick it and then from there select format data labels

from there select format data labels then the pane's going to open up on the

then the pane's going to open up on the right hand side and it should pop you up

right hand side and it should pop you up underneath label options label options

underneath label options label options then this label options and right now we

then this label options and right now we have this y value selected that's not

have this y value selected that's not what we want we want value from cell and

what we want we want value from cell and it says Hey select the data label range

it says Hey select the data label range what we want is right here all the way

what we want is right here all the way going down it's hidden behind here I'm

going down it's hidden behind here I'm going to sort of guess but I know it

going to sort of guess but I know it goes down to E11 click okay and

goes down to E11 click okay and scrolling it over bam we got all those

scrolling it over bam we got all those data labels on there now all right so

data labels on there now all right so now we need to clean this bad boy up

now we need to clean this bad boy up because well it's a hot mess that is all

because well it's a hot mess that is all up in the upper right hand quadrant

up in the upper right hand quadrant labels are overlapping we're going to

labels are overlapping we're going to fix all of this first thing is I'm going

fix all of this first thing is I'm going to correct the axises so I'm going to

to correct the axises so I'm going to click on the y or click on the x axis

click on the y or click on the x axis and it should go immediately to this

and it should go immediately to this minimum axis underneath access options

minimum axis underneath access options and I can see the first value stops

and I can see the first value stops around or begins around 880,000 so I'm

around or begins around 880,000 so I'm going to change this to that and press

going to change this to that and press enter okay similarly I'm going to select

enter okay similarly I'm going to select the Y AIS and if doesn't go to it should

the Y AIS and if doesn't go to it should be under access options inside that

be under access options inside that format access Pane and I'm going to

format access Pane and I'm going to select this first value that I want to

select this first value that I want to go to is three I'll leave the default of

go to is three I'll leave the default of nine there next thing is we need some

nine there next thing is we need some axis labels for the y axis we'll call

axis labels for the y axis we'll call this average skills requested for the

this average skills requested for the x-axis we'll call this median salary and

x-axis we'll call this median salary and we'll specify the units of USD speaking

we'll specify the units of USD speaking of which this is not formatted correctly

of which this is not formatted correctly for how we want the numbers so under

for how we want the numbers so under that format access pane under access

that format access pane under access options and under access opt options

options and under access opt options again under number we can go to the

again under number we can go to the custom option specifically you should

custom option specifically you should have this type hopefully appearing up if

have this type hopefully appearing up if not you can just enter it into this

not you can just enter it into this format code below and then press enter

format code below and then press enter all right the last two things to do is

all right the last two things to do is rename the title naming it do more

rename the title naming it do more skills equal more money for data nerds

skills equal more money for data nerds which from this chart it looks like it

which from this chart it looks like it does and we can actually confirm this if

does and we can actually confirm this if we want by adding a trend line now

we want by adding a trend line now there's different options here for trend

there's different options here for trend lines we've going over linear

lines we've going over linear exponential IAL linear forecast I feel

exponential IAL linear forecast I feel linear best meets this need here also

linear best meets this need here also like the coloring aspect of it so we're

like the coloring aspect of it so we're going to go with that all right the last

going to go with that all right the last thing to do is just fix some of these

thing to do is just fix some of these names on here so right now we have the

names on here so right now we have the data La labels appearing to the right of

data La labels appearing to the right of the data point and in cases where it's

the data point and in cases where it's close so data senior data scientist it's

close so data senior data scientist it's too close to the edge and so it's just

too close to the edge and so it's just sort of over the top of it anyway what

sort of over the top of it anyway what you can do is actually select it twice

you can do is actually select it twice so click it twice then you can drag and

so click it twice then you can drag and drop it and it should have these arrows

drop it and it should have these arrows or these connectors that connect the

or these connectors that connect the name to where it goes to all right so

name to where it goes to all right so now we have our final

now we have our final visualization and I'd say it's not too

visualization and I'd say it's not too bad some things I'm noticing about this

bad some things I'm noticing about this some correlation if you notice yes we do

some correlation if you notice yes we do see the average skills requested are

see the average skills requested are going up with the salary but those jobs

going up with the salary but those jobs I mean if you you can pretty much see it

I mean if you you can pretty much see it they div iding line those jobs that end

they div iding line those jobs that end an engineer Vice analyst or scientist

an engineer Vice analyst or scientist are commanding or requesting more skills

are commanding or requesting more skills but yet have sort of a similar pay to

but yet have sort of a similar pay to their data analyst or scientist

their data analyst or scientist counterparts so I don't know I guess it

counterparts so I don't know I guess it kind of pays to be a data analyst and

kind of pays to be a data analyst and not a data engineer don't tell my data

not a data engineer don't tell my data engineer friends I said

that all right last analysis we're going to get into is using filters to actually

to get into is using filters to actually aggregate so in this case right here

aggregate so in this case right here we're showing what we're going to get to

we're showing what we're going to get to the final thing of based on a job title

the final thing of based on a job title short value what is the median salary in

short value what is the median salary in this first column for the us then what

this first column for the us then what is the median salary for non us and then

is the median salary for non us and then finally that final column of median

finally that final column of median salary what is the median salary of in

salary what is the median salary of in this case the selected column is uh

this case the selected column is uh Argentina it's filter down basically I

Argentina it's filter down basically I call this filter function we're going to

call this filter function we're going to go over but we're going to be

go over but we're going to be calculating or figure out how to prevent

calculating or figure out how to prevent filters from affecting a visualization

filters from affecting a visualization so we can get core values what we may

so we can get core values what we may want so we're going to create a new

want so we're going to create a new sheet and I'm going to call this salary

sheet and I'm going to call this salary analysis like before we're going to

analysis like before we're going to insert a pivot table from our data model

insert a pivot table from our data model insert it into this new sheet and we're

insert it into this new sheet and we're going to be putting that job title short

going to be putting that job title short into the rows now we're obviously with

into the rows now we're obviously with this going to be calculating median

this going to be calculating median salary so I'm going to go ahead and just

salary so I'm going to go ahead and just drag that into the values to start

drag that into the values to start getting those median salaries

getting those median salaries additionally we're going to want to

additionally we're going to want to include a Slicer in here so based on the

include a Slicer in here so based on the job country so I'm going to insert

job country so I'm going to insert slicer on job country click okay and

slicer on job country click okay and then with this we can actually see if we

then with this we can actually see if we select something like Argentina it's

select something like Argentina it's going to filter down to what it is or

going to filter down to what it is or what the salary median salary is in

what the salary median salary is in Argentina but remember we're trying to

Argentina but remember we're trying to add two columns to this so we can

add two columns to this so we can compare these values of something like

compare these values of something like Argentina to us salaries and maybe non

Argentina to us salaries and maybe non us salaries so basically countries

us salaries so basically countries outside the US anyway we're going to be

outside the US anyway we're going to be using filter functions for this and for

using filter functions for this and for warning on this it says it here the

warning on this it says it here the filter and value functions in Dax are

filter and value functions in Dax are some of the most complex powerful and

some of the most complex powerful and differ greatly from Excel functions so

differ greatly from Excel functions so there's going to be a little bit of

there's going to be a little bit of complexity here in understanding this

complexity here in understanding this and for this filter function we're going

and for this filter function we're going to be using this one on calculate and

to be using this one on calculate and what it does is it evaluates an

what it does is it evaluates an expression in a modified filter context

expression in a modified filter context calculate is pretty simple in my opinion

calculate is pretty simple in my opinion first you provide an expression so such

first you provide an expression so such as hey perform a count of this column or

as hey perform a count of this column or a median of this column from there you

a median of this column from there you provide a filter or filters and as it

provide a filter or filters and as it states below here filters can be Boolean

states below here filters can be Boolean filter Expressions table filter or

filter Expressions table filter or filter modification functions main thing

filter modification functions main thing is here we're going to use things like

is here we're going to use things like logical operators in order to compare

logical operators in order to compare this to maybe a certain value we're

this to maybe a certain value we're going to expect so let's jump into

going to expect so let's jump into creating our first one with median

creating our first one with median salary evaluating for median salary in

salary evaluating for median salary in the United States

the United States so I want to create this measure inside

so I want to create this measure inside of our data job salary column sorry data

of our data job salary column sorry data job salary table and for this we're

job salary table and for this we're going to call it median salary us we're

going to call it median salary us we're going to be using the calculate function

going to be using the calculate function for this and inside of here we're going

for this and inside of here we're going to insert the ex an expression so in our

to insert the ex an expression so in our case the expression is the median of the

case the expression is the median of the salary year average column and what

salary year average column and what we're going to do actually I'm just

we're going to do actually I'm just going to leave this is cuz filter is

going to leave this is cuz filter is optional we can tell filter is optional

optional we can tell filter is optional based on the square brackets around it

based on the square brackets around it I'm going to just close out this

I'm going to just close out this calculate function change this to a

calculate function change this to a format of currency with zero decimal

format of currency with zero decimal places and then from there take that

places and then from there take that median salary us and actually drag it

median salary us and actually drag it onto here so right now calculate is

onto here so right now calculate is working by calculating the median salary

working by calculating the median salary and there's no filters applied to it so

and there's no filters applied to it so pretty simple so let's go in and

pretty simple so let's go in and actually edit this measure now now

actually edit this measure now now remember we have an explicit measure of

remember we have an explicit measure of median salary so I actually don't even

median salary so I actually don't even need to Define it like I did here I can

need to Define it like I did here I can actually just call out median salary in

actually just call out median salary in this case kicking okay still the same

this case kicking okay still the same value going back in and actually editing

value going back in and actually editing it we now want to apply a filter

it we now want to apply a filter specifically for this filter we want to

specifically for this filter we want to make sure that the job country column is

make sure that the job country column is equal to United States so I'm going to

equal to United States so I'm going to type in job country and we can use

type in job country and we can use logical operators so I'm going to use an

logical operators so I'm going to use an equal sign right next to this and I'm

equal sign right next to this and I'm going to specify United States need make

going to specify United States need make sure it's spelled exactly right I know

sure it's spelled exactly right I know it's that via the column okay so now

it's that via the column okay so now we're going to leave everything out El

we're going to leave everything out El as is click okay and Bam now it has the

as is click okay and Bam now it has the median salary filtered by the US and I

median salary filtered by the US and I can confirm this by scrolling down to

can confirm this by scrolling down to the United States clicking United States

the United States clicking United States and seeing that these values are the

and seeing that these values are the same but no matter what I actually click

same but no matter what I actually click the United States median salary is going

the United States median salary is going to stay the same additionally if you

to stay the same additionally if you noticed here when I click on something

noticed here when I click on something like the US virsion Islands would am I

like the US virsion Islands would am I moveing there they only have four job

moveing there they only have four job titles available so because of that they

titles available so because of that they just filter this table down to only show

just filter this table down to only show those four that are applicable it along

those four that are applicable it along with their applicable salaries in median

with their applicable salaries in median salary in the US so now let's calculate

salary in the US so now let's calculate the median salary for non us countries

the median salary for non us countries and actually see how they differ so come

and actually see how they differ so come into D job salary select add measure for

into D job salary select add measure for this we're going to be using non us

this we're going to be using non us values once again we want to use that

values once again we want to use that calculate fun function on the median

calculate fun function on the median salary measure that we created and for

salary measure that we created and for this one we're still evaluating the job

this one we're still evaluating the job country but we want it not equal to so

country but we want it not equal to so we're going to use basically a less than

we're going to use basically a less than and greater than sign right next to each

and greater than sign right next to each other say not equal to and we'll say

other say not equal to and we'll say United States we're going to format this

United States we're going to format this as a currency with zero decimal places

as a currency with zero decimal places click okay and then add this bad boy to

click okay and then add this bad boy to the values and I want to actually see a

the values and I want to actually see a country with more job postings in it so

country with more job postings in it so we'll go to something like Australia and

we'll go to something like Australia and now something like Australia we can see

now something like Australia we can see one comparing us to non Us in general

one comparing us to non Us in general the US well except for data Engineers

the US well except for data Engineers yeah it looks like only data Engineers

yeah it looks like only data Engineers are the lowest one in another country

are the lowest one in another country everything else is higher in the US but

everything else is higher in the US but now we can with this one compare hey

now we can with this one compare hey what does it look like something like

what does it look like something like Australia compared to us and non us

Australia compared to us and non us countries so super useful in actually

countries so super useful in actually filtering down providing the right

filtering down providing the right context for what we want to look at so

context for what we want to look at so as a data analyst median salary is

as a data analyst median salary is around 100,000 Which is higher than us

around 100,000 Which is higher than us and also any other non us median salary

and also any other non us median salary so may have to move to Australia one

so may have to move to Australia one last clean up right quick slicer itself

last clean up right quick slicer itself I don't like it to say job country we're

I don't like it to say job country we're going to name this to country all right

going to name this to country all right now wrap up the analysis for this all

now wrap up the analysis for this all right so you now have some practice

right so you now have some practice problems to go through and test out

problems to go through and test out these different Dax functions that we

these different Dax functions that we just went through along with some others

just went through along with some others now in this lesson we just did some

now in this lesson we just did some basic dacks in the next one we're going

basic dacks in the next one we're going to be moving into some more advanced

to be moving into some more advanced Stacks features that I do find myself

Stacks features that I do find myself using from time to time but overall most

using from time to time but overall most of the stuff we apply in this lesson I

of the stuff we apply in this lesson I use dayto day all right with that see

use dayto day all right with that see you in the next lesson we'll be wrapping

you in the next lesson we'll be wrapping up basically our final question in our

up basically our final question in our project and be done with our project see

project and be done with our project see you

there all right welcome to the last lesson in this course where we're going

lesson in this course where we're going to be going over more advanced decks

to be going over more advanced decks specifically we're going to be focusing

specifically we're going to be focusing more in depth on fil fter and also

more in depth on fil fter and also relation or relationship type functions

relation or relationship type functions these are going to be needed by our data

these are going to be needed by our data model in order to calculate what is the

model in order to calculate what is the salary or median salary for an

salary or median salary for an Associated skill if you remember back to

Associated skill if you remember back to a few lessons ago we had relationship

a few lessons ago we had relationship issues I know I feel that with having

issues I know I feel that with having them being able to filter tables in

them being able to filter tables in certain directions and we're going to be

certain directions and we're going to be able to see that and fix that in this

able to see that and fix that in this lesson

so in this lesson you can start with some the workbook from the last lesson

some the workbook from the last lesson or if you got lost dur in the way you

or if you got lost dur in the way you can go into the Dax intro workbook now

can go into the Dax intro workbook now let's do a quick overview of where we're

let's do a quick overview of where we're at with which analysis we've done for

at with which analysis we've done for this project we've identified what are

this project we've identified what are the top skills of data nerds along with

the top skills of data nerds along with different filters to filter for whatever

different filters to filter for whatever our interest is in my case I'm looking

our interest is in my case I'm looking for data analyst in the United States

for data analyst in the United States and I can see that se SQL Excel and

and I can see that se SQL Excel and Tableau are some of the highest

Tableau are some of the highest additionally we've zoomed out a little

additionally we've zoomed out a little bit and been able to identify based on

bit and been able to identify based on job titles where our job title of

job titles where our job title of Interest Falls compared to others and

Interest Falls compared to others and how many skills it requires for data

how many skills it requires for data analysts it's right above did business

analysts it's right above did business data analysts and based on the number of

data analysts and based on the number of skills it looks like it's appropriately

skills it looks like it's appropriately rewarded for the median salary and then

rewarded for the median salary and then final thing we did was be able to

final thing we did was be able to analyze additionally Based on data

analyze additionally Based on data analyst we can look at different

analyst we can look at different countries and compare it not only in

countries and compare it not only in that country but to within the US and

that country but to within the US and outside the US so a lot of good stuff

outside the US so a lot of good stuff related to well data analyst that

related to well data analyst that position and analyzing the salary but

position and analyzing the salary but what about skills well we haven't done

what about skills well we haven't done that yet we're going to get into

that yet we're going to get into actually analyzing in this first portion

actually analyzing in this first portion analyzing what is the expected median

analyzing what is the expected median salary based on one of the top 10 skills

salary based on one of the top 10 skills we did this back in the power query

we did this back in the power query lesson but now we have this new data

lesson but now we have this new data model we need to recalculate it anyway

model we need to recalculate it anyway we're going to run into some issues with

we're going to run into some issues with the data model as we're going to find

the data model as we're going to find out additionally we're going to be

out additionally we're going to be calculating the skill likelihood instead

calculating the skill likelihood instead of skill count basically finding the

of skill count basically finding the percentage of a skill in a job posting

percentage of a skill in a job posting this is somewhat complex so this portion

this is somewhat complex so this portion here will be optional and you'll be able

here will be optional and you'll be able to use job count instead if you don't

to use job count instead if you don't want to follow along with this skill

likelihood anyway back in your workbook whether you started from that uh Dax

whether you started from that uh Dax intro or you're continuing on with from

intro or you're continuing on with from the last lesson we're going to create

the last lesson we're going to create this new sheet for this and for this

this new sheet for this and for this we're going to name this

we're going to name this skill salary analysis as usual we're

skill salary analysis as usual we're going to go in and insert in a pivot

going to go in and insert in a pivot table from our data model so we can get

table from our data model so we can get into analyzing the skills going click

into analyzing the skills going click okay insert it in and so for this I want

okay insert it in and so for this I want to analyze what is the median salary for

to analyze what is the median salary for a skill so if I drag the job skills from

a skill so if I drag the job skills from the data jobs skills table into the rows

the data jobs skills table into the rows we have all the different skills pop up

we have all the different skills pop up underneath here and then if we went up

underneath here and then if we went up here and then tried to drag or we will

here and then tried to drag or we will be dragging in the median salary into

be dragging in the median salary into here all these values are going to be

here all these values are going to be the same addition we get this popup

the same addition we get this popup right here that relationships between

right here that relationships between tables may be needed basically we're

tables may be needed basically we're running into an issue with our data

running into an issue with our data model even if I click autod detect it's

model even if I click autod detect it's going to tell me no new new

going to tell me no new new relationships are found so what's going

relationships are found so what's going on here well let's actually analyze our

on here well let's actually analyze our data model by going to manage and then

data model by going to manage and then inside of here go into diagram view so

inside of here go into diagram view so the air resides with their filtering

the air resides with their filtering dire remember this Arrow right here

dire remember this Arrow right here signifies which way we can actually

signifies which way we can actually filter our data so in our case we have

filter our data so in our case we have job skills which is over here in the

job skills which is over here in the data job skills table and we're trying

data job skills table and we're trying to find the median salary the problem is

to find the median salary the problem is is we're basing that off of that salary

is we're basing that off of that salary or average value that's in the data jobs

or average value that's in the data jobs salary table and based on the direction

salary table and based on the direction of this Arrow we cannot flow in the

of this Arrow we cannot flow in the opposite direction this is what we're

opposite direction this is what we're call oneway way or single filtering now

call oneway way or single filtering now unfortunately Excel doesn't support bir

unfortunately Excel doesn't support bir directional filtering however in things

directional filtering however in things like powerbi you can actually go in and

like powerbi you can actually go in and change it from single filtering to both

change it from single filtering to both or bir directional filtering kind of

or bir directional filtering kind of makes me wish I was in powerbi right now

makes me wish I was in powerbi right now so back in Excel we can't actually

so back in Excel we can't actually control this via here and actually click

control this via here and actually click it to change this to bir directional

it to change this to bir directional filters we can only control the

filters we can only control the relationship itself but we we can use

relationship itself but we we can use Dax to fix this now in order to fix this

Dax to fix this now in order to fix this relationship we actually have

relationship we actually have relationship functions inside of Dax

relationship functions inside of Dax specifically we're going to use this

specifically we're going to use this cross filter function with this function

cross filter function with this function you put inside of cross filter the

you put inside of cross filter the column names so in our case we can

column names so in our case we can specify basically the job ID from job

specify basically the job ID from job salary and the job ID from data job

salary and the job ID from data job skills and then from there we specify

skills and then from there we specify the direction which the parameters under

the direction which the parameters under here we can go into what we can provide

here we can go into what we can provide to directions we can either provide none

to directions we can either provide none basically don't create a relationship

basically don't create a relationship both which is what we want filters on

both which is what we want filters on either side or one way which is what we

either side or one way which is what we have already we're not going to use this

have already we're not going to use this you also control filters left or filters

you also control filters left or filters right the one way we're also not messing

right the one way we're also not messing with that we want both now this cross

with that we want both now this cross filter remember is a filter function so

filter remember is a filter function so we need to use this in an appropriate

we need to use this in an appropriate for formula that we already know

for formula that we already know calculate in order to filter so I'm

calculate in order to filter so I'm going to x out of this box right here

going to x out of this box right here cuz that's not applicable

cuz that's not applicable what we're going to do is I'm going to

what we're going to do is I'm going to calculate median salary or a new median

calculate median salary or a new median salary if you will inside of the data

salary if you will inside of the data jobs skills table and because it's uh

jobs skills table and because it's uh going to use the same name but we're

going to use the same name but we're going to keep it in a different table

going to keep it in a different table it'll be perfectly fine and then for

it'll be perfectly fine and then for this remember we want to use still

this remember we want to use still calculate we want to have an expression

calculate we want to have an expression in here in our case we want to calculate

in here in our case we want to calculate what is the median salary and we'll just

what is the median salary and we'll just use the explicit measure that we already

use the explicit measure that we already defined then from there we'll get into

defined then from there we'll get into the filter one of what we want to

the filter one of what we want to actually filter we want to provide for

actually filter we want to provide for this cross filter and for this we're

this cross filter and for this we're going to specify the job ID of one table

going to specify the job ID of one table along with the job ID of the other table

along with the job ID of the other table then for the filter type we're going to

then for the filter type we're going to use both okay I'm going to go ahead and

use both okay I'm going to go ahead and close this now we're calculating median

close this now we're calculating median salary so I want this formatted as a

salary so I want this formatted as a currency with zero decimal places I'm

currency with zero decimal places I'm going go ahead and click okay and have

going go ahead and click okay and have an error in my formula should have known

an error in my formula should have known that by the X I need to actually put a

that by the X I need to actually put a closing parentheses on here and I'll

closing parentheses on here and I'll lied to you a measure a column with the

lied to you a measure a column with the name median already exists okay I

name median already exists okay I thought we could do that it's Sil me so

thought we could do that it's Sil me so we'll name it median salary skills go

we'll name it median salary skills go ahead and click okay okay now I'm going

ahead and click okay okay now I'm going to drag this into the values and we can

to drag this into the values and we can actually see with this one now that the

actually see with this one now that the associated median salaries are actually

associated median salaries are actually there and it's not all that 115,000

there and it's not all that 115,000 which is basically the median of the

which is basically the median of the entire data set so I'm going to go ahead

entire data set so I'm going to go ahead andove move this other median salary out

andove move this other median salary out of here and from there we're going to

of here and from there we're going to also drag skill count into here I just

also drag skill count into here I just want to look at the top 10 most common

want to look at the top 10 most common skills in this case so I'm going to go

skills in this case so I'm going to go up here into our filter and go to our

up here into our filter and go to our value filters for top one dot dot dot we

value filters for top one dot dot dot we want the top 10 items by in this case

want the top 10 items by in this case skill count and then from there based on

skill count and then from there based on these top 10 skills I'm going to sort it

these top 10 skills I'm going to sort it from largest to smallest but like usual

from largest to smallest but like usual this is no good unless we don't actually

this is no good unless we don't actually analyze for the country and also for the

analyze for the country and also for the title or job title so if I actually go

title or job title so if I actually go back into that skill jobs analysis I can

back into that skill jobs analysis I can just select these two slices right there

just select these two slices right there pressing control then copy it and paste

pressing control then copy it and paste them into here now you may notice

them into here now you may notice whenever I'm clicking this this is not

whenever I'm clicking this this is not affecting this pivot table right here so

affecting this pivot table right here so we can actually inspect this by going to

we can actually inspect this by going to the slicer and going to report

the slicer and going to report connections right now this slicer is

connections right now this slicer is only affect ing the skill job analysis

only affect ing the skill job analysis tab so this one right here in our case

tab so this one right here in our case for this job title we actually want to

for this job title we actually want to affect it on this page here of skill

affect it on this page here of skill salary analysis which is right down here

salary analysis which is right down here click okay looks like the salary is

click okay looks like the salary is updated also we want to do the same

updated also we want to do the same thing for Country adjusting the report

thing for Country adjusting the report connections for this as well and

connections for this as well and selecting this one right here for

selecting this one right here for underneath the sheet of skill salary

underneath the sheet of skill salary analysis clicking okay bam it updated as

analysis clicking okay bam it updated as well so now looking at the top skill of

well so now looking at the top skill of data analyst in the United States which

data analyst in the United States which I'm pretty familiar with I can see

I'm pretty familiar with I can see things like python Oracle and Tableau

things like python Oracle and Tableau are top three Excel does make the list

are top three Excel does make the list and it's the second to last at 84,000

and it's the second to last at 84,000 now with this I do want a visualization

now with this I do want a visualization with it specifically I want a combo

with it specifically I want a combo chart showing this so I'm going go into

chart showing this so I'm going go into insert pivot chart pivot chart and for

insert pivot chart pivot chart and for this go down to combo for this I want

this go down to combo for this I want the median salary to be the main focus

the median salary to be the main focus and then for the skill count we're going

and then for the skill count we're going to put that on a secondary axis because

to put that on a secondary axis because right now it's just way too low if we

right now it's just way too low if we keep it on the same axis and this has

keep it on the same axis and this has the format that I want right here go

the format that I want right here go ahead and click okay I'm going to hide

ahead and click okay I'm going to hide all the field buttons on the chart I'm

all the field buttons on the chart I'm going to add a primary vertical and also

going to add a primary vertical and also a secondary vertical axis along with a

a secondary vertical axis along with a chart title and then for the legend

chart title and then for the legend itself I'm going to click it and then

itself I'm going to click it and then rightclick it and go to format Legend

rightclick it and go to format Legend and for this it should go under Legend

and for this it should go under Legend options Legend options Legend options

options Legend options Legend options I'm going to unclick this of show The

I'm going to unclick this of show The Legend without overlapping the chart and

Legend without overlapping the chart and I'm just going to move it up here so not

I'm just going to move it up here so not bad I don't necessarily want this orange

bad I don't necessarily want this orange line right here for the skill kind I

line right here for the skill kind I don't really feel like a line is best to

don't really feel like a line is best to signify the count instead what I'm going

signify the count instead what I'm going to do is select the line and if it

to do is select the line and if it doesn't appear the format data series

doesn't appear the format data series you can also just right click it go to

you can also just right click it go to format data series and then underneath

format data series and then underneath fill and line they have line but also

fill and line they have line but also marker for the line we're going to go no

marker for the line we're going to go no line and then for the marker we're

line and then for the marker we're actually going to change the marker

actually going to change the marker options to builtin we'll change it to

options to builtin we'll change it to this square is going to be fine or we

this square is going to be fine or we can change it to a diamond we'll make it

can change it to a diamond we'll make it slightly bigger and I don't really like

slightly bigger and I don't really like the color so I'm going to go into design

the color so I'm going to go into design and change the color to this

and change the color to this monochromatic pallette 8 nope never mind

monochromatic pallette 8 nope never mind not that one I meant monochromatic

not that one I meant monochromatic palette one I want the bar charts to be

palette one I want the bar charts to be more visually popping than the actual

more visually popping than the actual markers themselves I change the title

markers themselves I change the title two what's the pay of the top 10 skills

two what's the pay of the top 10 skills and then change the primary access to

and then change the primary access to median salary USD and the other one one

median salary USD and the other one one to job count closing this out and then

to job count closing this out and then making some room over here for the

making some room over here for the actual visualization itself so now we

actual visualization itself so now we have our visualization that we want that

have our visualization that we want that looks at this and be able to show us

looks at this and be able to show us what are the top 10 skills for data

what are the top 10 skills for data analyst and their Associated pay now one

analyst and their Associated pay now one last thing for this regarding slicers I

last thing for this regarding slicers I want to actually make it to where

want to actually make it to where they're connected between the charts so

they're connected between the charts so right now I have it to where this

right now I have it to where this basically this one for skill salary

basically this one for skill salary analysis tab if I go over to the skill

analysis tab if I go over to the skill job analysis tab select business analyst

job analysis tab select business analyst it will change then go go back to skill

it will change then go go back to skill salary analysis it updated to business

salary analysis it updated to business analyst anyway I wanted to if we change

analyst anyway I wanted to if we change a slicer to make sure that it changes on

a slicer to make sure that it changes on the appropriate sheets so the job title

the appropriate sheets so the job title slicer is only on these two sheets

slicer is only on these two sheets actually that one's perfectly fine but

actually that one's perfectly fine but the one we actually have concerns with

the one we actually have concerns with now is the country specifically on this

now is the country specifically on this one I'm selected on the United States

one I'm selected on the United States the skill job analysis one it's also on

the skill job analysis one it's also on the United States and updates

the United States and updates appropriately but then if we look in the

appropriately but then if we look in the salary analysis that one's on Australia

salary analysis that one's on Australia it's not updating appropriately so we

it's not updating appropriately so we need to go to slicer report connections

need to go to slicer report connections and we're going to be putting the

and we're going to be putting the country one on all the different sheets

country one on all the different sheets so I'm going to go ahead and select all

so I'm going to go ahead and select all the sheets for this I'm going to do the

the sheets for this I'm going to do the same for skill salary analysis country

same for skill salary analysis country slicer which it looks like it updated

slicer which it looks like it updated along for the skill job analysis so what

along for the skill job analysis so what I'm going to do is actually copy this

I'm going to do is actually copy this now and put this into the salary verse

now and put this into the salary verse skills because we're controlling it on

skills because we're controlling it on this page as well and so now whatever I

this page as well and so now whatever I select select something like maybe

select select something like maybe United Kingdom it will update

United Kingdom it will update appropriately and update on other sheets

appropriately and update on other sheets as well anyway quick one quick note

as well anyway quick one quick note because we move those titles around that

because we move those titles around that one time sometimes it's not going to

one time sometimes it's not going to match up exactly how we had it before if

match up exactly how we had it before if you recall I'm going to go ahead and

you recall I'm going to go ahead and select all we set up these text box in

select all we set up these text box in order to view them whenever basically

order to view them whenever basically all countries were selected so that is

all countries were selected so that is one of the issues about dragging and

one of the issues about dragging and dropping those titles and making them

dropping those titles and making them stick to a certain location it messes it

stick to a certain location it messes it up your filters whenever you want to

up your filters whenever you want to filter down for something like the

filter down for something like the United

States so this wraps up basically our four major analysis that we did now I'm

four major analysis that we did now I'm going to take it a step further this

going to take it a step further this portion will be completely optional and

portion will be completely optional and that's this right now we're using skill

that's this right now we're using skill count in order to look at what is you

count in order to look at what is you know the skill count of in this case for

know the skill count of in this case for data analyst in we'll do United States

data analyst in we'll do United States we see that SQL is around 400 4,000 and

we see that SQL is around 400 4,000 and that Excel is around 3500 but what does

that Excel is around 3500 but what does that actually mean well if we go to the

that actually mean well if we go to the Future file of what we're going to get

Future file of what we're going to get to we're actually going to be

to we're actually going to be calculating a skill likelihood instead

calculating a skill likelihood instead which in this case is looking at what is

which in this case is looking at what is the proportion of a skill compared to

the proportion of a skill compared to all the different jobs that are

all the different jobs that are available for data analysts in the

available for data analysts in the United States and so that 4500

United States and so that 4500 and almost 3500 is equal to well greater

and almost 3500 is equal to well greater than 50% for SQL and about 40% for Excel

than 50% for SQL and about 40% for Excel so that makes in my mind a lot clearer

so that makes in my mind a lot clearer how important that skill is over account

how important that skill is over account in that you probably should be learning

in that you probably should be learning SQL and Excel as a data analyst so back

SQL and Excel as a data analyst so back in our sheet where we're actually

in our sheet where we're actually calculating with the job count how do we

calculating with the job count how do we calculate this well let's actually get

calculate this well let's actually get to moving this over to here go back into

to moving this over to here go back into our pivot table self and if we throw up

our pivot table self and if we throw up the job count you may get this

the job count you may get this relationship between toils maybe needed

relationship between toils maybe needed don't worry about it too much now these

don't worry about it too much now these values are all stagnant based on some

values are all stagnant based on some issues with the filter Direction but

issues with the filter Direction but that actually comes to our advantage

that actually comes to our advantage because for our filter right here

because for our filter right here specifically data analyst in the United

specifically data analyst in the United States the amount of jobs that actually

States the amount of jobs that actually are are

are are 8339 if I actually remove both of these

8339 if I actually remove both of these filters we would expect it to be the

filters we would expect it to be the total rows of the column which is

32672 so coincidentally this is actually doing what we need we just need to get a

doing what we need we just need to get a percentage of these two values and that

percentage of these two values and that can be done pretty easy so let's open

can be done pretty easy so let's open the show field list and actually get

the show field list and actually get into creating this measure we're going

into creating this measure we're going to create in the data job skill table

to create in the data job skill table we'll call this skill likelihood and

we'll call this skill likelihood and what this will do is take skill count

what this will do is take skill count and divide it by job count but remember

and divide it by job count but remember we probably want to use the divide

we probably want to use the divide function for for this so putting in

function for for this so putting in skill count and then job count now

skill count and then job count now there's no option to format this as a

there's no option to format this as a percentage unfortunately so I'm going to

percentage unfortunately so I'm going to go ahead and click okay from there I'm

go ahead and click okay from there I'm going to drag the skill likelihood into

going to drag the skill likelihood into the values and go through and format

the values and go through and format this appropriately selecting that it's a

this appropriately selecting that it's a percentage and then with this I'm going

percentage and then with this I'm going to select something that a value that I

to select something that a value that I know what it should be of data analyst

know what it should be of data analyst in the United States and with those

in the United States and with those values selected I can see that Excel is

values selected I can see that Excel is at 41% which I know that's what it is

at 41% which I know that's what it is and SE is at 53% for these values so bam

and SE is at 53% for these values so bam we have this skill likelihood now we can

we have this skill likelihood now we can now go in and remove these other two

now go in and remove these other two columns of skill count and job count and

columns of skill count and job count and then from here actually move this graph

then from here actually move this graph back over and unfortunately with the

back over and unfortunately with the adjusting to it we actually have to fix

adjusting to it we actually have to fix this and turn this back into a combo

this and turn this back into a combo chart so we're going to design change

chart so we're going to design change chart type into combo select for the

chart type into combo select for the skill likelihood we want this to be on

skill likelihood we want this to be on the secondary axis click okay go back to

the secondary axis click okay go back to format data series remove the line and

format data series remove the line and then change the marker option to be

then change the marker option to be built in and to be that diamond at 6

built in and to be that diamond at 6 point and then finally update that

point and then finally update that secondary access to basically say it's

secondary access to basically say it's skill likelihood and Bam now we have

skill likelihood and Bam now we have this final visualization now there's one

this final visualization now there's one more that we actually do need to clean

more that we actually do need to clean up and that's this one right here what

up and that's this one right here what are the top skills of data nerds right

are the top skills of data nerds right now we're doing a count of the job ID an

now we're doing a count of the job ID an implicit measure which you know how I

implicit measure which you know how I feel about that we should use an

feel about that we should use an explicit measure specifically we're

explicit measure specifically we're using skill likelihood instead of that

using skill likelihood instead of that and remove that count of job postings

and remove that count of job postings once again I need to actually format

once again I need to actually format this as a percentage so going to home

this as a percentage so going to home change it to a percentage and then from

change it to a percentage and then from there clicking in it and sorting from

there clicking in it and sorting from smallest to largest and Bam for this one

smallest to largest and Bam for this one data analyst in the United States once

data analyst in the United States once again we can actually see visually what

again we can actually see visually what are the top skills for this so now we

are the top skills for this so now we just updated both of these charts to

just updated both of these charts to have a more represen istic understanding

have a more represen istic understanding of what's going on with the data all

of what's going on with the data all right so you should be super proud of

right so you should be super proud of what we just accomplished in this

what we just accomplished in this project going through both power query

project going through both power query and power pivot and actually diving deep

and power pivot and actually diving deep to understand some key statistics about

to understand some key statistics about top paying skills and also top skills

top paying skills and also top skills you should be targeting depending on

you should be targeting depending on what job you're pursuing and what

what job you're pursuing and what country you're in now do have some

country you're in now do have some practice problems go through and test

practice problems go through and test out some of these more advanced

out some of these more advanced functions specifically this cross filter

functions specifically this cross filter function that we went over then after

function that we went over then after that in the next lesson we're going to

that in the next lesson we're going to be getting into how we can actually go

be getting into how we can actually go about sharing this project for those

about sharing this project for those that purchase the course practice ice

that purchase the course practice ice problems and also certificate you can

problems and also certificate you can now go through and complete that end of

now go through and complete that end of course survey and you'll be rewarded

course survey and you'll be rewarded this course certificate now if you

this course certificate now if you didn't do this it's not too late for you

didn't do this it's not too late for you to go in and purchase the course so way

to go in and purchase the course so way you get this course certificate all you

you get this course certificate all you got to do is go in and take that Endor

got to do is go in and take that Endor survey and you'll get it all right

survey and you'll get it all right congratulations on your work so far see

congratulations on your work so far see you in the next

one all right congratulations again for finishing that last project in this

finishing that last project in this video and the next video which are the

video and the next video which are the last two videos of this entire course

last two videos of this entire course they're going to be focused on how to

they're going to be focused on how to actually go through and share your

actually go through and share your projects in my recommended way

projects in my recommended way specifically we're going to be sharing

specifically we're going to be sharing this on GitHub so that way others can

this on GitHub so that way others can see it here I am on GitHub and also if

see it here I am on GitHub and also if you didn't notice there where you

you didn't notice there where you actually downloaded all those Excel

actually downloaded all those Excel files at the beginning of this course

files at the beginning of this course anyway inside of here is where I'm

anyway inside of here is where I'm hosting my different projects and you've

hosting my different projects and you've gone through and probably seen this but

gone through and probably seen this but you may not have clicked on something

you may not have clicked on something like the project One dashboard and in

like the project One dashboard and in this case yeah I have the Excel file but

this case yeah I have the Excel file but that read me in there displays below

that read me in there displays below this and this is what we're actually

this and this is what we're actually going to be doing in the next two videos

going to be doing in the next two videos to set this up and then create this read

to set this up and then create this read me and this allows you to detail all the

me and this allows you to detail all the different skills that you used along

different skills that you used along with detailing all the different

with detailing all the different analysis that you did while going

analysis that you did while going through this now that was Project one

through this now that was Project one project two is going to follow a similar

project two is going to follow a similar method and that it has the Excel file

method and that it has the Excel file and the readme and then in the readme

and the readme and then in the readme itself it details all the different work

itself it details all the different work that we did in

it so you may be like Luke why the heck am I going to be using GitHub in order

am I going to be using GitHub in order to share this project I'm not familiar

to share this project I'm not familiar with it I don't know how to use GitHub

with it I don't know how to use GitHub at all why am I going to waste my time

at all why am I going to waste my time with it well I think it's useful not

with it well I think it's useful not only in Excel but also other

only in Excel but also other Technologies specifically programming

Technologies specifically programming here I have my SQL project for my SQL

here I have my SQL project for my SQL course and this this is where I host my

course and this this is where I host my SQL code and all the different analysis

SQL code and all the different analysis that I did for it and similarly for my

that I did for it and similarly for my python course and the project we

python course and the project we creating that I also hosted on GitHub

creating that I also hosted on GitHub and detailed all the different the steps

and detailed all the different the steps that we did along with all the different

that we did along with all the different uh python files associated with it so

uh python files associated with it so more the story is I think github's a

more the story is I think github's a great tool to use in order to share your

great tool to use in order to share your work not only in Excel but also other

work not only in Excel but also other tools now if you recall from Project one

tools now if you recall from Project one we walk through the steps to quickly

we walk through the steps to quickly share your project on one drive if you

share your project on one drive if you had it accessible via like a paid

had it accessible via like a paid Microsoft subscription and this provided

Microsoft subscription and this provided a method to go through and share if you

a method to go through and share if you go up here and actually copy the link a

go up here and actually copy the link a usable link for others whether they have

usable link for others whether they have Excel or not to actually go in and then

Excel or not to actually go in and then manipulate your dashboards that you have

manipulate your dashboards that you have so you may be wondering why the heck are

so you may be wondering why the heck are we not doing this with this second Excel

we not doing this with this second Excel file that we created with all of our

file that we created with all of our analysis and then sharing it via this

analysis and then sharing it via this method well if you're called back to

method well if you're called back to this handy Dan table of the different

this handy Dan table of the different Microsoft versions and the different

Microsoft versions and the different skills or basically Technologies within

skills or basically Technologies within Excel that it uses Microsoft online

Excel that it uses Microsoft online which where we hosted that first project

which where we hosted that first project at doesn't have the capabilities of

at doesn't have the capabilities of power query or power pivot because of

power query or power pivot because of that I could go through the process of

that I could go through the process of adding the second project to this which

adding the second project to this which it's this file right here I'll open it

it's this file right here I'll open it up then actually investigating it well

up then actually investigating it well it does if you investigate all the

it does if you investigate all the different sheets does go through and

different sheets does go through and actually show the analysis that we did

actually show the analysis that we did but if you actually get into

but if you actually get into manipulating it like in this case let's

manipulating it like in this case let's say I wanted to see what are the top

say I wanted to see what are the top skills of data analyst you're going to

skills of data analyst you're going to get this popup right here that says this

get this popup right here that says this workbook contains external data

workbook contains external data connections or bi features that are not

connections or bi features that are not supported basically power pivot and

supported basically power pivot and power query aren't supported it can't

power query aren't supported it can't actually query the data it's just

actually query the data it's just showing the basic last snapshot of the

showing the basic last snapshot of the data right here and you can't manipulate

data right here and you can't manipulate it so in this case Microsoft online

it so in this case Microsoft online becomes pretty useless so that's why I'm

becomes pretty useless so that's why I'm recommending sharing it via GitHub as

recommending sharing it via GitHub as you can share all the associated files

you can share all the associated files with this if somebody want to they could

with this if somebody want to they could come in here and download it along with

come in here and download it along with going through and actually detailing

going through and actually detailing what you actually did so basically

what you actually did so basically controlling the story line and sharing

controlling the story line and sharing what the different analysis or insights

what the different analysis or insights that you actually found now this what

that you actually found now this what you're reading right now is a read me

you're reading right now is a read me and it requires understanding markdown

and it requires understanding markdown and how to write and markdown so we're

and how to write and markdown so we're going to be covering that more in depth

going to be covering that more in depth in the next video when we get into

in the next video when we get into markdown and creating the read me this

markdown and creating the read me this video is going to be primarily focused

video is going to be primarily focused on just getting this project into GitHub

on just getting this project into GitHub so what are we going to be doing for

so what are we going to be doing for this well we have five major steps we

this well we have five major steps we need to get through the first thing is

need to get through the first thing is installing git which is the core

installing git which is the core technology used behind GitHub we'll

technology used behind GitHub we'll explain more in a bit second and third

explain more in a bit second and third we'll be going through actually setting

we'll be going through actually setting up our GitHub account and then

up our GitHub account and then installing GitHub desktop to then manage

installing GitHub desktop to then manage with Git our different folders and

with Git our different folders and projects and then fourth and fifth we'll

projects and then fourth and fifth we'll be basically initializing the repository

be basically initializing the repository which is a fancy term for a folder and

which is a fancy term for a folder and from they are getting that folder

from they are getting that folder repository onto GitHub to then share so

repository onto GitHub to then share so before we install it what the heck is

before we install it what the heck is git well similar to how they have track

git well similar to how they have track changes and stuff like word and

changes and stuff like word and PowerPoint git does this it's a Version

PowerPoint git does this it's a Version Control System it tracks changes in not

Control System it tracks changes in not only files but also code and because of

only files but also code and because of all this it allows you also to

all this it allows you also to collaborate with others when working on

collaborate with others when working on a project git is the core technology

a project git is the core technology behind maap managing all these different

behind maap managing all these different things going on on your own local

things going on on your own local computer and then whenever you make any

computer and then whenever you make any of these changes get Hub is where it

of these changes get Hub is where it keeps track of these final changes if

keeps track of these final changes if you will and then displays it for the

you will and then displays it for the world to see and also pull those changes

world to see and also pull those changes so here's my Excel di analytics course

so here's my Excel di analytics course right here on GitHub and I have the same

right here on GitHub and I have the same folders or repository on my own local

folders or repository on my own local computer now there's actually hidden

computer now there's actually hidden folders or git folders in here managing

folders or git folders in here managing this and I can do a shortcut on Mac of

this and I can do a shortcut on Mac of command shift period to show that but

command shift period to show that but anyway I wanted to mainly show this of

anyway I wanted to mainly show this of this dogit folder in here and this thing

this dogit folder in here and this thing I don't necessarily touch this at all or

I don't necessarily touch this at all or work inside of it this.get folder

work inside of it this.get folder contains all the different revisions and

contains all the different revisions and tracks all the different changes within

tracks all the different changes within my project so in order to get this git

my project so in order to get this git folder inside your project and then also

folder inside your project and then also get it into GitHub we need to actually

get it into GitHub we need to actually install git

so navigate over to the git website into their downloads select your operating

their downloads select your operating system Choice whether Mac OS or Windows

system Choice whether Mac OS or Windows I want a Windows machine right here and

I want a Windows machine right here and from there I'm going to select the

from there I'm going to select the 64-bit version for Windows and click

64-bit version for Windows and click here to download Once download I'm going

here to download Once download I'm going to open the file as do I want to allow

to open the file as do I want to allow this to make changes in my device yes I

this to make changes in my device yes I do and then it's going to walk you

do and then it's going to walk you through the setup process for git all of

through the setup process for git all of these things are going to be left as

these things are going to be left as default so feel free to just go through

default so feel free to just go through and select it all after I've left all

and select it all after I've left all the default settings as is and selected

the default settings as is and selected that it then gets into the actual

that it then gets into the actual install itself looks like it installed

install itself looks like it installed properly we'll go ahead and click finish

properly we'll go ahead and click finish we can confirm it's installed by opening

we can confirm it's installed by opening something like terminal and you should

something like terminal and you should have a terminal app installed this is

have a terminal app installed this is just confirming it you don't necessarily

just confirming it you don't necessarily have to do this anyway mine opens in a

have to do this anyway mine opens in a Powershell and you can just type

Powershell and you can just type something like get and it shouldn't give

something like get and it shouldn't give you an error message it should instead

you an error message it should instead give you how you could go about using

give you how you could go about using git via the command line in terminal

git via the command line in terminal don't worry don't be AF of this we're

don't worry don't be AF of this we're not going to be using git via the

not going to be using git via the command line although I may need to make

command line although I may need to make a separate course on that instead we're

a separate course on that instead we're going to be using GitHub desktop to

going to be using GitHub desktop to manage

git so in order to use GitHub you need to have an account if you already have

to have an account if you already have an account you can feel free to just

an account you can feel free to just sign right on in but if you don't go

sign right on in but if you don't go through the whole process of entering

through the whole process of entering your email providing your different

your email providing your different credentials and then getting logged in

credentials and then getting logged in once logged in it should direct you to

once logged in it should direct you to your homepage if it doesn't you can come

your homepage if it doesn't you can come up here to this icon at the top and from

up here to this icon at the top and from there just select your profile I would

there just select your profile I would go through at this point and actually

go through at this point and actually customize your profile specifically

customize your profile specifically adding a picture your name a little

adding a picture your name a little description and any social media links

description and any social media links over here on the right hand side of on

over here on the right hand side of on my homepage I have some different pinned

my homepage I have some different pinned repositories because you just set it up

repositories because you just set it up you probably have none but this is where

you probably have none but this is where we're going to be putting your Excel

we're going to be putting your Excel project when you're complete so that way

project when you're complete so that way if people navigate to your profile they

if people navigate to your profile they can see it now that we have this account

can see it now that we have this account we need to actually get our project or

we need to actually get our project or our repository onto GitHub but

our repository onto GitHub but unfortunately there's not really an easy

unfortunately there's not really an easy method I've found with actually using

method I've found with actually using the UI from the website to do this and

the UI from the website to do this and that's mainly because there's a lot of

that's mainly because there's a lot of technical things going behind the scenes

technical things going behind the scenes and managing

git instead I'm going to recommend downloading github's application to

downloading github's application to install on your computer they have it

install on your computer they have it for both Mac and windows navigate to

for both Mac and windows navigate to this link here and for this we I'm going

this link here and for this we I'm going to go ahead and just download the 64-bit

to go ahead and just download the 64-bit version of this application this one's a

version of this application this one's a lot easier to install than get from here

lot easier to install than get from here once we have it downloaded I'm going to

once we have it downloaded I'm going to open the file the installer should open

open the file the installer should open this window for you to next sign into

this window for you to next sign into GitHub once you've enter your

GitHub once you've enter your credentials for GitHub you'll use this

credentials for GitHub you'll use this to configure git and for this you're

to configure git and for this you're going to basically say hey I want to use

going to basically say hey I want to use GitHub account and name and email

GitHub account and name and email address to manage all this and click

address to manage all this and click finish now it should navigate you to the

finish now it should navigate you to the let's go started screen anyway it has

let's go started screen anyway it has methods for you to go through and create

methods for you to go through and create a tutorial repository if you want to

a tutorial repository if you want to we're going to be doing that and it has

we're going to be doing that and it has some different options for this that you

some different options for this that you can also select via the file menu such

can also select via the file menu such as a new repository add local repository

as a new repository add local repository or clone repository we're going to be

or clone repository we're going to be creating a new repository and as a

creating a new repository and as a reminder repository it's basically a

reminder repository it's basically a fancy name for a folder but it's a way

fancy name for a folder but it's a way for us to maintain and collect all of

for us to maintain and collect all of our different files and not for what

our different files and not for what we're using in our project so for this

we're using in our project so for this we need to give it a name so I'm going

we need to give it a name so I'm going to give it some descriptive like Excel

to give it some descriptive like Excel project data analytics and for

project data analytics and for description I'll just give the simple

description I'll just give the simple one of my project Dem maturing my Excel

one of my project Dem maturing my Excel skills for the local path we need to

skills for the local path we need to actually point it to the folder that has

actually point it to the folder that has this so mine is inside my documents

this so mine is inside my documents folder and real quick inside that folder

folder and real quick inside that folder itself right now I would expect you to

itself right now I would expect you to have the project one and project two I

have the project one and project two I also going to be putting all the

also going to be putting all the different files that I have for the

different files that I have for the different Excel workbooks that we work

different Excel workbooks that we work through in the lesson if you don't have

through in the lesson if you don't have them don't feel like you need it the

them don't feel like you need it the main important thing is that you have

main important thing is that you have both project one and project 2 in there

both project one and project 2 in there and I have them conveniently located in

and I have them conveniently located in different folders inside of here never

different folders inside of here never getting out of that so I can select this

getting out of that so I can select this Excel project. analytics folder I'm

Excel project. analytics folder I'm going to select this folder it's going

going to select this folder it's going to ask if I want to initialize this

to ask if I want to initialize this repository with a read me I do as far as

repository with a read me I do as far as the get ignore I'll put none and license

the get ignore I'll put none and license none as well and we'll create the

none as well and we'll create the repository so now you're going to be

repository so now you're going to be navigated to this screen here here which

navigated to this screen here here which is basically the default screen of

is basically the default screen of GitHub desktop it allows you to select

GitHub desktop it allows you to select different repositories right now I have

different repositories right now I have only the Excel project analytics one it

only the Excel project analytics one it allows you to select different branches

allows you to select different branches we're going to say on one shifting to

we're going to say on one shifting to another Branch beyond the scope of this

another Branch beyond the scope of this course then up here at the top it has

course then up here at the top it has something like publish repository which

something like publish repository which we want to do but one quick thing real

we want to do but one quick thing real quick I can actually investigate what

quick I can actually investigate what files are going to be pushed up to

files are going to be pushed up to GitHub by going here into history and

GitHub by going here into history and right now it's just one I selected that

right now it's just one I selected that box for read me so the readme is in

box for read me so the readme is in there and the other one's just do get

there and the other one's just do get attributes the other ones aren't in

attributes the other ones aren't in there and I'm doing this on a Windows

there and I'm doing this on a Windows machine well if I navigate back to the

machine well if I navigate back to the folder that contains my project so here

folder that contains my project so here I have Excel project. analytics which I

I have Excel project. analytics which I selected two from the GitHub desktop

selected two from the GitHub desktop whenever I go into it it actually

whenever I go into it it actually created another folder inside of it and

created another folder inside of it and that has theget attributes and read me

that has theget attributes and read me that it's talking about about now I've

that it's talking about about now I've done this on both Windows and Mac and

done this on both Windows and Mac and Mac doesn't cause this issue of putting

Mac doesn't cause this issue of putting another folder inside your other folder

another folder inside your other folder so for Mac users you may not have this

so for Mac users you may not have this problem so completely ignore this but

problem so completely ignore this but for Windows user this is a problem

for Windows user this is a problem because this right here is the project

because this right here is the project or the folder was going to get uploaded

or the folder was going to get uploaded to GitHub so what we need to do is take

to GitHub so what we need to do is take all the contents of this by selecting it

all the contents of this by selecting it all and just pressing control to select

all and just pressing control to select it all and then dragging it into that

it all and then dragging it into that folder so a little confusing but if we

folder so a little confusing but if we go back to the documents we have our

go back to the documents we have our Excel project. analytics folder then

Excel project. analytics folder then inside of that we have our GitHub repo

inside of that we have our GitHub repo and then now navigating back into GitHub

and then now navigating back into GitHub desktop I go over here and I see changes

desktop I go over here and I see changes we have 85 of 8 five different files and

we have 85 of 8 five different files and folders within there it's actually

folders within there it's actually picking up on all those different files

picking up on all those different files that I have in there once again if

that I have in there once again if you're on a Mac you may not see this

you're on a Mac you may not see this because it's already in there in history

because it's already in there in history and you can see it's actually within the

and you can see it's actually within the this portion of the guy anyway the thing

this portion of the guy anyway the thing now is if we go ahead and publish this

now is if we go ahead and publish this repository to GitHub it's only going to

repository to GitHub it's only going to have what's inside of our history right

have what's inside of our history right now under this what we're calling a

now under this what we're calling a commit and a commit is a snapshot of

commit and a commit is a snapshot of your

your repository at the time that you're

repository at the time that you're basically committing it so we need to do

basically committing it so we need to do a commit in order to get all these

a commit in order to get all these different changes into a repository cuz

different changes into a repository cuz technically right now they're in an area

technically right now they're in an area called a staging area or the working

called a staging area or the working area anyway we need to provide a summary

area anyway we need to provide a summary that's required and I'm going to add

that's required and I'm going to add something simple like add all Excel

something simple like add all Excel files doesn't need to be super

files doesn't need to be super descriptive and from there I'm going to

descriptive and from there I'm going to click commit to main now if I go into

click commit to main now if I go into history I have this initial commit that

history I have this initial commit that it did but then that add all Excel files

it did but then that add all Excel files it's going to then have in all those

it's going to then have in all those different Excel files that I added into

it so now that our local repository on your machine is is up to date we need to

your machine is is up to date we need to then publish this repository to GitHub

then publish this repository to GitHub and we can either click this button or

and we can either click this button or this button here for this we're going to

this button here for this we're going to keep the same name and description that

keep the same name and description that we have before we don't want to keep

we have before we don't want to keep this code private so we're going to

this code private so we're going to uncheck that box and then from there

uncheck that box and then from there we're going to click publish repository

we're going to click publish repository so my repository has quite a bit of

so my repository has quite a bit of Excel files and the memory size of it is

Excel files and the memory size of it is pretty large so it is taking a little

pretty large so it is taking a little bit of time to do this so now we've

bit of time to do this so now we've completed pushing our local repository

completed pushing our local repository to our remote repository on GitHub so

to our remote repository on GitHub so inside of GitHub I can navigate up here

inside of GitHub I can navigate up here to the right hand side and I go to your

to the right hand side and I go to your repositories and here it is the Excel

repositories and here it is the Excel project data analytics that we made

project data analytics that we made public and it's all in here so now

public and it's all in here so now somebody can come in here and see our

somebody can come in here and see our different work in this case our project

different work in this case our project One dashboard is inside of here we have

One dashboard is inside of here we have our Excel file in there and Bam we've

our Excel file in there and Bam we've set up git and also GitHub and that was

set up git and also GitHub and that was a push so now we need to demonstrate

a push so now we need to demonstrate what is a pull

and so in order to do that a pull request we need to actually make changes

request we need to actually make changes on our remote repository so that on

on our remote repository so that on GitHub and then pull it into our local

GitHub and then pull it into our local repository so here's what we can do for

repository so here's what we can do for that I'm going to just go in and we

that I'm going to just go in and we created this read me. markdown file upon

created this read me. markdown file upon creation because we selected that

creation because we selected that checkbox you can actually come in here

checkbox you can actually come in here and edit this read me by clicking the

and edit this read me by clicking the edit file button and and I'm just going

edit file button and and I'm just going to come in here and I'm just going to

to come in here and I'm just going to say hey I added this on github.com

say hey I added this on github.com adding it in the bottom now we're going

adding it in the bottom now we're going to go into markdown formats and stuff as

to go into markdown formats and stuff as you can see we have this hashtag here

you can see we have this hashtag here we're going to go all that in the next

we're going to go all that in the next lesson but anyway I made this changes to

lesson but anyway I made this changes to here so we need to like we did on our

here so we need to like we did on our local repository and making a change we

local repository and making a change we need to commit those changes here and

need to commit those changes here and conveniently it just gives us a commit

conveniently it just gives us a commit message of update read me confirm the

message of update read me confirm the correct email and it conects directly to

correct email and it conects directly to the main branch we're just staying on

the main branch we're just staying on that Branch we're not shifting for this

that Branch we're not shifting for this course at all from there I'm going to

course at all from there I'm going to commit changes so now if I go back into

commit changes so now if I go back into the project itself scroll on down to see

the project itself scroll on down to see the read me I can see that I have I

the read me I can see that I have I added this on GitHub whereas on my local

added this on GitHub whereas on my local machine if I go into look at the readme

machine if I go into look at the readme markdown it doesn't have that addition

markdown it doesn't have that addition that I added to the readme file so we

that I added to the readme file so we need to pull those changes going back to

need to pull those changes going back to the GitHub desktop app I'm going to come

the GitHub desktop app I'm going to come up here and you notice that it says

up here and you notice that it says fetch or this isn't going to do anything

fetch or this isn't going to do anything this is just going to fetch origin

this is just going to fetch origin basically the main branch and Pull It in

basically the main branch and Pull It in this isn't going to make any changes to

this isn't going to make any changes to your file it's just going to update it

your file it's just going to update it of what's on GitHub and we can see based

of what's on GitHub and we can see based on this that we have basically one

on this that we have basically one change here by this one and this down

change here by this one and this down Mark and so in order to get these

Mark and so in order to get these changes we need to pull the origin pull

changes we need to pull the origin pull it and so I'm just going to click it to

it and so I'm just going to click it to pull and now when we go into the history

pull and now when we go into the history we now have this new one of update read

we now have this new one of update read me we can see that this readme has this

me we can see that this readme has this addition because it's in green of I edit

addition because it's in green of I edit this on github.com and then inspecting

this on github.com and then inspecting this in the readme itself it now updated

this in the readme itself it now updated to say hey I added this on github.com so

to say hey I added this on github.com so bam we just demonstrated how to push and

bam we just demonstrated how to push and also pull from our local repository and

also pull from our local repository and machine to our remote

machine to our remote repository so now that we have GitHub

repository so now that we have GitHub and git all set up we now need to get in

and git all set up we now need to get in to actually building out those readms

to actually building out those readms and explaining what we did in our

and explaining what we did in our project and demonstrating those skills

project and demonstrating those skills that we gained in this course so that's

that we gained in this course so that's what we'll be doing in the next lesson

what we'll be doing in the next lesson if you're getting stuck at any point

if you're getting stuck at any point during the way I highly recommend that

during the way I highly recommend that you take use of something like chat gbt

you take use of something like chat gbt or even gemini or whatnot and actually

or even gemini or whatnot and actually paste in your error code and it will

paste in your error code and it will help you with troubleshooting it it's a

help you with troubleshooting it it's a lot quicker than posting a comment in

lot quicker than posting a comment in here saying that you had an issue all

here saying that you had an issue all right with that see you in the next one

right with that see you in the next one we're getting into the Remy see you

there welcome to the last video in this course and in this we're going to be

course and in this we're going to be going over how we're going to actually

going over how we're going to actually document all the different work that you

document all the different work that you did for project one and for project two

did for project one and for project two we're going to putting this into our

we're going to putting this into our markdown file or our read me and then

markdown file or our read me and then from there getting it onto GitHub and

from there getting it onto GitHub and then finally going through how to share

then finally going through how to share it on LinkedIn so right now navigating

it on LinkedIn so right now navigating to our GitHub repo with our project in

to our GitHub repo with our project in it you should have at least two folders

it you should have at least two folders in there one for your project One

in there one for your project One dashboard and one for your project 2 if

dashboard and one for your project 2 if you have your other folders for all the

you have your other folders for all the work that you did for all the other

work that you did for all the other lessons in this course that's awesome

lessons in this course that's awesome too but not required mainly just have

too but not required mainly just have your project work in there anyway we

your project work in there anyway we have this read me for the entire project

have this read me for the entire project itself and right now it's pretty Bare

itself and right now it's pretty Bare Bones and if we navigate into that

Bones and if we navigate into that project One dashboard right now you

project One dashboard right now you should have only have a file in there

should have only have a file in there specifically that Excel file but we need

specifically that Excel file but we need also a readme in here as well so we can

also a readme in here as well so we can description add a description of what we

description add a description of what we did in that dashboard similarly project

did in that dashboard similarly project 2 doesn't have a read me as

well now we have demonstrated in that last lesson how we can actually go into

last lesson how we can actually go into something like the readme and then from

something like the readme and then from there edit it inside of your web browser

there edit it inside of your web browser by just clicking this edit this file

by just clicking this edit this file icon it shows not only the edits for you

icon it shows not only the edits for you to actually go through and maybe type

to actually go through and maybe type something but also the preview itself

something but also the preview itself itself of what the file is going to look

itself of what the file is going to look like don't worry we're going to be going

like don't worry we're going to be going over markdown syntax in a little bit but

over markdown syntax in a little bit but anyway that's how we're going to be

anyway that's how we're going to be doing all these different changes to the

doing all these different changes to the files for this I'm not going to do these

files for this I'm not going to do these changes I'm actually going to cancel

changes I'm actually going to cancel these changes now an alternate option to

these changes now an alternate option to making edits to something like a readme

making edits to something like a readme is using a text editer or IDE integrated

is using a text editer or IDE integrated development environment such as

development environment such as something as Visual Studio code which is

something as Visual Studio code which is completely free and is I have it

completely free and is I have it launched here in my app um is an app

launched here in my app um is an app that I use in order to edit and manage

that I use in order to edit and manage my different files I can also go through

my different files I can also go through if I'm editing the read me itself I can

if I'm editing the read me itself I can type inside of here and edit it but also

type inside of here and edit it but also during that I can actually go in and

during that I can actually go in and view what's going on with the actual

view what's going on with the actual read me itself off to the side while I'm

read me itself off to the side while I'm typing here in this other window anyway

typing here in this other window anyway I just want to make you aware of this

I just want to make you aware of this that is an option for you to go through

that is an option for you to go through but it does take some experience with

but it does take some experience with knowing how to use vs code setting this

knowing how to use vs code setting this all up so based on the complexity we've

all up so based on the complexity we've already built up already we're going to

already built up already we're going to stick to just editing our readms inside

stick to just editing our readms inside of github.com

so before we get into building our project readms we need to understand

project readms we need to understand some syntax here specifically if you

some syntax here specifically if you notice this Excel project analytics is

notice this Excel project analytics is capitalized and everything else is

capitalized and everything else is lowercased and if we actually go in and

lowercased and if we actually go in and edit the file we can see that we have

edit the file we can see that we have this hashtag at the front which

this hashtag at the front which translates this into a heading so they

translates this into a heading so they have special characters that you can

have special characters that you can actually use in front or around text to

actually use in front or around text to manipulate text

manipulate text and the team that created markdown

and the team that created markdown conveniently created this cheat sheet

conveniently created this cheat sheet which I'll link here and it shows all

which I'll link here and it shows all the different methods that you can use

the different methods that you can use to actually manipulate and make

to actually manipulate and make different things happen inside your

different things happen inside your markdown file so let's actually look at

markdown file so let's actually look at a few here I have a heading one heading

a few here I have a heading one heading two and heading three denoted by how

two and heading three denoted by how many hashtags and a space and then if I

many hashtags and a space and then if I preview this heading one heading two and

preview this heading one heading two and heading three next we can either bold or

heading three next we can either bold or italicize text by surrounding it either

italicize text by surrounding it either double asteris or single asteris and the

double asteris or single asteris and the final results right here is bold and

final results right here is bold and italicized notice how the Bold text and

italicized notice how the Bold text and italicize are on the same line it's

italicize are on the same line it's important that after you go to a new

important that after you go to a new line you actually put two spaces in

line you actually put two spaces in there now that I have that in there it

there now that I have that in there it will actually shift it to the next line

will actually shift it to the next line we can also do things like an ordered

we can also do things like an ordered list or an unordered list which would be

list or an unordered list which would be like bullet points and it conveniently

like bullet points and it conveniently indents that and makes it look a lot

indents that and makes it look a lot nicer we can o surround something by a

nicer we can o surround something by a back tick which is located up at the top

back tick which is located up at the top of your keyboard or you could do triple

of your keyboard or you could do triple back ticks at the top and bottom for if

back ticks at the top and bottom for if you have multiple lines of code and if

you have multiple lines of code and if we actually go to preview this we can

we actually go to preview this we can see that the single line of code was

see that the single line of code was just surrounded whereas a multiline

just surrounded whereas a multiline creates this entire coding block the

creates this entire coding block the final two worth mentioning are links and

final two worth mentioning are links and also images for the link for the text

also images for the link for the text that you wanted to appear for the link

that you wanted to appear for the link you'll put in square brackets and then

you'll put in square brackets and then for the hyperlink itself you're going to

for the hyperlink itself you're going to put that inside a parentheses right next

put that inside a parentheses right next to it and then actually changing this to

to it and then actually changing this to a real world example of something like

a real world example of something like google.com if I go to preview and then I

google.com if I go to preview and then I click this link it's going to ask me if

click this link it's going to ask me if I want to leave site and go to Google

I want to leave site and go to Google I'm not going to do it because it's

I'm not going to do it because it's going to mess up all my changes but you

going to mess up all my changes but you get the point for images is very similar

get the point for images is very similar but the text you provide in the square

but the text you provide in the square brackets is just your alternate text so

brackets is just your alternate text so whenever you scroll over it what the

whenever you scroll over it what the text is displays and then from there is

text is displays and then from there is the actual image location however this

the actual image location however this isn't an actual image location so I have

isn't an actual image location so I have this eror message that goes on with this

this eror message that goes on with this alt text hence this broken file you're

alt text hence this broken file you're going to notice that if any of your

going to notice that if any of your files for your images are broken anyway

files for your images are broken anyway github.com actually makes it pretty easy

github.com actually makes it pretty easy to get images in in this case I have a

to get images in in this case I have a gif of the dashboard you could also use

gif of the dashboard you could also use an image file but all I have to do is

an image file but all I have to do is take it and drag it into here and if you

take it and drag it into here and if you notice it automatically formatted it

notice it automatically formatted it with alt text and then the actual link

with alt text and then the actual link location itself so saving the file

location itself so saving the file itself and it puts that exclamation

itself and it puts that exclamation point at the front signifying that it's

point at the front signifying that it's an image or in this case GIF if I go to

an image or in this case GIF if I go to preview scrolling down we can see that

preview scrolling down we can see that we have our image once again you need to

we have our image once again you need to put spaces after that other one to make

put spaces after that other one to make sure that you're not having it all in

sure that you're not having it all in the same line but you get the

the same line but you get the point anyway let's actually get into

point anyway let's actually get into creating this read me that's on the

creating this read me that's on the homepage if you will of our actual

homepage if you will of our actual project and the main point of this one

project and the main point of this one is I want people to be navigated to the

is I want people to be navigated to the appropriate project depending on what

appropriate project depending on what they're looking for so I went ahead and

they're looking for so I went ahead and put in some text already for how I want

put in some text already for how I want to break this down I'll break uh I'll

to break this down I'll break uh I'll shift over to preview and I'm going have

shift over to preview and I'm going have a title such as my excel. analytics

a title such as my excel. analytics projects from there we're going to have

projects from there we're going to have the salary dashboard project and the

the salary dashboard project and the salary analysis right now the image that

salary analysis right now the image that I have for the dashboard is in the wrong

I have for the dashboard is in the wrong location actually shift that up now I

location actually shift that up now I went ahead and added the images also for

went ahead and added the images also for our salary analysis while cleaning up

our salary analysis while cleaning up where the salary dashboard is which I

where the salary dashboard is which I included only just two graphs here but I

included only just two graphs here but I just want to give a sneak peek of what's

just want to give a sneak peek of what's going to be inside of those other readms

going to be inside of those other readms that were about to build out now you may

that were about to build out now you may be wondering how the heck do I get

be wondering how the heck do I get screenshots of graphs in my different

screenshots of graphs in my different dashboard well depending on if you're

dashboard well depending on if you're using Mac or Windows they have software

using Mac or Windows they have software installed already and so these shortcuts

installed already and so these shortcuts should work for you in order to perform

should work for you in order to perform your appropriate screen capture I

your appropriate screen capture I primarily use on a Mac command Shift 4

primarily use on a Mac command Shift 4 to select a certain area and it allows

to select a certain area and it allows me to basically just hover over

me to basically just hover over something and snapshot it this same

something and snapshot it this same thing can be done on a window Windows

thing can be done on a window Windows machine you're just going to press

machine you're just going to press Windows shift plus s so I went through

Windows shift plus s so I went through also and just added a quick description

also and just added a quick description to each section I'm go into preview

to each section I'm go into preview because it's a little bit easier to read

because it's a little bit easier to read there anyway underneath this I just

there anyway underneath this I just detail hey this contains all my Excel

detail hey this contains all my Excel files to follow along in my case my free

files to follow along in my case my free course of Excel for data analytics I

course of Excel for data analytics I would word it differently for you of

would word it differently for you of that you're actually providing all your

that you're actually providing all your different Project work in this

different Project work in this repository additionally I provide a

repository additionally I provide a short description for the first project

short description for the first project and then also a short description for

and then also a short description for the second project make sure in this

the second project make sure in this case you actually are putting spaces

case you actually are putting spaces after those lines so you don't have

after those lines so you don't have those images overlay on top of it now

those images overlay on top of it now the last thing I would do as you see

the last thing I would do as you see here I link to my course but I think

here I link to my course but I think more importantly what you need to do is

more importantly what you need to do is actually link to the appropriate files

actually link to the appropriate files within this repository so people can

within this repository so people can quickly get to the salary dashboard or

quickly get to the salary dashboard or the salary analysis and so I'm going to

the salary analysis and so I'm going to add this link of connecting to that

add this link of connecting to that appropriate project by first adding this

appropriate project by first adding this text of check out my work here

text of check out my work here and then inside parentheses I'm going to

and then inside parentheses I'm going to list the folder of project One dashboard

list the folder of project One dashboard you have to make sure you spell it

you have to make sure you spell it exactly like the folder that is inside

exactly like the folder that is inside of your repository or the Link's not

of your repository or the Link's not going to work I'm going to do the same

going to work I'm going to do the same with the project two dashboard as well

with the project two dashboard as well and going to preview it I can see it's

and going to preview it I can see it's all there I probably want some spaces in

all there I probably want some spaces in between

between this and so just put an extra enter in

this and so just put an extra enter in there okay that's good enough I'm going

there okay that's good enough I'm going to get into committing the changes this

to get into committing the changes this is update my readme that sounds good I'm

is update my readme that sounds good I'm going to commit them so now on our home

going to commit them so now on our home folder of our repository of excel

folder of our repository of excel project. analytics scrolling down I have

project. analytics scrolling down I have my read me here it tells me about it and

my read me here it tells me about it and then for the salary dashboard it says

then for the salary dashboard it says hey check out my work here when I click

hey check out my work here when I click on it it navigates me into this folder

on it it navigates me into this folder for the salary dashboard which you need

for the salary dashboard which you need to now create a readme 4 also it's just

to now create a readme 4 also it's just good practice to make sure that you

good practice to make sure that you check to make sure that other link works

check to make sure that other link works as well and in this case it didn't it's

as well and in this case it didn't it's a good thing we checked it I had project

a good thing we checked it I had project 2 dashboard and instead it was actually

2 dashboard and instead it was actually project 2 analysis I'm going to commit

project 2 analysis I'm going to commit changes and then now when I actually try

changes and then now when I actually try it out bam navigates me to the right

it out bam navigates me to the right location so now you have now the basics

location so now you have now the basics to go through you understand markdown

to go through you understand markdown enough to edit it I'm going to walk

enough to edit it I'm going to walk through how I built out the project one

through how I built out the project one read me and also the project 2 read me

read me and also the project 2 read me so that way you have some understanding

so that way you have some understanding of what you should do going forward with

of what you should do going forward with the project one I recommend including a

the project one I recommend including a picture of the dashboard to start and

picture of the dashboard to start and then a brief intro detailing why you

then a brief intro detailing why you wanted to do this project underneath

wanted to do this project underneath this make sure you include a link to the

this make sure you include a link to the file itself which is conveniently right

file itself which is conveniently right here and then inside of here detailing

here and then inside of here detailing the different skills that you use with

the different skills that you use with building this is really important for

building this is really important for job Seekers that way if a recruiter

job Seekers that way if a recruiter comes and looks at this they see what

comes and looks at this they see what the skills are you used in this and then

the skills are you used in this and then from there I talk about the data set

from there I talk about the data set itself talking about what we were trying

itself talking about what we were trying to get or extract out of the data so

to get or extract out of the data so basically all the foundation they need

basically all the foundation they need in the introduction portion this portion

in the introduction portion this portion I recommend keep being the similar

I recommend keep being the similar format the next portion you can feel

format the next portion you can feel free to go about however you want

free to go about however you want specifically I go into the dashboard

specifically I go into the dashboard build breaking it down into three main

build breaking it down into three main areas of focus on first is the charts

areas of focus on first is the charts itself I highlight the different median

itself I highlight the different median salaries all of the different job titles

salaries all of the different job titles themselves I go into some insights from

themselves I go into some insights from that I also talk about the country map

that I also talk about the country map and the insights from this as well next

and the insights from this as well next after charts I move into functions and

after charts I move into functions and formulas detailing one of the key

formulas detailing one of the key functions that we used using median and

functions that we used using median and then an if statement in order to build

then an if statement in order to build out an array formula so not only

out an array formula so not only breaking it down but also explaining

breaking it down but also explaining what insights we're able to get with

what insights we're able to get with this formula and then the third skill I

this formula and then the third skill I talk about is data validation talking

talk about is data validation talking about why it's used a gif of How It's

about why it's used a gif of How It's actually applicable or how it's actually

actually applicable or how it's actually visually seen in Excel and then finally

visually seen in Excel and then finally I just wrap it up with a conclusion so

I just wrap it up with a conclusion so to recap for the first project you need

to recap for the first project you need an intro statement describing what we're

an intro statement describing what we're doing and why you did it and what skills

doing and why you did it and what skills you used then then from there on the

you used then then from there on the build itself explaining what you

build itself explaining what you actually built how you use those skills

actually built how you use those skills and what insights you got out of it and

and what insights you got out of it and then finally wrap it up with a

then finally wrap it up with a conclusion for the second project mine

conclusion for the second project mine is very similar formatted in that I have

is very similar formatted in that I have an introduction Excel skills used the

an introduction Excel skills used the data set and then since this one was

data set and then since this one was primarily focused on analysis I included

primarily focused on analysis I included the four questions that we went through

the four questions that we went through and actually answered for our analysis

and actually answered for our analysis so then with the template of these four

so then with the template of these four questions I broke each one of those down

questions I broke each one of those down with those questions primarily focusing

with those questions primarily focusing on one what skill did I use to help

on one what skill did I use to help answer that question and then two what

answer that question and then two what is the analysis insights I got out of

is the analysis insights I got out of answering that question I repeat the

answering that question I repeat the same thing for the second question

same thing for the second question specifying the skills that we use for

specifying the skills that we use for this and then the analysis or what

this and then the analysis or what insights we got out of it after going

insights we got out of it after going through questions three and four we then

through questions three and four we then get to our final thing of a conclusion

get to our final thing of a conclusion of what you actually learn and extracted

of what you actually learn and extracted from insights for this so it's really

from insights for this so it's really good to put all this stuff in it I

good to put all this stuff in it I wouldn't be overwhelmed and think you

wouldn't be overwhelmed and think you need to include everything in it think

need to include everything in it think about a job recruiter themselves they

about a job recruiter themselves they don't have a lot of time so keeping it

don't have a lot of time so keeping it as short and to the point as possible is

as short and to the point as possible is going to be best for

you once you're done actually gone through and built out your repo with all

through and built out your repo with all its Associated read me it's time to get

its Associated read me it's time to get into actually sharing this on social

into actually sharing this on social media via LinkedIn I recommend the same

media via LinkedIn I recommend the same approach that we used back in Project

approach that we used back in Project one of listing this down in your project

one of listing this down in your project section by going through and actually

section by going through and actually clicking the add icon and adding the

clicking the add icon and adding the projects if you did go through and

projects if you did go through and actually add that salary dashboard

actually add that salary dashboard already I would just focus this one on

already I would just focus this one on the salary analysis so I'd put in

the salary analysis so I'd put in something like a name of the data

something like a name of the data science job analysis a description add

science job analysis a description add any appropriate skills there's a ton of

any appropriate skills there's a ton of different skills you actually select for

different skills you actually select for what you use I would focus on primarily

what you use I would focus on primarily these of Microsoft Excel power query

these of Microsoft Excel power query data modeling ETL and pivot tables for

data modeling ETL and pivot tables for the media in this case I would include a

the media in this case I would include a link to your repo and paste it on into

link to your repo and paste it on into here and click add it will then provide

here and click add it will then provide this snapshot thumbnail of what's going

this snapshot thumbnail of what's going on here and a title I like it all I'll

on here and a title I like it all I'll click apply now if you recall back from

click apply now if you recall back from that first project we tried to provide

that first project we tried to provide the link of that one drive link for

the link of that one drive link for Excel and it didn't work so if you have

Excel and it didn't work so if you have that project on LinkedIn I would go

that project on LinkedIn I would go through and also attach this link as

through and also attach this link as well to that so that way they know how

well to that so that way they know how to navigate to it finally select your

to navigate to it finally select your start and stop date if you have any

start and stop date if you have any contributors are associated with I don't

contributors are associated with I don't have in this case and then from there

have in this case and then from there save it the last thing I recommend doing

save it the last thing I recommend doing is making a post telling others about

is making a post telling others about your project so they can come in and see

your project so they can come in and see it in it I would definitely include

it in it I would definitely include something like a link and feel free to

something like a link and feel free to tag Kelly or myself in it I love

tag Kelly or myself in it I love checking out your projects and seeing

checking out your projects and seeing the different work that you've done for

the different work that you've done for it so once again congratulations for

it so once again congratulations for finishing this course been nothing short

finishing this course been nothing short of your hard work Excel was the first

of your hard work Excel was the first skill or main skill that I learned in

skill or main skill that I learned in helping me land my first data analytics

helping me land my first data analytics opportunity so I feel the same can go

opportunity so I feel the same can go for you as well now after you taking a

for you as well now after you taking a short break and you're ready to get back

short break and you're ready to get back into learning more skills I do have a

into learning more skills I do have a squel course that I recommend you taking

squel course that I recommend you taking as you've learned from analyzing this

as you've learned from analyzing this data Excel and SQL are two of the most

data Excel and SQL are two of the most top skills of data analyst so it pays to

top skills of data analyst so it pays to know it and you can basically learn it

know it and you can basically learn it in a weekend all right with that I'll

in a weekend all right with that I'll see you then either in the next video or

see you then either in the next video or in the next course see you there

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