Python Pivot Tables Tutorial | Create Pandas Pivot Tables | Python Tutorial | Examples, Subtotals

Learn all about the Pandas Pivot Table function using this tutorial! If you want to follow along a written tutorial, check out my full guide here: datagy.io/python-pivot-tables/
To download the dataset, check this link: github.com/datagy/mediumdata/...
0:00 Introduction
0:26 Why Use Pivot Tables?
0:47 Pandas Pivot Tables
0:59 Pandas Pivot Table Function
1:33 Writing Pandas Pivot Table Function
3:56 Pandas Pivot Table Values
4:56 Pandas Pivot Table aggfunc Parameter
6:54 Pandas Pivot Table Columns
7:40 Totals and Margins
9:00 Conclusion
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[@AdventuresOfChinchin]

I had searched Google and youtube for an entire day to gain some clarity in this concept. Finally got the right video. Thanks!

[@datagy]

I’m so glad it was helpful!

[@idlejam86]

same

[@datagy]

Thank you so much!

[@vicka_zhurina]

Nik, thank you for such a clear explanation of the syntax and all the features! It’s not the first of your videos that I have seen, and each time I am amazed how simply Python might be clarified. Good luck and a lot of inspiration for your new videos!

[@datagy]

Thank you so much for your kind words! I’ll have more videos coming soon! :)

[@AnalyticInsight]

Thanks for your clear and complete treatment of pivot table. Easy to comprehend, started to use immediately.

[@datagy]

Thanks so much for your comment! I appreciate the feedback :)

[@gauthamambethkar4483]

The way you explained was perfect. Keep up the good work. Hoping to see a lot more data science and Machine Learning videos from you

[@datagy]

Thanks so much, Gautham! I have lots more planned :)

[@jamesgilmore5538]

This was the most helpful video I've seen on anything pandas. Thank you. Appreciate the simple and short examples/steps that explain the arguments.

[@datagy]

Thanks so much, James! That means a lot to me!

[@OberynPinkViper]

Just wanted to say thank you for the incredibly simple yet comprehensive video. I stumbled upon the pivot() method while working through data visualisation, and I wasn't 100% sure how it worked.
After this watching this video, everything is much more clearer and understandable to me.

[@datagy]

Thank you so much for your kind words! That means a lot!

[@DrSpacemann]

Killed it again! Very clear and easy to follow,thank you!

[@datagy]

Thanks so much! 😊

[@rferstahl]

simple and to the point, exactly what I was looking for. Thanks

[@datagy]

I’m so glad!

[@SetoAjiNugroho]

I skipped every basics of machine learning and now i realized that i need basic like this. Thanks to made it easy to learn. Very great explained :D

[@datagy]

I’m so glad it was helpful! :)

[@toddbrannon6262]

Thanks for this video. So straight to the point. I learned something I can now put to use!

[@datagy]

Thanks so much, Todd!

[@rajeeb101]

Fantastic work! Simple and to the point. Thank you.

[@datagy]

Thank you so much!

[@coachjeffnac]

I normally get my info on youtube videos and go. This video quickly/easily helped me solve something I'd been struggling with! I had a groupby that I couldn't figure out how to transpose. PIVOT is what I wanted! Thanks!

[@datagy]

I’m glad it helped! :)

[@mrescience2554]

Oh my goodness, this is exactly what I needed! Great explanation, thank you so much.

[@datagy]

Thank you so much! I’m glad it was helpful!

[@Danielmelian3]

I was looking for this everywhere, Thankyou so much!

[@datagy]

Thanks so much, Daniel!

[@MayankSinghParmar]

Simple and Clear. Very good video

[@datagy]

Thank you so much!

[@irvingescobar3977]

This is exactly the video I needed! Been looking to transition out of excel pivots due to huge data sets and this was super helpful.

[@datagy]

I’m so glad it was helpful, Irving!

[@irvingescobar3977]

@@datagy Hoping you do some more deep dives into data analysis soon :D

[@datagy]

Thanks!! I’ve got a lot of exciting stuff coming!

[@rohitbhosale3617]

Thank you so much!To the point.
Love from India

[@Dimejesi]

Thank you so much. I just started learning python for data Science and you really broke this down and made it easy for me to understand

[@datagy]

Thank you!! That means a lot to me!

[@bevg1]

wow! you are a good teacher... straight to the point and it is not boring. 👍

[@datagy]

Thank you so much!

[@TotallyAqua]

Really helpful video. I liked how you explained adding totals to the rows and columns.

[@datagy]

Thanks so much!

[@JDUDEadventure]

Thank you video was super helpful to better understand pivot tables with pandas

[@cocoapebbles10]

This is awesome dude! You really saved my bacon here. It's so difficult to learn this stuff over Zoom class.

[@datagy]

I'm so glad it was helpful!

[@jongcheulkim7284]

Thank you very much. This is very helpful.

[@mapa5000]

Very well explained !!! . thank you !

[@datagy]

Thanks so much, Marco!

[@luqmanhakim7781]

Crystal clear explanation ! Thanks for sharing.. looking forward for more content like this :)

[@datagy]

Thank you so much Luqman! I’ll be releasing more videos soon! :)

[@luqmanhakim7781]

@@datagy keep it up the good work man 👍

[@ravirajshelar250]

Thanks you just made me learn it so easily.😊

[@datagy]

Thanks so much! I'm glad it was helpful!

[@alfonsoborges4885]

Thanks, great explanation !

[@datagy]

Thanks for your comment!

[@azrflourish9032]

clear explanation! thank you

[@datagy]

Thank you!

[@SayanChakraborty10397]

This was great! Thanks a lot :)

[@datagy]

Thank you, Sayan!

[@acesovernines]

Succinct and super effective. Thank you so much

[@datagy]

Thanks so much!

[@TrungNguyen-te1wm]

Great tutorial. Thanks

[@datagy]

Thanks Trung!

[@d00lph1n]

Thank you. Great explanation :)

[@datagy]

Thanks for your comment!

[@SoulSheIS]

Thank you for keeping your videos short, yet informative and engaging.

[@datagy]

I’m glad you liked it!

[@SoulSheIS]

@@datagy Absolutely!
May I ask how would you know when to use the pivot method as oppose to the pivot_table method?

[@datagy]

@@SoulSheIS the pivot_table method is a bit more flexible. Essentially, if you have duplicates in your data, the pivot_table method is necessary. Similarly, it allows you to use multiple indices.
Historically, the pivot_table method is built on pivot, but was introduced to not break previous functionality.
Hope this helps!

[@SoulSheIS]

@@datagy Ah, okay, makes a lot of sense. Thank you for clarifying!

[@datagy]

@@SoulSheIS Glad it helped!

[@mariaromero3488]

so helpful, thanks!

[@datagy]

Thanks so much!

[@nicozing4552]

Thank you so much! very clear :)

[@datagy]

Thanks Nico!

[@SunGlassesBlue]

Thank you dude, you saved my life !
Subscribing is not an option =)

[@datagy]

Glad it helped!

[@krishnaRaog21]

Very nice ...You made things so simple

[@datagy]

Thanks! I’m glad you liked it!

[@syedrizvi2687]

Thank you so much!

[@datagy]

Thanks so much for your comment!

[@timfairfield407]

great explanation. thanks

[@datagy]

Thanks Tim!

[@gvvlogsriderunrefresh6155]

One of the best videos i have ever seen. So simplified and So effective

[@datagy]

Thank you, Gaurav!

[@gvvlogsriderunrefresh6155]

@@datagy Hey Nik , Can you also put in some videos on Seaborn usage for Visualization and on Statistics in Python. It will be a great favour brother

[@datagy]

Hey Gaurav! Seaborn is definitely planned (as well as plotly). What kind of statistics in python are you looking for? :) thanks for the ideas!

[@gvvlogsriderunrefresh6155]

Dear Nik, In statistics if you can cover working with scipy.stats , cover some tests in python etc . Thanks a lot again for your prompt response

[@datagy]

@@gvvlogsriderunrefresh6155 Thanks! I'll add this to the list!

[@elfridhasman4181]

Wow, thank you very much 🙏🙏😍

[@datagy]

Thanks for your comment, Elfrid!

[@tuandino6990]

well explained!

[@datagy]

Thank you!!

[@Diamond_Hanz]

NYC here...Data Science Major.

[@datagy]

Welcome to the channel!

[@boppanibhanuprasad4612]

Plain and simple.

[@datagy]

Thank you!

[@MagnusAnand]

Cool video

[@datagy]

Thanks Guz!

[@user-fh3gr7sq1z]

tnx alot. how can we claculate the precentage by the total (for each column....) ?

[@ShawVishal]

Thanks

[@datagy]

You’re welcome!

[@ahmedhelal920]

thanks for this useful information , i am trying to add pivot on function and add this function using xlwings on excel , the function works good , but i need it come with porders GUI instead off normal cells

[@datagy]

Hi Ahmed, thanks for your comment! Could you explain what you mean by porders?

[@86Maryj]

Hi can you pls to pivot with multiple sheets

[@ravindrareddy5478]

is there any way to merge empty cells using python in a pivot table

[@yellowsun7241]

Thanks for this. How can I make jupyter print these nice looking tables like in the video ? Mine are very plain and all over the place. Cheers!

[@datagy]

Thanks for your comment! It should work if you simply write the object name without calling print(). Hope this helps! :)

[@yellowsun7241]

@@datagy thanks Nick! ;)

[@MrFishingo]

hello datagy!! two questions, how can I calculate a weighted average on the pivot table?? Second, after results are printed, how can I sort values within a column? thanks for the great videos!!

[@datagy]

Hi Ricardo! Thanks so much for your comment!
To sort your data, you'd technically want to sort it before printing it (or in the print function). You can sort data. Such as print(df.sort_values(by=['colname'])). I have a video on this topic here: th-cam.com/video/41XLTQI1qzI/w-d-xo.html
To create a weighted average you can follow along with my written tutorial here: datagy.io/pandas-weighted-average/
It'll walk you through a number of different ways in which you can calculate a weighted average (including using Pandas).

[@DIGITAL_COOKING]

please i have one question if you want the mean values to be integers how you can do that, thanks!

[@datagy]

You can convert the column to integers by apply the .astype('int') method on the column of the resulting dataframe :). Such as:
pivot['col'] = pivot['col'].astype('int')

[@DIGITAL_COOKING]

@@datagy thanks a lot for your help

[@parthraval6052]

hey nice video..one problem - suppose i have values in a column starting with 5555 eg(55551,55553,55557 etc)....how to filter it out

[@datagy]

Hi Parth,
Thanks for your comment! I'd say, and there's probably much better ways to do this, but one way you could do this is to filter a string version of the column:
df = df[df['colname'].astype('str').str.contains('5555')]

[@parthraval6052]

@@datagy thanks for your reply I will try it out 👍

[@chinmaychourdia6929]

3:56 , What if we want only the region which has maximum sales

[@XuanTran-ri1hn]

Thank you very much for your video. May I ask if you can explain the value in the pivot 5? Is it average value or sum? I just need a confirmation :)

[@datagy]

Hi Xuan, thanks for your comment! By default, a Pandas pivot table will calculate the average value :).

[@XuanTran-ri1hn]

@@datagy Thanks :)

[@amrimanel3855]

thank you very much for your explanation ; handsome man. do you have a document that contains all the equation please ? the links : all of them error

[@datagy]

Thanks Amri! I'm glad it was helpful!
I'm not able to find any formal documentation on this, but you can pass in many different kinds of functions, including numpy's functions.

[@AnjanBasumatary]

How to display emty rows and column combination? ....in the output I only get those rows and column which have values

[@datagy]

You can use dropna =False in the pivot_table function :)

[@AnjanBasumatary]

@@datagy Table3TEST3= PL.pivot_table(values =( 'ID','IN'),index = 'SEGMENT', columns='CUTOFF',dropna= False, aggfunc = {'ID':'count','IN':sum})
I have used dropna=False but still not working files uploaded in this link:
drive.google.com/drive/folders/1Pnc4YMjqL0loclfX-5Nxi3KTpxFd1ffm?usp=sharing

[@debjanidas6779]

Can you just tell me what and why you made changes between 7:39 sec to 7:42 sec.
Than you great video

[@alcapone6796]

How do I use the pivot table values to create a histogram?

[@datagy]

You may not need to pivot anything to create the histogram, as the histogram will create bins for you automatically. I’d suggest checking out my video on histograms: th-cam.com/video/m0y5uqU--YQ/w-d-xo.html

[@syhusada1130]

how would you pivot multiple columns?

[@datagy]

If you’re looking to aggregate multiple columns, you could place them as a list into the values parameter :)

[@gouthamkarakavalasa4267]

Hi can you pls let me know how to create pivot tables with mode as function, no mean. I looking a way to analyse data by pivoting on object data type with mode function. Kindly do the needful.

[@datagy]

Hi there! Thanks so much for your great question!
Import mode from scipy.stats using:
from scipy.stats import mode
Then, in your pivot table, as the aggfunc= use the following:
aggfunc=lambda x: x.mode().iat[0]
Just tested it and it works well :)

[@gouthamkarakavalasa4267]

@@datagy Hey, Thank u very much.. it worked:)

[@datagy]

I’m so glad! Thanks for letting me know :)

[@deep.jain.]

How to add filter to these pivot tables?

[@datagy]

You’d filter the dataframe either beforehand or when you pass it into the data argument :)

[@tobecontinued...5712]

What if the value i want its sum is a string?? what can i do to get the sum of a string value?

[@datagy]

Hi there! Is the "string" a number? i.e., "9" formatted as a string?

[@tobecontinued...5712]

@@datagy no ,the value is " lancé, terminé, provisoire ", and i have different section, and I want the sum of the values of each section.

[@datagy]

@@tobecontinued...5712 Ah, you want the values broken out by those categories?
So each section lance, termine, provisoire (forgive my lack of accents) would have numeric values beside it?

[@milkway731]

i just found if I set margin, the code will fail. Traceback (most recent call last)

[@kinanradaideh5479]

@6:21

[@seekthehorizon6854]

😅😊

[@hhbbhvvbjhbbyjj]

u couldnt of made the video more clear

[@datagy]

Thanks so much!!

[@Xiler6969]

delete intro music