Group By and Aggregate Functions in Pandas | Python Pandas Tutorials

[@pstefanics]

3:27 note that to avoid a FutureWarning (and an error later), you need to specify df.groupby('Base Flavor').mean(numeric_only = True)

[@srijanrawat4014]

thanks man that helped me a lot

[@christoperivander6496]

Thank you very much man, so useful

[@louisamkeyakala9420]

super useful ...thank you

[@bottonline4544]

Gracias amigo , me salvastes el día . Tenias horas con este problema . que no me ocurría en la versión 1.2.1 de Pandas . pero al subir a la versión 2.1.1. me daba error . por no incluir "numeric_only = True"

[@nirmaljohnson]

It was very helpful, Thank You

[@Kwuasimoto]

The "I've spent years researching this" at the start killed me 😂

[@pancakez2181]

“Squiggly bracket” > “curly bracket” 😂 Also the first time I’ve seen describe() with groupby(). Makes total sense, thank you!

[@LeonardDim]

love this thank you, 2 years ago and still commenting

[@Merrickul]

Thanks Alex this was a great video. Short, concise and to the point !

[@sj1795]

Great run through of the popular aggregate functions. Really appreciate the little summary definitions you do at the beginning of your videos. Example: "Group by: groups together values in a column and displays them all on the same row", etc. As always, THANK YOU ALEX!! Happy New Year!

[@ahmadch9275]

Hey Alex, Hope you are doing well. First to let you know that you have been a great help for me in navigating the data analytics domain. You once mentioned in one of your videos that cloud computing is now a necessary skills for Data analysts and that you would explain this in detail in one of your video. we are eagerly waiting for this video. Please make one when feasible.

[@AlexTheAnalyst]

I do have those videos coming up on AWS and Azure!

[@ahmadch9275]

@@AlexTheAnalyst thanks buddy, and please know that we all appreciate the kind work that you are doing. God bless you

[@toygar8699]

For those who get error in mean, df.groupby('Base Flavor').mean(['Flavor Rating','Texture Rating','Total Rating'])

[@kalyan4807]

Thanks man !!

[@navyajuvvaladinne5045]

Thank you for your msg, it helped me, but i wanted to know , how come in the video alex got the output with out inputting any column names in mean(), can you help

[@toygar8699]

@@navyajuvvaladinne5045 yw, I don't know, maybe old version

[@rayyanahmed321]

Bro I was trying to solve this for days,I completed pandas,numpy completly but can't do groupby and then I saw your comment❤ Jizaq Allah❤ Thanks❤

[@toygar8699]

I'm so glad I helped ❤

[@theweirdfriend562]

Thank you very much! as always, your videos are very helpful!

[@data_with_dylan]

This was very helpful, thank you!

[@rafaeldeavila1210]

Thanks a lot Alex! First one🎉🎉

[@mgsports9561]

One question if I get this "AttributeError: 'DataFrame' object has no attribute 'gruopby" how can fix it?

[@umamiimamu]

Thank you, lovely useful content

[@moxie1189]

What did Boris do, to be the pandas course of choice on Udemy to receive paid promotion?

[@ssteo4136]

dear alex, could you please add sort after group by analysis ?

[@rabiahchaudhry9774]

Hey alex... thanks for the wonderful work... i have been following along your tutorials and practicing them but for some reason my mean agg function is not working... the rest of them are working just fine... what could be the reason behind that...

[@AnatolyKosharovsky]

Try use: group_by_frame = df.groupby('Base Flavor')[['Flavor Rating', 'Texture Rating', 'Total Rating']].mean() - It's recommended to specify the columns for which you want to apply the mean() function. Works for me

[@dimitrijemarinkovic4451]

How can i save grouped dataframe to csv but i also need to save index as column values

[@anjunie99]

is data analyst oversaturated? someone said that, wdyt alex?

[@SACHINKUMAR-px8kq]

Thanks Sir

[@ebsaumare3387]

Thanks sir🎉🎉🎉🎉

[@DreaSimply21]

Why the query would not let me run df.groupby('Base Flavor').mean(), unless I put 'Based Flavor' in the aggregation function? However, it allowed me to run the other aggregations without having to include the column I am looking for in the function.

[@srijanbansal6078]

put numeric_only = True

[@pearldarkowaayeboah1210]

I have the same issue: were you able to resolve it?

[@DreaSimply21]

⁠@@pearldarkowaayeboah1210yes, you have to put numeric_only=True

[@ComedyJunctionPro]

@@srijanbansal6078 Thanks

[@pylu6874]

Thanks 🤩🤩🤩

[@sirrobotoftheinternet4078]

I need help anytime I try to move from the mean part of video on my laptop all I get is an error. However everything else works. Like sum, count, max, min. Does anyone have any tips for me please and thank you ? At the bottom of my error says “ could not convert chocolaterocky roadchocolate fudge brownie to numeric

[@boavidasitoe7007]

I am interested to become a data analyst where do i begin, dont you have a beginner course? Or community so that we can join? I dont have any information about data analyst so i want to be taught from beginner friendly

[@Honking_Goose]

Not this lol excel really is the main starting point, then onto SQL look into courses like Google data analyst professional certification

[@GhulamHussainKhuhro]

Dear Alex, I'm writing to express my sincere gratitude for your video tutorial on groupby in Jupyter Notebook. It was very helpful in understanding the basics of calculating means for grouped data. However, I noticed that the tutorial didn't explicitly address how group_by.mean() handles non-numeric data. In the current version of pandas, attempting to calculate the mean of a column with non-numeric values will raise a TypeError. I found solution that by passing numeric_only = True in mean () the issue is resolved. I would be grateful if you could consider updating the video to include a note to pass numeric_only = True in mean() Thank you again for your excellent tutorials ❤❤

[@wkorn89]

Thanks Alex, you saved me with this video

[@KUKRETI07]

very few channel has this comment "greak"

[@CODwontons]

This made me lol

[@Niranga.555]

Thanks for your great work Alex..!

[@natnaelberhanu-i8w]

you da man

[@furrywarrior8765]

I really like this series and many thanks to Alex for sharing such useful knowledge.

[@skugga7]

Where did you collect this data from? It looks incredibly thorough and well-organized for its size

[@Eng_Aldo-tp2hy]

Thank a lot for your video, it´s great!!

[@01Ashish01]

[@eda569]

Why did the SUM function give this output? output: Flavor Liked Flavor Rating Texture Rating Total Rating Base Flavor Chocolate ChocolateRocky RoadChocolte Fudge Brownie YesYesYes 25.2 21.7 47.1 Vanilla Mint Chocolate ChipVanillaCookie DoughPistachi... YesNoYesNoYesNo 34.2 33.9 68.1

[@yanpaucon1043]

have you found the solution? same output. just doing it now

[@yanpaucon1043]

df.groupby('Base Flavor').sum(numeric_only = True)

[@ecstazyrm]

Excellent. Much better than edx ibm course

[@Lorryduckie2]

neat content ! thanks

[@TheFootballPlaya]

very clear tutorial. nice work!

[@mohamadrezahoseynifard8116]

why my pandas program in python work like this print(df.groupby(['Base Flavor', 'Liked']).mean(['Base Flavor', 'Liked'])) and don’t work like this: print(df.groupby(['Base Flavor', 'Liked']).mean())