Python Pandas Aggregation Tutorial | How to use "groupby" in Pandas | Data Analysis with Pandas

[@shreyashkhurud7217]

Best explaination found so far !
Thank You sir!

[@ankitbansal6]

Most welcome!

[@damoncaffrey4921]

Mean will also work in groupby's agg function if you put it under colons like this :
df.groupby('category').agg({"sales" : "mean", "profit" : "max"})

[@shaileshsingh1445]

crisp and clear !!!! please can you advise a roadmap to learn Python (any good online platform/course/book/GitHub )

[@sravyasrinivas]

This is super useful for data analysis. Waiting for this one for a long. Thank you so much

[@ankitbansal6]

Glad it was helpful!

[@hugodaniel8975]

My dream is to become a data engineer but my sql skills are basically "from * import" 😢 gonne binge watch your channel

[@ankitbansal6]

Sure

[@AKAK-nn5gy]

Excellent. Easy to understand.

[@vedprakashshukla404]

Really informative videos Sir Kindly make a playlist on Python like your SQL.

[@ankitbansal6]

Sure I will

[@hugodaniel8975]

Wow didnt know those panda functions, thank you

[@ankitbansal6]

Happy to help

[@aashishmalhotra]

We can find mean by importing Numpy and then use np.mean
df.groupby('Team').agg({'Salary':np.mean,'Age':max})

[@ankitbansal6]

Ok. If we give mean in quotes that also works

[@harshitkak]

Pls make more vedios related to python

[@SACHINKUMAR-px8kq]

Thanks Sir For Sharing Such a great

[@ankitbansal6]

Most welcome

[@jojven7514]

Awesome👏👍👍

[@ankitbansal6]

Thank you! Cheers!

[@chandramouliramakrishnan2810]

when u ran group by on 2 columns, category and city, for chennai city the category is blank displayed.. why ? time 4.36 on the video

[@praveentanikella4078]

Brother can do do completely EDA in python and same for SQL because am not getting concept right so it will useful for me

[@nishitnishikant8548]

Great 👍

[@shashankemani1609]

Thank you for the tutorial!

[@ankitbansal6]

Glad it was helpful!

[@utkarshdixit3502]

Nice video 👏🏽

[@ankitbansal6]

Thank you 🤗

[@FakeAmazon]

How to find the sum of Marks and Average of Age for the below data frame?
data = {
‘Student’: [‘A’,’B’,’C’,’D’]
'Age': [29, 36, 25,40],
'Marks': [79, 56, 91,99]
}
df = pd.DataFrame(data)
Can you provide answer for this

[@ThePragyashree]

Thank you 💖🙏

[@ankitbansal6]

You are so welcome

[@hugodaniel8975]

Why do people always import pandas as pd? Why not as p or pan?

[@ankitbansal6]

That's a general practice 😊

[@sriramabonam6183]

Please share data set

[@hugodaniel8975]

Fortunately there is no mean 😢

[@ankitbansal6]

There is, you have to give in single quotes 😃

[@dhruviart413]

@@ankitbansal6 ..Thank you for the videos . that's correct. Its work with single quotes..... df.groupby('category').agg({'sales':'mean','profit':'max'})

[@vijaykumarboni4869]

np.mean should work ig