Group Multiple Columns by a Single Column — Pandas Dataframe

Question

I am trying to group the average of columns B and C by column A . I am unsure how to accomplish this using the groupby function:

import pandas as pd
pd.DataFrame({'B' : df.groupby(['A'])['B'].mean()}).reset_index()

Because I can only figure out how to find the average and group a single column by another. If this is my Current Dataframe :

A  B   C

0  70  12
0  20  14
0  46  11
1  25  9
2  86  2
2  14  6

This is my Expected Outcome . Grouping all like values of A together, corresponding values in B and C are averaged in their respective columns:

A  B     C

0  45.3  12.3
1  25    9
2  50    4

Answer 1

Try this

df.groupby('A').mean()
Out[339]: 
           B          C
A                      
0  45.333333  12.333333
1  25.000000   9.000000
2  50.000000   4.000000

Answer 2

Although .mean() is the most obvious solution, you can also aggregate the results:

>>> df.groupby('A').agg('mean')
           B          C
A                      
0  45.333333  12.333333
1  25.000000   9.000000
2  50.000000   4.000000

Using .agg , you can aggregate multiple functions simultaneously, eg:

>>> df.groupby('A').agg(['mean', 'std'])
           B                     C          
        mean        std       mean       std
A                                           
a  45.333333  25.006666  12.333333  1.527525
b  25.000000        NaN   9.000000       NaN
c  50.000000  50.911688   4.000000  2.828427