Adding a 'count' column to the result of a groupby in pandas?

Question

I think this is a fairly basic question, but I can\'t seem to find the solution.

I have a pandas dataframe similar to the following:

import pandas as         


        

Answer 1

You can using size

df.groupby(['A','B']).size()
Out[590]: 
A  B
x  p    2
y  q    1
z  r    2
dtype: int64

For your solution adding one of the columns

df.groupby(['A','B']).B.agg('count')
Out[591]: 
A  B
x  p    2
y  q    1
z  r    2
Name: B, dtype: int64

Update :

df.groupby(['A','B']).B.agg('count').to_frame('c').reset_index()

#df.groupby(['A','B']).size().to_frame('c').reset_index()
Out[593]: 
   A  B  c
0  x  p  2
1  y  q  1
2  z  r  2

Answer 2

pandas >= 1.1: DataFrame.value_counts

This is an identical replacement for df.groupby(['A', 'B']).size().

df.value_counts(['A', 'B'])

A  B
z  r    2
x  p    2
y  q    1
dtype: int64

df.value_counts(['A', 'B']).reset_index(name='c')

   A  B  c
0  z  r  2
1  x  p  2
2  y  q  1