Sample each group after pandas groupby

I know this must have been answered some where but I just could not find it.

Problem: Sample each group after groupby operation.

import pandas as pd

df = pd.DataFrame({'a': [1,2,3,4,5,6,7],
                   'b': [1,1,1,0,0,0,0]})

grouped = df.groupby('b')

# now sample from each group, e.g., I want 30% of each group

Answers:

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Method 1

Apply a lambda and call sample with param frac:

In [2]:
df = pd.DataFrame({'a': [1,2,3,4,5,6,7],
                   'b': [1,1,1,0,0,0,0]})
​
grouped = df.groupby('b')
grouped.apply(lambda x: x.sample(frac=0.3))

Out[2]:
     a  b
b        
0 6  7  0
1 2  3  1

Method 2

pandas >= 1.1: GroupBy.sample

This works like magic:

# np.random.seed(0)
df.groupby('b').sample(frac=.3) 

   a  b
5  6  0
0  1  1

pandas <= 1.0.X

You can use GroupBy.apply with sample. You do not need to use a lambda; apply accepts keyword arguments:

df.groupby('b', group_keys=False).apply(pd.DataFrame.sample, frac=.3)

   a  b
5  6  0
0  1  1

All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0