How to get the mean of pandas cut categorical column

Question

I was using pandas cut for the binning continuous values. I wonder how to get the mean for each bin.

MWE

import numpy as np
import pandas as pd

np.random.seed(100)
df = pd.DataFrame({'a': np.random.randint(1,10,10)})
df['bins_a'] = pd.cut(df['a'],4)

print(df)
   a        bins_a
0  9    (7.0, 9.0]
1  9    (7.0, 9.0]
2  4    (3.0, 5.0]
3  8    (7.0, 9.0]
4  8    (7.0, 9.0]
5  1  (0.992, 3.0]
6  5    (3.0, 5.0]
7  3  (0.992, 3.0]
8  6    (5.0, 7.0]
9  3  (0.992, 3.0]

I tried:

df['bins_a_mean'] = df['bins_a'].mean()

But this fails.

How to get the means for each interval?

Answer 1

Try this:

df['bins_a_mean'] = df.groupby('bins_a')['a'].transform('mean')

print(df)
   a        bins_a  bins_a_mean
0  9    (7.0, 9.0]     8.500000
1  9    (7.0, 9.0]     8.500000
2  4    (3.0, 5.0]     4.500000
3  8    (7.0, 9.0]     8.500000
4  8    (7.0, 9.0]     8.500000
5  1  (0.992, 3.0]     2.333333
6  5    (3.0, 5.0]     4.500000
7  3  (0.992, 3.0]     2.333333
8  6    (5.0, 7.0]     6.000000
9  3  (0.992, 3.0]     2.333333