How to separate a numpy array into separate columns in pandas

Question

I have a dataframe that looks like

  ID_0 ID_1  ID_2
0    a    b  0.05
1    a    b  0.10
2    a    b  0.19
3    a    c  0.25
4    a    c  0.40
5    a    c  0.65
6    a    c  0.71
7    d    c  0.95
8    d    c  1.00

I want to groupby and make a normalized histogram of the ID_2 column for each group. So I do

df.groupby(['ID_0', 'ID_1']).apply(lambda x: np.histogram(x['ID_2'], range = (0,1), density=True)[0]).reset_index(name='ID_2')

However what I would really like is for the 11 elements of the numpy arrays to be in separate columns of the dataframe.

How can I do this?

akuiper · Accepted Answer · 2016-09-28 19:48:04Z

3

You can construct a series object from each numpy array and the elements will be broadcasted as columns:

import pandas as pd
import numpy as np
df.groupby(['ID_0', 'ID_1']).apply(lambda x: pd.Series(np.histogram(x['ID_2'], range = (0,1), density=True)[0])).reset_index()

answered Sep 28, 2016 at 19:48

akuiper

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1 Comment

Simd Over a year ago

That's clever. Thank you!

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