How to divide each column of pandas Dataframe by a Series?

Question

I have a pandas dataframe in which I want to divide each column by the same data series values for each row. Each column and the data series have the same length. The data series has only float numbers but some cells in the dataframe have NaNs.

I tried various things but somehow I cannot get it solved.

df = df.divide(data_series, axis=1)

Any suggestions? many thanks!

I think you should try groupby – Afshin Amiri May 31 '18 at 14:47 — Afshin Amiri, May 31 '18 at 14:47
just found it, axis = 0 solves it. Many thanks – Rolf12 May 31 '18 at 14:48 — Rolf12, May 31 '18 at 14:48

score 15 · Answer 1 · edited Jan 10 '23 at 12:15

15

I found the solution: setting axis = 0 solves the issue.

df = df.divide(data_series, axis=0)

many thanks

edited Jan 10 '23 at 12:15

Julia Meshcheryakova

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answered May 31 '18 at 14:49

Rolf12

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score 2 · Answer 2 · answered May 31 '18 at 14:56

2

Format your Series index with df columns

df.div(pd.Series([100,100,100],index=df.columns))
Out[132]: 
      A     B    id
0  0.01  0.02  0.01
1  0.02  0.03  0.01
2  0.04  0.00  0.03
3  0.05  0.06  0.01
4  0.08  0.09  0.03
5  0.09  0.07  0.03

answered May 31 '18 at 14:56

BENY

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score 1 · Answer 3 · answered May 31 '18 at 14:58

1

Given dataframe df and series s, you can also use numpy:

res = pd.DataFrame(df.values / s.values[:, None],
                   index=df.index, columns=df.columns)

answered May 31 '18 at 14:58

jpp

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How to divide each column of pandas Dataframe by a Series?

3 Answers3