如何按系列划分pandas Dataframe的每一列？

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!

Answer 1

I found the solution

Setting axis = 0 solves the issue.

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

many thanks

Answer 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

Answer 3

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)