pandas 在多个数据框列上执行算术运算的最有效方法

Question

my first post! I'm running python 3.8.5 & pandas 1.1.0 on jupyter notebooks.

I want to divide several columns by the corresponding elements in another column of the same dataframe. For example:

import pandas as pd
df = pd.DataFrame({'a': [2, 3, 4], 'b': [4, 6, 8], 'c':[6, 9, 12]})
df

    a   b   c
0   2   4   6
1   3   6   9
2   4   8   12

I'd like to divide columns 'b' & 'c' by the corresponding values in 'a' and substitute the values in 'b' and 'c' with the result of this division. So the above dataframe becomes:

    a   b   c
0   2   2   3
1   3   2   3
2   4   2   3

I tried

df.iloc[: , 1:] = df.iloc[: , 1:] / df['a']

but this gives:

    a   b   c
0   2   NaN NaN
1   3   NaN NaN
2   4   NaN NaN

I got it working by doing:

for colname in df.columns[1:]:
    df[colname] = (df[colname] / df['a'])

Is there a faster way of doing the above by avoiding the for loop?

thanks, mk

Answer 1

差不多了，使用div和axis=0 ：

df.iloc[:,1:] = df.iloc[:,1:].div(df.a, axis=0)

Answer 2

df.b= df.b/df.a
df.c=df.c/df.a

or

df[['b','c']]=df.apply(lambda x: x[['b','c']]/x.a ,axis=1)