如何在列的子集上使用廣播系列修改熊貓數據框

Question

給出下表：

 import numpy as np
 import pandas as pd
 data = pd.DataFrame(data = np.arange(16).reshape((4, 4)),
                     index = ['Chile', 'Argentina', 'Peru', 'Bolivia'],
                     columns = ['one', 'two', 'three', 'four'])


           one  two three  four
 Chile      0    1   2      3
 Argentina  4    5   6      7
 Peru       8    9   10     11
 Bolivia    12   13  14     15

我想通過在將修改 （更新）表的列的子集（ one列和three列）上廣播熊貓系列來執行一項操作。 所以..

ser_to_broad = pd.Series([1, 2], index = ['one', 'three'])
data + ser_to_broad

           one  two three  four
Chile       1   NaN   4     NaN
Argentina   5   NaN   8     NaN    
Peru        9   NaN   12    NaN    
Bolivia     13  NaN   16    NaN 

是否存在一種使用廣播方法保留two和four列的原始值的方法？

Answer 1

使用reindex ，因為ser_to_broad有未命中的列，則它將返回NaN （ NaN + somevalue = NaN ）

data+ser_to_broad.reindex(data.columns,fill_value=0)
Out[106]: 
           one  two  three  four
Chile        1    1      4     3
Argentina    5    5      8     7
Peru         9    9     12    11
Bolivia     13   13     16    15

Answer 2

如果您想更新數據，我認為這可以做到：

ser_to_broad = pd.Series([1, 2], index=['one', 'three'])
data[ser_to_broad.index] += ser_to_broad

print(data)

輸出量

           one  two  three  four
Chile        1    1      4     3
Argentina    5    5      8     7
Peru         9    9     12    11
Bolivia     13   13     16    15