pandas 数据框fillna()仅存在一些列 [英] Pandas dataframe fillna() only some columns in place

问题描述

我只尝试对列的某些子集用0填充Pandas数据框中的任何值.

I am trying to fill none values in a Pandas dataframe with 0's for only some subset of columns.

当我这样做时:

import pandas as pd
df = pd.DataFrame(data={'a':[1,2,3,None],'b':[4,5,None,6],'c':[None,None,7,8]})
print df
df.fillna(value=0, inplace=True)
print df

输出:

     a    b    c
0  1.0  4.0  NaN
1  2.0  5.0  NaN
2  3.0  NaN  7.0
3  NaN  6.0  8.0
     a    b    c
0  1.0  4.0  0.0
1  2.0  5.0  0.0
2  3.0  0.0  7.0
3  0.0  6.0  8.0

它将每个None替换为0.我想做的是，仅替换a和b列中的None，而不能替换c.

It replaces every None with 0's. What I want to do is, only replace Nones in columns a and b, but not c.

做到这一点的最佳方法是什么?

What is the best way of doing this?

推荐答案

您可以选择所需的列并通过分配来完成:

You can select your desired columns and do it by assignment:

df[['a', 'b']] = df[['a','b']].fillna(value=0)

结果输出符合预期:

     a    b    c
0  1.0  4.0  NaN
1  2.0  5.0  NaN
2  3.0  0.0  7.0
3  0.0  6.0  8.0

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