pandas.fillna（）未在Python 3中填充DataFrame中的值

Question

我在Python 3中运行Pandas，发现以下内容：

import pandas as pd
import numpy as np
from pandas import DataFrame
from numpy import nan

df = DataFrame([[1, nan], [nan, 4], [5, 6]])

print(df)

df2 = df
df2.fillna(0)

print(df2)

返回以下内容：

 0   1
0   1 NaN
1 NaN   4
2   5   6
    0   1
0   1 NaN
1 NaN   4
2   5   6

而以下：

import pandas as pd
import numpy as np
from pandas import Series
from numpy import nan

sr1 = Series([1,2,3,nan,5,6,7])

sr1.fillna(0)

返回以下内容：

0    1
1    2
2    3
3    0
4    5
5    6
6    7
dtype: float64

因此，当我使用.fillna（）时，它填充的是Series值，而不是0的DataFrame值。这是Python
3的问题吗？否则，我在这里缺少什么来代替DataFrames中的空值以获得0？谢谢！

Answer 1

它与调用fillna()函数的方式有关。

如果这样做inplace=True（请参见下面的代码），它们将被填充到位并覆盖原始数据框。

In [1]: paste
import pandas as pd
import numpy as np
from pandas import DataFrame
from numpy import nan

df = DataFrame([[1, nan], [nan, 4], [5, 6]])
## -- End pasted text --

In [2]:

In [2]: df
Out[2]: 
    0   1
0   1 NaN
1 NaN   4
2   5   6

In [3]: df.fillna(0)
Out[3]: 
   0  1
0  1  0
1  0  4
2  5  6

In [4]: df2 = df

In [5]: df2.fillna(0)
Out[5]: 
   0  1
0  1  0
1  0  4
2  5  6

In [6]: df2  # note how this is unchanged.
Out[6]: 
    0   1
0   1 NaN
1 NaN   4
2   5   6

In [7]: df.fillna(0, inplace=True)  # this will replace the values.

In [8]: df
Out[8]: 
   0  1
0  1  0
1  0  4
2  5  6

In [9]: