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

问题描述

我正在Python 3中运行Pandas，我注意到以下内容:

I'm running Pandas in Python 3 and I noticed that the following:

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

以下内容:

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！

So it's filling in Series values but not DataFrame values with 0 when I use .fillna(). Is this a problem with Python 3? Otherwise, what am I missing here to get 0s in place of null values in DataFrames? Thanks!

推荐答案

它与您调用fillna()函数的方式有关.

It has to do with the way you're calling the fillna() function.

如果执行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.

If you do inplace=True (see code below), they will be filled in place and overwrite your original data frame.

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]: 

这篇关于 pandas .fillna()未在Python 3中填充DataFrame中的值的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！