我在Python 3中运行Pandas,我注意到以下内容:
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
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
当我使用.fillna()时,它填充了Series值,但没有填充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?谢谢!
答案 0 :(得分:2)
正如您在documentation中所读到的那样,方法fillna(newValue)
会返回另一个DataFrame
,就像前一个nan
一样,但df = DataFrame([[1, nan], [nan, 2], [3, 2]])
df2 = df.fillna(0)
print(df2)
# Outputs
# 0 1
# 0 1 0
# 1 0 2
# 2 3 2
print(df)
# Outputs (The previous one isn't modified)
# 0 1
# 0 1 nan
# 1 nan 2
# 2 3 2
值会替换为新值。< / p>
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答案 1 :(得分:2)
这与您调用fillna()
功能的方式有关。
如果您执行inplace=True
(请参阅下面的代码),它们将被填充并覆盖原始数据框。
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]: