Python 使用 applymap 替换 Pandas Dataframe 中的空值
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replacing null values in a Pandas Dataframe using applymap
提问by useRj
I've got an "Age" column, but sometimes NaN values are displayed. I know I can use "fillna" for this purposes but I've tried to define my own function (and learning to do this way) and use applymap to dataframe
我有一个“年龄”列，但有时会显示 NaN 值。我知道我可以为此目的使用“fillna”，但我尝试定义我自己的函数（并学习这样做）并将 applymap 用于数据框
no success so far.
到目前为止没有成功。
Age
69
49
NaN
54
NaN
I've tried
我试过了
def get_rid_of_nulls(value):
if value == np.nan:
return 'Is Null value'
else:
return value
with this not working either
这也不起作用
if value == None
if value isnull
if value == np.na
if value ==''
if value == NaN
if value == 'NaN'
None of the comparisons seems to work. I'm wrong for sure but I'm stuck and I'm very stubborn to use fillna
这些比较似乎都不起作用。我肯定错了，但我被卡住了，而且我很固执地使用fillna
thanks
谢谢
采纳答案by mgc
As there is "replacing" in your title, and you mentioned fillnabut not the replace()method, you can also obtain the same result doing something like that :
由于您的标题中有“替换”，并且您提到了fillna但没有提到replace()方法，因此您也可以通过执行以下操作获得相同的结果：
df.Age.replace(np.NaN, 'Is Null value', inplace=True)
# Or, depending on your needs:
df['Age'] = df.Age.replace(np.NaN, 'Is Null value')
# Or without `replace` :
df['Age'] = df.Age.apply(lambda x: x if not pd.isnull(x) else 'Is Null value')
回答by EdChum
You can use pd.isnull():
您可以使用pd.isnull()：
In [4]:
def get_rid_of_nulls(value):
if pd.isnull(value):
return 'Is Null value'
else:
return value
df['Age'].apply(get_rid_of_nulls)
Out[4]:
0 69
1 49
2 Is Null value
3 54
4 Is Null value
Name: Age, dtype: object
Similarly you can use the property that NaNdoes not equal itself:
同样，您可以使用NaN不等于自身的属性：
In [5]:
def get_rid_of_nulls(value):
if value != value:
return 'Is Null value'
else:
return value
df['Age'].apply(get_rid_of_nulls)
Out[5]:
0 69
1 49
2 Is Null value
3 54
4 Is Null value
Name: Age, dtype: object
