pandas 获取所有具有 NaN 值的行
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Getting all rows with NaN value
提问by MJP
I have a table with a column that has some NaN values in it:
我有一个表，其中有一列包含一些 NaN 值：
A B C D
2 3 2 Nan
3 4 5 5
2 3 1 Nan
I'd like to get all rows where D = NaN. How can I do this?
我想获得 D = NaN 的所有行。我怎样才能做到这一点？
回答by Nipun Batra
Creating a df for illustration (containing Nan)
为插图创建一个 df（包含 Nan）
In [86]: df =pd.DataFrame({'a':[1,2,3],'b':[3,4,5],'c':[np.nan, 4,5]})
In [87]: df
Out[87]:
a b c
0 1 3 NaN
1 2 4 4
2 3 5 5
Checking which indices have null for column c
检查列 c 的哪些索引为空
In [88]: pd.isnull(df['c'])
Out[88]:
0 True
1 False
2 False
Name: c, dtype: bool
Checking which indices dont have null for column c
检查列 c 的哪些索引不为空
In [90]: pd.notnull(df['c'])
Out[90]:
0 False
1 True
2 True
Name: c, dtype: bool
Selecting rows of df where c is not null
选择 df 的行，其中 c 不为空
In [91]: df[pd.notnull(df['c'])]
Out[91]:
a b c
1 2 4 4
2 3 5 5
Selecting rows of df where c is null
选择 df 的行，其中 c 为空
In [93]: df[pd.isnull(df['c'])]
Out[93]:
a b c
0 1 3 NaN
Selecting rows of column c of df where c is not null
选择 df 的 c 列的行，其中 c 不为空
In [94]: df['c'][pd.notnull(df['c'])]
Out[94]:
1 4
2 5
Name: c, dtype: float64
回答by Vincenzooo
For a solution that doesn't involve pandas, you can do something like:
对于不涉及Pandas的解决方案，您可以执行以下操作：
goodind=np.where(np.sum(np.isnan(y),axis=1)==0)[0] #indices of rows non containing nans
(or the negation if you want rows with nan) and use the indices to slice data.
I am not sure sumis the best way to combine booleans, but np.anyand np.alldon't seem to have a axisparameter, so this is the best way I found.
（或者如果你想要带有 nan 的行）并使用索引来切片数据。我不知道sum是布尔值相结合的最佳方式，但np.any并np.all似乎没有有一个axis参数，所以这是我找到的最好方式。
