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如何选择特定列中带有NaN的行？

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问题：如何选择特定列中带有NaN的行？
回答 0
回答 1

问题：如何选择特定列中带有NaN的行？

给定此数据框，如何仅选择“ Col2”等于的行NaN？

In [56]: df = pd.DataFrame([range(3), [0, np.NaN, 0], [0, 0, np.NaN], range(3), range(3)], columns=["Col1", "Col2", "Col3"])

In [57]: df
Out[57]: 
   0   1   2
0  0   1   2
1  0 NaN   0
2  0   0 NaN
3  0   1   2
4  0   1   2

结果应该是这样的：

Out[57]: 
   0   1   2
1  0 NaN   0
点击查看英文原文

Given this dataframe, how to select only those rows that have “Col2” equal to NaN?

In [56]: df = pd.DataFrame([range(3), [0, np.NaN, 0], [0, 0, np.NaN], range(3), range(3)], columns=["Col1", "Col2", "Col3"])

In [57]: df
Out[57]: 
   0   1   2
0  0   1   2
1  0 NaN   0
2  0   0 NaN
3  0   1   2
4  0   1   2

The result should be this one:

Out[57]: 
   0   1   2
1  0 NaN   0

回答 0

请尝试以下操作：

df[df['Col2'].isnull()]
点击查看英文原文

Try the following:

df[df['Col2'].isnull()]

回答 1

@qbzenker提供了最惯用的方法IMO

这里有一些选择：

In [28]: df.query('Col2 != Col2') # Using the fact that: np.nan != np.nan
Out[28]:
   Col1  Col2  Col3
1     0   NaN   0.0

In [29]: df[np.isnan(df.Col2)]
Out[29]:
   Col1  Col2  Col3
1     0   NaN   0.0
点击查看英文原文

@qbzenker provided the most idiomatic method IMO

Here are a few alternatives:

In [28]: df.query('Col2 != Col2') # Using the fact that: np.nan != np.nan
Out[28]:
   Col1  Col2  Col3
1     0   NaN   0.0

In [29]: df[np.isnan(df.Col2)]
Out[29]:
   Col1  Col2  Col3
1     0   NaN   0.0