Pandas：IndexingError：不可对齐的布尔系列作为索引器提供

我正在尝试运行我认为简单的代码来消除所有具有 NaN 的任何列，但无法让它工作（axis = 1消除行时效果很好）：

import pandas as pd
import numpy as np

df = pd.DataFrame({'a':[1,2,np.nan,np.nan], 'b':[4,np.nan,6,np.nan], 'c':[np.nan, 8,9,np.nan], 'd':[np.nan,np.nan,np.nan,np.nan]})

df = df[df.notnull().any(axis = 0)]

print df

完整错误：

raise IndexingError('Unalignable boolean Series provided as 'pandas.core.indexing.IndexingError: Unalignable boolean Series provided as indexer (index of the boolean Series and of the indexed object do not match

预期输出：

     a    b    c
0  1.0  4.0  NaN
1  2.0  NaN  8.0
2  NaN  6.0  9.0
3  NaN  NaN  NaN

你需要loc http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.loc.html，因为按列过滤：

print (df.notnull().any(axis = 0))
a     True
b     True
c     True
d    False
dtype: bool

df = df.loc[:, df.notnull().any(axis = 0)]
print (df)

     a    b    c
0  1.0  4.0  NaN
1  2.0  NaN  8.0
2  NaN  6.0  9.0
3  NaN  NaN  NaN

或者过滤列，然后选择依据[]:

print (df.columns[df.notnull().any(axis = 0)])
Index(['a', 'b', 'c'], dtype='object')

df = df[df.columns[df.notnull().any(axis = 0)]]
print (df)

     a    b    c
0  1.0  4.0  NaN
1  2.0  NaN  8.0
2  NaN  6.0  9.0
3  NaN  NaN  NaN

Or dropna http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.dropna.html带参数how='all'用于删除填充的所有列NaNs only:

print (df.dropna(axis=1, how='all'))
     a    b    c
0  1.0  4.0  NaN
1  2.0  NaN  8.0
2  NaN  6.0  9.0
3  NaN  NaN  NaN