pandas :IndexingError:作为索引器提供的不可对齐的布尔系列 [英] Pandas: IndexingError: Unalignable boolean Series provided as indexer

问题描述

我正在尝试运行我认为简单的代码来消除所有带有NaN的列，但无法使其正常工作(axis = 1在消除行时效果很好):

I'm trying to run what I think is simple code to eliminate any columns with all NaNs, but can't get this to work (axis = 1 works just fine when eliminating rows):

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

推荐答案

您需要 loc ，因为按列过滤:

You need loc, because filter by columns:

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

或过滤列，然后按[]进行选择:

Or filter columns and then select by []:

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

或 dropna how='all'用于删除仅由NaN填充的所有列:

Or dropna with parameter how='all' for remove all columns filled by 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

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