python Pandas : pivot_table silently drops indices with nans

Question

是否可以选择不删除其中包含 NaN 的索引？我认为默默地从枢轴上删除这些行会在某些时候给某人带来严重的痛苦。

import pandas
import numpy

a = [['a', 'b', 12, 12, 12], ['a', numpy.nan, 12.3, 233., 12], ['b', 'a', 123.23, 123, 1], ['a', 'b', 1, 1, 1.]]

df = pandas.DataFrame(a, columns=['a', 'b', 'c', 'd', 'e'])

df_pivot = df.pivot_table(index=['a', 'b'], values=['c', 'd', 'e'], aggfunc=sum)
print(df)
print(df_pivot)

输出:

   a    b       c    d   e
0  a    b   12.00   12  12
1  a  NaN   12.30  233  12
2  b    a  123.23  123   1
3  a    b    1.00    1   1
          c    d   e
a b                 
a b   13.00   13  13
b a  123.23  123   1

Answer 1

目前不支持此功能，请参阅此问题以获取增强功能:https://github.com/pydata/pandas/issues/3729 .

用虚拟、数据透视和替换填充索引的解决方法

In [28]: df = df.reset_index()

In [29]: df['b'] = df['b'].fillna('dummy')

In [30]: df['dummy'] = np.nan

In [31]: df
Out[31]: 
   a      b       c    d   e  dummy
0  a      b   12.00   12  12    NaN
1  a  dummy   12.30  233  12    NaN
2  b      a  123.23  123   1    NaN
3  a      b    1.00    1   1    NaN

In [32]: df.pivot_table(index=['a', 'b'], values=['c', 'd', 'e'], aggfunc=sum)
Out[32]: 
              c    d   e
a b                     
a b       13.00   13  13
  dummy   12.30  233  12
b a      123.23  123   1

In [33]: df.pivot_table(index=['a', 'b'], values=['c', 'd', 'e'], aggfunc=sum).reset_index().replace('dummy',np.nan).set_index(['a','b'])
Out[33]: 
            c    d   e
a b                   
a b     13.00   13  13
  NaN   12.30  233  12
b a    123.23  123   1