使用多索引切片时出现KeyError

虽然我能够绕过这个问题,但我想知道为什么会发生这个错误。。 数据帧

import pandas as pd
import itertools

sl_df=pd.DataFrame(
    data=list(range(18)), 
    index=pd.MultiIndex.from_tuples(
        list(itertools.product(
            ['A','B','C'],
            ['I','II','III'],
            ['x','y']))),
    columns=['one'])

出:

         one
A I   x    0
      y    1
  II  x    2
      y    3
  III x    4
      y    5
B I   x    6
      y    7
  II  x    8
      y    9
  III x   10
      y   11
C I   x   12
      y   13
  II  x   14
      y   15
  III x   16
      y   17

简单的切片

sl_df.loc[pd.IndexSlice['A',:,'x']]

出:

         one
A I   x    0
  II  x    2
  III x    4

引发错误的部分:

sl_df.loc[pd.IndexSlice[:,'II']]

出:

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-6-4bfd2d65fd21> in <module>()
----> 1 sl_df.loc[pd.IndexSlice[:,'II']]

...\pandas\core\indexing.pyc in __getitem__(self, key)
   1470             except (KeyError, IndexError):
   1471                 pass
-> 1472             return self._getitem_tuple(key)
   1473         else:
   1474             # we by definition only have the 0th axis

...\pandas\core\indexing.pyc in _getitem_tuple(self, tup)
    868     def _getitem_tuple(self, tup):
    869         try:
--> 870             return self._getitem_lowerdim(tup)
    871         except IndexingError:
    872             pass

...\pandas\core\indexing.pyc in _getitem_lowerdim(self, tup)
    977         # we may have a nested tuples indexer here
    978         if self._is_nested_tuple_indexer(tup):
--> 979             return self._getitem_nested_tuple(tup)
    980
    981         # we maybe be using a tuple to represent multiple dimensions here

...\pandas\core\indexing.pyc in _getitem_nested_tuple(self, tup)
   1056
   1057             current_ndim = obj.ndim
-> 1058             obj = getattr(obj, self.name)._getitem_axis(key, axis=axis)
   1059             axis += 1
   1060

...\pandas\core\indexing.pyc in _getitem_axis(self, key, axis)
   1909
   1910         # fall thru to straight lookup
-> 1911         self._validate_key(key, axis)
   1912         return self._get_label(key, axis=axis)
   1913

...\pandas\core\indexing.pyc in _validate_key(self, key, axis)
   1796                 raise
   1797             except:
-> 1798                 error()
   1799
   1800     def _is_scalar_access(self, key):

...\pandas\core\indexing.pyc in error()
   1783                 raise KeyError(u"the label [{key}] is not in the [{axis}]"
   1784                                .format(key=key,
-> 1785                                        axis=self.obj._get_axis_name(axis)))
   1786
   1787             try:

KeyError: u'the label [II] is not in the [columns]'

解决方法: (或者当索引的第一级上有“:”时,正确的方法。)

sl_df.loc[pd.IndexSlice[:,'II'],:]

出:

        one
A II x    2
     y    3
B II x    8
     y    9
C II x   14
     y   15

问题:为什么只有在多索引的第一级使用“:”时,才必须在轴1上指定“:”?你会不会同意,它在其他级别上工作,但在多索引的第一个级别上不工作,这有点奇怪(参见上面的简单切片)?