python - 值错误 : Length mismatch: Expected axis has 0 elements while creating hierarchical columns in pandas dataframe

Question

我正在浏览 documentation关于 Pandas 中的层次索引。我尝试测试其中的示例以创建具有分层索引的空数据框:

In [5]: df = pd.DataFrame()

In [6]: df.columns = pd.MultiIndex(levels = [['first', 'second'], ['a', 'b']], labels = [[0, 0, 1, 1], [0, 1, 0, 1]])

但是，它会抛出一个错误:

ValueError                                Traceback (most recent call last)
<ipython-input-6-dd823f9b8d22> in <module>()
----> 1 df.columns = pd.MultiIndex(levels = [['first', 'second'], ['a', 'b']], labels = [[0, 0, 1, 1], [0, 1, 0, 1]])

/usr/local/lib/python3.4/dist-packages/pandas/core/generic.py in __setattr__(self, name, value)
   2755         try:
   2756             object.__getattribute__(self, name)
-> 2757             return object.__setattr__(self, name, value)
   2758         except AttributeError:
   2759             pass

pandas/src/properties.pyx in pandas.lib.AxisProperty.__set__ (pandas/lib.c:44873)()

/usr/local/lib/python3.4/dist-packages/pandas/core/generic.py in _set_axis(self, axis, labels)
    446 
    447     def _set_axis(self, axis, labels):
--> 448         self._data.set_axis(axis, labels)
    449         self._clear_item_cache()
    450 

/usr/local/lib/python3.4/dist-packages/pandas/core/internals.py in set_axis(self, axis, new_labels)
   2800             raise ValueError('Length mismatch: Expected axis has %d elements, '
   2801                              'new values have %d elements' %
-> 2802                              (old_len, new_len))
   2803 
   2804         self.axes[axis] = new_labels

ValueError: Length mismatch: Expected axis has 0 elements, new values have 4 elements

我没有发现我的代码有任何问题。知道发生了什么吗？

Answer 1

问题是您有一个包含零列的空数据框，并且您正试图为其分配一个四列多索引；如果您最初创建一个四列的空数据框，错误将消失:

df = pd.DataFrame(pd.np.empty((0, 4)))    
df.columns = pd.MultiIndex(levels = [['first', 'second'], ['a', 'b']], labels = [[0, 0, 1, 1], [0, 1, 0, 1]])

或者您可以使用多索引创建空数据框，如下所示:

multi_index = pd.MultiIndex(levels = [['first', 'second'], ['a', 'b']], labels = [[0, 0, 1, 1], [0, 1, 0, 1]])    
df = pd.DataFrame(columns=multi_index)

df
#   first    second
#  a    b   a     b