使用此處pandas找到的文檔中的示例，以下索引完美運行，結果為：pd.Seriesimport pandas as pdtuples = [(1, 'red'), (1, 'blue'),          (2, 'red'), (2, 'blue')]columns = pd.MultiIndex.from_tuples(tuples, names=('number', 'color'))asdf = pd.DataFrame(columns=columns, index=[0, 1])asdf.loc[:, (1, 'red')]但是如果我稍微改變一下代碼，去掉一層，同樣的索引就不起作用了：import pandas as pdtuples = [(1,), (2,)]columns = pd.MultiIndex.from_tuples(tuples, names=['number'])asdf = pd.DataFrame(columns=columns, index=[0, 1])asdf.loc[:, (1,)]IndexError                                Traceback (most recent call last)<ipython-input-43-d55399a979fa> in <module>----> 1 asdf.loc[:, (1,)]/opt/conda/lib/python3.8/site-packages/pandas/core/indexing.py in __getitem__(self, key)   1760                 except (KeyError, IndexError, AttributeError):   1761                     pass-> 1762             return self._getitem_tuple(key)   1763         else:   1764             # we by definition only have the 0th axis/opt/conda/lib/python3.8/site-packages/pandas/core/indexing.py in _getitem_tuple(self, tup)   1270     def _getitem_tuple(self, tup: Tuple):   1271         try:-> 1272             return self._getitem_lowerdim(tup)   1273         except IndexingError:   1274             pass/opt/conda/lib/python3.8/site-packages/pandas/core/indexing.py in _getitem_lowerdim(self, tup)   1371         # we may have a nested tuples indexer here   1372         if self._is_nested_tuple_indexer(tup):-> 1373             return self._getitem_nested_tuple(tup)   1374    1375         # we maybe be using a tuple to represent multiple dimensions hereIndexError: tuple index out of range此外，將其索引為asdf.loc[:, 1]throws a TypeError，更進一步，將其索引為asdf.loc[:, ((1,),)]works ，但結果是 a pd.DataFrame，而不是pd.Series!為什么會這樣？非常感謝您！PS：我有興趣從這些問題中“抽象”我的代碼（一個級別與一個級別中的多個級別pd.DataFrame.columns）。在我工作的公司中，有時我們會獲得需要多個級別的客戶數據，但有時只需要一個級別。