DOC: Basic indexing on axis with Multiindex

[sroener]

Location of the documentation

Basic indexing on axis with MultiIndex

Documentation problem

The following example seems not to work:

arrays = [
         np.array(["bar", "bar", "baz", "baz", "foo", "foo", "qux", "qux"]),
         np.array(["one", "two", "one", "two", "one", "two", "one", "two"]),
     ]
    
df = pd.DataFrame(np.random.randn(8, 4), index=arrays)

df["bar"]

The code throws an error:

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-13-6ea2f6413a49> in <module>
----> 1 df["bar"]

~/anaconda3/envs/jupyter/lib/python3.8/site-packages/pandas/core/frame.py in __getitem__(self, key)
   3022             if self.columns.nlevels > 1:
   3023                 return self._getitem_multilevel(key)
-> 3024             indexer = self.columns.get_loc(key)
   3025             if is_integer(indexer):
   3026                 indexer = [indexer]

~/anaconda3/envs/jupyter/lib/python3.8/site-packages/pandas/core/indexes/range.py in get_loc(self, key, method, tolerance)
    352                 except ValueError as err:
    353                     raise KeyError(key) from err
--> 354             raise KeyError(key)
    355         return super().get_loc(key, method=method, tolerance=tolerance)
    356 

KeyError: 'bar'

When asking for help, it is suggested to use df.loc["bar"] instead with as shown in another part of the documentation (advanced indexing with hierarchical index).

Suggested fix for documentation

An explanation for when partial indexing without the usage of .loc[] is applicable would be helpful or choosing an example that works in the current version. Trying to reproduce documentation code that does not work leads to confusion.

[attack68]

linking to #39775, this is about a different issue but I agree behaviour should be clearer.