I had a multi-indexed pandas series with more than two levels in the row multi-index.

arrays = [
    ["bar", "baz",  "foo",   "qux"],
    ["one", "two",],
    ["a", "b","c" ]
]

index = pd.MultiIndex.from_product(arrays, names=["first", "second","third"])

s = pd.Series(np.random.randn(24), index=index)

I was able to slice this dataframe like so:

df.loc[(slice(None), slice(None), "a")

with output

first  second
bar    one       1.574135
       two       1.557756
baz    one      -0.023177
       two      -0.537326
foo    one      -0.183099
       two      -1.776498
qux    one       0.425121
       two       0.451778
dtype: float64

To make certain kinds of plots easier, I reset the index to incorporate the third column as a row

s = s.reset_index(level = [2])

                third   0
first   second      
bar one a   1.574135
        one b   -2.450800
        one c   0.966331
        two a   1.557756
        two b   -0.800615
        two c   0.405982
baz one a   -0.023177
        one b   1.743043
        one c   0.847148
        two a   -0.537326
        two b   -1.157622
        two c   -0.229345
foo one a   -0.183099
        one b   1.047875
        one c   -1.980324
        two a   -1.776498
        two b   -1.169729
        two c   -1.509195
qux one a   0.425121
        one b   0.903984
        one c   -0.455681
        two a   0.451778
        two b   0.215866
        two c   -0.090196

Now, slicing using the same format results in a KeyError

s.loc[(slice(None),"one")]

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
File c:filepath\pandas\core\indexes\base.py:3812, in Index.get_loc(self, key)
   3811 try:
-> 3812     return self._engine.get_loc(casted_key)
   3813 except KeyError as err:

File pandas/_libs/index.pyx:167, in pandas._libs.index.IndexEngine.get_loc()

File pandas/_libs/index.pyx:196, in pandas._libs.index.IndexEngine.get_loc()

File pandas/_libs/hashtable_class_helper.pxi:7088, in pandas._libs.hashtable.PyObjectHashTable.get_item()

File pandas/_libs/hashtable_class_helper.pxi:7096, in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 'one'

The above exception was the direct cause of the following exception:

KeyError                                  Traceback (most recent call last)
Cell In[65], line 1
----> 1 s.loc[(slice(None),"one")]

File c:filepath\pandas\core\indexing.py:1184, in _LocationIndexer.__getitem__(self, key)
   1182     if self._is_scalar_access(key):
...
   3822     #  InvalidIndexError. Otherwise we fall through and re-raise
   3823     #  the TypeError.
   3824     self._check_indexing_error(key)

KeyError: 'one'

After scratching my head for a while, I thought that maybe because there were only two arguments passed during slicing, pandas was assuming that the second one was a column slice, even though it was inside the parenthesis. Sure enough, adding a slice(None) outside to let pandas know that the second argument wasn't for a column led to

s.loc[(slice(None),"one"),slice(None)]


            third   0
first   second      
bar one a   1.574135
        one b   -2.450800
        one c   0.966331
baz one a   -0.023177
        one b   1.743043
        one c   0.847148
foo one a   -0.183099
        one b   1.047875
        one c   -1.980324
qux one a   0.425121
        one b   0.903984
        one c   -0.455681

Why is pandas behaving this way? Is this just a quirk? What should I do to avoid this problem in the future?