BUG: .loc failing to drop first level

pandas/core/indexes/multi.py

@@ -3030,16 +3030,20 @@ def maybe_mi_droplevels(indexer, levels):
                                 # everything
                                 continue
                             else:
-                                raise TypeError(
-                                    f"Expected label or tuple of labels, got {key}"
-                                )
+                                # e.g. test_xs_IndexSlice_argument_not_implemented
+                                k_index = np.zeros(len(self), dtype=bool)
+                                k_index[loc_level] = True
+
                         else:
                             k_index = loc_level
 
                     elif com.is_null_slice(k):
                         # taking everything, does not affect `indexer` below
                         continue
+
                     else:
+                        # FIXME: this message can be inaccurate, e.g.
+                        #  test_series_varied_multiindex_alignment
                         raise TypeError(f"Expected label or tuple of labels, got {key}")
 
                     if indexer is None:

pandas/core/indexing.py

@@ -882,17 +882,21 @@ def _getitem_nested_tuple(self, tup: tuple):
             if self.name != "loc":
                 # This should never be reached, but lets be explicit about it
                 raise ValueError("Too many indices")
-            if isinstance(self.obj, ABCSeries) and any(
-                isinstance(k, tuple) for k in tup
-            ):
-                # GH#35349 Raise if tuple in tuple for series
-                raise ValueError("Too many indices")
             if all(is_hashable(x) or com.is_null_slice(x) for x in tup):
                 # GH#10521 Series should reduce MultiIndex dimensions instead of
                 #  DataFrame, IndexingError is not raised when slice(None,None,None)
                 #  with one row.
                 with suppress(IndexingError):
                     return self._handle_lowerdim_multi_index_axis0(tup)
+            elif isinstance(self.obj, ABCSeries) and any(
+                isinstance(k, tuple) for k in tup
+            ):
+                # GH#35349 Raise if tuple in tuple for series
+                # Do this after the all-hashable-or-null-slice check so that
+                #  we are only getting non-hashable tuples, in particular ones
+                #  that themselves contain a slice entry
+                # See test_loc_series_getitem_too_many_dimensions
+                raise ValueError("Too many indices")
 
             # this is a series with a multi-index specified a tuple of
             # selectors
@@ -1127,6 +1131,9 @@ def _handle_lowerdim_multi_index_axis0(self, tup: tuple):
             return self._get_label(tup, axis=axis)
         except TypeError as err:
             # slices are unhashable
+            # FIXME: this raises when we have a DatetimeIndex first level and a
+            #  string for the first tup entry
+            #  see test_partial_slicing_with_multiindex
             raise IndexingError("No label returned") from err
 
         except KeyError as ek:

pandas/tests/frame/indexing/test_xs.py

@@ -318,12 +318,13 @@ def test_xs_IndexSlice_argument_not_implemented(self, klass):
         if klass is Series:
             obj = obj[0]
 
-        msg = (
-            "Expected label or tuple of labels, got "
-            r"\(\('foo', 'qux', 0\), slice\(None, None, None\)\)"
-        )
-        with pytest.raises(TypeError, match=msg):
-            obj.xs(IndexSlice[("foo", "qux", 0), :])
+        expected = obj.iloc[-2:].droplevel(0)
+
+        result = obj.xs(IndexSlice[("foo", "qux", 0), :])
+        tm.assert_equal(result, expected)
+
+        result = obj.loc[IndexSlice[("foo", "qux", 0), :]]
+        tm.assert_equal(result, expected)
 
     @pytest.mark.parametrize("klass", [DataFrame, Series])
     def test_xs_levels_raises(self, klass):

pandas/tests/indexing/test_loc.py

@@ -1663,6 +1663,18 @@ def test_loc_multiindex_levels_contain_values_not_in_index_anymore(self, lt_valu
         with pytest.raises(KeyError, match=r"\['b'\] not in index"):
             df.loc[df["a"] < lt_value, :].loc[["b"], :]
 
+    def test_loc_drops_level(self):
+        # Based on test_series_varied_multiindex_alignment, where
+        #  this used to fail to drop the first level
+        mi = MultiIndex.from_product(
+            [list("ab"), list("xy"), [1, 2]], names=["ab", "xy", "num"]
+        )
+        ser = Series(range(8), index=mi)
+
+        loc_result = ser.loc["a", :, :]
+        expected = ser.index.droplevel(0)[:4]
+        tm.assert_index_equal(loc_result.index, expected)
+
 
 class TestLocSetitemWithExpansion:
     @pytest.mark.slow

pandas/tests/series/test_arithmetic.py

@@ -924,7 +924,7 @@ def test_series_varied_multiindex_alignment():
         [1000 * i for i in range(1, 5)],
         index=pd.MultiIndex.from_product([list("xy"), [1, 2]], names=["xy", "num"]),
     )
-    result = s1.loc[pd.IndexSlice["a", :, :]] + s2
+    result = s1.loc[pd.IndexSlice[["a"], :, :]] + s2
     expected = Series(
         [1000, 2001, 3002, 4003],
         index=pd.MultiIndex.from_tuples(