BUG: loc dropping levels when df has only one row (#38150)

Author: phofl

doc/source/whatsnew/v1.3.0.rst

@@ -234,7 +234,7 @@ Indexing
 - Bug in :meth:`CategoricalIndex.get_indexer` failing to raise ``InvalidIndexError`` when non-unique (:issue:`38372`)
 - Bug in inserting many new columns into a :class:`DataFrame` causing incorrect subsequent indexing behavior (:issue:`38380`)
 - Bug in :meth:`DataFrame.iloc.__setitem__` and :meth:`DataFrame.loc.__setitem__` with mixed dtypes when setting with a dictionary value (:issue:`38335`)
--
+- Bug in :meth:`DataFrame.loc` dropping levels of :class:`MultiIndex` when :class:`DataFrame` used as input has only one row (:issue:`10521`)
 -
 
 Missing

pandas/core/indexing.py

@@ -842,8 +842,12 @@ 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")
-            with suppress(IndexingError):
-                return self._handle_lowerdim_multi_index_axis0(tup)
+            if self.ndim == 1 or not any(isinstance(x, slice) 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)
 
             # this is a series with a multi-index specified a tuple of
             # selectors

pandas/tests/indexing/multiindex/test_loc.py

@@ -695,3 +695,17 @@ def test_loc_getitem_index_differently_ordered_slice_none():
         columns=["a", "b"],
     )
     tm.assert_frame_equal(result, expected)
+
+
+def test_loc_getitem_drops_levels_for_one_row_dataframe():
+    # GH#10521
+    mi = MultiIndex.from_arrays([["x"], ["y"], ["z"]], names=["a", "b", "c"])
+    df = DataFrame({"d": [0]}, index=mi)
+    expected = df.copy()
+    result = df.loc["x", :, "z"]
+    tm.assert_frame_equal(result, expected)
+
+    ser = Series([0], index=mi)
+    result = ser.loc["x", :, "z"]
+    expected = Series([0], index=Index(["y"], name="b"))
+    tm.assert_series_equal(result, expected)