BUG: .loc with MultiIndex with names[1] = 0

doc/source/whatsnew/v1.2.0.rst

@@ -430,6 +430,7 @@ Indexing
 - Bug in indexing with boolean masks on datetime-like values sometimes returning a view instead of a copy (:issue:`36210`)
 - Bug in :meth:`DataFrame.__getitem__` and :meth:`DataFrame.loc.__getitem__` with :class:`IntervalIndex` columns and a numeric indexer (:issue:`26490`)
 - Bug in :meth:`Series.loc.__getitem__` with a non-unique :class:`MultiIndex` and an empty-list indexer (:issue:`13691`)
+- Bug in indexing on a :class:`Series` or :class:`DataFrame` with a :class:`MultiIndex` with a level named "0" (:issue:`37194`)
 
 Missing
 ^^^^^^^

pandas/core/generic.py

@@ -3684,7 +3684,9 @@ class   animal   locomotion
         index = self.index
         if isinstance(index, MultiIndex):
             try:
-                loc, new_index = self.index.get_loc_level(key, drop_level=drop_level)
+                loc, new_index = self.index._get_loc_level(
+                    key, level=0, drop_level=drop_level
+                )
             except TypeError as e:
                 raise TypeError(f"Expected label or tuple of labels, got {key}") from e
         else:

pandas/core/indexes/base.py

@@ -1552,12 +1552,19 @@ def droplevel(self, level=0):
 
         levnums = sorted(self._get_level_number(lev) for lev in level)[::-1]
 
-        if len(level) == 0:
+        return self._drop_level_numbers(levnums)
+
+    def _drop_level_numbers(self, levnums: List[int]):
+        """
+        Drop MultiIndex levels by level _number_, not name.
+        """
+
+        if len(levnums) == 0:
             return self
-        if len(level) >= self.nlevels:
+        if len(levnums) >= self.nlevels:
             raise ValueError(
-                f"Cannot remove {len(level)} levels from an index with {self.nlevels} "
-                "levels: at least one level must be left."
+                f"Cannot remove {len(levnums)} levels from an index with "
+                f"{self.nlevels} levels: at least one level must be left."
             )
         # The two checks above guarantee that here self is a MultiIndex
         self = cast("MultiIndex", self)

pandas/core/indexes/multi.py

@@ -2864,16 +2864,29 @@ def get_loc_level(self, key, level=0, drop_level: bool = True):
         >>> mi.get_loc_level(['b', 'e'])
         (1, None)
         """
+        if not isinstance(level, (list, tuple)):
+            level = self._get_level_number(level)
+        else:
+            level = [self._get_level_number(lev) for lev in level]
+        return self._get_loc_level(key, level=level, drop_level=drop_level)
+
+    def _get_loc_level(
+        self, key, level: Union[int, List[int]] = 0, drop_level: bool = True
+    ):
+        """
+        get_loc_level but with `level` known to be positional, not name-based.
+        """
+
         # different name to distinguish from maybe_droplevels
         def maybe_mi_droplevels(indexer, levels, drop_level: bool):
             if not drop_level:
                 return self[indexer]
             # kludge around
             orig_index = new_index = self[indexer]
-            levels = [self._get_level_number(i) for i in levels]
+
             for i in sorted(levels, reverse=True):
                 try:
-                    new_index = new_index.droplevel(i)
+                    new_index = new_index._drop_level_numbers([i])
                 except ValueError:
 
                     # no dropping here
@@ -2887,7 +2900,7 @@ def maybe_mi_droplevels(indexer, levels, drop_level: bool):
                 )
             result = None
             for lev, k in zip(level, key):
-                loc, new_index = self.get_loc_level(k, level=lev)
+                loc, new_index = self._get_loc_level(k, level=lev)
                 if isinstance(loc, slice):
                     mask = np.zeros(len(self), dtype=bool)
                     mask[loc] = True
@@ -2897,8 +2910,6 @@ def maybe_mi_droplevels(indexer, levels, drop_level: bool):
 
             return result, maybe_mi_droplevels(result, level, drop_level)
 
-        level = self._get_level_number(level)
-
         # kludge for #1796
         if isinstance(key, list):
             key = tuple(key)
@@ -2963,7 +2974,8 @@ def partial_selection(key, indexer=None):
             indexer = self._get_level_indexer(key, level=level)
             return indexer, maybe_mi_droplevels(indexer, [level], drop_level)
 
-    def _get_level_indexer(self, key, level=0, indexer=None):
+    def _get_level_indexer(self, key, level: int = 0, indexer=None):
+        # `level` kwarg is _always_ positional, never name
         # return an indexer, boolean array or a slice showing where the key is
         # in the totality of values
         # if the indexer is provided, then use this
@@ -3767,13 +3779,13 @@ def maybe_droplevels(index, key):
     if isinstance(key, tuple):
         for _ in key:
             try:
-                index = index.droplevel(0)
+                index = index._drop_level_numbers([0])
             except ValueError:
                 # we have dropped too much, so back out
                 return original_index
     else:
         try:
-            index = index.droplevel(0)
+            index = index._drop_level_numbers([0])
         except ValueError:
             pass
 

pandas/tests/indexing/multiindex/test_loc.py

@@ -524,6 +524,30 @@ def test_loc_with_mi_indexer():
     tm.assert_frame_equal(result, expected)
 
 
+def test_loc_mi_with_level1_named_0():
+    # GH#37194
+    dti = pd.date_range("2016-01-01", periods=3, tz="US/Pacific")
+
+    ser = Series(range(3), index=dti)
+    df = ser.to_frame()
+    df[1] = dti
+
+    df2 = df.set_index(0, append=True)
+    assert df2.index.names == (None, 0)
+    df2.index.get_loc(dti[0])  # smoke test
+
+    result = df2.loc[dti[0]]
+    expected = df2.iloc[[0]].droplevel(None)
+    tm.assert_frame_equal(result, expected)
+
+    ser2 = df2[1]
+    assert ser2.index.names == (None, 0)
+
+    result = ser2.loc[dti[0]]
+    expected = ser2.iloc[[0]].droplevel(None)
+    tm.assert_series_equal(result, expected)
+
+
 def test_getitem_str_slice(datapath):
     # GH#15928
     path = datapath("reshape", "merge", "data", "quotes2.csv")