Backport PR #48178 on branch 1.4.x (REGR: loc not working with NamedT…

…uple) (#48217)

Backport PR #48178: REGR: loc not working with NamedTuple

Co-authored-by: Patrick Hoefler <61934744+phofl@users.noreply.github.com>

doc/source/whatsnew/v1.4.4.rst

@@ -20,6 +20,7 @@ Fixed regressions
 - Fixed regression in calling bitwise numpy ufuncs (for example, ``np.bitwise_and``) on Index objects (:issue:`46769`)
 - Fixed regression in :func:`cut` using a ``datetime64`` IntervalIndex as bins (:issue:`46218`)
 - Fixed regression in :meth:`DataFrame.select_dtypes` where ``include="number"`` included :class:`BooleanDtype` (:issue:`46870`)
+- Fixed regression in :meth:`DataFrame.loc` raising error when indexing with a ``NamedTuple`` (:issue:`48124`)
 - Fixed regression in :meth:`DataFrame.loc` not updating the cache correctly after values were set (:issue:`47867`)
 - Fixed regression in :meth:`DataFrame.loc` not aligning index in some cases when setting a :class:`DataFrame` (:issue:`47578`)
 - Fixed regression in :meth:`DataFrame.loc` setting a length-1 array like value to a single value in the DataFrame (:issue:`46268`)

pandas/core/indexing.py

@@ -1175,6 +1175,9 @@ def _getitem_axis(self, key, axis: int):
 
         labels = self.obj._get_axis(axis)
 
+        if isinstance(key, tuple) and isinstance(labels, MultiIndex):
+            key = tuple(key)
+
         if isinstance(key, slice):
             self._validate_key(key, axis)
             return self._get_slice_axis(key, axis=axis)

pandas/tests/frame/indexing/test_indexing.py

@@ -1,3 +1,4 @@
+from collections import namedtuple
 from datetime import (
     datetime,
     timedelta,
@@ -1339,6 +1340,23 @@ def test_loc_setitem_rhs_frame(self, idxr, val):
         expected = DataFrame({"a": [np.nan, val]})
         tm.assert_frame_equal(df, expected)
 
+    def test_loc_named_tuple_for_midx(self):
+        # GH#48124
+        df = DataFrame(
+            index=MultiIndex.from_product(
+                [["A", "B"], ["a", "b", "c"]], names=["first", "second"]
+            )
+        )
+        indexer_tuple = namedtuple("Indexer", df.index.names)
+        idxr = indexer_tuple(first="A", second=["a", "b"])
+        result = df.loc[idxr, :]
+        expected = DataFrame(
+            index=MultiIndex.from_tuples(
+                [("A", "a"), ("A", "b")], names=["first", "second"]
+            )
+        )
+        tm.assert_frame_equal(result, expected)
+
 
 class TestDataFrameIndexingUInt64:
     def test_setitem(self, uint64_frame):