Backport PR #27855: BUG: add back check for MultiIndex case and take_split_path (#27887)

Author: meeseeksmachine

doc/source/whatsnew/v0.25.1.rst

@@ -84,7 +84,7 @@ Indexing
 
 - Bug in partial-string indexing returning a NumPy array rather than a ``Series`` when indexing with a scalar like ``.loc['2015']`` (:issue:`27516`)
 - Break reference cycle involving :class:`Index` to allow garbage collection of :class:`Index` objects without running the GC. (:issue:`27585`)
--
+- Fix regression in assigning values to a single column of a DataFrame with a ``MultiIndex`` columns (:issue:`27841`).
 -
 
 Missing

pandas/core/indexing.py

@@ -326,6 +326,17 @@ def _setitem_with_indexer(self, indexer, value):
                 val = list(value.values()) if isinstance(value, dict) else value
                 take_split_path = not blk._can_hold_element(val)
 
+        # if we have any multi-indexes that have non-trivial slices
+        # (not null slices) then we must take the split path, xref
+        # GH 10360, GH 27841
+        if isinstance(indexer, tuple) and len(indexer) == len(self.obj.axes):
+            for i, ax in zip(indexer, self.obj.axes):
+                if isinstance(ax, MultiIndex) and not (
+                    is_integer(i) or com.is_null_slice(i)
+                ):
+                    take_split_path = True
+                    break
+
         if isinstance(indexer, tuple):
             nindexer = []
             for i, idx in enumerate(indexer):

pandas/tests/indexing/multiindex/test_loc.py

@@ -390,3 +390,26 @@ def test_loc_getitem_lowerdim_corner(multiindex_dataframe_random_data):
     expected = 0
     result = df.sort_index().loc[("bar", "three"), "B"]
     assert result == expected
+
+
+def test_loc_setitem_single_column_slice():
+    # case from https://github.com/pandas-dev/pandas/issues/27841
+    df = DataFrame(
+        "string",
+        index=list("abcd"),
+        columns=MultiIndex.from_product([["Main"], ("another", "one")]),
+    )
+    df["labels"] = "a"
+    df.loc[:, "labels"] = df.index
+    tm.assert_numpy_array_equal(np.asarray(df["labels"]), np.asarray(df.index))
+
+    # test with non-object block
+    df = DataFrame(
+        np.nan,
+        index=range(4),
+        columns=MultiIndex.from_tuples([("A", "1"), ("A", "2"), ("B", "1")]),
+    )
+    expected = df.copy()
+    df.loc[:, "B"] = np.arange(4)
+    expected.iloc[:, 2] = np.arange(4)
+    tm.assert_frame_equal(df, expected)