BUG: Fix DataFrame.reindex and Series.reindex loosing values when reindexing single to multiindex

Author: Roline Stapny Saldanha

doc/source/whatsnew/v3.0.0.rst

@@ -788,8 +788,7 @@ MultiIndex
 - Bug in :class:`DataFrame` arithmetic operations in case of unaligned MultiIndex columns (:issue:`60498`)
 - Bug in :class:`DataFrame` arithmetic operations with :class:`Series` in case of unaligned MultiIndex (:issue:`61009`)
 - Bug in :meth:`MultiIndex.from_tuples` causing wrong output with input of type tuples having NaN values (:issue:`60695`, :issue:`60988`)
-- Bug in :meth:`DataFrame.reindex` where reindexing a Dataframe with a named Index to a MultiIndex would incorrectly set all values to ``NaN``. Now correctly preserves values when the source index name matches a target level name (:issue:`60923`)
-- Bug in :meth:`Series.reindex` where reindexing a Series with a named Index to a MultiIndex would incorrectly set all values to ``NaN``. Now correctly preserves values when the source index name matches a target level name (:issue:`60923`)
+- Bug in :meth:`DataFrame.reindex` and :meth:`Series.reindex` where reindexing :class:`Index` to a :class:`MultiIndex` would incorrectly set all values to ``NaN``.(:issue:`60923`)
 
 I/O
 ^^^

pandas/core/generic.py

@@ -5373,6 +5373,18 @@ def reindex(
         """
         # TODO: Decide if we care about having different examples for different
         # kinds
+
+        # Automatically detect matching level when reindexing from Index to MultiIndex.
+        # This prevents values from being incorrectly set to NaN when the source index
+        # name matches a index name in the target MultiIndex
+        if (
+            level is None
+            and index is not None
+            and isinstance(index, MultiIndex)
+            and not isinstance(self.index, MultiIndex)
+            and self.index.name in index.names
+        ):
+            level = self.index.name
         self._check_copy_deprecation(copy)
 
         if index is not None and columns is not None and labels is not None:

pandas/core/series.py

@@ -4886,15 +4886,6 @@ def reindex(  # type: ignore[override]
         limit: int | None = None,
         tolerance=None,
     ) -> Series:
-        # Automatically detect matching level when reindexing from Index to MultiIndex.
-        # This prevents values from being incorrectly set to NaN when the source index
-        # name matches a level name in the target MultiIndex
-        if (
-            level is None
-            and isinstance(index, MultiIndex)
-            and self.index.name in index.names
-        ):
-            level = self.index.name
         return super().reindex(
             index=index,
             method=method,

pandas/tests/frame/methods/test_reindex.py

@@ -1260,53 +1260,26 @@ def test_invalid_method(self):
             df.reindex([1, 0, 2], method="asfreq")
 
     def test_reindex_index_name_matches_multiindex_level(self):
-        """
-        Test automatic level detection when reindexing from Index to MultiIndex.
-        When source index name matches a level name in target MultiIndex and level
-        is not specified, should behave same as if level was explicitly set.
-        """
-        # Create source DataFrame with named Index
         df = DataFrame(
             {"value": [1, 2], "other": ["A", "B"]},
             index=Index([10, 20], name="a"),
         )
-
-        # Create target MultiIndex with matching level name
         target = MultiIndex.from_product(
             [[10, 20], ["x", "y"]],
-            names=["a", "b"],  # 'a' matches source index name
+            names=["a", "b"],
         )
 
         result = df.reindex(index=target)
         expected = df.reindex(index=target, level="a")
-
         tm.assert_frame_equal(result, expected)
 
-        # Verify values are propagated correctly
-        expected_values = {
-            (10, "x"): {"value": 1, "other": "A"},
-            (10, "y"): {"value": 1, "other": "A"},
-            (20, "x"): {"value": 2, "other": "B"},
-            (20, "y"): {"value": 2, "other": "B"},
-        }
-        for idx, expected_row in expected_values.items():
-            for col, val in expected_row.items():
-                assert result.loc[idx, col] == val
-
     def test_reindex_index_name_no_match_multiindex_level(self):
-        """
-        Test reindexing behavior when source index name doesn't match any level
-        in target MultiIndex. Should fill with NaN since there's no level match.
-        """
         df = DataFrame({"value": [1, 2]}, index=Index([10, 20], name="different_name"))
-
         target = MultiIndex.from_product([[10, 20], ["x", "y"]], names=["a", "b"])
 
         result = df.reindex(index=target)
-
-        # Should fill with NaN since no level match
-        assert result.isna().all().all()
-
-        # Verify shape is correct
-        assert result.index.equals(target)
-        assert result.columns.equals(df.columns)
+        expected = DataFrame(
+            {"value": [np.nan] * 4},
+            index=MultiIndex.from_product([[10, 20], ["x", "y"]], names=["a", "b"]),
+        )
+        tm.assert_frame_equal(result, expected)

pandas/tests/series/methods/test_reindex.py

@@ -439,18 +439,12 @@ def test_reindex_expand_nonnano_nat(dtype):
 @pytest.mark.parametrize(
     "name, expected_match_level_a",
     [
-        # Source index has matching name - should match level "a"
         ("a", True),
-        # Source index has no name - should not match any level
         (None, False),
-        # Source index name doesn't match any level - should not match
         ("x", False),
     ],
 )
 def test_reindex_multiindex_automatic_level(name, expected_match_level_a):
-    """
-    Test automatic level detection when reindexing from Index to MultiIndex.
-    """
     series = Series([26.73, 24.255], index=Index([81, 82], name=name))
     target = MultiIndex.from_product(
         [[81, 82], [np.nan], ["2018-06-01", "2018-07-01"]], names=["a", "b", "c"]
@@ -459,19 +453,14 @@ def test_reindex_multiindex_automatic_level(name, expected_match_level_a):
     result = series.reindex(target)
 
     if expected_match_level_a:
-        # Should match behavior of explicit level="a"
         expected = series.reindex(target, level="a")
     else:
-        # Should contain all NaN values
         expected = Series(np.nan, index=target, dtype=series.dtype)
 
     tm.assert_series_equal(result, expected)
 
 
 def test_reindex_multiindex_explicit_level_overrides():
-    """
-    Test that explicit level parameter overrides automatic detection.
-    """
     series = Series([26.73, 24.255], index=Index([81, 82], name="a"))
     target = MultiIndex.from_product(
         [[81, 82], [np.nan], ["2018-06-01", "2018-07-01"]], names=["a", "b", "c"]