fix(frame): ensure proper name attribute when setting new column with scalar value

- Address issue where name attribute was lost when setting new column with scalar value and tuple key in MultiIndex DataFrame
- Implement check for tuple key and scalar value in MultiIndex DataFrame
- Create Series with proper name to ensure name attribute matches the key
- Update test case to assert Series name in scalar assignment with MultiIndex

Author: MengAiDev

pandas/core/frame.py

@@ -4517,7 +4517,20 @@ def _set_item(self, key, value) -> None:
         Series/TimeSeries will be conformed to the DataFrames index to
         ensure homogeneity.
         """
-        value, refs = self._sanitize_column(value)
+        # Check if we're setting a new column with a tuple key in a MultiIndex DataFrame
+        # and the value is a scalar. In this case, we need to create a Series with the
+        # proper name to ensure the name attribute matches the key.
+        if (
+            isinstance(key, tuple)
+            and isinstance(self.columns, MultiIndex)
+            and not is_list_like(value)
+            and key not in self.columns
+        ):
+            # Create a Series with the proper name
+            value = Series([value] * len(self.index), index=self.index, name=key)
+            value, refs = self._sanitize_column(value)
+        else:
+            value, refs = self._sanitize_column(value)
 
         if (
             key in self.columns

pandas/tests/frame/indexing/test_setitem.py

@@ -653,10 +653,12 @@ def test_setitem_multiindex_scalar_indexer(self):
         # Test scalar assignment with 3-level MultiIndex
         df_3level[("Z", "C", "3")] = 42
         assert ("Z", "C", "3") in df_3level.columns
-        tm.assert_series_equal(df_3level[("Z", "C", "3")], Series([42, 42, 42, 42]))
+        tm.assert_series_equal(
+            df_3level[("Z", "C", "3")], Series([42, 42, 42, 42], name=("Z", "C", "3"))
+        )
 
         # Test Series assignment with 3-level MultiIndex
-        new_series = Series([1, 2, 3, 4])
+        new_series = Series([1, 2, 3, 4], name=("W", "D", "4"))
         df_3level[("W", "D", "4")] = new_series
         tm.assert_series_equal(df_3level[("W", "D", "4")], new_series)