BUG: DataFrame loc set incorrectly aligns on scalar column assignment…

doc/source/whatsnew/v3.1.0.rst

@@ -303,6 +303,7 @@ Indexing
 - Bug in :meth:`DataFrame.loc` and :meth:`Series.loc` replacing the index name with the key's name when indexing with an :class:`Index` (:issue:`17110`)
 - Bug in :meth:`DataFrame.loc` raising ``ValueError`` when setting a row on a :class:`DataFrame` with no columns and the label is not in the index (:issue:`17895`)
 - Bug in :meth:`DataFrame.loc` returning incorrect dtype when the column key is a ``slice`` (:issue:`63071`)
+- Bug in :meth:`DataFrame.loc` where setting a scalar column with a :class:`DataFrame` value failed to align indices properly (:issue:`58482`)
 - Bug in :meth:`Index.get_indexer` where ``method="pad"``, ``"backfill"``, or ``"nearest"`` returned incorrect results when the target contained ``NaT`` or ``NaN`` instead of ``-1`` (:issue:`32572`)
 - Bugs in setitem-with-expansion when adding new rows failing to keep the original dtype in some cases (:issue:`32346`, :issue:`15231`, :issue:`47503`, :issue:`6485`, :issue:`25383`, :issue:`52235`, :issue:`17026`, :issue:`56010`)
 - Bug in :meth:`DataFrame.__getitem__` raising ``InvalidIndexError`` when indexing with a tuple containing a ``slice`` on a :class:`DataFrame` with :class:`MultiIndex` columns (e.g., ``df[:, "t1"]``) (:issue:`26511`)

pandas/core/indexing.py

@@ -2834,6 +2834,24 @@ def _setitem_single_block(self, indexer, value, name: str) -> None:
 
         info_axis = self.obj._info_axis_number
         item_labels = self.obj._get_axis(info_axis)
+
+        if isinstance(indexer, tuple):
+            indexer = maybe_convert_ix(*indexer)  # e.g. test_setitem_frame_align
+
+        if isinstance(value, ABCDataFrame) and name != "iloc":
+            if (
+                isinstance(indexer, tuple)
+                and self.ndim == len(indexer) == 2
+                and is_integer(indexer[info_axis])
+            ):
+                col = item_labels[indexer[info_axis]]
+                if col in value.columns:
+                    value = self._align_series(indexer, value[col])
+                else:
+                    value = np.nan
+            else:
+                value = self._align_frame(indexer, value)._values
+
         if isinstance(indexer, tuple):
             # if we are setting on the info axis ONLY
             # set using those methods to avoid block-splitting
@@ -2850,11 +2868,6 @@ def _setitem_single_block(self, indexer, value, name: str) -> None:
                     self._setitem_single_column(loc, value, indexer[0])
                     return
 
-            indexer = maybe_convert_ix(*indexer)  # e.g. test_setitem_frame_align
-
-        if isinstance(value, ABCDataFrame) and name != "iloc":
-            value = self._align_frame(indexer, value)._values
-
         # actually do the set
         self.obj._mgr = self.obj._mgr.setitem(indexer=indexer, value=value)
 

pandas/tests/indexing/test_loc.py

@@ -1514,13 +1514,9 @@ def test_loc_setitem_datetimeindex_tz(self, idxer, tz_naive_fixture):
         # if result started off with object dtype, then the .loc.__setitem__
         #  below would retain object dtype
         result = DataFrame(index=idx, columns=["var"], dtype=np.float64)
-        if idxer == "var":
-            with pytest.raises(TypeError, match="Invalid value"):
-                result.loc[:, idxer] = expected
-        else:
-            # See https://github.com/pandas-dev/pandas/issues/56223
-            result.loc[:, idxer] = expected
-            tm.assert_frame_equal(result, expected)
+        # See https://github.com/pandas-dev/pandas/issues/56223
+        result.loc[:, idxer] = expected
+        tm.assert_frame_equal(result, expected)
 
     def test_loc_setitem_time_key(self):
         index = date_range("2012-01-01", "2012-01-05", freq="30min")
@@ -3755,3 +3751,18 @@ def test_loc_setitem_extension_array_into_object_series():
     ser.loc[:] = arr
     expected = Series(list(arr), dtype=object)
     tm.assert_series_equal(ser, expected)
+
+
+class TestLocSetitemDataFrameAlignment:
+    def test_loc_setitem_scalar_column_dataframe_alignment(self):
+        # GH 58482
+        df = DataFrame([[1.0, 2], [3.0, 4]], index=["x", "y"], columns=["A", "B"])
+        item = DataFrame([100], columns=["A"], index=["v"])
+
+        # Setting a single block dataframe's column with a dataframe should align
+        df.loc[:, "A"] = item
+
+        expected = DataFrame(
+            [[np.nan, 2], [np.nan, 4]], index=["x", "y"], columns=["A", "B"]
+        )
+        tm.assert_frame_equal(df, expected)