BUG: DataFrame.loc not aligning dict when setting to a column

Author: phofl

doc/source/whatsnew/v1.5.0.rst

@@ -821,6 +821,7 @@ Indexing
 - Bug in :meth:`loc.__setitem__` treating ``range`` keys as positional instead of label-based (:issue:`45479`)
 - Bug in :meth:`Series.__setitem__` when setting ``boolean`` dtype values containing ``NA`` incorrectly raising instead of casting to ``boolean`` dtype (:issue:`45462`)
 - Bug in :meth:`Series.__setitem__` where setting :attr:`NA` into a numeric-dtpye :class:`Series` would incorrectly upcast to object-dtype rather than treating the value as ``np.nan`` (:issue:`44199`)
+- Bug in :meth:`DataFrame.loc` when setting values to a column and right hand side is a dictionary (:issue:`47216`)
 - Bug in :meth:`Series.__setitem__` with ``datetime64[ns]`` dtype, an all-``False`` boolean mask, and an incompatible value incorrectly casting to ``object`` instead of retaining ``datetime64[ns]`` dtype (:issue:`45967`)
 - Bug in :meth:`Index.__getitem__`  raising ``ValueError`` when indexer is from boolean dtype with ``NA`` (:issue:`45806`)
 - Bug in :meth:`Series.mask` with ``inplace=True`` or setting values with a boolean mask with small integer dtypes incorrectly raising (:issue:`45750`)

pandas/core/frame.py

@@ -4699,6 +4699,8 @@ def _sanitize_column(self, value) -> ArrayLike:
         # We should never get here with DataFrame value
         if isinstance(value, Series):
             return _reindex_for_setitem(value, self.index)
+        elif isinstance(value, dict):
+            return _reindex_for_setitem(Series(value), self.index)
 
         if is_list_like(value):
             com.require_length_match(value, self.index)

pandas/tests/frame/indexing/test_setitem.py

@@ -702,6 +702,15 @@ def test_setitem_npmatrix_2d(self):
 
         tm.assert_frame_equal(df, expected)
 
+    @pytest.mark.parametrize("vals", [{}, {"d": "a"}])
+    def test_setitem_aligning_dict_with_index(self, vals):
+        # GH#47216
+        df = DataFrame({"a": [1, 2], "b": [3, 4], **vals})
+        df.loc[:, "a"] = {1: 100, 0: 200}
+        df.loc[:, "c"] = {0: 5, 1: 6}
+        expected = DataFrame({"a": [200, 100], "b": [3, 4], **vals, "c": [5, 6]})
+        tm.assert_frame_equal(df, expected)
+
 
 class TestSetitemTZAwareValues:
     @pytest.fixture