REGR: Fix fillna making a copy when dict was given as fill value and inplace is set

doc/source/whatsnew/v1.4.3.rst

@@ -16,6 +16,7 @@ Fixed regressions
 ~~~~~~~~~~~~~~~~~
 - Fixed regression in :meth:`DataFrame.replace` when the replacement value was explicitly ``None`` when passed in a dictionary to ``to_replace`` also casting other columns to object dtype even when there were no values to replace (:issue:`46634`)
 - Fixed regression when setting values with :meth:`DataFrame.loc` updating :class:`RangeIndex` when index was set as new column and column was updated afterwards (:issue:`47128`)
+- Fixed regression in :meth:`DataFrame.fillna` creating a copy when a dictionary was given as a fill value (:issue:`47188`)
 - Fixed regression in :meth:`DataFrame.nsmallest` led to wrong results when ``np.nan`` in the sorting column (:issue:`46589`)
 - Fixed regression in :func:`read_fwf` raising ``ValueError`` when ``widths`` was specified with ``usecols`` (:issue:`46580`)
 - Fixed regression in :func:`concat` not sorting columns for mixed column names (:issue:`47127`)

pandas/core/generic.py

@@ -6521,7 +6521,9 @@ def fillna(
                     if k not in result:
                         continue
                     downcast_k = downcast if not is_dict else downcast.get(k)
-                    result[k] = result[k].fillna(v, limit=limit, downcast=downcast_k)
+                    result.loc[:, k] = result[k].fillna(
+                        v, limit=limit, downcast=downcast_k
+                    )
                 return result if not inplace else None
 
             elif not is_list_like(value):

pandas/tests/frame/methods/test_fillna.py

@@ -673,6 +673,16 @@ def test_fillna_inplace_with_columns_limit_and_value(self):
         df.fillna(axis=1, value=100, limit=1, inplace=True)
         tm.assert_frame_equal(df, expected)
 
+    @pytest.mark.parametrize("val", [-1, {"x": -1, "y": -1}])
+    def test_inplace_dict_update_view(self, val):
+        # GH#47188
+        df = DataFrame({"x": [np.nan, 2], "y": [np.nan, 2]})
+        result_view = df["x"]
+        df.fillna(val, inplace=True)
+        expected = DataFrame({"x": [-1, 2.0], "y": [-1.0, 2]})
+        tm.assert_frame_equal(df, expected)
+        tm.assert_series_equal(result_view, expected["x"])
+
 
 def test_fillna_nonconsolidated_frame():
     # https://github.com/pandas-dev/pandas/issues/36495