REGR: fillna not filling NaNs after pivot without explicitly listing pivot values

doc/source/whatsnew/v1.1.3.rst

@@ -34,6 +34,7 @@ Fixed regressions
 - Fixed regression when adding a :meth:`timedelta_range` to a :class:``Timestamp`` raised an ``ValueError`` (:issue:`35897`)
 - Fixed regression in :meth:`Series.__getitem__` incorrectly raising when the input was a tuple (:issue:`35534`)
 - Fixed regression in :meth:`Series.__getitem__` incorrectly raising when the input was a frozenset (:issue:`35747`)
+- Fixed regression where :meth:`DataFrame.fillna` not filling ``NaN`` after :meth:`DataFrame.pivot` operation (:issue:`36495`)
 - Fixed regression in :meth:`read_excel` with ``engine="odf"`` caused ``UnboundLocalError`` in some cases where cells had nested child nodes (:issue:`36122`, :issue:`35802`)
 - Fixed regression in :meth:`DataFrame.replace` inconsistent replace when using a float in the replace method (:issue:`35376`)
 - Fixed regression in :class:`DataFrame` and :class:`Series` comparisons between numeric arrays and strings (:issue:`35700`, :issue:`36377`)

pandas/core/internals/managers.py

@@ -372,6 +372,8 @@ def apply(
         result_blocks: List[Block] = []
         # fillna: Series/DataFrame is responsible for making sure value is aligned
 
+        self._consolidate_inplace()
+
         aligned_args = {k: kwargs[k] for k in align_keys}
 
         for b in self.blocks:

pandas/tests/frame/test_missing.py

@@ -718,3 +718,31 @@ def test_fill_corner(self, float_frame, float_string_frame):
 
         # TODO(wesm): unused?
         result = empty_float.fillna(value=0)  # noqa
+
+    def test_fillna_after_pivot(self):
+        # https://github.com/pandas-dev/pandas/issues/36495
+        df = DataFrame(
+            [
+                [1, 1, 1, 1.0],
+                [2, 2, 2, 2.0],
+                [3, 3, 3, 3.0],
+            ],
+            columns=["i1", "i2", "i3", "f1"],
+        )
+
+        result = df.pivot("i1", "i2").fillna(0)
+
+        expected = DataFrame(
+            [
+                [1.0, 0.0, 0.0, 1.0, 0.0, 0.0],
+                [0.0, 2.0, 0.0, 0.0, 2.0, 0.0],
+                [0.0, 0.0, 3.0, 0.0, 0.0, 3.0],
+            ],
+            index=pd.Int64Index([1, 2, 3], dtype="int64", name="i1"),
+            columns=pd.MultiIndex.from_tuples(
+                [("i3", 1), ("i3", 2), ("i3", 3), ("f1", 1), ("f1", 2), ("f1", 3)],
+                names=[None, "i2"],
+            ),
+        )
+
+        tm.assert_frame_equal(result, expected)