addressing comments

doc/source/whatsnew/v1.1.0.rst

@@ -1081,8 +1081,7 @@ Groupby/resample/rolling
 - Bug in :meth:`DataFrame.ewm.cov` was throwing ``AssertionError`` for :class:`MultiIndex` inputs (:issue:`34440`)
 - Bug in :meth:`core.groupby.DataFrameGroupBy.transform` when ``func='nunique'`` and columns are of type ``datetime64``, the result would also be of type ``datetime64`` instead of ``int64`` (:issue:`35109`)
 - Bug in :meth:'DataFrameGroupBy.first' and :meth:'DataFrameGroupBy.last' that would raise an unnecessary ``ValueError`` when grouping on multiple ``Categoricals`` (:issue:`34951`)
-- Bug in :meth:`DataFrameGroupBy.count` was returning ``NaN`` for missing categories when grouped on multiple ``Categoricals``. Now returning ``0`` (:issue:`35028`)
-- Bug in :meth:`DataFrameGroupBy.sum` and :meth:`SeriesGroupBy.sum` was reutrning ``NaN`` for missing categories when grouped on multiple ``Categorials``. Now returning ``0`` (:issue:`31422`)
+- Bug in :meth:`DataFrameGroupBy.count` and :meth:`GroupBy.sum` returning ``NaN`` for missing categories when grouped on multiple ``Categoricals``. Now returning ``0`` (:issue:`35028`)
 
 
 Reshaping
@@ -1118,8 +1117,7 @@ Reshaping
 - Bug in :meth:`Series.where` with an empty Series and empty ``cond`` having non-bool dtype (:issue:`34592`)
 - Fixed regression where :meth:`DataFrame.apply` would raise ``ValueError`` for elements whth ``S`` dtype (:issue:`34529`)
 - Bug in :meth:`DataFrame.append` leading to sorting columns even when ``sort=False`` is specified (:issue:`35092`)
-- Bug in :meth:`DataFrame.pivot_table` with ``aggfunc='count'``, was returning ``NaN`` for missing categories when pivoted on a ``Categorical``. Now returning ``0`` (:issue:`35028`)
-- Bug in :meth:`DataFrame.pivot_table` with ``aggfunc='sum'``, was reutrning ``NaN`` for missing categories when pivoted on a ``Categorical``. Now returning ``0`` (:issue:`31422`)
+- Bug in :meth:`DataFrame.pivot_table` with ``aggfunc='count'`` or ``aggfunc='sum'`` returning ``NaN`` for missing categories when pivoted on a ``Categorical``. Now returning ``0`` (:issue:`31422`)
 
 Sparse
 ^^^^^^

pandas/core/groupby/generic.py

@@ -70,7 +70,6 @@
  GroupBy,
  _agg_template,
  _apply_docs,
- _observed_is_true,
  _transform_template,
  get_groupby,
 )
@@ -1833,7 +1832,7 @@ def count(self):
  # _wrap_agged_blocks() returns. We set self.observed=True for the call to
  # _wrap_agged_blocks() to avoid it reindexing. We then reindex below with
  # fill_value=0. See GH 35028
- with _observed_is_true(self):
+ with com.temp_setattr(self, "observed", True):
  result = self._wrap_agged_blocks(blocks, items=data.items)
 
  return self._reindex_output(result, fill_value=0)

pandas/core/groupby/groupby.py

@@ -464,17 +464,6 @@ def _group_selection_context(groupby):
  groupby._reset_group_selection()
 
 
-@contextmanager
-def _observed_is_true(groupby):
- """
- Set GroupBy.observed to True, then restore to original value
- """
- original_value = groupby.observed
- groupby.observed = True
- yield groupby
- groupby.observed = original_value
-
-
 _KeysArgType = Union[
  Hashable,
  List[Hashable],
@@ -1548,7 +1537,7 @@ def sum(self, numeric_only: bool = True, min_count: int = 0):
  # _agg_general() returns. We set self.observed=True for the call to
  # _agg_general() to avoid it reindexing. We then reindex below with
  # fill_value=0. See GH 31422
- with _observed_is_true(self):
+ with com.temp_setattr(self, "observed", True):
  result = self._agg_general(
  numeric_only=numeric_only,
  min_count=min_count,