REF: Compute correct result_index upfront in groupby

Author: rhshadrach

pandas/core/groupby/generic.py

@@ -416,7 +416,6 @@ def _wrap_applied_output(
  # GH #823 #24880
  index = self.grouper.result_index
  res_df = self.obj._constructor_expanddim(values, index=index)
- res_df = self._reindex_output(res_df)
  # if self.observed is False,
  # keep all-NaN rows created while re-indexing
  res_ser = res_df.stack(future_stack=True)
@@ -442,7 +441,7 @@ def _wrap_applied_output(
  if not self.as_index:
  result = self._insert_inaxis_grouper(result)
  result.index = default_index(len(result))
- return self._reindex_output(result)
+ return result
 
  def _aggregate_named(self, func, *args, **kwargs):
  # Note: this is very similar to _aggregate_series_pure_python,
@@ -672,7 +671,7 @@ def nunique(self, dropna: bool = True) -> Series | DataFrame:
  2023-02-01 1
  Freq: MS, dtype: int64
  """
- ids, _, _ = self.grouper.group_info
+ ids, _ = self.grouper.group_info
 
  val = self.obj._values
 
@@ -721,7 +720,7 @@ def nunique(self, dropna: bool = True) -> Series | DataFrame:
  if not self.as_index:
  result = self._insert_inaxis_grouper(result)
  result.index = default_index(len(result))
- return self._reindex_output(result, fill_value=0)
+ return result
 
  @doc(Series.describe)
  def describe(self, percentiles=None, include=None, exclude=None) -> Series:
@@ -749,7 +748,7 @@ def value_counts(
  from pandas.core.reshape.merge import get_join_indexers
  from pandas.core.reshape.tile import cut
 
- ids, _, _ = self.grouper.group_info
+ ids, _ = self.grouper.group_info
  val = self.obj._values
 
  index_names = self.grouper.names + [self.obj.name]
@@ -819,9 +818,18 @@ def value_counts(
  rep = partial(np.repeat, repeats=np.add.reduceat(inc, idx))
 
  # multi-index components
- codes = self.grouper.reconstructed_codes
+ if isinstance(self.grouper.result_index, MultiIndex):
+ codes = list(self.grouper.result_index.codes)
+ else:
+ codes = [
+ algorithms.factorize(
+ self.grouper.result_index,
+ sort=self.grouper._sort,
+ use_na_sentinel=self.grouper.dropna,
+ )[0]
+ ]
  codes = [rep(level_codes) for level_codes in codes] + [llab(lab, inc)]
- levels = [ping.group_index for ping in self.grouper.groupings] + [lev]
+ levels = self.grouper.levels + [lev]
 
  if dropna:
  mask = codes[-1] != -1
@@ -1686,7 +1694,7 @@ def _wrap_applied_output_series(
  if not self.as_index:
  result = self._insert_inaxis_grouper(result)
 
- return self._reindex_output(result)
+ return result
 
  def _cython_transform(
  self,