def _aggregate_series_fast(self, obj: Series, func):
# At this point we have already checked that
# - obj.index is not a MultiIndex
# - obj is backed by an ndarray, not ExtensionArray
# - len(obj) > 0
# - ngroups != 0
func = self._is_builtin_func(func)
group_index, _, ngroups = self.group_info
# avoids object / Series creation overhead
dummy = obj._get_values(slice(None, 0))
indexer = get_group_index_sorter(group_index, ngroups)
obj = obj.take(indexer)
group_index = algorithms.take_nd(group_index, indexer, allow_fill=False)
grouper = libreduction.SeriesGrouper(obj, func, group_index, ngroups, dummy)
result, counts = grouper.get_result()
return result, counts
def _chop(self, sdata: Series, slice_obj: slice) -> Series:
return sdata._get_values(slice_obj)
