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)