def agg_series(self, obj: Series, func: F):
# Caller is responsible for checking ngroups != 0
assert self.ngroups != 0
assert len(
self.bins) > 0 # otherwise we'd get IndexError in get_result
if is_extension_array_dtype(obj.dtype):
# preempt SeriesBinGrouper from raising TypeError
return self._aggregate_series_pure_python(obj, func)
dummy = obj[:0]
grouper = libreduction.SeriesBinGrouper(obj, func, self.bins, dummy)
return grouper.get_result()
def _aggregate_series_fast(self, obj, func):
# At this point we have already checked that obj.index is not a MultiIndex
# and that obj is backed by an ndarray, not ExtensionArray
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 _aggregate_series_fast(self, obj: Series, func: F):
# 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
indexer = get_group_index_sorter(group_index, ngroups)
obj = obj.take(indexer)
group_index = group_index.take(indexer)
grouper = libreduction.SeriesGrouper(obj, func, group_index, ngroups)
result, counts = grouper.get_result()
return result, counts
