def _groupby_and_aggregate(self, how, grouper=None, *args, **kwargs):
""" re-evaluate the obj with a groupby aggregation """
if grouper is None:
self._set_binner()
grouper = self.grouper
obj = self._selected_obj
try:
grouped = groupby(obj, by=None, grouper=grouper, axis=self.axis)
except TypeError:
# panel grouper
grouped = PanelGroupBy(obj, grouper=grouper, axis=self.axis)
try:
if isinstance(obj, ABCDataFrame) and compat.callable(how):
# Check if the function is reducing or not.
result = grouped._aggregate_item_by_item(how, *args, **kwargs)
else:
result = grouped.aggregate(how, *args, **kwargs)
except Exception:
# we have a non-reducing function
# try to evaluate
result = grouped.apply(how, *args, **kwargs)
result = self._apply_loffset(result)
return self._wrap_result(result)
def _groupby_and_aggregate(self, grouper, how, *args, **kwargs):
""" revaluate the obj with a groupby aggregation """
if grouper is None:
self._set_binner()
grouper = self.grouper
obj = self._selected_obj
try:
grouped = groupby(obj, by=None, grouper=grouper, axis=self.axis)
except TypeError:
# panel grouper
grouped = PanelGroupBy(obj, grouper=grouper, axis=self.axis)
try:
result = grouped.aggregate(how, *args, **kwargs)
except Exception:
# we have a non-reducing function
# try to evaluate
result = grouped.apply(how, *args, **kwargs)
return self._wrap_result(result)
def groupby(self, function, axis='major'):
"""
Group data on given axis, returning GroupBy object
Parameters
----------
function : callable
Mapping function for chosen access
axis : {'major', 'minor', 'items'}, default 'major'
Returns
-------
grouped : PanelGroupBy
"""
from pandas.core.groupby import PanelGroupBy
axis = self._get_axis_number(axis)
return PanelGroupBy(self, function, axis=axis)