Re-evaluate the obj with a groupby aggregation.
(self, how, *args, **kwargs)
| 530 | return grouped |
| 531 | |
| 532 | def _groupby_and_aggregate(self, how, *args, **kwargs): |
| 533 | """ |
| 534 | Re-evaluate the obj with a groupby aggregation. |
| 535 | """ |
| 536 | grouper = self._grouper |
| 537 | |
| 538 | # Excludes `on` column when provided |
| 539 | obj = self._obj_with_exclusions |
| 540 | |
| 541 | grouped = get_groupby(obj, by=None, grouper=grouper, group_keys=self.group_keys) |
| 542 | |
| 543 | try: |
| 544 | if callable(how): |
| 545 | # TODO: test_resample_apply_with_additional_args fails if we go |
| 546 | # through the non-lambda path, not clear that it should. |
| 547 | func = lambda x: how(x, *args, **kwargs) |
| 548 | result = grouped.aggregate(func) |
| 549 | else: |
| 550 | result = grouped.aggregate(how, *args, **kwargs) |
| 551 | except (AttributeError, KeyError): |
| 552 | # we have a non-reducing function; try to evaluate |
| 553 | # alternatively we want to evaluate only a column of the input |
| 554 | |
| 555 | # test_apply_to_one_column_of_df the function being applied references |
| 556 | # a DataFrame column, but aggregate_item_by_item operates column-wise |
| 557 | # on Series, raising AttributeError or KeyError |
| 558 | # (depending on whether the column lookup uses getattr/__getitem__) |
| 559 | result = grouped.apply(how, *args, **kwargs) |
| 560 | |
| 561 | except ValueError as err: |
| 562 | if "Must produce aggregated value" in str(err): |
| 563 | # raised in _aggregate_named |
| 564 | # see test_apply_without_aggregation, test_apply_with_mutated_index |
| 565 | pass |
| 566 | else: |
| 567 | raise |
| 568 | |
| 569 | # we have a non-reducing function |
| 570 | # try to evaluate |
| 571 | result = grouped.apply(how, *args, **kwargs) |
| 572 | |
| 573 | return self._wrap_result(result) |
| 574 | |
| 575 | @final |
| 576 | def _get_resampler_for_grouping( |
no test coverage detected