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REF: remove aggregate_item_by_item #51222

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Merged
merged 1 commit into from
Feb 8, 2023
Merged

REF: remove aggregate_item_by_item #51222

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16 changes: 0 additions & 16 deletions pandas/core/groupby/generic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1378,22 +1378,6 @@ def _aggregate_frame(self, func, *args, **kwargs) -> DataFrame:

return out

def _aggregate_item_by_item(self, func, *args, **kwargs) -> DataFrame:
# only for axis==0
# tests that get here with non-unique cols:
# test_resample_with_timedelta_yields_no_empty_groups,
# test_resample_apply_product

obj = self._obj_with_exclusions
result: dict[int, NDFrame] = {}

for i, (item, sgb) in enumerate(self._iterate_column_groupbys(obj)):
result[i] = sgb.aggregate(func, *args, **kwargs)

res_df = self.obj._constructor(result)
res_df.columns = obj.columns
return res_df

def _wrap_applied_output(
self,
data: DataFrame,
Expand Down
17 changes: 6 additions & 11 deletions pandas/core/resample.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,10 +40,7 @@
npt,
)
from pandas.compat.numpy import function as nv
from pandas.errors import (
AbstractMethodError,
DataError,
)
from pandas.errors import AbstractMethodError
from pandas.util._decorators import (
Appender,
Substitution,
Expand Down Expand Up @@ -423,15 +420,13 @@ def _groupby_and_aggregate(self, how, *args, **kwargs):
)

try:
if isinstance(obj, ABCDataFrame) and callable(how):
# Check if the function is reducing or not.
# e.g. test_resample_apply_with_additional_args
result = grouped._aggregate_item_by_item(how, *args, **kwargs)
if callable(how):
# TODO: test_resample_apply_with_additional_args fails if we go
# through the non-lambda path, not clear that it should.
func = lambda x: how(x, *args, **kwargs)
result = grouped.aggregate(func)
else:
result = grouped.aggregate(how, *args, **kwargs)
except DataError:
# got TypeErrors on aggregation
result = grouped.apply(how, *args, **kwargs)
except (AttributeError, KeyError):
# we have a non-reducing function; try to evaluate
# alternatively we want to evaluate only a column of the input
Expand Down