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CLN: remove _recast_datetimelike_result #38156

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Merged
merged 1 commit into from
Nov 30, 2020
Merged

CLN: remove _recast_datetimelike_result #38156

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40 changes: 1 addition & 39 deletions pandas/core/groupby/generic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -46,7 +46,6 @@
is_integer_dtype,
is_interval_dtype,
is_numeric_dtype,
is_object_dtype,
is_scalar,
needs_i8_conversion,
)
Expand Down Expand Up @@ -1283,7 +1282,7 @@ def _wrap_applied_output_series(
# as we are stacking can easily have object dtypes here
so = self._selected_obj
if so.ndim == 2 and so.dtypes.apply(needs_i8_conversion).any():
result = _recast_datetimelike_result(result)
result = result._convert(datetime=True)
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.apply(to_datetime) ?

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we only want to do it on object-dtype columns which is what _convert does

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kk cool, then this is fine. ping on green.

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ping

else:
result = result._convert(datetime=True)

Expand Down Expand Up @@ -1836,40 +1835,3 @@ def nunique(self, dropna: bool = True) -> DataFrame:
return results

boxplot = boxplot_frame_groupby


def _recast_datetimelike_result(result: DataFrame) -> DataFrame:
"""
If we have date/time like in the original, then coerce dates
as we are stacking can easily have object dtypes here.

Parameters
----------
result : DataFrame

Returns
-------
DataFrame

Notes
-----
- Assumes Groupby._selected_obj has ndim==2 and at least one
datetimelike column
"""
result = result.copy()

obj_cols = [
idx
for idx in range(len(result.columns))
if is_object_dtype(result.dtypes.iloc[idx])
]

# See GH#26285
for n in obj_cols:
values = result.iloc[:, n].values
converted = lib.maybe_convert_objects(
values, convert_datetime=True, convert_timedelta=True
)

result.iloc[:, n] = converted
return result