From e4a637a9a96a0a7f223e2192f7ac9dbe2ba52eed Mon Sep 17 00:00:00 2001 From: Brock Date: Sun, 29 Nov 2020 11:13:50 -0800 Subject: [PATCH] CLN: remove _recast_datetimelike_result --- pandas/core/groupby/generic.py | 40 +--------------------------------- 1 file changed, 1 insertion(+), 39 deletions(-) diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py index b9226732d5a69..d35e6f900b87f 100644 --- a/pandas/core/groupby/generic.py +++ b/pandas/core/groupby/generic.py @@ -46,7 +46,6 @@ is_integer_dtype, is_interval_dtype, is_numeric_dtype, - is_object_dtype, is_scalar, needs_i8_conversion, ) @@ -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) else: result = result._convert(datetime=True) @@ -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