diff --git a/ci/code_checks.sh b/ci/code_checks.sh index a9967dcb8efe6..52d236ae7460d 100755 --- a/ci/code_checks.sh +++ b/ci/code_checks.sh @@ -682,60 +682,40 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then -i "pandas.core.groupby.DataFrameGroupBy.__iter__ RT03,SA01" \ -i "pandas.core.groupby.DataFrameGroupBy.agg RT03" \ -i "pandas.core.groupby.DataFrameGroupBy.aggregate RT03" \ - -i "pandas.core.groupby.DataFrameGroupBy.apply RT03" \ -i "pandas.core.groupby.DataFrameGroupBy.boxplot PR07,RT03,SA01" \ - -i "pandas.core.groupby.DataFrameGroupBy.cummax RT03" \ - -i "pandas.core.groupby.DataFrameGroupBy.cummin RT03" \ - -i "pandas.core.groupby.DataFrameGroupBy.cumprod RT03" \ - -i "pandas.core.groupby.DataFrameGroupBy.cumsum RT03" \ - -i "pandas.core.groupby.DataFrameGroupBy.filter RT03,SA01" \ + -i "pandas.core.groupby.DataFrameGroupBy.filter SA01" \ -i "pandas.core.groupby.DataFrameGroupBy.get_group RT03,SA01" \ -i "pandas.core.groupby.DataFrameGroupBy.groups SA01" \ -i "pandas.core.groupby.DataFrameGroupBy.hist RT03" \ -i "pandas.core.groupby.DataFrameGroupBy.indices SA01" \ -i "pandas.core.groupby.DataFrameGroupBy.max SA01" \ - -i "pandas.core.groupby.DataFrameGroupBy.mean RT03" \ -i "pandas.core.groupby.DataFrameGroupBy.median SA01" \ -i "pandas.core.groupby.DataFrameGroupBy.min SA01" \ -i "pandas.core.groupby.DataFrameGroupBy.nth PR02" \ - -i "pandas.core.groupby.DataFrameGroupBy.nunique RT03,SA01" \ + -i "pandas.core.groupby.DataFrameGroupBy.nunique SA01" \ -i "pandas.core.groupby.DataFrameGroupBy.ohlc SA01" \ -i "pandas.core.groupby.DataFrameGroupBy.plot PR02,SA01" \ -i "pandas.core.groupby.DataFrameGroupBy.prod SA01" \ - -i "pandas.core.groupby.DataFrameGroupBy.rank RT03" \ - -i "pandas.core.groupby.DataFrameGroupBy.resample RT03" \ -i "pandas.core.groupby.DataFrameGroupBy.sem SA01" \ - -i "pandas.core.groupby.DataFrameGroupBy.skew RT03" \ -i "pandas.core.groupby.DataFrameGroupBy.sum SA01" \ - -i "pandas.core.groupby.DataFrameGroupBy.transform RT03" \ -i "pandas.core.groupby.SeriesGroupBy.__iter__ RT03,SA01" \ -i "pandas.core.groupby.SeriesGroupBy.agg RT03" \ -i "pandas.core.groupby.SeriesGroupBy.aggregate RT03" \ - -i "pandas.core.groupby.SeriesGroupBy.apply RT03" \ - -i "pandas.core.groupby.SeriesGroupBy.cummax RT03" \ - -i "pandas.core.groupby.SeriesGroupBy.cummin RT03" \ - -i "pandas.core.groupby.SeriesGroupBy.cumprod RT03" \ - -i "pandas.core.groupby.SeriesGroupBy.cumsum RT03" \ - -i "pandas.core.groupby.SeriesGroupBy.filter PR01,RT03,SA01" \ + -i "pandas.core.groupby.SeriesGroupBy.filter PR01,SA01" \ -i "pandas.core.groupby.SeriesGroupBy.get_group RT03,SA01" \ -i "pandas.core.groupby.SeriesGroupBy.groups SA01" \ -i "pandas.core.groupby.SeriesGroupBy.indices SA01" \ -i "pandas.core.groupby.SeriesGroupBy.is_monotonic_decreasing SA01" \ -i "pandas.core.groupby.SeriesGroupBy.is_monotonic_increasing SA01" \ -i "pandas.core.groupby.SeriesGroupBy.max SA01" \ - -i "pandas.core.groupby.SeriesGroupBy.mean RT03" \ -i "pandas.core.groupby.SeriesGroupBy.median SA01" \ -i "pandas.core.groupby.SeriesGroupBy.min SA01" \ -i "pandas.core.groupby.SeriesGroupBy.nth PR02" \ -i "pandas.core.groupby.SeriesGroupBy.ohlc SA01" \ -i "pandas.core.groupby.SeriesGroupBy.plot PR02,SA01" \ -i "pandas.core.groupby.SeriesGroupBy.prod SA01" \ - -i "pandas.core.groupby.SeriesGroupBy.rank RT03" \ - -i "pandas.core.groupby.SeriesGroupBy.resample RT03" \ -i "pandas.core.groupby.SeriesGroupBy.sem SA01" \ - -i "pandas.core.groupby.SeriesGroupBy.skew RT03" \ -i "pandas.core.groupby.SeriesGroupBy.sum SA01" \ - -i "pandas.core.groupby.SeriesGroupBy.transform RT03" \ -i "pandas.core.resample.Resampler.__iter__ RT03,SA01" \ -i "pandas.core.resample.Resampler.ffill RT03" \ -i "pandas.core.resample.Resampler.get_group RT03,SA01" \ diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py index 3b20b854b344e..c955e58d2960f 100644 --- a/pandas/core/groupby/generic.py +++ b/pandas/core/groupby/generic.py @@ -240,6 +240,7 @@ def apply(self, func, *args, **kwargs) -> Series: Returns ------- Series or DataFrame + A pandas object with the result of applying ``func`` to each group. See Also -------- @@ -600,6 +601,7 @@ def filter(self, func, dropna: bool = True, *args, **kwargs): Returns ------- Series + The filtered subset of the original Series. Notes ----- @@ -1078,6 +1080,7 @@ def skew( Returns ------- Series + Unbiased skew within groups. See Also -------- @@ -1939,6 +1942,7 @@ def filter(self, func, dropna: bool = True, *args, **kwargs) -> DataFrame: Returns ------- DataFrame + The filtered subset of the original DataFrame. Notes ----- @@ -2106,6 +2110,7 @@ def nunique(self, dropna: bool = True) -> DataFrame: Returns ------- nunique: DataFrame + Counts of unique elements in each position. Examples -------- @@ -2504,6 +2509,7 @@ def skew( Returns ------- DataFrame + Unbiased skew within groups. See Also -------- diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py index 0b61938d474b9..1e9b467bfb08c 100644 --- a/pandas/core/groupby/groupby.py +++ b/pandas/core/groupby/groupby.py @@ -333,6 +333,8 @@ class providing the base-class of operations. Returns ------- %(klass)s + %(klass)s with the same indexes as the original object filled + with transformed values. See Also -------- @@ -1550,6 +1552,7 @@ def apply(self, func, *args, include_groups: bool = True, **kwargs) -> NDFrameT: Returns ------- Series or DataFrame + A pandas object with the result of applying ``func`` to each group. See Also -------- @@ -2244,6 +2247,7 @@ def mean( Returns ------- pandas.Series or pandas.DataFrame + Mean of values within each group. Same object type as the caller. %(see_also)s Examples -------- @@ -3511,11 +3515,8 @@ def resample(self, rule, *args, include_groups: bool = True, **kwargs) -> Resamp Returns ------- - pandas.api.typing.DatetimeIndexResamplerGroupby, - pandas.api.typing.PeriodIndexResamplerGroupby, or - pandas.api.typing.TimedeltaIndexResamplerGroupby - Return a new groupby object, with type depending on the data - being resampled. + DatetimeIndexResampler, PeriodIndexResampler or TimdeltaResampler + Resampler object for the type of the index. See Also -------- @@ -4590,7 +4591,8 @@ def rank( Returns ------- - DataFrame with ranking of values within each group + DataFrame + The ranking of values within each group. %(see_also)s Examples -------- @@ -4662,6 +4664,7 @@ def cumprod(self, *args, **kwargs) -> NDFrameT: Returns ------- Series or DataFrame + Cumulative product for each group. Same object type as the caller. %(see_also)s Examples -------- @@ -4720,6 +4723,7 @@ def cumsum(self, *args, **kwargs) -> NDFrameT: Returns ------- Series or DataFrame + Cumulative sum for each group. Same object type as the caller. %(see_also)s Examples -------- @@ -4782,6 +4786,7 @@ def cummin( Returns ------- Series or DataFrame + Cumulative min for each group. Same object type as the caller. %(see_also)s Examples -------- @@ -4852,6 +4857,7 @@ def cummax( Returns ------- Series or DataFrame + Cumulative max for each group. Same object type as the caller. %(see_also)s Examples --------