diff --git a/ci/code_checks.sh b/ci/code_checks.sh index a21b87950cee1c3d16aa86494dac68c449e8a134..f23481b3da3a2bfe8b8a8b5db3aa1a84f873f0e5 100755 --- a/ci/code_checks.sh +++ b/ci/code_checks.sh @@ -86,19 +86,15 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then -i "pandas.arrays.TimedeltaArray PR07,SA01" \ -i "pandas.core.groupby.DataFrameGroupBy.boxplot PR07,RT03,SA01" \ -i "pandas.core.groupby.DataFrameGroupBy.get_group RT03,SA01" \ - -i "pandas.core.groupby.DataFrameGroupBy.nunique SA01" \ -i "pandas.core.groupby.DataFrameGroupBy.plot PR02" \ - -i "pandas.core.groupby.DataFrameGroupBy.sem SA01" \ -i "pandas.core.groupby.SeriesGroupBy.get_group RT03,SA01" \ -i "pandas.core.groupby.SeriesGroupBy.plot PR02" \ - -i "pandas.core.groupby.SeriesGroupBy.sem SA01" \ -i "pandas.core.resample.Resampler.get_group RT03,SA01" \ -i "pandas.core.resample.Resampler.max PR01,RT03,SA01" \ -i "pandas.core.resample.Resampler.mean SA01" \ -i "pandas.core.resample.Resampler.min PR01,RT03,SA01" \ -i "pandas.core.resample.Resampler.prod SA01" \ -i "pandas.core.resample.Resampler.quantile PR01,PR07" \ - -i "pandas.core.resample.Resampler.sem SA01" \ -i "pandas.core.resample.Resampler.std SA01" \ -i "pandas.core.resample.Resampler.transform PR01,RT03,SA01" \ -i "pandas.core.resample.Resampler.var SA01" \ diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py index 35ec09892ede67fbce587ed38cfeb6195ffbea0e..3a917e0147396e23d760caff6265ab636bd86e0f 100644 --- a/pandas/core/groupby/generic.py +++ b/pandas/core/groupby/generic.py @@ -2453,6 +2453,10 @@ class DataFrameGroupBy(GroupBy[DataFrame]): nunique: DataFrame Counts of unique elements in each position. + See Also + -------- + DataFrame.nunique : Count number of distinct elements in specified axis. + Examples -------- >>> df = pd.DataFrame( diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py index 48d4e0456d4fa1f32323728f82ed9f7458b54d8d..e750c606a4c44ccb0cd0683affbc2d3e191349fb 100644 --- a/pandas/core/groupby/groupby.py +++ b/pandas/core/groupby/groupby.py @@ -2658,6 +2658,11 @@ class GroupBy(BaseGroupBy[NDFrameT]): Series or DataFrame Standard error of the mean of values within each group. + See Also + -------- + DataFrame.sem : Return unbiased standard error of the mean over requested axis. + Series.sem : Return unbiased standard error of the mean over requested axis. + Examples -------- For SeriesGroupBy: