@@ -80,74 +80,38 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i " pandas.CategoricalIndex.codes SA01" \
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-i " pandas.CategoricalIndex.ordered SA01" \
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-i " pandas.DataFrame.__dataframe__ SA01" \
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- -i " pandas.DataFrame.__iter__ SA01" \
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-i " pandas.DataFrame.at_time PR01" \
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- -i " pandas.DataFrame.columns SA01" \
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- -i " pandas.DataFrame.copy SA01" \
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- -i " pandas.DataFrame.droplevel SA01" \
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- -i " pandas.DataFrame.first_valid_index SA01" \
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-i " pandas.DataFrame.hist RT03" \
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-i " pandas.DataFrame.infer_objects RT03" \
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- -i " pandas.DataFrame.keys SA01" \
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-i " pandas.DataFrame.kurt RT03,SA01" \
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-i " pandas.DataFrame.kurtosis RT03,SA01" \
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- -i " pandas.DataFrame.last_valid_index SA01" \
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-i " pandas.DataFrame.max RT03" \
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-i " pandas.DataFrame.mean RT03,SA01" \
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-i " pandas.DataFrame.median RT03,SA01" \
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-i " pandas.DataFrame.min RT03" \
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-i " pandas.DataFrame.plot PR02,SA01" \
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- -i " pandas.DataFrame.pop SA01" \
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-i " pandas.DataFrame.prod RT03" \
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-i " pandas.DataFrame.product RT03" \
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-i " pandas.DataFrame.reorder_levels SA01" \
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-i " pandas.DataFrame.sem PR01,RT03,SA01" \
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-i " pandas.DataFrame.skew RT03,SA01" \
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- -i " pandas.DataFrame.sparse PR01,SA01" \
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- -i " pandas.DataFrame.sparse.density SA01" \
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- -i " pandas.DataFrame.sparse.from_spmatrix SA01" \
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- -i " pandas.DataFrame.sparse.to_coo SA01" \
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- -i " pandas.DataFrame.sparse.to_dense SA01" \
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+ -i " pandas.DataFrame.sparse PR01" \
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-i " pandas.DataFrame.std PR01,RT03,SA01" \
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-i " pandas.DataFrame.sum RT03" \
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-i " pandas.DataFrame.swaplevel SA01" \
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- -i " pandas.DataFrame.to_feather SA01" \
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-i " pandas.DataFrame.to_markdown SA01" \
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-i " pandas.DataFrame.to_parquet RT03" \
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-i " pandas.DataFrame.var PR01,RT03,SA01" \
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- -i " pandas.DatetimeIndex.ceil SA01" \
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- -i " pandas.DatetimeIndex.date SA01" \
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- -i " pandas.DatetimeIndex.day SA01" \
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- -i " pandas.DatetimeIndex.day_name SA01" \
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- -i " pandas.DatetimeIndex.day_of_year SA01" \
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- -i " pandas.DatetimeIndex.dayofyear SA01" \
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- -i " pandas.DatetimeIndex.floor SA01" \
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-i " pandas.DatetimeIndex.freqstr SA01" \
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- -i " pandas.DatetimeIndex.hour SA01" \
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-i " pandas.DatetimeIndex.indexer_at_time PR01,RT03" \
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-i " pandas.DatetimeIndex.indexer_between_time RT03" \
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- -i " pandas.DatetimeIndex.inferred_freq SA01" \
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- -i " pandas.DatetimeIndex.is_leap_year SA01" \
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- -i " pandas.DatetimeIndex.microsecond SA01" \
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- -i " pandas.DatetimeIndex.minute SA01" \
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- -i " pandas.DatetimeIndex.month SA01" \
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- -i " pandas.DatetimeIndex.month_name SA01" \
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- -i " pandas.DatetimeIndex.nanosecond SA01" \
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- -i " pandas.DatetimeIndex.quarter SA01" \
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- -i " pandas.DatetimeIndex.round SA01" \
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- -i " pandas.DatetimeIndex.second SA01" \
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- -i " pandas.DatetimeIndex.snap PR01,RT03,SA01" \
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+ -i " pandas.DatetimeIndex.snap PR01,RT03" \
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-i " pandas.DatetimeIndex.std PR01,RT03" \
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- -i " pandas.DatetimeIndex.time SA01" \
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- -i " pandas.DatetimeIndex.timetz SA01" \
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-i " pandas.DatetimeIndex.to_period RT03" \
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-i " pandas.DatetimeIndex.to_pydatetime RT03,SA01" \
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- -i " pandas.DatetimeIndex.tz SA01" \
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-i " pandas.DatetimeIndex.tz_convert RT03" \
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- -i " pandas.DatetimeIndex.year SA01" \
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-i " pandas.DatetimeTZDtype SA01" \
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-i " pandas.DatetimeTZDtype.tz SA01" \
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- -i " pandas.DatetimeTZDtype.unit SA01" \
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-i " pandas.Grouper PR02" \
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-i " pandas.HDFStore.get SA01" \
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-i " pandas.HDFStore.groups SA01" \
@@ -159,50 +123,38 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i " pandas.Index PR07" \
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-i " pandas.Index.T SA01" \
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-i " pandas.Index.append PR07,RT03,SA01" \
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- -i " pandas.Index.astype SA01" \
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-i " pandas.Index.copy PR07,SA01" \
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-i " pandas.Index.difference PR07,RT03,SA01" \
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-i " pandas.Index.drop PR07,SA01" \
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-i " pandas.Index.drop_duplicates RT03" \
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-i " pandas.Index.droplevel RT03,SA01" \
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-i " pandas.Index.dropna RT03,SA01" \
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- -i " pandas.Index.dtype SA01" \
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-i " pandas.Index.duplicated RT03" \
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-i " pandas.Index.empty GL08" \
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- -i " pandas.Index.equals SA01" \
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-i " pandas.Index.fillna RT03" \
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-i " pandas.Index.get_indexer PR07,SA01" \
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-i " pandas.Index.get_indexer_for PR01,SA01" \
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-i " pandas.Index.get_indexer_non_unique PR07,SA01" \
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-i " pandas.Index.get_loc PR07,RT03,SA01" \
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-i " pandas.Index.get_slice_bound PR07" \
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- -i " pandas.Index.hasnans SA01" \
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-i " pandas.Index.identical PR01,SA01" \
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-i " pandas.Index.inferred_type SA01" \
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-i " pandas.Index.insert PR07,RT03,SA01" \
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-i " pandas.Index.intersection PR07,RT03,SA01" \
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-i " pandas.Index.item SA01" \
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-i " pandas.Index.join PR07,RT03,SA01" \
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- -i " pandas.Index.map SA01" \
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-i " pandas.Index.memory_usage RT03" \
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- -i " pandas.Index.name SA01" \
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-i " pandas.Index.names GL08" \
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- -i " pandas.Index.nbytes SA01" \
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- -i " pandas.Index.ndim SA01" \
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-i " pandas.Index.nunique RT03" \
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-i " pandas.Index.putmask PR01,RT03" \
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-i " pandas.Index.ravel PR01,RT03" \
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-i " pandas.Index.reindex PR07" \
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- -i " pandas.Index.shape SA01" \
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- -i " pandas.Index.size SA01" \
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-i " pandas.Index.slice_indexer PR07,RT03,SA01" \
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-i " pandas.Index.slice_locs RT03" \
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-i " pandas.Index.str PR01,SA01" \
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-i " pandas.Index.symmetric_difference PR07,RT03,SA01" \
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-i " pandas.Index.take PR01,PR07" \
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- -i " pandas.Index.to_list RT03" \
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-i " pandas.Index.union PR07,RT03,SA01" \
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- -i " pandas.Index.unique RT03" \
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-i " pandas.Index.view GL08" \
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-i " pandas.Int16Dtype SA01" \
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-i " pandas.Int32Dtype SA01" \
@@ -309,51 +261,32 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i " pandas.Series.cat.rename_categories PR01,PR02" \
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-i " pandas.Series.cat.reorder_categories PR01,PR02" \
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-i " pandas.Series.cat.set_categories PR01,PR02" \
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- -i " pandas.Series.copy SA01" \
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-i " pandas.Series.div PR07" \
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- -i " pandas.Series.droplevel SA01" \
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-i " pandas.Series.dt.as_unit PR01,PR02" \
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- -i " pandas.Series.dt.ceil PR01,PR02,SA01 " \
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+ -i " pandas.Series.dt.ceil PR01,PR02" \
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-i " pandas.Series.dt.components SA01" \
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- -i " pandas.Series.dt.date SA01" \
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- -i " pandas.Series.dt.day SA01" \
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- -i " pandas.Series.dt.day_name PR01,PR02,SA01" \
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- -i " pandas.Series.dt.day_of_year SA01" \
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- -i " pandas.Series.dt.dayofyear SA01" \
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+ -i " pandas.Series.dt.day_name PR01,PR02" \
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-i " pandas.Series.dt.days SA01" \
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-i " pandas.Series.dt.days_in_month SA01" \
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-i " pandas.Series.dt.daysinmonth SA01" \
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- -i " pandas.Series.dt.floor PR01,PR02,SA01 " \
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+ -i " pandas.Series.dt.floor PR01,PR02" \
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-i " pandas.Series.dt.freq GL08" \
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- -i " pandas.Series.dt.hour SA01" \
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- -i " pandas.Series.dt.is_leap_year SA01" \
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- -i " pandas.Series.dt.microsecond SA01" \
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-i " pandas.Series.dt.microseconds SA01" \
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- -i " pandas.Series.dt.minute SA01" \
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- -i " pandas.Series.dt.month SA01" \
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- -i " pandas.Series.dt.month_name PR01,PR02,SA01" \
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- -i " pandas.Series.dt.nanosecond SA01" \
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+ -i " pandas.Series.dt.month_name PR01,PR02" \
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-i " pandas.Series.dt.nanoseconds SA01" \
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-i " pandas.Series.dt.normalize PR01" \
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- -i " pandas.Series.dt.quarter SA01" \
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-i " pandas.Series.dt.qyear GL08" \
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- -i " pandas.Series.dt.round PR01,PR02,SA01" \
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- -i " pandas.Series.dt.second SA01" \
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+ -i " pandas.Series.dt.round PR01,PR02" \
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-i " pandas.Series.dt.seconds SA01" \
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-i " pandas.Series.dt.strftime PR01,PR02" \
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- -i " pandas.Series.dt.time SA01" \
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- -i " pandas.Series.dt.timetz SA01" \
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-i " pandas.Series.dt.to_period PR01,PR02,RT03" \
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-i " pandas.Series.dt.total_seconds PR01" \
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- -i " pandas.Series.dt.tz SA01" \
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-i " pandas.Series.dt.tz_convert PR01,PR02,RT03" \
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-i " pandas.Series.dt.tz_localize PR01,PR02" \
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-i " pandas.Series.dt.unit GL08" \
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- -i " pandas.Series.dt.year SA01" \
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-i " pandas.Series.dtype SA01" \
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-i " pandas.Series.empty GL08" \
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-i " pandas.Series.eq PR07,SA01" \
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- -i " pandas.Series.first_valid_index SA01" \
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-i " pandas.Series.floordiv PR07" \
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-i " pandas.Series.ge PR07,SA01" \
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-i " pandas.Series.gt PR07,SA01" \
@@ -363,10 +296,8 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i " pandas.Series.is_monotonic_increasing SA01" \
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-i " pandas.Series.is_unique SA01" \
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-i " pandas.Series.item SA01" \
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- -i " pandas.Series.keys SA01" \
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-i " pandas.Series.kurt RT03,SA01" \
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-i " pandas.Series.kurtosis RT03,SA01" \
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- -i " pandas.Series.last_valid_index SA01" \
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-i " pandas.Series.le PR07,SA01" \
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-i " pandas.Series.list.__getitem__ SA01" \
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-i " pandas.Series.list.flatten SA01" \
@@ -379,8 +310,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i " pandas.Series.mod PR07" \
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-i " pandas.Series.mode SA01" \
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-i " pandas.Series.mul PR07" \
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- -i " pandas.Series.nbytes SA01" \
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- -i " pandas.Series.ndim SA01" \
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-i " pandas.Series.ne PR07,SA01" \
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-i " pandas.Series.nunique RT03" \
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-i " pandas.Series.pad PR01,SA01" \
@@ -400,7 +329,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i " pandas.Series.rtruediv PR07" \
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-i " pandas.Series.sem PR01,RT03,SA01" \
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-i " pandas.Series.shape SA01" \
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- -i " pandas.Series.size SA01" \
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-i " pandas.Series.skew RT03,SA01" \
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-i " pandas.Series.sparse PR01,SA01" \
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-i " pandas.Series.sparse.density SA01" \
@@ -446,7 +374,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i " pandas.Series.swaplevel SA01" \
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-i " pandas.Series.to_dict SA01" \
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-i " pandas.Series.to_frame SA01" \
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- -i " pandas.Series.to_list RT03" \
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-i " pandas.Series.to_markdown SA01" \
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-i " pandas.Series.to_string SA01" \
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-i " pandas.Series.truediv PR07" \
@@ -469,14 +396,10 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i " pandas.Timedelta.total_seconds SA01" \
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-i " pandas.Timedelta.view SA01" \
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-i " pandas.TimedeltaIndex.as_unit RT03,SA01" \
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- -i " pandas.TimedeltaIndex.ceil SA01" \
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-i " pandas.TimedeltaIndex.components SA01" \
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-i " pandas.TimedeltaIndex.days SA01" \
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- -i " pandas.TimedeltaIndex.floor SA01" \
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- -i " pandas.TimedeltaIndex.inferred_freq SA01" \
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-i " pandas.TimedeltaIndex.microseconds SA01" \
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-i " pandas.TimedeltaIndex.nanoseconds SA01" \
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- -i " pandas.TimedeltaIndex.round SA01" \
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-i " pandas.TimedeltaIndex.seconds SA01" \
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-i " pandas.TimedeltaIndex.to_pytimedelta RT03,SA01" \
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-i " pandas.Timestamp PR07,SA01" \
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