@@ -70,39 +70,11 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
7070 --format=actions \
7171 -i ES01 ` # For now it is ok if docstrings are missing the extended summary` \
7272 -i " pandas.Series.dt PR01" ` # Accessors are implemented as classes, but we do not document the Parameters section` \
73- -i " pandas.MultiIndex.reorder_levels RT03,SA01" \
74- -i " pandas.MultiIndex.to_frame RT03" \
7573 -i " pandas.NA SA01" \
76- -i " pandas.NaT SA01" \
7774 -i " pandas.Period.freq GL08" \
78- -i " pandas.Period.freqstr SA01" \
7975 -i " pandas.Period.ordinal GL08" \
80- -i " pandas.Period.strftime PR01,SA01" \
8176 -i " pandas.Period.to_timestamp SA01" \
82- -i " pandas.PeriodDtype SA01" \
8377 -i " pandas.PeriodDtype.freq SA01" \
84- -i " pandas.PeriodIndex.day SA01" \
85- -i " pandas.PeriodIndex.day_of_week SA01" \
86- -i " pandas.PeriodIndex.day_of_year SA01" \
87- -i " pandas.PeriodIndex.dayofweek SA01" \
88- -i " pandas.PeriodIndex.dayofyear SA01" \
89- -i " pandas.PeriodIndex.days_in_month SA01" \
90- -i " pandas.PeriodIndex.daysinmonth SA01" \
91- -i " pandas.PeriodIndex.from_fields PR07,SA01" \
92- -i " pandas.PeriodIndex.from_ordinals SA01" \
93- -i " pandas.PeriodIndex.hour SA01" \
94- -i " pandas.PeriodIndex.is_leap_year SA01" \
95- -i " pandas.PeriodIndex.minute SA01" \
96- -i " pandas.PeriodIndex.month SA01" \
97- -i " pandas.PeriodIndex.quarter SA01" \
98- -i " pandas.PeriodIndex.qyear GL08" \
99- -i " pandas.PeriodIndex.second SA01" \
100- -i " pandas.PeriodIndex.to_timestamp RT03,SA01" \
101- -i " pandas.PeriodIndex.week SA01" \
102- -i " pandas.PeriodIndex.weekday SA01" \
103- -i " pandas.PeriodIndex.weekofyear SA01" \
104- -i " pandas.PeriodIndex.year SA01" \
105- -i " pandas.RangeIndex PR07" \
10678 -i " pandas.RangeIndex.from_range PR01,SA01" \
10779 -i " pandas.RangeIndex.start SA01" \
10880 -i " pandas.RangeIndex.step SA01" \
@@ -124,7 +96,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
12496 -i " pandas.Series.dt.month_name PR01,PR02" \
12597 -i " pandas.Series.dt.nanoseconds SA01" \
12698 -i " pandas.Series.dt.normalize PR01" \
127- -i " pandas.Series.dt.qyear GL08" \
12899 -i " pandas.Series.dt.round PR01,PR02" \
129100 -i " pandas.Series.dt.seconds SA01" \
130101 -i " pandas.Series.dt.strftime PR01,PR02" \
@@ -133,34 +104,11 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
133104 -i " pandas.Series.dt.tz_convert PR01,PR02" \
134105 -i " pandas.Series.dt.tz_localize PR01,PR02" \
135106 -i " pandas.Series.dt.unit GL08" \
136- -i " pandas.Series.gt SA01" \
137- -i " pandas.Series.list.__getitem__ SA01" \
138- -i " pandas.Series.list.flatten SA01" \
139- -i " pandas.Series.list.len SA01" \
140- -i " pandas.Series.lt SA01" \
141- -i " pandas.Series.ne SA01" \
142107 -i " pandas.Series.pad PR01,SA01" \
143- -i " pandas.Series.pop SA01" \
144- -i " pandas.Series.prod RT03" \
145- -i " pandas.Series.product RT03" \
146- -i " pandas.Series.reorder_levels RT03,SA01" \
147- -i " pandas.Series.sem PR01,RT03,SA01" \
148- -i " pandas.Series.sparse PR01,SA01" \
149- -i " pandas.Series.sparse.density SA01" \
150108 -i " pandas.Series.sparse.fill_value SA01" \
151109 -i " pandas.Series.sparse.from_coo PR07,SA01" \
152110 -i " pandas.Series.sparse.npoints SA01" \
153111 -i " pandas.Series.sparse.sp_values SA01" \
154- -i " pandas.Series.sparse.to_coo PR07,RT03,SA01" \
155- -i " pandas.Series.std PR01,RT03,SA01" \
156- -i " pandas.Series.str.match RT03" \
157- -i " pandas.Series.str.normalize RT03,SA01" \
158- -i " pandas.Series.str.repeat SA01" \
159- -i " pandas.Series.str.replace SA01" \
160- -i " pandas.Series.str.wrap RT03,SA01" \
161- -i " pandas.Series.str.zfill RT03" \
162- -i " pandas.Series.struct.dtypes SA01" \
163- -i " pandas.Series.to_markdown SA01" \
164112 -i " pandas.Timedelta.asm8 SA01" \
165113 -i " pandas.Timedelta.ceil SA01" \
166114 -i " pandas.Timedelta.components SA01" \
@@ -173,41 +121,18 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
173121 -i " pandas.Timedelta.to_timedelta64 SA01" \
174122 -i " pandas.Timedelta.total_seconds SA01" \
175123 -i " pandas.Timedelta.view SA01" \
176- -i " pandas.TimedeltaIndex.as_unit RT03,SA01" \
177124 -i " pandas.TimedeltaIndex.components SA01" \
178125 -i " pandas.TimedeltaIndex.microseconds SA01" \
179126 -i " pandas.TimedeltaIndex.nanoseconds SA01" \
180127 -i " pandas.TimedeltaIndex.seconds SA01" \
181128 -i " pandas.TimedeltaIndex.to_pytimedelta RT03,SA01" \
182- -i " pandas.Timestamp.day GL08" \
183- -i " pandas.Timestamp.fold GL08" \
184- -i " pandas.Timestamp.hour GL08" \
185129 -i " pandas.Timestamp.max PR02" \
186- -i " pandas.Timestamp.microsecond GL08" \
187130 -i " pandas.Timestamp.min PR02" \
188- -i " pandas.Timestamp.minute GL08" \
189- -i " pandas.Timestamp.month GL08" \
190131 -i " pandas.Timestamp.nanosecond GL08" \
191132 -i " pandas.Timestamp.resolution PR02" \
192- -i " pandas.Timestamp.second GL08" \
193133 -i " pandas.Timestamp.tzinfo GL08" \
194- -i " pandas.Timestamp.value GL08" \
195134 -i " pandas.Timestamp.year GL08" \
196- -i " pandas.api.extensions.ExtensionArray._pad_or_backfill PR01,RT03,SA01" \
197- -i " pandas.api.extensions.ExtensionArray._reduce RT03,SA01" \
198- -i " pandas.api.extensions.ExtensionArray._values_for_factorize SA01" \
199- -i " pandas.api.extensions.ExtensionArray.astype SA01" \
200- -i " pandas.api.extensions.ExtensionArray.dropna RT03,SA01" \
201- -i " pandas.api.extensions.ExtensionArray.dtype SA01" \
202- -i " pandas.api.extensions.ExtensionArray.duplicated RT03,SA01" \
203- -i " pandas.api.extensions.ExtensionArray.fillna SA01" \
204- -i " pandas.api.extensions.ExtensionArray.insert PR07,RT03,SA01" \
205135 -i " pandas.api.extensions.ExtensionArray.interpolate PR01,SA01" \
206- -i " pandas.api.extensions.ExtensionArray.isin PR07,RT03,SA01" \
207- -i " pandas.api.extensions.ExtensionArray.tolist RT03,SA01" \
208- -i " pandas.api.extensions.ExtensionArray.unique RT03,SA01" \
209- -i " pandas.api.extensions.ExtensionArray.view SA01" \
210- -i " pandas.api.interchange.from_dataframe RT03,SA01" \
211136 -i " pandas.api.types.is_bool PR01,SA01" \
212137 -i " pandas.api.types.is_categorical_dtype SA01" \
213138 -i " pandas.api.types.is_complex PR01,SA01" \
@@ -259,7 +184,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
259184 -i " pandas.core.groupby.DataFrameGroupBy.nunique SA01" \
260185 -i " pandas.core.groupby.DataFrameGroupBy.ohlc SA01" \
261186 -i " pandas.core.groupby.DataFrameGroupBy.plot PR02" \
262- -i " pandas.core.groupby.DataFrameGroupBy.prod SA01" \
263187 -i " pandas.core.groupby.DataFrameGroupBy.sem SA01" \
264188 -i " pandas.core.groupby.DataFrameGroupBy.sum SA01" \
265189 -i " pandas.core.groupby.SeriesGroupBy.__iter__ RT03,SA01" \
@@ -276,7 +200,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
276200 -i " pandas.core.groupby.SeriesGroupBy.nth PR02" \
277201 -i " pandas.core.groupby.SeriesGroupBy.ohlc SA01" \
278202 -i " pandas.core.groupby.SeriesGroupBy.plot PR02" \
279- -i " pandas.core.groupby.SeriesGroupBy.prod SA01" \
280203 -i " pandas.core.groupby.SeriesGroupBy.sem SA01" \
281204 -i " pandas.core.groupby.SeriesGroupBy.sum SA01" \
282205 -i " pandas.core.resample.Resampler.__iter__ RT03,SA01" \
@@ -295,13 +218,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
295218 -i " pandas.core.resample.Resampler.sum SA01" \
296219 -i " pandas.core.resample.Resampler.transform PR01,RT03,SA01" \
297220 -i " pandas.core.resample.Resampler.var SA01" \
298- -i " pandas.core.window.expanding.Expanding.corr PR01" \
299- -i " pandas.core.window.expanding.Expanding.count PR01" \
300- -i " pandas.core.window.rolling.Rolling.max PR01" \
301- -i " pandas.core.window.rolling.Window.std PR01" \
302- -i " pandas.core.window.rolling.Window.var PR01" \
303221 -i " pandas.date_range RT03" \
304- -i " pandas.errors.AbstractMethodError PR01,SA01" \
305222 -i " pandas.errors.AttributeConflictWarning SA01" \
306223 -i " pandas.errors.CSSWarning SA01" \
307224 -i " pandas.errors.CategoricalConversionWarning SA01" \
@@ -329,34 +246,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
329246 -i " pandas.errors.UnsupportedFunctionCall SA01" \
330247 -i " pandas.errors.ValueLabelTypeMismatch SA01" \
331248 -i " pandas.infer_freq SA01" \
332- -i " pandas.io.formats.style.Styler.apply RT03" \
333- -i " pandas.io.formats.style.Styler.apply_index RT03" \
334- -i " pandas.io.formats.style.Styler.background_gradient RT03" \
335- -i " pandas.io.formats.style.Styler.bar RT03,SA01" \
336- -i " pandas.io.formats.style.Styler.clear SA01" \
337- -i " pandas.io.formats.style.Styler.concat RT03,SA01" \
338- -i " pandas.io.formats.style.Styler.export RT03" \
339- -i " pandas.io.formats.style.Styler.from_custom_template SA01" \
340- -i " pandas.io.formats.style.Styler.hide RT03,SA01" \
341- -i " pandas.io.formats.style.Styler.highlight_between RT03" \
342- -i " pandas.io.formats.style.Styler.highlight_max RT03" \
343- -i " pandas.io.formats.style.Styler.highlight_min RT03" \
344- -i " pandas.io.formats.style.Styler.highlight_null RT03" \
345- -i " pandas.io.formats.style.Styler.highlight_quantile RT03" \
346- -i " pandas.io.formats.style.Styler.map RT03" \
347- -i " pandas.io.formats.style.Styler.map_index RT03" \
348- -i " pandas.io.formats.style.Styler.set_caption RT03,SA01" \
349- -i " pandas.io.formats.style.Styler.set_properties RT03,SA01" \
350- -i " pandas.io.formats.style.Styler.set_sticky RT03,SA01" \
351- -i " pandas.io.formats.style.Styler.set_table_attributes PR07,RT03" \
352- -i " pandas.io.formats.style.Styler.set_table_styles RT03" \
353- -i " pandas.io.formats.style.Styler.set_td_classes RT03" \
354- -i " pandas.io.formats.style.Styler.set_tooltips RT03,SA01" \
355- -i " pandas.io.formats.style.Styler.set_uuid PR07,RT03,SA01" \
356- -i " pandas.io.formats.style.Styler.text_gradient RT03" \
357- -i " pandas.io.formats.style.Styler.to_excel PR01" \
358- -i " pandas.io.formats.style.Styler.to_string SA01" \
359- -i " pandas.io.formats.style.Styler.use RT03" \
360249 -i " pandas.io.json.build_table_schema PR07,RT03,SA01" \
361250 -i " pandas.io.stata.StataReader.data_label SA01" \
362251 -i " pandas.io.stata.StataReader.value_labels RT03,SA01" \
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