@@ -70,125 +70,22 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
70
70
--format=actions \
71
71
-i ES01 ` # For now it is ok if docstrings are missing the extended summary` \
72
72
-i " pandas.Series.dt PR01" ` # Accessors are implemented as classes, but we do not document the Parameters section` \
73
- -i " pandas.Categorical.__array__ SA01" \
74
- -i " pandas.Categorical.codes SA01" \
75
- -i " pandas.Categorical.dtype SA01" \
76
- -i " pandas.Categorical.from_codes SA01" \
77
- -i " pandas.Categorical.ordered SA01" \
78
- -i " pandas.CategoricalDtype.categories SA01" \
79
- -i " pandas.CategoricalDtype.ordered SA01" \
80
- -i " pandas.CategoricalIndex.codes SA01" \
81
- -i " pandas.CategoricalIndex.ordered SA01" \
82
- -i " pandas.DataFrame.__dataframe__ SA01" \
83
- -i " pandas.DataFrame.__iter__ SA01" \
84
- -i " pandas.DataFrame.at_time PR01" \
85
- -i " pandas.DataFrame.columns SA01" \
86
- -i " pandas.DataFrame.droplevel SA01" \
87
- -i " pandas.DataFrame.hist RT03" \
88
- -i " pandas.DataFrame.infer_objects RT03" \
89
- -i " pandas.DataFrame.kurt RT03,SA01" \
90
- -i " pandas.DataFrame.kurtosis RT03,SA01" \
91
73
-i " pandas.DataFrame.max RT03" \
92
74
-i " pandas.DataFrame.mean RT03,SA01" \
93
75
-i " pandas.DataFrame.median RT03,SA01" \
94
76
-i " pandas.DataFrame.min RT03" \
95
77
-i " pandas.DataFrame.plot PR02,SA01" \
96
- -i " pandas.DataFrame.pop SA01" \
97
- -i " pandas.DataFrame.prod RT03" \
98
- -i " pandas.DataFrame.product RT03" \
99
- -i " pandas.DataFrame.reorder_levels SA01" \
100
- -i " pandas.DataFrame.sem PR01,RT03,SA01" \
101
- -i " pandas.DataFrame.skew RT03,SA01" \
102
- -i " pandas.DataFrame.sparse PR01" \
103
78
-i " pandas.DataFrame.std PR01,RT03,SA01" \
104
79
-i " pandas.DataFrame.sum RT03" \
105
80
-i " pandas.DataFrame.swaplevel SA01" \
106
- -i " pandas.DataFrame.to_feather SA01" \
107
81
-i " pandas.DataFrame.to_markdown SA01" \
108
- -i " pandas.DataFrame.to_parquet RT03" \
109
82
-i " pandas.DataFrame.var PR01,RT03,SA01" \
110
- -i " pandas.DatetimeIndex.ceil SA01" \
111
- -i " pandas.DatetimeIndex.date SA01" \
112
- -i " pandas.DatetimeIndex.day SA01" \
113
- -i " pandas.DatetimeIndex.day_of_year SA01" \
114
- -i " pandas.DatetimeIndex.dayofyear SA01" \
115
- -i " pandas.DatetimeIndex.floor SA01" \
116
- -i " pandas.DatetimeIndex.freqstr SA01" \
117
- -i " pandas.DatetimeIndex.indexer_at_time PR01,RT03" \
118
- -i " pandas.DatetimeIndex.indexer_between_time RT03" \
119
- -i " pandas.DatetimeIndex.inferred_freq SA01" \
120
- -i " pandas.DatetimeIndex.is_leap_year SA01" \
121
- -i " pandas.DatetimeIndex.microsecond SA01" \
122
- -i " pandas.DatetimeIndex.nanosecond SA01" \
123
- -i " pandas.DatetimeIndex.quarter SA01" \
124
- -i " pandas.DatetimeIndex.round SA01" \
125
- -i " pandas.DatetimeIndex.snap PR01,RT03,SA01" \
126
- -i " pandas.DatetimeIndex.std PR01,RT03" \
127
- -i " pandas.DatetimeIndex.time SA01" \
128
- -i " pandas.DatetimeIndex.timetz SA01" \
129
- -i " pandas.DatetimeIndex.to_period RT03" \
130
- -i " pandas.DatetimeIndex.to_pydatetime RT03,SA01" \
131
- -i " pandas.DatetimeIndex.tz SA01" \
132
- -i " pandas.DatetimeIndex.tz_convert RT03" \
133
- -i " pandas.DatetimeTZDtype SA01" \
134
- -i " pandas.DatetimeTZDtype.tz SA01" \
135
- -i " pandas.DatetimeTZDtype.unit SA01" \
136
83
-i " pandas.Grouper PR02" \
137
- -i " pandas.HDFStore.groups SA01" \
138
- -i " pandas.HDFStore.info RT03,SA01" \
139
- -i " pandas.HDFStore.keys SA01" \
140
- -i " pandas.HDFStore.put PR01,SA01" \
141
- -i " pandas.HDFStore.select SA01" \
142
- -i " pandas.HDFStore.walk SA01" \
143
84
-i " pandas.Index PR07" \
144
- -i " pandas.Index.T SA01" \
145
- -i " pandas.Index.append PR07,RT03,SA01" \
146
- -i " pandas.Index.astype SA01" \
147
- -i " pandas.Index.copy PR07,SA01" \
148
- -i " pandas.Index.difference PR07,RT03,SA01" \
149
- -i " pandas.Index.drop PR07,SA01" \
150
- -i " pandas.Index.drop_duplicates RT03" \
151
- -i " pandas.Index.droplevel RT03,SA01" \
152
- -i " pandas.Index.dropna RT03,SA01" \
153
- -i " pandas.Index.dtype SA01" \
154
- -i " pandas.Index.duplicated RT03" \
155
- -i " pandas.Index.empty GL08" \
156
- -i " pandas.Index.equals SA01" \
157
- -i " pandas.Index.fillna RT03" \
158
- -i " pandas.Index.get_indexer PR07,SA01" \
159
- -i " pandas.Index.get_indexer_for PR01,SA01" \
160
- -i " pandas.Index.get_indexer_non_unique PR07,SA01" \
161
- -i " pandas.Index.get_loc PR07,RT03,SA01" \
162
- -i " pandas.Index.get_slice_bound PR07" \
163
- -i " pandas.Index.hasnans SA01" \
164
- -i " pandas.Index.identical PR01,SA01" \
165
- -i " pandas.Index.inferred_type SA01" \
166
- -i " pandas.Index.insert PR07,RT03,SA01" \
167
- -i " pandas.Index.intersection PR07,RT03,SA01" \
168
- -i " pandas.Index.item SA01" \
169
85
-i " pandas.Index.join PR07,RT03,SA01" \
170
- -i " pandas.Index.map SA01" \
171
- -i " pandas.Index.memory_usage RT03" \
172
- -i " pandas.Index.name SA01" \
173
86
-i " pandas.Index.names GL08" \
174
- -i " pandas.Index.nbytes SA01" \
175
- -i " pandas.Index.nunique RT03" \
176
- -i " pandas.Index.putmask PR01,RT03" \
177
87
-i " pandas.Index.ravel PR01,RT03" \
178
- -i " pandas.Index.reindex PR07" \
179
- -i " pandas.Index.slice_indexer PR07,RT03,SA01" \
180
- -i " pandas.Index.slice_locs RT03" \
181
88
-i " pandas.Index.str PR01,SA01" \
182
- -i " pandas.Index.symmetric_difference PR07,RT03,SA01" \
183
- -i " pandas.Index.take PR01,PR07" \
184
- -i " pandas.Index.to_list RT03" \
185
- -i " pandas.Index.union PR07,RT03,SA01" \
186
- -i " pandas.Index.unique RT03" \
187
- -i " pandas.Index.view GL08" \
188
- -i " pandas.Int16Dtype SA01" \
189
- -i " pandas.Int32Dtype SA01" \
190
- -i " pandas.Int64Dtype SA01" \
191
- -i " pandas.Int8Dtype SA01" \
192
89
-i " pandas.Interval PR02" \
193
90
-i " pandas.Interval.closed SA01" \
194
91
-i " pandas.Interval.left SA01" \
@@ -198,7 +95,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
198
95
-i " pandas.IntervalDtype.subtype SA01" \
199
96
-i " pandas.IntervalIndex.closed SA01" \
200
97
-i " pandas.IntervalIndex.contains RT03" \
201
- -i " pandas.IntervalIndex.get_indexer PR07,SA01" \
202
98
-i " pandas.IntervalIndex.get_loc PR07,RT03,SA01" \
203
99
-i " pandas.IntervalIndex.is_non_overlapping_monotonic SA01" \
204
100
-i " pandas.IntervalIndex.left GL08" \
@@ -211,9 +107,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
211
107
-i " pandas.MultiIndex.append PR07,SA01" \
212
108
-i " pandas.MultiIndex.copy PR07,RT03,SA01" \
213
109
-i " pandas.MultiIndex.drop PR07,RT03,SA01" \
214
- -i " pandas.MultiIndex.droplevel RT03,SA01" \
215
110
-i " pandas.MultiIndex.dtypes SA01" \
216
- -i " pandas.MultiIndex.get_indexer PR07,SA01" \
217
111
-i " pandas.MultiIndex.get_level_values SA01" \
218
112
-i " pandas.MultiIndex.get_loc PR07" \
219
113
-i " pandas.MultiIndex.get_loc_level PR07" \
@@ -252,7 +146,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
252
146
-i " pandas.PeriodIndex.dayofyear SA01" \
253
147
-i " pandas.PeriodIndex.days_in_month SA01" \
254
148
-i " pandas.PeriodIndex.daysinmonth SA01" \
255
- -i " pandas.PeriodIndex.freqstr SA01" \
256
149
-i " pandas.PeriodIndex.from_fields PR07,SA01" \
257
150
-i " pandas.PeriodIndex.from_ordinals SA01" \
258
151
-i " pandas.PeriodIndex.hour SA01" \
@@ -273,70 +166,52 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
273
166
-i " pandas.RangeIndex.step SA01" \
274
167
-i " pandas.RangeIndex.stop SA01" \
275
168
-i " pandas.Series SA01" \
276
- -i " pandas.Series.T SA01" \
277
169
-i " pandas.Series.__iter__ RT03,SA01" \
278
170
-i " pandas.Series.add PR07" \
279
- -i " pandas.Series.at_time PR01" \
280
171
-i " pandas.Series.backfill PR01,SA01" \
281
172
-i " pandas.Series.case_when RT03" \
282
173
-i " pandas.Series.cat PR07,SA01" \
283
174
-i " pandas.Series.cat.add_categories PR01,PR02" \
284
175
-i " pandas.Series.cat.as_ordered PR01" \
285
176
-i " pandas.Series.cat.as_unordered PR01" \
286
177
-i " pandas.Series.cat.codes SA01" \
287
- -i " pandas.Series.cat.ordered SA01" \
288
178
-i " pandas.Series.cat.remove_categories PR01,PR02" \
289
179
-i " pandas.Series.cat.remove_unused_categories PR01" \
290
180
-i " pandas.Series.cat.rename_categories PR01,PR02" \
291
181
-i " pandas.Series.cat.reorder_categories PR01,PR02" \
292
182
-i " pandas.Series.cat.set_categories PR01,PR02" \
293
183
-i " pandas.Series.div PR07" \
294
- -i " pandas.Series.droplevel SA01" \
295
184
-i " pandas.Series.dt.as_unit PR01,PR02" \
296
- -i " pandas.Series.dt.ceil PR01,PR02,SA01 " \
185
+ -i " pandas.Series.dt.ceil PR01,PR02" \
297
186
-i " pandas.Series.dt.components SA01" \
298
- -i " pandas.Series.dt.date SA01" \
299
- -i " pandas.Series.dt.day SA01" \
300
187
-i " pandas.Series.dt.day_name PR01,PR02" \
301
- -i " pandas.Series.dt.day_of_year SA01" \
302
- -i " pandas.Series.dt.dayofyear SA01" \
303
188
-i " pandas.Series.dt.days SA01" \
304
189
-i " pandas.Series.dt.days_in_month SA01" \
305
190
-i " pandas.Series.dt.daysinmonth SA01" \
306
- -i " pandas.Series.dt.floor PR01,PR02,SA01 " \
191
+ -i " pandas.Series.dt.floor PR01,PR02" \
307
192
-i " pandas.Series.dt.freq GL08" \
308
- -i " pandas.Series.dt.is_leap_year SA01" \
309
- -i " pandas.Series.dt.microsecond SA01" \
310
193
-i " pandas.Series.dt.microseconds SA01" \
311
194
-i " pandas.Series.dt.month_name PR01,PR02" \
312
- -i " pandas.Series.dt.nanosecond SA01" \
313
195
-i " pandas.Series.dt.nanoseconds SA01" \
314
196
-i " pandas.Series.dt.normalize PR01" \
315
- -i " pandas.Series.dt.quarter SA01" \
316
197
-i " pandas.Series.dt.qyear GL08" \
317
- -i " pandas.Series.dt.round PR01,PR02,SA01 " \
198
+ -i " pandas.Series.dt.round PR01,PR02" \
318
199
-i " pandas.Series.dt.seconds SA01" \
319
200
-i " pandas.Series.dt.strftime PR01,PR02" \
320
- -i " pandas.Series.dt.time SA01" \
321
- -i " pandas.Series.dt.timetz SA01" \
322
- -i " pandas.Series.dt.to_period PR01,PR02,RT03" \
201
+ -i " pandas.Series.dt.to_period PR01,PR02" \
323
202
-i " pandas.Series.dt.total_seconds PR01" \
324
- -i " pandas.Series.dt.tz SA01" \
325
- -i " pandas.Series.dt.tz_convert PR01,PR02,RT03" \
203
+ -i " pandas.Series.dt.tz_convert PR01,PR02" \
326
204
-i " pandas.Series.dt.tz_localize PR01,PR02" \
327
205
-i " pandas.Series.dt.unit GL08" \
328
206
-i " pandas.Series.dtype SA01" \
329
- -i " pandas.Series.empty GL08" \
330
207
-i " pandas.Series.eq PR07,SA01" \
331
208
-i " pandas.Series.floordiv PR07" \
332
209
-i " pandas.Series.ge PR07,SA01" \
333
210
-i " pandas.Series.gt PR07,SA01" \
334
211
-i " pandas.Series.hasnans SA01" \
335
- -i " pandas.Series.infer_objects RT03" \
336
212
-i " pandas.Series.is_monotonic_decreasing SA01" \
337
213
-i " pandas.Series.is_monotonic_increasing SA01" \
338
214
-i " pandas.Series.is_unique SA01" \
339
- -i " pandas.Series.item SA01" \
340
215
-i " pandas.Series.kurt RT03,SA01" \
341
216
-i " pandas.Series.kurtosis RT03,SA01" \
342
217
-i " pandas.Series.le PR07,SA01" \
@@ -351,9 +226,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
351
226
-i " pandas.Series.mod PR07" \
352
227
-i " pandas.Series.mode SA01" \
353
228
-i " pandas.Series.mul PR07" \
354
- -i " pandas.Series.nbytes SA01" \
355
229
-i " pandas.Series.ne PR07,SA01" \
356
- -i " pandas.Series.nunique RT03" \
357
230
-i " pandas.Series.pad PR01,SA01" \
358
231
-i " pandas.Series.plot PR02,SA01" \
359
232
-i " pandas.Series.pop RT03,SA01" \
@@ -416,7 +289,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
416
289
-i " pandas.Series.swaplevel SA01" \
417
290
-i " pandas.Series.to_dict SA01" \
418
291
-i " pandas.Series.to_frame SA01" \
419
- -i " pandas.Series.to_list RT03" \
420
292
-i " pandas.Series.to_markdown SA01" \
421
293
-i " pandas.Series.to_string SA01" \
422
294
-i " pandas.Series.truediv PR07" \
@@ -439,14 +311,10 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
439
311
-i " pandas.Timedelta.total_seconds SA01" \
440
312
-i " pandas.Timedelta.view SA01" \
441
313
-i " pandas.TimedeltaIndex.as_unit RT03,SA01" \
442
- -i " pandas.TimedeltaIndex.ceil SA01" \
443
314
-i " pandas.TimedeltaIndex.components SA01" \
444
315
-i " pandas.TimedeltaIndex.days SA01" \
445
- -i " pandas.TimedeltaIndex.floor SA01" \
446
- -i " pandas.TimedeltaIndex.inferred_freq SA01" \
447
316
-i " pandas.TimedeltaIndex.microseconds SA01" \
448
317
-i " pandas.TimedeltaIndex.nanoseconds SA01" \
449
- -i " pandas.TimedeltaIndex.round SA01" \
450
318
-i " pandas.TimedeltaIndex.seconds SA01" \
451
319
-i " pandas.TimedeltaIndex.to_pytimedelta RT03,SA01" \
452
320
-i " pandas.Timestamp PR07,SA01" \
@@ -517,10 +385,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
517
385
-i " pandas.Timestamp.weekday SA01" \
518
386
-i " pandas.Timestamp.weekofyear SA01" \
519
387
-i " pandas.Timestamp.year GL08" \
520
- -i " pandas.UInt16Dtype SA01" \
521
- -i " pandas.UInt32Dtype SA01" \
522
- -i " pandas.UInt64Dtype SA01" \
523
- -i " pandas.UInt8Dtype SA01" \
524
388
-i " pandas.api.extensions.ExtensionArray SA01" \
525
389
-i " pandas.api.extensions.ExtensionArray._accumulate RT03,SA01" \
526
390
-i " pandas.api.extensions.ExtensionArray._concat_same_type PR07,SA01" \
0 commit comments