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‎.pre-commit-config.yaml

+1-1
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@@ -108,7 +108,7 @@ repos:
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types: [python]
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stages: [manual]
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additional_dependencies: &pyright_dependencies
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- pyright@1.1.351
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- pyright@1.1.352
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- id: pyright
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# note: assumes python env is setup and activated
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name: pyright reportGeneralTypeIssues

‎ci/code_checks.sh

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@@ -70,134 +70,22 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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--format=actions \
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-i ES01 `# For now it is ok if docstrings are missing the extended summary` \
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-i "pandas.Series.dt PR01" `# Accessors are implemented as classes, but we do not document the Parameters section` \
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-i "pandas.Categorical.__array__ SA01" \
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-i "pandas.Categorical.codes SA01" \
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-i "pandas.Categorical.dtype SA01" \
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-i "pandas.Categorical.from_codes SA01" \
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-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" \
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-i "pandas.DataFrame.columns SA01" \
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-i "pandas.DataFrame.droplevel 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.kurt RT03,SA01" \
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-i "pandas.DataFrame.kurtosis RT03,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.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" \
112-
-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_of_year SA01" \
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-i "pandas.DatetimeIndex.dayofyear SA01" \
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-i "pandas.DatetimeIndex.floor SA01" \
120-
-i "pandas.DatetimeIndex.freqstr SA01" \
121-
-i "pandas.DatetimeIndex.indexer_at_time PR01,RT03" \
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-i "pandas.DatetimeIndex.indexer_between_time RT03" \
123-
-i "pandas.DatetimeIndex.inferred_freq SA01" \
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-i "pandas.DatetimeIndex.is_leap_year SA01" \
125-
-i "pandas.DatetimeIndex.microsecond 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.snap PR01,RT03,SA01" \
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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.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.append PR01,SA01" \
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-i "pandas.HDFStore.get SA01" \
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-i "pandas.HDFStore.groups SA01" \
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-i "pandas.HDFStore.info RT03,SA01" \
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-i "pandas.HDFStore.keys SA01" \
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-i "pandas.HDFStore.put PR01,SA01" \
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-i "pandas.HDFStore.select SA01" \
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-i "pandas.HDFStore.walk SA01" \
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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" \
192-
-i "pandas.Index.take PR01,PR07" \
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-i "pandas.Index.to_list RT03" \
194-
-i "pandas.Index.union PR07,RT03,SA01" \
195-
-i "pandas.Index.unique RT03" \
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-i "pandas.Index.view GL08" \
197-
-i "pandas.Int16Dtype SA01" \
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-i "pandas.Int32Dtype SA01" \
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-i "pandas.Int64Dtype SA01" \
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-i "pandas.Int8Dtype SA01" \
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-i "pandas.Interval PR02" \
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-i "pandas.Interval.closed SA01" \
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-i "pandas.Interval.left SA01" \
@@ -207,7 +95,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
20795
-i "pandas.IntervalDtype.subtype SA01" \
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-i "pandas.IntervalIndex.closed SA01" \
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-i "pandas.IntervalIndex.contains RT03" \
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-i "pandas.IntervalIndex.get_indexer PR07,SA01" \
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-i "pandas.IntervalIndex.get_loc PR07,RT03,SA01" \
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-i "pandas.IntervalIndex.is_non_overlapping_monotonic SA01" \
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-i "pandas.IntervalIndex.left GL08" \
@@ -220,9 +107,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
220107
-i "pandas.MultiIndex.append PR07,SA01" \
221108
-i "pandas.MultiIndex.copy PR07,RT03,SA01" \
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-i "pandas.MultiIndex.drop PR07,RT03,SA01" \
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-i "pandas.MultiIndex.droplevel RT03,SA01" \
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-i "pandas.MultiIndex.dtypes SA01" \
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-i "pandas.MultiIndex.get_indexer PR07,SA01" \
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-i "pandas.MultiIndex.get_level_values SA01" \
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-i "pandas.MultiIndex.get_loc PR07" \
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-i "pandas.MultiIndex.get_loc_level PR07" \
@@ -261,7 +146,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.PeriodIndex.dayofyear SA01" \
262147
-i "pandas.PeriodIndex.days_in_month SA01" \
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-i "pandas.PeriodIndex.daysinmonth SA01" \
264-
-i "pandas.PeriodIndex.freqstr SA01" \
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-i "pandas.PeriodIndex.from_fields PR07,SA01" \
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-i "pandas.PeriodIndex.from_ordinals SA01" \
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-i "pandas.PeriodIndex.hour SA01" \
@@ -282,70 +166,52 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.RangeIndex.step SA01" \
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-i "pandas.RangeIndex.stop SA01" \
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-i "pandas.Series SA01" \
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-i "pandas.Series.T SA01" \
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-i "pandas.Series.__iter__ RT03,SA01" \
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-i "pandas.Series.add PR07" \
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-i "pandas.Series.at_time PR01" \
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-i "pandas.Series.backfill PR01,SA01" \
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-i "pandas.Series.case_when RT03" \
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-i "pandas.Series.cat PR07,SA01" \
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-i "pandas.Series.cat.add_categories PR01,PR02" \
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-i "pandas.Series.cat.as_ordered PR01" \
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-i "pandas.Series.cat.as_unordered PR01" \
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-i "pandas.Series.cat.codes SA01" \
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-i "pandas.Series.cat.ordered SA01" \
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-i "pandas.Series.cat.remove_categories PR01,PR02" \
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-i "pandas.Series.cat.remove_unused_categories PR01" \
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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.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" \
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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.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" \
191+
-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.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.month_name PR01,PR02" \
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-i "pandas.Series.dt.nanosecond SA01" \
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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.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.to_period PR01,PR02" \
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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_convert PR01,PR02" \
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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.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.floordiv PR07" \
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-i "pandas.Series.ge PR07,SA01" \
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-i "pandas.Series.gt PR07,SA01" \
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-i "pandas.Series.hasnans SA01" \
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-i "pandas.Series.infer_objects RT03" \
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-i "pandas.Series.is_monotonic_decreasing SA01" \
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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.kurt RT03,SA01" \
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-i "pandas.Series.kurtosis RT03,SA01" \
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-i "pandas.Series.le PR07,SA01" \
@@ -360,10 +226,7 @@ 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" \
363-
-i "pandas.Series.nbytes SA01" \
364-
-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" \
368231
-i "pandas.Series.plot PR02,SA01" \
369232
-i "pandas.Series.pop RT03,SA01" \
@@ -381,7 +244,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
381244
-i "pandas.Series.rtruediv PR07" \
382245
-i "pandas.Series.sem PR01,RT03,SA01" \
383246
-i "pandas.Series.shape SA01" \
384-
-i "pandas.Series.size SA01" \
385247
-i "pandas.Series.skew RT03,SA01" \
386248
-i "pandas.Series.sparse PR01,SA01" \
387249
-i "pandas.Series.sparse.density SA01" \
@@ -427,7 +289,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
427289
-i "pandas.Series.swaplevel SA01" \
428290
-i "pandas.Series.to_dict SA01" \
429291
-i "pandas.Series.to_frame SA01" \
430-
-i "pandas.Series.to_list RT03" \
431292
-i "pandas.Series.to_markdown SA01" \
432293
-i "pandas.Series.to_string SA01" \
433294
-i "pandas.Series.truediv PR07" \
@@ -450,14 +311,10 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
450311
-i "pandas.Timedelta.total_seconds SA01" \
451312
-i "pandas.Timedelta.view SA01" \
452313
-i "pandas.TimedeltaIndex.as_unit RT03,SA01" \
453-
-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" \
@@ -528,10 +385,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.Timestamp.weekday SA01" \
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-i "pandas.Timestamp.weekofyear SA01" \
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-i "pandas.Timestamp.year GL08" \
531-
-i "pandas.UInt16Dtype SA01" \
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-i "pandas.UInt32Dtype SA01" \
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-i "pandas.UInt64Dtype SA01" \
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-i "pandas.UInt8Dtype SA01" \
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-i "pandas.api.extensions.ExtensionArray SA01" \
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-i "pandas.api.extensions.ExtensionArray._accumulate RT03,SA01" \
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-i "pandas.api.extensions.ExtensionArray._concat_same_type PR07,SA01" \

‎doc/source/development/community.rst

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@@ -100,6 +100,8 @@ The pandas mailing list `pandas-dev@python.org <mailto://pandas-dev@python
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conversations and to engage people in the wider community who might not
101101
be active on the issue tracker but we would like to include in discussions.
102102

103+
Join the mailing list and view the archives `here <https://mail.python.org/mailman/listinfo/pandas-dev>`_.
104+
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.. _community.slack:
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Community slack

‎doc/source/development/contributing_codebase.rst

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@@ -557,11 +557,12 @@ is being raised, using ``pytest.raises`` instead.
557557
Testing a warning
558558
^^^^^^^^^^^^^^^^^
559559

560-
Use ``tm.assert_produces_warning`` as a context manager to check that a block of code raises a warning.
560+
Use ``tm.assert_produces_warning`` as a context manager to check that a block of code raises a warning
561+
and specify the warning message using the ``match`` argument.
561562

562563
.. code-block:: python
563564
564-
with tm.assert_produces_warning(DeprecationWarning):
565+
with tm.assert_produces_warning(DeprecationWarning, match="the warning message"):
565566
pd.deprecated_function()
566567
567568
If a warning should specifically not happen in a block of code, pass ``False`` into the context manager.

‎doc/source/user_guide/style.ipynb

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"- Provide an API that is pleasing to use interactively and is \"good enough\" for many tasks\n",
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"- Provide the foundations for dedicated libraries to build on\n",
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"\n",
1911-
"If you build a great library on top of this, let us know and we'll [link](https://pandas.pydata.org/pandas-docs/stable/ecosystem.html) to it.\n",
1911+
"If you build a great library on top of this, let us know and we'll [link](https://pandas.pydata.org/community/ecosystem.html) to it.\n",
19121912
"\n",
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"### Subclassing\n",
19141914
"\n",

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