Repository: pandas-dev/pandas
Pull request #57879 (2024-03-18 01:30:35)

CI: Better error control in the validation of docstrings
Making the validation of docstrings more robust, main changes:

- If we ignore an error that doesn't fail, the CI will report it and break (there were 30 errors being ignored that are already fixed and removed from the list of ignores here)
- Instead of specifying all the errors to validate (that are all but one now) we can specify errors to skip (there is one only that we skip, the lack of an extended summary in a docstring). This simplifies the script a bit
- In case an unknown error code is used when ignoring errors, the message should be more descriptive
- I created an alias for `--ignore_errors` as `-i`, so the list of errors to ignore is a bit easier to read

CC: @dontgoto @jordan-d-murphy 

jordan-d-murphy: Nice work! thank you @datapythonista 
jordan-d-murphy: with this ticket, and now that [CI: speedup docstring check consecutive runs #57826](https://github.com/pandas-dev/pandas/pull/57826) is merged in, I'm closing the following issues And opening a new issue to address this based on the new approach we've implemented. 

> [DOC: fix GL08 errors in docstrings](https://github.com/pandas-dev/pandas/issues/57443)
> [DOC: fix PR01 errors in docstrings](https://github.com/pandas-dev/pandas/issues/57438)
> [DOC: fix PR07 errors in docstrings](https://github.com/pandas-dev/pandas/issues/57420)
> [DOC: fix SA01 errors in docstrings](https://github.com/pandas-dev/pandas/issues/57417)
> [DOC: fix RT03 errors in docstrings](https://github.com/pandas-dev/pandas/issues/57416)
> [DOC: fix PR02 errors in docstrings](https://github.com/pandas-dev/pandas/issues/57111)

Thanks for all the work that's gone into this! this is a much cleaner approach, and fixing these will now be more straightforward. Big win in my opinion! 
datapythonista: > And opening a new issue to address these based on the new approach we've implemented.

What I'd do is create a master issue if there is not one already to fix the docstrings, and then create smaller issues labelled as "good first issue". For example:

Issue 1 to address:
```
        -i pandas.Categorical.__array__ SA01\
        -i pandas.Categorical.codes SA01\
        -i pandas.Categorical.dtype SA01\
        -i pandas.Categorical.from_codes SA01\
        -i pandas.Categorical.ordered SA01\
        -i pandas.CategoricalDtype.categories SA01\
        -i pandas.CategoricalDtype.ordered SA01\
        -i pandas.CategoricalIndex.codes SA01\
        -i pandas.CategoricalIndex.ordered SA01\
```

Issue 2 to address:
```
        -i pandas.HDFStore.append PR01,SA01\
        -i pandas.HDFStore.get SA01\
        -i pandas.HDFStore.groups SA01\
        -i pandas.HDFStore.info RT03,SA01\
        -i pandas.HDFStore.keys SA01\
        -i pandas.HDFStore.put PR01,SA01\
        -i pandas.HDFStore.select SA01\
        -i pandas.HDFStore.walk SA01\
```

Issue 3 to address:
```
        -i pandas.Int16Dtype SA01\
        -i pandas.Int32Dtype SA01\
        -i pandas.Int64Dtype SA01\
        -i pandas.Int8Dtype SA01\
```

Issue 4 to address:
```
        -i pandas.Interval PR02\
        -i pandas.Interval.closed SA01\
        -i pandas.Interval.left SA01\
        -i pandas.Interval.mid SA01\
        -i pandas.Interval.right SA01\
```

...

I think it'll make the work of contributors easier by addressing those in groups. In particular, the see also section of many of those would be quite easy since the docstrings they'll be cross-referencing each other in many cases.

If you don't have triagge permissions in this repo, please let me know, I'll give them to you, so you can labelled the issues as "good first issue" and anything else needed.
jordan-d-murphy: Thanks for the guidance, @datapythonista ! 

I agree, that sounds like a great approach. I'll set it up once this gets merged in so I can grab the updated code snippets from main. 

I don't have those permissions, it would be helpful if you can grant them to me. Thank you! 


dontgoto: That's some great simplifications for the error handling logic!

Patch:
diff --git a/Dockerfile b/Dockerfile
index c697f0c1c6..03f76f39b8 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -9,6 +9,6 @@ RUN apt-get install -y build-essential
 RUN apt-get install -y libhdf5-dev libgles2-mesa-dev
 
 RUN python -m pip install --upgrade pip
-RUN python -m pip install \
-    -r https://raw.githubusercontent.com/pandas-dev/pandas/main/requirements-dev.txt
+COPY requirements-dev.txt /tmp
+RUN python -m pip install -r /tmp/requirements-dev.txt
 CMD ["/bin/bash"]
diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 4b8e632f32..3c46cb39ee 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -65,1236 +65,1217 @@ fi
 ### DOCSTRINGS ###
 if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
 
-    PARAMETERS=(\
-        --format=actions\
-        --errors=EX01,EX03,EX04,GL01,GL02,GL03,GL04,GL05,GL06,GL07,GL08,GL09,GL10,PD01,PR01,PR02,PR03,PR04,PR05,PR06,PR07,PR08,PR09,PR10,RT01,RT02,RT03,RT04,RT05,SA01,SA02,SA03,SA04,SA05,SS01,SS02,SS03,SS04,SS05,SS06\
-        --ignore_errors pandas.Categorical.__array__ SA01\
-        --ignore_errors pandas.Categorical.codes SA01\
-        --ignore_errors pandas.Categorical.dtype SA01\
-        --ignore_errors pandas.Categorical.from_codes SA01\
-        --ignore_errors pandas.Categorical.ordered SA01\
-        --ignore_errors pandas.CategoricalDtype.categories SA01\
-        --ignore_errors pandas.CategoricalDtype.ordered SA01\
-        --ignore_errors pandas.CategoricalIndex.codes SA01\
-        --ignore_errors pandas.CategoricalIndex.ordered SA01\
-        --ignore_errors pandas.DataFrame.__dataframe__ SA01\
-        --ignore_errors pandas.DataFrame.__iter__ SA01\
-        --ignore_errors pandas.DataFrame.assign SA01\
-        --ignore_errors pandas.DataFrame.at_time PR01\
-        --ignore_errors pandas.DataFrame.axes SA01\
-        --ignore_errors pandas.DataFrame.backfill PR01,SA01\
-        --ignore_errors pandas.DataFrame.bfill SA01\
-        --ignore_errors pandas.DataFrame.columns SA01\
-        --ignore_errors pandas.DataFrame.copy SA01\
-        --ignore_errors pandas.DataFrame.droplevel SA01\
-        --ignore_errors pandas.DataFrame.dtypes SA01\
-        --ignore_errors pandas.DataFrame.ffill SA01\
-        --ignore_errors pandas.DataFrame.first_valid_index SA01\
-        --ignore_errors pandas.DataFrame.get PR01,SA01\
-        --ignore_errors pandas.DataFrame.hist RT03\
-        --ignore_errors pandas.DataFrame.infer_objects RT03\
-        --ignore_errors pandas.DataFrame.keys SA01\
-        --ignore_errors pandas.DataFrame.kurt RT03,SA01\
-        --ignore_errors pandas.DataFrame.kurtosis RT03,SA01\
-        --ignore_errors pandas.DataFrame.last_valid_index SA01\
-        --ignore_errors pandas.DataFrame.mask RT03\
-        --ignore_errors pandas.DataFrame.max RT03\
-        --ignore_errors pandas.DataFrame.mean RT03,SA01\
-        --ignore_errors pandas.DataFrame.median RT03,SA01\
-        --ignore_errors pandas.DataFrame.min RT03\
-        --ignore_errors pandas.DataFrame.pad PR01,SA01\
-        --ignore_errors pandas.DataFrame.plot PR02,SA01\
-        --ignore_errors pandas.DataFrame.pop SA01\
-        --ignore_errors pandas.DataFrame.prod RT03\
-        --ignore_errors pandas.DataFrame.product RT03\
-        --ignore_errors pandas.DataFrame.reorder_levels SA01\
-        --ignore_errors pandas.DataFrame.sem PR01,RT03,SA01\
-        --ignore_errors pandas.DataFrame.skew RT03,SA01\
-        --ignore_errors pandas.DataFrame.sparse PR01,SA01\
-        --ignore_errors pandas.DataFrame.sparse.density SA01\
-        --ignore_errors pandas.DataFrame.sparse.from_spmatrix SA01\
-        --ignore_errors pandas.DataFrame.sparse.to_coo SA01\
-        --ignore_errors pandas.DataFrame.sparse.to_dense SA01\
-        --ignore_errors pandas.DataFrame.std PR01,RT03,SA01\
-        --ignore_errors pandas.DataFrame.sum RT03\
-        --ignore_errors pandas.DataFrame.swapaxes PR01,SA01\
-        --ignore_errors pandas.DataFrame.swaplevel SA01\
-        --ignore_errors pandas.DataFrame.to_feather SA01\
-        --ignore_errors pandas.DataFrame.to_markdown SA01\
-        --ignore_errors pandas.DataFrame.to_parquet RT03\
-        --ignore_errors pandas.DataFrame.to_period SA01\
-        --ignore_errors pandas.DataFrame.to_timestamp SA01\
-        --ignore_errors pandas.DataFrame.tz_convert SA01\
-        --ignore_errors pandas.DataFrame.tz_localize SA01\
-        --ignore_errors pandas.DataFrame.unstack RT03\
-        --ignore_errors pandas.DataFrame.value_counts RT03\
-        --ignore_errors pandas.DataFrame.var PR01,RT03,SA01\
-        --ignore_errors pandas.DataFrame.where RT03\
-        --ignore_errors pandas.DatetimeIndex.ceil SA01\
-        --ignore_errors pandas.DatetimeIndex.date SA01\
-        --ignore_errors pandas.DatetimeIndex.day SA01\
-        --ignore_errors pandas.DatetimeIndex.day_name SA01\
-        --ignore_errors pandas.DatetimeIndex.day_of_year SA01\
-        --ignore_errors pandas.DatetimeIndex.dayofyear SA01\
-        --ignore_errors pandas.DatetimeIndex.floor SA01\
-        --ignore_errors pandas.DatetimeIndex.freqstr SA01\
-        --ignore_errors pandas.DatetimeIndex.hour SA01\
-        --ignore_errors pandas.DatetimeIndex.indexer_at_time PR01,RT03\
-        --ignore_errors pandas.DatetimeIndex.indexer_between_time RT03\
-        --ignore_errors pandas.DatetimeIndex.inferred_freq SA01\
-        --ignore_errors pandas.DatetimeIndex.is_leap_year SA01\
-        --ignore_errors pandas.DatetimeIndex.microsecond SA01\
-        --ignore_errors pandas.DatetimeIndex.minute SA01\
-        --ignore_errors pandas.DatetimeIndex.month SA01\
-        --ignore_errors pandas.DatetimeIndex.month_name SA01\
-        --ignore_errors pandas.DatetimeIndex.nanosecond SA01\
-        --ignore_errors pandas.DatetimeIndex.quarter SA01\
-        --ignore_errors pandas.DatetimeIndex.round SA01\
-        --ignore_errors pandas.DatetimeIndex.second SA01\
-        --ignore_errors pandas.DatetimeIndex.snap PR01,RT03,SA01\
-        --ignore_errors pandas.DatetimeIndex.std PR01,RT03\
-        --ignore_errors pandas.DatetimeIndex.time SA01\
-        --ignore_errors pandas.DatetimeIndex.timetz SA01\
-        --ignore_errors pandas.DatetimeIndex.to_period RT03\
-        --ignore_errors pandas.DatetimeIndex.to_pydatetime RT03,SA01\
-        --ignore_errors pandas.DatetimeIndex.tz SA01\
-        --ignore_errors pandas.DatetimeIndex.tz_convert RT03\
-        --ignore_errors pandas.DatetimeIndex.year SA01\
-        --ignore_errors pandas.DatetimeTZDtype SA01\
-        --ignore_errors pandas.DatetimeTZDtype.tz SA01\
-        --ignore_errors pandas.DatetimeTZDtype.unit SA01\
-        --ignore_errors pandas.ExcelFile PR01,SA01\
-        --ignore_errors pandas.ExcelFile.parse PR01,SA01\
-        --ignore_errors pandas.ExcelWriter SA01\
-        --ignore_errors pandas.Flags SA01\
-        --ignore_errors pandas.Float32Dtype SA01\
-        --ignore_errors pandas.Float64Dtype SA01\
-        --ignore_errors pandas.Grouper PR02,SA01\
-        --ignore_errors pandas.HDFStore.append PR01,SA01\
-        --ignore_errors pandas.HDFStore.get SA01\
-        --ignore_errors pandas.HDFStore.groups SA01\
-        --ignore_errors pandas.HDFStore.info RT03,SA01\
-        --ignore_errors pandas.HDFStore.keys SA01\
-        --ignore_errors pandas.HDFStore.put PR01,SA01\
-        --ignore_errors pandas.HDFStore.select SA01\
-        --ignore_errors pandas.HDFStore.walk SA01\
-        --ignore_errors pandas.Index PR07\
-        --ignore_errors pandas.Index.T SA01\
-        --ignore_errors pandas.Index.append PR07,RT03,SA01\
-        --ignore_errors pandas.Index.astype SA01\
-        --ignore_errors pandas.Index.copy PR07,SA01\
-        --ignore_errors pandas.Index.difference PR07,RT03,SA01\
-        --ignore_errors pandas.Index.drop PR07,SA01\
-        --ignore_errors pandas.Index.drop_duplicates RT03\
-        --ignore_errors pandas.Index.droplevel RT03,SA01\
-        --ignore_errors pandas.Index.dropna RT03,SA01\
-        --ignore_errors pandas.Index.dtype SA01\
-        --ignore_errors pandas.Index.duplicated RT03\
-        --ignore_errors pandas.Index.empty GL08\
-        --ignore_errors pandas.Index.equals SA01\
-        --ignore_errors pandas.Index.fillna RT03\
-        --ignore_errors pandas.Index.get_indexer PR07,SA01\
-        --ignore_errors pandas.Index.get_indexer_for PR01,SA01\
-        --ignore_errors pandas.Index.get_indexer_non_unique PR07,SA01\
-        --ignore_errors pandas.Index.get_loc PR07,RT03,SA01\
-        --ignore_errors pandas.Index.get_slice_bound PR07\
-        --ignore_errors pandas.Index.hasnans SA01\
-        --ignore_errors pandas.Index.identical PR01,SA01\
-        --ignore_errors pandas.Index.inferred_type SA01\
-        --ignore_errors pandas.Index.insert PR07,RT03,SA01\
-        --ignore_errors pandas.Index.intersection PR07,RT03,SA01\
-        --ignore_errors pandas.Index.item SA01\
-        --ignore_errors pandas.Index.join PR07,RT03,SA01\
-        --ignore_errors pandas.Index.map SA01\
-        --ignore_errors pandas.Index.memory_usage RT03\
-        --ignore_errors pandas.Index.name SA01\
-        --ignore_errors pandas.Index.names GL08\
-        --ignore_errors pandas.Index.nbytes SA01\
-        --ignore_errors pandas.Index.ndim SA01\
-        --ignore_errors pandas.Index.nunique RT03\
-        --ignore_errors pandas.Index.putmask PR01,RT03\
-        --ignore_errors pandas.Index.ravel PR01,RT03\
-        --ignore_errors pandas.Index.reindex PR07\
-        --ignore_errors pandas.Index.shape SA01\
-        --ignore_errors pandas.Index.size SA01\
-        --ignore_errors pandas.Index.slice_indexer PR07,RT03,SA01\
-        --ignore_errors pandas.Index.slice_locs RT03\
-        --ignore_errors pandas.Index.str PR01,SA01\
-        --ignore_errors pandas.Index.symmetric_difference PR07,RT03,SA01\
-        --ignore_errors pandas.Index.take PR01,PR07\
-        --ignore_errors pandas.Index.to_list RT03\
-        --ignore_errors pandas.Index.union PR07,RT03,SA01\
-        --ignore_errors pandas.Index.unique RT03\
-        --ignore_errors pandas.Index.value_counts RT03\
-        --ignore_errors pandas.Index.view GL08\
-        --ignore_errors pandas.Int16Dtype SA01\
-        --ignore_errors pandas.Int32Dtype SA01\
-        --ignore_errors pandas.Int64Dtype SA01\
-        --ignore_errors pandas.Int8Dtype SA01\
-        --ignore_errors pandas.Interval PR02\
-        --ignore_errors pandas.Interval.closed SA01\
-        --ignore_errors pandas.Interval.left SA01\
-        --ignore_errors pandas.Interval.mid SA01\
-        --ignore_errors pandas.Interval.right SA01\
-        --ignore_errors pandas.IntervalDtype PR01,SA01\
-        --ignore_errors pandas.IntervalDtype.subtype SA01\
-        --ignore_errors pandas.IntervalIndex.closed SA01\
-        --ignore_errors pandas.IntervalIndex.contains RT03\
-        --ignore_errors pandas.IntervalIndex.get_indexer PR07,SA01\
-        --ignore_errors pandas.IntervalIndex.get_loc PR07,RT03,SA01\
-        --ignore_errors pandas.IntervalIndex.is_non_overlapping_monotonic SA01\
-        --ignore_errors pandas.IntervalIndex.left GL08\
-        --ignore_errors pandas.IntervalIndex.length GL08\
-        --ignore_errors pandas.IntervalIndex.mid GL08\
-        --ignore_errors pandas.IntervalIndex.right GL08\
-        --ignore_errors pandas.IntervalIndex.set_closed RT03,SA01\
-        --ignore_errors pandas.IntervalIndex.to_tuples RT03,SA01\
-        --ignore_errors pandas.MultiIndex PR01\
-        --ignore_errors pandas.MultiIndex.append PR07,SA01\
-        --ignore_errors pandas.MultiIndex.copy PR07,RT03,SA01\
-        --ignore_errors pandas.MultiIndex.drop PR07,RT03,SA01\
-        --ignore_errors pandas.MultiIndex.droplevel RT03,SA01\
-        --ignore_errors pandas.MultiIndex.dtypes SA01\
-        --ignore_errors pandas.MultiIndex.get_indexer PR07,SA01\
-        --ignore_errors pandas.MultiIndex.get_level_values SA01\
-        --ignore_errors pandas.MultiIndex.get_loc PR07\
-        --ignore_errors pandas.MultiIndex.get_loc_level PR07\
-        --ignore_errors pandas.MultiIndex.levels SA01\
-        --ignore_errors pandas.MultiIndex.levshape SA01\
-        --ignore_errors pandas.MultiIndex.names SA01\
-        --ignore_errors pandas.MultiIndex.nlevels SA01\
-        --ignore_errors pandas.MultiIndex.remove_unused_levels RT03,SA01\
-        --ignore_errors pandas.MultiIndex.reorder_levels RT03,SA01\
-        --ignore_errors pandas.MultiIndex.set_codes SA01\
-        --ignore_errors pandas.MultiIndex.set_levels RT03,SA01\
-        --ignore_errors pandas.MultiIndex.sortlevel PR07,SA01\
-        --ignore_errors pandas.MultiIndex.to_frame RT03\
-        --ignore_errors pandas.MultiIndex.truncate SA01\
-        --ignore_errors pandas.NA SA01\
-        --ignore_errors pandas.NaT SA01\
-        --ignore_errors pandas.NamedAgg SA01\
-        --ignore_errors pandas.Period SA01\
-        --ignore_errors pandas.Period.asfreq SA01\
-        --ignore_errors pandas.Period.freq GL08\
-        --ignore_errors pandas.Period.freqstr SA01\
-        --ignore_errors pandas.Period.is_leap_year SA01\
-        --ignore_errors pandas.Period.month SA01\
-        --ignore_errors pandas.Period.now SA01\
-        --ignore_errors pandas.Period.ordinal GL08\
-        --ignore_errors pandas.Period.quarter SA01\
-        --ignore_errors pandas.Period.strftime PR01,SA01\
-        --ignore_errors pandas.Period.to_timestamp SA01\
-        --ignore_errors pandas.Period.year SA01\
-        --ignore_errors pandas.PeriodDtype SA01\
-        --ignore_errors pandas.PeriodDtype.freq SA01\
-        --ignore_errors pandas.PeriodIndex.day SA01\
-        --ignore_errors pandas.PeriodIndex.day_of_week SA01\
-        --ignore_errors pandas.PeriodIndex.day_of_year SA01\
-        --ignore_errors pandas.PeriodIndex.dayofweek SA01\
-        --ignore_errors pandas.PeriodIndex.dayofyear SA01\
-        --ignore_errors pandas.PeriodIndex.days_in_month SA01\
-        --ignore_errors pandas.PeriodIndex.daysinmonth SA01\
-        --ignore_errors pandas.PeriodIndex.freq GL08\
-        --ignore_errors pandas.PeriodIndex.freqstr SA01\
-        --ignore_errors pandas.PeriodIndex.from_fields PR07,SA01\
-        --ignore_errors pandas.PeriodIndex.from_ordinals SA01\
-        --ignore_errors pandas.PeriodIndex.hour SA01\
-        --ignore_errors pandas.PeriodIndex.is_leap_year SA01\
-        --ignore_errors pandas.PeriodIndex.minute SA01\
-        --ignore_errors pandas.PeriodIndex.month SA01\
-        --ignore_errors pandas.PeriodIndex.quarter SA01\
-        --ignore_errors pandas.PeriodIndex.qyear GL08\
-        --ignore_errors pandas.PeriodIndex.second SA01\
-        --ignore_errors pandas.PeriodIndex.to_timestamp RT03,SA01\
-        --ignore_errors pandas.PeriodIndex.week SA01\
-        --ignore_errors pandas.PeriodIndex.weekday SA01\
-        --ignore_errors pandas.PeriodIndex.weekofyear SA01\
-        --ignore_errors pandas.PeriodIndex.year SA01\
-        --ignore_errors pandas.RangeIndex PR07\
-        --ignore_errors pandas.RangeIndex.from_range PR01,SA01\
-        --ignore_errors pandas.RangeIndex.start SA01\
-        --ignore_errors pandas.RangeIndex.step SA01\
-        --ignore_errors pandas.RangeIndex.stop SA01\
-        --ignore_errors pandas.Series SA01\
-        --ignore_errors pandas.Series.T SA01\
-        --ignore_errors pandas.Series.__iter__ RT03,SA01\
-        --ignore_errors pandas.Series.add PR07\
-        --ignore_errors pandas.Series.align PR07,SA01\
-        --ignore_errors pandas.Series.astype RT03\
-        --ignore_errors pandas.Series.at_time PR01,RT03\
-        --ignore_errors pandas.Series.backfill PR01,SA01\
-        --ignore_errors pandas.Series.bfill SA01\
-        --ignore_errors pandas.Series.case_when RT03\
-        --ignore_errors pandas.Series.cat PR07,SA01\
-        --ignore_errors pandas.Series.cat.add_categories PR01,PR02\
-        --ignore_errors pandas.Series.cat.as_ordered PR01\
-        --ignore_errors pandas.Series.cat.as_unordered PR01\
-        --ignore_errors pandas.Series.cat.codes SA01\
-        --ignore_errors pandas.Series.cat.ordered SA01\
-        --ignore_errors pandas.Series.cat.remove_categories PR01,PR02\
-        --ignore_errors pandas.Series.cat.remove_unused_categories PR01\
-        --ignore_errors pandas.Series.cat.rename_categories PR01,PR02\
-        --ignore_errors pandas.Series.cat.reorder_categories PR01,PR02\
-        --ignore_errors pandas.Series.cat.set_categories PR01,PR02,RT03\
-        --ignore_errors pandas.Series.copy SA01\
-        --ignore_errors pandas.Series.div PR07\
-        --ignore_errors pandas.Series.droplevel SA01\
-        --ignore_errors pandas.Series.dt PR01`# Accessors are implemented as classes, but we do not document the Parameters section` \
-        --ignore_errors pandas.Series.dt.as_unit GL08,PR01,PR02\
-        --ignore_errors pandas.Series.dt.ceil PR01,PR02,SA01\
-        --ignore_errors pandas.Series.dt.components SA01\
-        --ignore_errors pandas.Series.dt.date SA01\
-        --ignore_errors pandas.Series.dt.day SA01\
-        --ignore_errors pandas.Series.dt.day_name PR01,PR02,SA01\
-        --ignore_errors pandas.Series.dt.day_of_year SA01\
-        --ignore_errors pandas.Series.dt.dayofyear SA01\
-        --ignore_errors pandas.Series.dt.days SA01\
-        --ignore_errors pandas.Series.dt.days_in_month SA01\
-        --ignore_errors pandas.Series.dt.daysinmonth SA01\
-        --ignore_errors pandas.Series.dt.floor PR01,PR02,SA01\
-        --ignore_errors pandas.Series.dt.freq GL08\
-        --ignore_errors pandas.Series.dt.hour SA01\
-        --ignore_errors pandas.Series.dt.is_leap_year SA01\
-        --ignore_errors pandas.Series.dt.microsecond SA01\
-        --ignore_errors pandas.Series.dt.microseconds SA01\
-        --ignore_errors pandas.Series.dt.minute SA01\
-        --ignore_errors pandas.Series.dt.month SA01\
-        --ignore_errors pandas.Series.dt.month_name PR01,PR02,SA01\
-        --ignore_errors pandas.Series.dt.nanosecond SA01\
-        --ignore_errors pandas.Series.dt.nanoseconds SA01\
-        --ignore_errors pandas.Series.dt.normalize PR01\
-        --ignore_errors pandas.Series.dt.quarter SA01\
-        --ignore_errors pandas.Series.dt.qyear GL08\
-        --ignore_errors pandas.Series.dt.round PR01,PR02,SA01\
-        --ignore_errors pandas.Series.dt.second SA01\
-        --ignore_errors pandas.Series.dt.seconds SA01\
-        --ignore_errors pandas.Series.dt.strftime PR01,PR02\
-        --ignore_errors pandas.Series.dt.time SA01\
-        --ignore_errors pandas.Series.dt.timetz SA01\
-        --ignore_errors pandas.Series.dt.to_period PR01,PR02,RT03\
-        --ignore_errors pandas.Series.dt.total_seconds PR01\
-        --ignore_errors pandas.Series.dt.tz SA01\
-        --ignore_errors pandas.Series.dt.tz_convert PR01,PR02,RT03\
-        --ignore_errors pandas.Series.dt.tz_localize PR01,PR02\
-        --ignore_errors pandas.Series.dt.unit GL08\
-        --ignore_errors pandas.Series.dt.year SA01\
-        --ignore_errors pandas.Series.dtype SA01\
-        --ignore_errors pandas.Series.dtypes SA01\
-        --ignore_errors pandas.Series.empty GL08\
-        --ignore_errors pandas.Series.eq PR07,SA01\
-        --ignore_errors pandas.Series.ewm RT03\
-        --ignore_errors pandas.Series.expanding RT03\
-        --ignore_errors pandas.Series.ffill SA01\
-        --ignore_errors pandas.Series.filter RT03\
-        --ignore_errors pandas.Series.first_valid_index RT03,SA01\
-        --ignore_errors pandas.Series.floordiv PR07\
-        --ignore_errors pandas.Series.ge PR07,SA01\
-        --ignore_errors pandas.Series.get PR01,PR07,RT03,SA01\
-        --ignore_errors pandas.Series.gt PR07,SA01\
-        --ignore_errors pandas.Series.hasnans SA01\
-        --ignore_errors pandas.Series.infer_objects RT03\
-        --ignore_errors pandas.Series.is_monotonic_decreasing SA01\
-        --ignore_errors pandas.Series.is_monotonic_increasing SA01\
-        --ignore_errors pandas.Series.is_unique SA01\
-        --ignore_errors pandas.Series.item SA01\
-        --ignore_errors pandas.Series.keys SA01\
-        --ignore_errors pandas.Series.kurt RT03,SA01\
-        --ignore_errors pandas.Series.kurtosis RT03,SA01\
-        --ignore_errors pandas.Series.last_valid_index RT03,SA01\
-        --ignore_errors pandas.Series.le PR07,SA01\
-        --ignore_errors pandas.Series.list.__getitem__ SA01\
-        --ignore_errors pandas.Series.list.flatten SA01\
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-        --ignore_errors pandas.errors.UndefinedVariableError PR01,SA01\
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-        --ignore_errors pandas.io.formats.style.Styler.apply RT03\
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-        --ignore_errors pandas.io.formats.style.Styler.bar RT03,SA01\
-        --ignore_errors pandas.io.formats.style.Styler.clear SA01\
-        --ignore_errors pandas.io.formats.style.Styler.concat RT03,SA01\
-        --ignore_errors pandas.io.formats.style.Styler.export RT03\
-        --ignore_errors pandas.io.formats.style.Styler.format RT03\
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-        --ignore_errors pandas.io.formats.style.Styler.from_custom_template SA01\
-        --ignore_errors pandas.io.formats.style.Styler.hide RT03,SA01\
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-        --ignore_errors pandas.io.formats.style.Styler.set_caption RT03,SA01\
-        --ignore_errors pandas.io.formats.style.Styler.set_properties RT03,SA01\
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-        --ignore_errors pandas.io.formats.style.Styler.to_excel PR01\
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-        --ignore_errors pandas.tseries.offsets.BusinessHour PR02,SA01\
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-        --ignore_errors pandas.tseries.offsets.BusinessHour.copy SA01\
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-        --ignore_errors pandas.tseries.offsets.BusinessMonthBegin PR02\
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-        --ignore_errors pandas.tseries.offsets.BusinessMonthBegin.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.BusinessMonthEnd PR02\
-        --ignore_errors pandas.tseries.offsets.BusinessMonthEnd.copy SA01\
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-        --ignore_errors pandas.tseries.offsets.BusinessMonthEnd.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.CBMonthBegin PR02\
-        --ignore_errors pandas.tseries.offsets.CBMonthEnd PR02\
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-        --ignore_errors pandas.tseries.offsets.CustomBusinessDay PR02,SA01\
-        --ignore_errors pandas.tseries.offsets.CustomBusinessDay.calendar GL08\
-        --ignore_errors pandas.tseries.offsets.CustomBusinessDay.copy SA01\
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-        --ignore_errors pandas.tseries.offsets.CustomBusinessHour PR02,SA01\
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-        --ignore_errors pandas.tseries.offsets.CustomBusinessHour.copy SA01\
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-        --ignore_errors pandas.tseries.offsets.CustomBusinessHour.freqstr SA01\
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-        --ignore_errors pandas.tseries.offsets.CustomBusinessHour.start GL08\
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-        --ignore_errors pandas.tseries.offsets.CustomBusinessMonthBegin PR02\
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-        --ignore_errors pandas.tseries.offsets.CustomBusinessMonthBegin.copy SA01\
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-        --ignore_errors pandas.tseries.offsets.CustomBusinessMonthEnd PR02\
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-        --ignore_errors pandas.tseries.offsets.Day PR02\
-        --ignore_errors pandas.tseries.offsets.Day.copy SA01\
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-        --ignore_errors pandas.tseries.offsets.Micro.normalize GL08\
-        --ignore_errors pandas.tseries.offsets.Micro.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.Milli PR02\
-        --ignore_errors pandas.tseries.offsets.Milli.copy SA01\
-        --ignore_errors pandas.tseries.offsets.Milli.delta GL08\
-        --ignore_errors pandas.tseries.offsets.Milli.freqstr SA01\
-        --ignore_errors pandas.tseries.offsets.Milli.is_on_offset GL08\
-        --ignore_errors pandas.tseries.offsets.Milli.kwds SA01\
-        --ignore_errors pandas.tseries.offsets.Milli.n GL08\
-        --ignore_errors pandas.tseries.offsets.Milli.name SA01\
-        --ignore_errors pandas.tseries.offsets.Milli.nanos SA01\
-        --ignore_errors pandas.tseries.offsets.Milli.normalize GL08\
-        --ignore_errors pandas.tseries.offsets.Milli.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.Minute PR02\
-        --ignore_errors pandas.tseries.offsets.Minute.copy SA01\
-        --ignore_errors pandas.tseries.offsets.Minute.delta GL08\
-        --ignore_errors pandas.tseries.offsets.Minute.freqstr SA01\
-        --ignore_errors pandas.tseries.offsets.Minute.is_on_offset GL08\
-        --ignore_errors pandas.tseries.offsets.Minute.kwds SA01\
-        --ignore_errors pandas.tseries.offsets.Minute.n GL08\
-        --ignore_errors pandas.tseries.offsets.Minute.name SA01\
-        --ignore_errors pandas.tseries.offsets.Minute.nanos SA01\
-        --ignore_errors pandas.tseries.offsets.Minute.normalize GL08\
-        --ignore_errors pandas.tseries.offsets.Minute.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.MonthBegin PR02\
-        --ignore_errors pandas.tseries.offsets.MonthBegin.copy SA01\
-        --ignore_errors pandas.tseries.offsets.MonthBegin.freqstr SA01\
-        --ignore_errors pandas.tseries.offsets.MonthBegin.is_on_offset GL08\
-        --ignore_errors pandas.tseries.offsets.MonthBegin.kwds SA01\
-        --ignore_errors pandas.tseries.offsets.MonthBegin.n GL08\
-        --ignore_errors pandas.tseries.offsets.MonthBegin.name SA01\
-        --ignore_errors pandas.tseries.offsets.MonthBegin.nanos GL08\
-        --ignore_errors pandas.tseries.offsets.MonthBegin.normalize GL08\
-        --ignore_errors pandas.tseries.offsets.MonthBegin.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.MonthEnd PR02\
-        --ignore_errors pandas.tseries.offsets.MonthEnd.copy SA01\
-        --ignore_errors pandas.tseries.offsets.MonthEnd.freqstr SA01\
-        --ignore_errors pandas.tseries.offsets.MonthEnd.is_on_offset GL08\
-        --ignore_errors pandas.tseries.offsets.MonthEnd.kwds SA01\
-        --ignore_errors pandas.tseries.offsets.MonthEnd.n GL08\
-        --ignore_errors pandas.tseries.offsets.MonthEnd.name SA01\
-        --ignore_errors pandas.tseries.offsets.MonthEnd.nanos GL08\
-        --ignore_errors pandas.tseries.offsets.MonthEnd.normalize GL08\
-        --ignore_errors pandas.tseries.offsets.MonthEnd.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.Nano PR02\
-        --ignore_errors pandas.tseries.offsets.Nano.copy SA01\
-        --ignore_errors pandas.tseries.offsets.Nano.delta GL08\
-        --ignore_errors pandas.tseries.offsets.Nano.freqstr SA01\
-        --ignore_errors pandas.tseries.offsets.Nano.is_on_offset GL08\
-        --ignore_errors pandas.tseries.offsets.Nano.kwds SA01\
-        --ignore_errors pandas.tseries.offsets.Nano.n GL08\
-        --ignore_errors pandas.tseries.offsets.Nano.name SA01\
-        --ignore_errors pandas.tseries.offsets.Nano.nanos SA01\
-        --ignore_errors pandas.tseries.offsets.Nano.normalize GL08\
-        --ignore_errors pandas.tseries.offsets.Nano.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.QuarterBegin PR02\
-        --ignore_errors pandas.tseries.offsets.QuarterBegin.copy SA01\
-        --ignore_errors pandas.tseries.offsets.QuarterBegin.freqstr SA01\
-        --ignore_errors pandas.tseries.offsets.QuarterBegin.is_on_offset GL08\
-        --ignore_errors pandas.tseries.offsets.QuarterBegin.kwds SA01\
-        --ignore_errors pandas.tseries.offsets.QuarterBegin.n GL08\
-        --ignore_errors pandas.tseries.offsets.QuarterBegin.name SA01\
-        --ignore_errors pandas.tseries.offsets.QuarterBegin.nanos GL08\
-        --ignore_errors pandas.tseries.offsets.QuarterBegin.normalize GL08\
-        --ignore_errors pandas.tseries.offsets.QuarterBegin.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.QuarterBegin.startingMonth GL08\
-        --ignore_errors pandas.tseries.offsets.QuarterEnd PR02\
-        --ignore_errors pandas.tseries.offsets.QuarterEnd.copy SA01\
-        --ignore_errors pandas.tseries.offsets.QuarterEnd.freqstr SA01\
-        --ignore_errors pandas.tseries.offsets.QuarterEnd.is_on_offset GL08\
-        --ignore_errors pandas.tseries.offsets.QuarterEnd.kwds SA01\
-        --ignore_errors pandas.tseries.offsets.QuarterEnd.n GL08\
-        --ignore_errors pandas.tseries.offsets.QuarterEnd.name SA01\
-        --ignore_errors pandas.tseries.offsets.QuarterEnd.nanos GL08\
-        --ignore_errors pandas.tseries.offsets.QuarterEnd.normalize GL08\
-        --ignore_errors pandas.tseries.offsets.QuarterEnd.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.QuarterEnd.startingMonth GL08\
-        --ignore_errors pandas.tseries.offsets.Second PR02\
-        --ignore_errors pandas.tseries.offsets.Second.copy SA01\
-        --ignore_errors pandas.tseries.offsets.Second.delta GL08\
-        --ignore_errors pandas.tseries.offsets.Second.freqstr SA01\
-        --ignore_errors pandas.tseries.offsets.Second.is_on_offset GL08\
-        --ignore_errors pandas.tseries.offsets.Second.kwds SA01\
-        --ignore_errors pandas.tseries.offsets.Second.n GL08\
-        --ignore_errors pandas.tseries.offsets.Second.name SA01\
-        --ignore_errors pandas.tseries.offsets.Second.nanos SA01\
-        --ignore_errors pandas.tseries.offsets.Second.normalize GL08\
-        --ignore_errors pandas.tseries.offsets.Second.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.SemiMonthBegin PR02,SA01\
-        --ignore_errors pandas.tseries.offsets.SemiMonthBegin.copy SA01\
-        --ignore_errors pandas.tseries.offsets.SemiMonthBegin.day_of_month GL08\
-        --ignore_errors pandas.tseries.offsets.SemiMonthBegin.freqstr SA01\
-        --ignore_errors pandas.tseries.offsets.SemiMonthBegin.is_on_offset GL08\
-        --ignore_errors pandas.tseries.offsets.SemiMonthBegin.kwds SA01\
-        --ignore_errors pandas.tseries.offsets.SemiMonthBegin.n GL08\
-        --ignore_errors pandas.tseries.offsets.SemiMonthBegin.name SA01\
-        --ignore_errors pandas.tseries.offsets.SemiMonthBegin.nanos GL08\
-        --ignore_errors pandas.tseries.offsets.SemiMonthBegin.normalize GL08\
-        --ignore_errors pandas.tseries.offsets.SemiMonthBegin.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.SemiMonthEnd PR02,SA01\
-        --ignore_errors pandas.tseries.offsets.SemiMonthEnd.copy SA01\
-        --ignore_errors pandas.tseries.offsets.SemiMonthEnd.day_of_month GL08\
-        --ignore_errors pandas.tseries.offsets.SemiMonthEnd.freqstr SA01\
-        --ignore_errors pandas.tseries.offsets.SemiMonthEnd.is_on_offset GL08\
-        --ignore_errors pandas.tseries.offsets.SemiMonthEnd.kwds SA01\
-        --ignore_errors pandas.tseries.offsets.SemiMonthEnd.n GL08\
-        --ignore_errors pandas.tseries.offsets.SemiMonthEnd.name SA01\
-        --ignore_errors pandas.tseries.offsets.SemiMonthEnd.nanos GL08\
-        --ignore_errors pandas.tseries.offsets.SemiMonthEnd.normalize GL08\
-        --ignore_errors pandas.tseries.offsets.SemiMonthEnd.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.Tick GL08\
-        --ignore_errors pandas.tseries.offsets.Tick.copy SA01\
-        --ignore_errors pandas.tseries.offsets.Tick.delta GL08\
-        --ignore_errors pandas.tseries.offsets.Tick.freqstr SA01\
-        --ignore_errors pandas.tseries.offsets.Tick.is_on_offset GL08\
-        --ignore_errors pandas.tseries.offsets.Tick.kwds SA01\
-        --ignore_errors pandas.tseries.offsets.Tick.n GL08\
-        --ignore_errors pandas.tseries.offsets.Tick.name SA01\
-        --ignore_errors pandas.tseries.offsets.Tick.nanos SA01\
-        --ignore_errors pandas.tseries.offsets.Tick.normalize GL08\
-        --ignore_errors pandas.tseries.offsets.Tick.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.Week PR02\
-        --ignore_errors pandas.tseries.offsets.Week.copy SA01\
-        --ignore_errors pandas.tseries.offsets.Week.freqstr SA01\
-        --ignore_errors pandas.tseries.offsets.Week.is_on_offset GL08\
-        --ignore_errors pandas.tseries.offsets.Week.kwds SA01\
-        --ignore_errors pandas.tseries.offsets.Week.n GL08\
-        --ignore_errors pandas.tseries.offsets.Week.name SA01\
-        --ignore_errors pandas.tseries.offsets.Week.nanos GL08\
-        --ignore_errors pandas.tseries.offsets.Week.normalize GL08\
-        --ignore_errors pandas.tseries.offsets.Week.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.Week.weekday GL08\
-        --ignore_errors pandas.tseries.offsets.WeekOfMonth PR02,SA01\
-        --ignore_errors pandas.tseries.offsets.WeekOfMonth.copy SA01\
-        --ignore_errors pandas.tseries.offsets.WeekOfMonth.freqstr SA01\
-        --ignore_errors pandas.tseries.offsets.WeekOfMonth.is_on_offset GL08\
-        --ignore_errors pandas.tseries.offsets.WeekOfMonth.kwds SA01\
-        --ignore_errors pandas.tseries.offsets.WeekOfMonth.n GL08\
-        --ignore_errors pandas.tseries.offsets.WeekOfMonth.name SA01\
-        --ignore_errors pandas.tseries.offsets.WeekOfMonth.nanos GL08\
-        --ignore_errors pandas.tseries.offsets.WeekOfMonth.normalize GL08\
-        --ignore_errors pandas.tseries.offsets.WeekOfMonth.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.WeekOfMonth.week GL08\
-        --ignore_errors pandas.tseries.offsets.WeekOfMonth.weekday GL08\
-        --ignore_errors pandas.tseries.offsets.YearBegin PR02\
-        --ignore_errors pandas.tseries.offsets.YearBegin.copy SA01\
-        --ignore_errors pandas.tseries.offsets.YearBegin.freqstr SA01\
-        --ignore_errors pandas.tseries.offsets.YearBegin.is_on_offset GL08\
-        --ignore_errors pandas.tseries.offsets.YearBegin.kwds SA01\
-        --ignore_errors pandas.tseries.offsets.YearBegin.month GL08\
-        --ignore_errors pandas.tseries.offsets.YearBegin.n GL08\
-        --ignore_errors pandas.tseries.offsets.YearBegin.name SA01\
-        --ignore_errors pandas.tseries.offsets.YearBegin.nanos GL08\
-        --ignore_errors pandas.tseries.offsets.YearBegin.normalize GL08\
-        --ignore_errors pandas.tseries.offsets.YearBegin.rule_code GL08\
-        --ignore_errors pandas.tseries.offsets.YearEnd PR02\
-        --ignore_errors pandas.tseries.offsets.YearEnd.copy SA01\
-        --ignore_errors pandas.tseries.offsets.YearEnd.freqstr SA01\
-        --ignore_errors pandas.tseries.offsets.YearEnd.is_on_offset GL08\
-        --ignore_errors pandas.tseries.offsets.YearEnd.kwds SA01\
-        --ignore_errors pandas.tseries.offsets.YearEnd.month GL08\
-        --ignore_errors pandas.tseries.offsets.YearEnd.n GL08\
-        --ignore_errors pandas.tseries.offsets.YearEnd.name SA01\
-        --ignore_errors pandas.tseries.offsets.YearEnd.nanos GL08\
-        --ignore_errors pandas.tseries.offsets.YearEnd.normalize GL08\
-        --ignore_errors pandas.tseries.offsets.YearEnd.rule_code GL08\
-        --ignore_errors pandas.unique PR07\
-        --ignore_errors pandas.util.hash_array PR07,SA01\
-        --ignore_errors pandas.util.hash_pandas_object PR07,SA01 # There should be no backslash in the final line, please keep this comment in the last ignored function
-    )
-    $BASE_DIR/scripts/validate_docstrings.py ${PARAMETERS[@]}
-    RET=$(($RET + $?)) ;
+    MSG='Validate Docstrings' ; echo $MSG
+    $BASE_DIR/scripts/validate_docstrings.py \
+        --format=actions \
+        -i '*' ES01 `# For now it is ok if docstrings are missing the extended summary` \
+        -i pandas.Series.dt PR01 `# Accessors are implemented as classes, but we do not document the Parameters section` \
+        -i pandas.Categorical.__array__ SA01\
+        -i pandas.Categorical.codes SA01\
+        -i pandas.Categorical.dtype SA01\
+        -i pandas.Categorical.from_codes SA01\
+        -i pandas.Categorical.ordered SA01\
+        -i pandas.CategoricalDtype.categories SA01\
+        -i pandas.CategoricalDtype.ordered SA01\
+        -i pandas.CategoricalIndex.codes SA01\
+        -i pandas.CategoricalIndex.ordered SA01\
+        -i pandas.DataFrame.__dataframe__ SA01\
+        -i pandas.DataFrame.__iter__ SA01\
+        -i pandas.DataFrame.assign SA01\
+        -i pandas.DataFrame.at_time PR01\
+        -i pandas.DataFrame.axes SA01\
+        -i pandas.DataFrame.backfill PR01,SA01\
+        -i pandas.DataFrame.bfill SA01\
+        -i pandas.DataFrame.columns SA01\
+        -i pandas.DataFrame.copy SA01\
+        -i pandas.DataFrame.droplevel SA01\
+        -i pandas.DataFrame.dtypes SA01\
+        -i pandas.DataFrame.ffill SA01\
+        -i pandas.DataFrame.first_valid_index SA01\
+        -i pandas.DataFrame.get SA01\
+        -i pandas.DataFrame.hist RT03\
+        -i pandas.DataFrame.infer_objects RT03\
+        -i pandas.DataFrame.keys SA01\
+        -i pandas.DataFrame.kurt RT03,SA01\
+        -i pandas.DataFrame.kurtosis RT03,SA01\
+        -i pandas.DataFrame.last_valid_index SA01\
+        -i pandas.DataFrame.mask RT03\
+        -i pandas.DataFrame.max RT03\
+        -i pandas.DataFrame.mean RT03,SA01\
+        -i pandas.DataFrame.median RT03,SA01\
+        -i pandas.DataFrame.min RT03\
+        -i pandas.DataFrame.pad PR01,SA01\
+        -i pandas.DataFrame.plot PR02,SA01\
+        -i pandas.DataFrame.pop SA01\
+        -i pandas.DataFrame.prod RT03\
+        -i pandas.DataFrame.product RT03\
+        -i pandas.DataFrame.reorder_levels SA01\
+        -i pandas.DataFrame.sem PR01,RT03,SA01\
+        -i pandas.DataFrame.skew RT03,SA01\
+        -i pandas.DataFrame.sparse PR01,SA01\
+        -i pandas.DataFrame.sparse.density SA01\
+        -i pandas.DataFrame.sparse.from_spmatrix SA01\
+        -i pandas.DataFrame.sparse.to_coo SA01\
+        -i pandas.DataFrame.sparse.to_dense SA01\
+        -i pandas.DataFrame.std PR01,RT03,SA01\
+        -i pandas.DataFrame.sum RT03\
+        -i pandas.DataFrame.swapaxes PR01,SA01\
+        -i pandas.DataFrame.swaplevel SA01\
+        -i pandas.DataFrame.to_feather SA01\
+        -i pandas.DataFrame.to_markdown SA01\
+        -i pandas.DataFrame.to_parquet RT03\
+        -i pandas.DataFrame.to_period SA01\
+        -i pandas.DataFrame.to_timestamp SA01\
+        -i pandas.DataFrame.tz_convert SA01\
+        -i pandas.DataFrame.tz_localize SA01\
+        -i pandas.DataFrame.unstack RT03\
+        -i pandas.DataFrame.value_counts RT03\
+        -i pandas.DataFrame.var PR01,RT03,SA01\
+        -i pandas.DataFrame.where RT03\
+        -i pandas.DatetimeIndex.ceil SA01\
+        -i pandas.DatetimeIndex.date SA01\
+        -i pandas.DatetimeIndex.day SA01\
+        -i pandas.DatetimeIndex.day_name SA01\
+        -i pandas.DatetimeIndex.day_of_year SA01\
+        -i pandas.DatetimeIndex.dayofyear SA01\
+        -i pandas.DatetimeIndex.floor SA01\
+        -i pandas.DatetimeIndex.freqstr SA01\
+        -i pandas.DatetimeIndex.hour SA01\
+        -i pandas.DatetimeIndex.indexer_at_time PR01,RT03\
+        -i pandas.DatetimeIndex.indexer_between_time RT03\
+        -i pandas.DatetimeIndex.inferred_freq SA01\
+        -i pandas.DatetimeIndex.is_leap_year SA01\
+        -i pandas.DatetimeIndex.microsecond SA01\
+        -i pandas.DatetimeIndex.minute SA01\
+        -i pandas.DatetimeIndex.month SA01\
+        -i pandas.DatetimeIndex.month_name SA01\
+        -i pandas.DatetimeIndex.nanosecond SA01\
+        -i pandas.DatetimeIndex.quarter SA01\
+        -i pandas.DatetimeIndex.round SA01\
+        -i pandas.DatetimeIndex.second SA01\
+        -i pandas.DatetimeIndex.snap PR01,RT03,SA01\
+        -i pandas.DatetimeIndex.std PR01,RT03\
+        -i pandas.DatetimeIndex.time SA01\
+        -i pandas.DatetimeIndex.timetz SA01\
+        -i pandas.DatetimeIndex.to_period RT03\
+        -i pandas.DatetimeIndex.to_pydatetime RT03,SA01\
+        -i pandas.DatetimeIndex.tz SA01\
+        -i pandas.DatetimeIndex.tz_convert RT03\
+        -i pandas.DatetimeIndex.year SA01\
+        -i pandas.DatetimeTZDtype SA01\
+        -i pandas.DatetimeTZDtype.tz SA01\
+        -i pandas.DatetimeTZDtype.unit SA01\
+        -i pandas.ExcelFile PR01,SA01\
+        -i pandas.ExcelFile.parse PR01,SA01\
+        -i pandas.ExcelWriter SA01\
+        -i pandas.Float32Dtype SA01\
+        -i pandas.Float64Dtype SA01\
+        -i pandas.Grouper PR02,SA01\
+        -i pandas.HDFStore.append PR01,SA01\
+        -i pandas.HDFStore.get SA01\
+        -i pandas.HDFStore.groups SA01\
+        -i pandas.HDFStore.info RT03,SA01\
+        -i pandas.HDFStore.keys SA01\
+        -i pandas.HDFStore.put PR01,SA01\
+        -i pandas.HDFStore.select SA01\
+        -i pandas.HDFStore.walk SA01\
+        -i pandas.Index PR07\
+        -i pandas.Index.T SA01\
+        -i pandas.Index.append PR07,RT03,SA01\
+        -i pandas.Index.astype SA01\
+        -i pandas.Index.copy PR07,SA01\
+        -i pandas.Index.difference PR07,RT03,SA01\
+        -i pandas.Index.drop PR07,SA01\
+        -i pandas.Index.drop_duplicates RT03\
+        -i pandas.Index.droplevel RT03,SA01\
+        -i pandas.Index.dropna RT03,SA01\
+        -i pandas.Index.dtype SA01\
+        -i pandas.Index.duplicated RT03\
+        -i pandas.Index.empty GL08\
+        -i pandas.Index.equals SA01\
+        -i pandas.Index.fillna RT03\
+        -i pandas.Index.get_indexer PR07,SA01\
+        -i pandas.Index.get_indexer_for PR01,SA01\
+        -i pandas.Index.get_indexer_non_unique PR07,SA01\
+        -i pandas.Index.get_loc PR07,RT03,SA01\
+        -i pandas.Index.get_slice_bound PR07\
+        -i pandas.Index.hasnans SA01\
+        -i pandas.Index.identical PR01,SA01\
+        -i pandas.Index.inferred_type SA01\
+        -i pandas.Index.insert PR07,RT03,SA01\
+        -i pandas.Index.intersection PR07,RT03,SA01\
+        -i pandas.Index.item SA01\
+        -i pandas.Index.join PR07,RT03,SA01\
+        -i pandas.Index.map SA01\
+        -i pandas.Index.memory_usage RT03\
+        -i pandas.Index.name SA01\
+        -i pandas.Index.names GL08\
+        -i pandas.Index.nbytes SA01\
+        -i pandas.Index.ndim SA01\
+        -i pandas.Index.nunique RT03\
+        -i pandas.Index.putmask PR01,RT03\
+        -i pandas.Index.ravel PR01,RT03\
+        -i pandas.Index.reindex PR07\
+        -i pandas.Index.shape SA01\
+        -i pandas.Index.size SA01\
+        -i pandas.Index.slice_indexer PR07,RT03,SA01\
+        -i pandas.Index.slice_locs RT03\
+        -i pandas.Index.str PR01,SA01\
+        -i pandas.Index.symmetric_difference PR07,RT03,SA01\
+        -i pandas.Index.take PR01,PR07\
+        -i pandas.Index.to_list RT03\
+        -i pandas.Index.union PR07,RT03,SA01\
+        -i pandas.Index.unique RT03\
+        -i pandas.Index.value_counts RT03\
+        -i pandas.Index.view GL08\
+        -i pandas.Int16Dtype SA01\
+        -i pandas.Int32Dtype SA01\
+        -i pandas.Int64Dtype SA01\
+        -i pandas.Int8Dtype SA01\
+        -i pandas.Interval PR02\
+        -i pandas.Interval.closed SA01\
+        -i pandas.Interval.left SA01\
+        -i pandas.Interval.mid SA01\
+        -i pandas.Interval.right SA01\
+        -i pandas.IntervalDtype PR01,SA01\
+        -i pandas.IntervalDtype.subtype SA01\
+        -i pandas.IntervalIndex.closed SA01\
+        -i pandas.IntervalIndex.contains RT03\
+        -i pandas.IntervalIndex.get_indexer PR07,SA01\
+        -i pandas.IntervalIndex.get_loc PR07,RT03,SA01\
+        -i pandas.IntervalIndex.is_non_overlapping_monotonic SA01\
+        -i pandas.IntervalIndex.left GL08\
+        -i pandas.IntervalIndex.length GL08\
+        -i pandas.IntervalIndex.mid GL08\
+        -i pandas.IntervalIndex.right GL08\
+        -i pandas.IntervalIndex.set_closed RT03,SA01\
+        -i pandas.IntervalIndex.to_tuples RT03,SA01\
+        -i pandas.MultiIndex PR01\
+        -i pandas.MultiIndex.append PR07,SA01\
+        -i pandas.MultiIndex.copy PR07,RT03,SA01\
+        -i pandas.MultiIndex.drop PR07,RT03,SA01\
+        -i pandas.MultiIndex.droplevel RT03,SA01\
+        -i pandas.MultiIndex.dtypes SA01\
+        -i pandas.MultiIndex.get_indexer PR07,SA01\
+        -i pandas.MultiIndex.get_level_values SA01\
+        -i pandas.MultiIndex.get_loc PR07\
+        -i pandas.MultiIndex.get_loc_level PR07\
+        -i pandas.MultiIndex.levels SA01\
+        -i pandas.MultiIndex.levshape SA01\
+        -i pandas.MultiIndex.names SA01\
+        -i pandas.MultiIndex.nlevels SA01\
+        -i pandas.MultiIndex.remove_unused_levels RT03,SA01\
+        -i pandas.MultiIndex.reorder_levels RT03,SA01\
+        -i pandas.MultiIndex.set_codes SA01\
+        -i pandas.MultiIndex.set_levels RT03,SA01\
+        -i pandas.MultiIndex.sortlevel PR07,SA01\
+        -i pandas.MultiIndex.to_frame RT03\
+        -i pandas.MultiIndex.truncate SA01\
+        -i pandas.NA SA01\
+        -i pandas.NaT SA01\
+        -i pandas.NamedAgg SA01\
+        -i pandas.Period SA01\
+        -i pandas.Period.asfreq SA01\
+        -i pandas.Period.freq GL08\
+        -i pandas.Period.freqstr SA01\
+        -i pandas.Period.is_leap_year SA01\
+        -i pandas.Period.month SA01\
+        -i pandas.Period.now SA01\
+        -i pandas.Period.ordinal GL08\
+        -i pandas.Period.quarter SA01\
+        -i pandas.Period.strftime PR01,SA01\
+        -i pandas.Period.to_timestamp SA01\
+        -i pandas.Period.year SA01\
+        -i pandas.PeriodDtype SA01\
+        -i pandas.PeriodDtype.freq SA01\
+        -i pandas.PeriodIndex.day SA01\
+        -i pandas.PeriodIndex.day_of_week SA01\
+        -i pandas.PeriodIndex.day_of_year SA01\
+        -i pandas.PeriodIndex.dayofweek SA01\
+        -i pandas.PeriodIndex.dayofyear SA01\
+        -i pandas.PeriodIndex.days_in_month SA01\
+        -i pandas.PeriodIndex.daysinmonth SA01\
+        -i pandas.PeriodIndex.freqstr SA01\
+        -i pandas.PeriodIndex.from_fields PR07,SA01\
+        -i pandas.PeriodIndex.from_ordinals SA01\
+        -i pandas.PeriodIndex.hour SA01\
+        -i pandas.PeriodIndex.is_leap_year SA01\
+        -i pandas.PeriodIndex.minute SA01\
+        -i pandas.PeriodIndex.month SA01\
+        -i pandas.PeriodIndex.quarter SA01\
+        -i pandas.PeriodIndex.qyear GL08\
+        -i pandas.PeriodIndex.second SA01\
+        -i pandas.PeriodIndex.to_timestamp RT03,SA01\
+        -i pandas.PeriodIndex.week SA01\
+        -i pandas.PeriodIndex.weekday SA01\
+        -i pandas.PeriodIndex.weekofyear SA01\
+        -i pandas.PeriodIndex.year SA01\
+        -i pandas.RangeIndex PR07\
+        -i pandas.RangeIndex.from_range PR01,SA01\
+        -i pandas.RangeIndex.start SA01\
+        -i pandas.RangeIndex.step SA01\
+        -i pandas.RangeIndex.stop SA01\
+        -i pandas.Series SA01\
+        -i pandas.Series.T SA01\
+        -i pandas.Series.__iter__ RT03,SA01\
+        -i pandas.Series.add PR07\
+        -i pandas.Series.at_time PR01\
+        -i pandas.Series.backfill PR01,SA01\
+        -i pandas.Series.bfill SA01\
+        -i pandas.Series.case_when RT03\
+        -i pandas.Series.cat PR07,SA01\
+        -i pandas.Series.cat.add_categories PR01,PR02\
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+        -i pandas.Series.cat.as_unordered PR01\
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+        -i pandas.Series.cat.ordered SA01\
+        -i pandas.Series.cat.remove_categories PR01,PR02\
+        -i pandas.Series.cat.remove_unused_categories PR01\
+        -i pandas.Series.cat.rename_categories PR01,PR02\
+        -i pandas.Series.cat.reorder_categories PR01,PR02\
+        -i pandas.Series.cat.set_categories PR01,PR02\
+        -i pandas.Series.copy SA01\
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+        -i pandas.Series.droplevel SA01\
+        -i pandas.Series.dt.as_unit PR01,PR02\
+        -i pandas.Series.dt.ceil PR01,PR02,SA01\
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+        -i pandas.Series.dt.date SA01\
+        -i pandas.Series.dt.day SA01\
+        -i pandas.Series.dt.day_name PR01,PR02,SA01\
+        -i pandas.Series.dt.day_of_year SA01\
+        -i pandas.Series.dt.dayofyear SA01\
+        -i pandas.Series.dt.days SA01\
+        -i pandas.Series.dt.days_in_month SA01\
+        -i pandas.Series.dt.daysinmonth SA01\
+        -i pandas.Series.dt.floor PR01,PR02,SA01\
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+        -i pandas.Series.dt.is_leap_year SA01\
+        -i pandas.Series.dt.microsecond SA01\
+        -i pandas.Series.dt.microseconds SA01\
+        -i pandas.Series.dt.minute SA01\
+        -i pandas.Series.dt.month SA01\
+        -i pandas.Series.dt.month_name PR01,PR02,SA01\
+        -i pandas.Series.dt.nanosecond SA01\
+        -i pandas.Series.dt.nanoseconds SA01\
+        -i pandas.Series.dt.normalize PR01\
+        -i pandas.Series.dt.quarter SA01\
+        -i pandas.Series.dt.qyear GL08\
+        -i pandas.Series.dt.round PR01,PR02,SA01\
+        -i pandas.Series.dt.second SA01\
+        -i pandas.Series.dt.seconds SA01\
+        -i pandas.Series.dt.strftime PR01,PR02\
+        -i pandas.Series.dt.time SA01\
+        -i pandas.Series.dt.timetz SA01\
+        -i pandas.Series.dt.to_period PR01,PR02,RT03\
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+        -i pandas.Series.dt.tz SA01\
+        -i pandas.Series.dt.tz_convert PR01,PR02,RT03\
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+        -i pandas.Series.dt.unit GL08\
+        -i pandas.Series.dt.year SA01\
+        -i pandas.Series.dtype SA01\
+        -i pandas.Series.dtypes SA01\
+        -i pandas.Series.empty GL08\
+        -i pandas.Series.eq PR07,SA01\
+        -i pandas.Series.ffill SA01\
+        -i pandas.Series.first_valid_index SA01\
+        -i pandas.Series.floordiv PR07\
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+        -i pandas.Series.get SA01\
+        -i pandas.Series.gt PR07,SA01\
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+        -i pandas.Series.infer_objects RT03\
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+        -i pandas.Series.is_monotonic_increasing SA01\
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+        -i pandas.Series.item SA01\
+        -i pandas.Series.keys SA01\
+        -i pandas.Series.kurt RT03,SA01\
+        -i pandas.Series.kurtosis RT03,SA01\
+        -i pandas.Series.last_valid_index SA01\
+        -i pandas.Series.le PR07,SA01\
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+        -i pandas.Series.list.flatten SA01\
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+        -i pandas.Series.mask RT03\
+        -i pandas.Series.max RT03\
+        -i pandas.Series.mean RT03,SA01\
+        -i pandas.Series.median RT03,SA01\
+        -i pandas.Series.min RT03\
+        -i pandas.Series.mod PR07\
+        -i pandas.Series.mode SA01\
+        -i pandas.Series.mul PR07\
+        -i pandas.Series.nbytes SA01\
+        -i pandas.Series.ndim SA01\
+        -i pandas.Series.ne PR07,SA01\
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+        -i pandas.Series.pad PR01,SA01\
+        -i pandas.Series.plot PR02,SA01\
+        -i pandas.Series.pop RT03,SA01\
+        -i pandas.Series.pow PR07\
+        -i pandas.Series.prod RT03\
+        -i pandas.Series.product RT03\
+        -i pandas.Series.radd PR07\
+        -i pandas.Series.rdiv PR07\
+        -i pandas.Series.reorder_levels RT03,SA01\
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+        -i pandas.Series.rmod PR07\
+        -i pandas.Series.rmul PR07\
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+        -i pandas.Series.rtruediv PR07\
+        -i pandas.Series.sem PR01,RT03,SA01\
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+        -i pandas.Series.size SA01\
+        -i pandas.Series.skew RT03,SA01\
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+        -i pandas.Series.sparse.density SA01\
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+        -i pandas.Series.sparse.npoints SA01\
+        -i pandas.Series.sparse.sp_values SA01\
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+        -i pandas.Series.str PR01,SA01\
+        -i pandas.Series.str.capitalize RT03\
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+        -i pandas.Series.str.center RT03,SA01\
+        -i pandas.Series.str.decode PR07,RT03,SA01\
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+        -i pandas.Series.str.fullmatch RT03\
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+        -i pandas.Series.str.lstrip RT03\
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+        -i pandas.Series.str.replace SA01\
+        -i pandas.Series.str.rfind RT03\
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+        -i pandas.Series.str.rjust RT03,SA01\
+        -i pandas.Series.str.rpartition RT03\
+        -i pandas.Series.str.rstrip RT03\
+        -i pandas.Series.str.strip RT03\
+        -i pandas.Series.str.swapcase RT03\
+        -i pandas.Series.str.title RT03\
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+        -i pandas.Series.str.wrap RT03,SA01\
+        -i pandas.Series.str.zfill RT03\
+        -i pandas.Series.struct.dtypes SA01\
+        -i pandas.Series.sub PR07\
+        -i pandas.Series.sum RT03\
+        -i pandas.Series.swaplevel SA01\
+        -i pandas.Series.to_dict SA01\
+        -i pandas.Series.to_frame SA01\
+        -i pandas.Series.to_list RT03\
+        -i pandas.Series.to_markdown SA01\
+        -i pandas.Series.to_period SA01\
+        -i pandas.Series.to_string SA01\
+        -i pandas.Series.to_timestamp RT03,SA01\
+        -i pandas.Series.truediv PR07\
+        -i pandas.Series.tz_convert SA01\
+        -i pandas.Series.tz_localize SA01\
+        -i pandas.Series.unstack SA01\
+        -i pandas.Series.update PR07,SA01\
+        -i pandas.Series.value_counts RT03\
+        -i pandas.Series.var PR01,RT03,SA01\
+        -i pandas.Series.where RT03\
+        -i pandas.SparseDtype SA01\
+        -i pandas.Timedelta PR07,SA01\
+        -i pandas.Timedelta.as_unit SA01\
+        -i pandas.Timedelta.asm8 SA01\
+        -i pandas.Timedelta.ceil SA01\
+        -i pandas.Timedelta.components SA01\
+        -i pandas.Timedelta.days SA01\
+        -i pandas.Timedelta.floor SA01\
+        -i pandas.Timedelta.max PR02,PR07,SA01\
+        -i pandas.Timedelta.min PR02,PR07,SA01\
+        -i pandas.Timedelta.resolution PR02,PR07,SA01\
+        -i pandas.Timedelta.round SA01\
+        -i pandas.Timedelta.to_numpy PR01\
+        -i pandas.Timedelta.to_timedelta64 SA01\
+        -i pandas.Timedelta.total_seconds SA01\
+        -i pandas.Timedelta.view SA01\
+        -i pandas.TimedeltaIndex PR01\
+        -i pandas.TimedeltaIndex.as_unit RT03,SA01\
+        -i pandas.TimedeltaIndex.ceil SA01\
+        -i pandas.TimedeltaIndex.components SA01\
+        -i pandas.TimedeltaIndex.days SA01\
+        -i pandas.TimedeltaIndex.floor SA01\
+        -i pandas.TimedeltaIndex.inferred_freq SA01\
+        -i pandas.TimedeltaIndex.microseconds SA01\
+        -i pandas.TimedeltaIndex.nanoseconds SA01\
+        -i pandas.TimedeltaIndex.round SA01\
+        -i pandas.TimedeltaIndex.seconds SA01\
+        -i pandas.TimedeltaIndex.to_pytimedelta RT03,SA01\
+        -i pandas.Timestamp PR07,SA01\
+        -i pandas.Timestamp.as_unit SA01\
+        -i pandas.Timestamp.asm8 SA01\
+        -i pandas.Timestamp.astimezone SA01\
+        -i pandas.Timestamp.ceil SA01\
+        -i pandas.Timestamp.combine PR01,SA01\
+        -i pandas.Timestamp.ctime SA01\
+        -i pandas.Timestamp.date SA01\
+        -i pandas.Timestamp.day GL08\
+        -i pandas.Timestamp.day_name SA01\
+        -i pandas.Timestamp.day_of_week SA01\
+        -i pandas.Timestamp.day_of_year SA01\
+        -i pandas.Timestamp.dayofweek SA01\
+        -i pandas.Timestamp.dayofyear SA01\
+        -i pandas.Timestamp.days_in_month SA01\
+        -i pandas.Timestamp.daysinmonth SA01\
+        -i pandas.Timestamp.dst SA01\
+        -i pandas.Timestamp.floor SA01\
+        -i pandas.Timestamp.fold GL08\
+        -i pandas.Timestamp.fromordinal SA01\
+        -i pandas.Timestamp.fromtimestamp PR01,SA01\
+        -i pandas.Timestamp.hour GL08\
+        -i pandas.Timestamp.is_leap_year SA01\
+        -i pandas.Timestamp.isocalendar SA01\
+        -i pandas.Timestamp.isoformat SA01\
+        -i pandas.Timestamp.isoweekday SA01\
+        -i pandas.Timestamp.max PR02,PR07,SA01\
+        -i pandas.Timestamp.microsecond GL08\
+        -i pandas.Timestamp.min PR02,PR07,SA01\
+        -i pandas.Timestamp.minute GL08\
+        -i pandas.Timestamp.month GL08\
+        -i pandas.Timestamp.month_name SA01\
+        -i pandas.Timestamp.nanosecond GL08\
+        -i pandas.Timestamp.normalize SA01\
+        -i pandas.Timestamp.now SA01\
+        -i pandas.Timestamp.quarter SA01\
+        -i pandas.Timestamp.replace PR07,SA01\
+        -i pandas.Timestamp.resolution PR02,PR07,SA01\
+        -i pandas.Timestamp.round SA01\
+        -i pandas.Timestamp.second GL08\
+        -i pandas.Timestamp.strftime SA01\
+        -i pandas.Timestamp.strptime PR01,SA01\
+        -i pandas.Timestamp.time SA01\
+        -i pandas.Timestamp.timestamp SA01\
+        -i pandas.Timestamp.timetuple SA01\
+        -i pandas.Timestamp.timetz SA01\
+        -i pandas.Timestamp.to_datetime64 SA01\
+        -i pandas.Timestamp.to_julian_date SA01\
+        -i pandas.Timestamp.to_numpy PR01\
+        -i pandas.Timestamp.to_period PR01,SA01\
+        -i pandas.Timestamp.to_pydatetime PR01,SA01\
+        -i pandas.Timestamp.today SA01\
+        -i pandas.Timestamp.toordinal SA01\
+        -i pandas.Timestamp.tz SA01\
+        -i pandas.Timestamp.tz_convert SA01\
+        -i pandas.Timestamp.tz_localize SA01\
+        -i pandas.Timestamp.tzinfo GL08\
+        -i pandas.Timestamp.tzname SA01\
+        -i pandas.Timestamp.unit SA01\
+        -i pandas.Timestamp.utcfromtimestamp PR01,SA01\
+        -i pandas.Timestamp.utcnow SA01\
+        -i pandas.Timestamp.utcoffset SA01\
+        -i pandas.Timestamp.utctimetuple SA01\
+        -i pandas.Timestamp.value GL08\
+        -i pandas.Timestamp.week SA01\
+        -i pandas.Timestamp.weekday SA01\
+        -i pandas.Timestamp.weekofyear SA01\
+        -i pandas.Timestamp.year GL08\
+        -i pandas.UInt16Dtype SA01\
+        -i pandas.UInt32Dtype SA01\
+        -i pandas.UInt64Dtype SA01\
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+        -i pandas.api.extensions.ExtensionArray SA01\
+        -i pandas.api.extensions.ExtensionArray._accumulate RT03,SA01\
+        -i pandas.api.extensions.ExtensionArray._concat_same_type PR07,SA01\
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+        -i pandas.api.extensions.ExtensionArray._from_sequence SA01\
+        -i pandas.api.extensions.ExtensionArray._from_sequence_of_strings SA01\
+        -i pandas.api.extensions.ExtensionArray._hash_pandas_object RT03,SA01\
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+        -i pandas.api.extensions.register_extension_dtype SA01\
+        -i pandas.api.indexers.BaseIndexer PR01,SA01\
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+        -i pandas.api.indexers.VariableOffsetWindowIndexer PR01,SA01\
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+        -i pandas.api.types.infer_dtype PR07,SA01\
+        -i pandas.api.types.is_any_real_numeric_dtype SA01\
+        -i pandas.api.types.is_bool PR01,SA01\
+        -i pandas.api.types.is_bool_dtype SA01\
+        -i pandas.api.types.is_categorical_dtype SA01\
+        -i pandas.api.types.is_complex PR01,SA01\
+        -i pandas.api.types.is_complex_dtype SA01\
+        -i pandas.api.types.is_datetime64_any_dtype SA01\
+        -i pandas.api.types.is_datetime64_dtype SA01\
+        -i pandas.api.types.is_datetime64_ns_dtype SA01\
+        -i pandas.api.types.is_datetime64tz_dtype SA01\
+        -i pandas.api.types.is_dict_like PR07,SA01\
+        -i pandas.api.types.is_extension_array_dtype SA01\
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+        -i pandas.api.types.is_float_dtype SA01\
+        -i pandas.api.types.is_hashable PR01,RT03,SA01\
+        -i pandas.api.types.is_int64_dtype SA01\
+        -i pandas.api.types.is_integer PR01,SA01\
+        -i pandas.api.types.is_integer_dtype SA01\
+        -i pandas.api.types.is_interval_dtype SA01\
+        -i pandas.api.types.is_iterator PR07,SA01\
+        -i pandas.api.types.is_list_like SA01\
+        -i pandas.api.types.is_named_tuple PR07,SA01\
+        -i pandas.api.types.is_numeric_dtype SA01\
+        -i pandas.api.types.is_object_dtype SA01\
+        -i pandas.api.types.is_period_dtype SA01\
+        -i pandas.api.types.is_re PR07,SA01\
+        -i pandas.api.types.is_re_compilable PR07,SA01\
+        -i pandas.api.types.is_scalar SA01\
+        -i pandas.api.types.is_signed_integer_dtype SA01\
+        -i pandas.api.types.is_sparse SA01\
+        -i pandas.api.types.is_string_dtype SA01\
+        -i pandas.api.types.is_timedelta64_dtype SA01\
+        -i pandas.api.types.is_timedelta64_ns_dtype SA01\
+        -i pandas.api.types.is_unsigned_integer_dtype SA01\
+        -i pandas.api.types.pandas_dtype PR07,RT03,SA01\
+        -i pandas.api.types.union_categoricals RT03,SA01\
+        -i pandas.arrays.ArrowExtensionArray PR07,SA01\
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+        -i pandas.arrays.DatetimeArray SA01\
+        -i pandas.arrays.FloatingArray SA01\
+        -i pandas.arrays.IntegerArray SA01\
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+        -i pandas.arrays.IntervalArray.contains RT03\
+        -i pandas.arrays.IntervalArray.is_non_overlapping_monotonic SA01\
+        -i pandas.arrays.IntervalArray.left SA01\
+        -i pandas.arrays.IntervalArray.length SA01\
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+        -i pandas.arrays.IntervalArray.right SA01\
+        -i pandas.arrays.IntervalArray.set_closed RT03,SA01\
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+        -i pandas.arrays.SparseArray PR07,SA01\
+        -i pandas.arrays.TimedeltaArray PR07,SA01\
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+        -i pandas.core.groupby.DataFrameGroupBy.__iter__ RT03,SA01\
+        -i pandas.core.groupby.DataFrameGroupBy.agg RT03\
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+        -i pandas.core.groupby.DataFrameGroupBy.apply RT03\
+        -i pandas.core.groupby.DataFrameGroupBy.boxplot PR07,RT03,SA01\
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+        -i pandas.core.groupby.DataFrameGroupBy.cumprod RT03\
+        -i pandas.core.groupby.DataFrameGroupBy.cumsum RT03\
+        -i pandas.core.groupby.DataFrameGroupBy.filter RT03,SA01\
+        -i pandas.core.groupby.DataFrameGroupBy.get_group RT03,SA01\
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+        -i pandas.core.groupby.DataFrameGroupBy.hist RT03\
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+        -i pandas.core.groupby.DataFrameGroupBy.max SA01\
+        -i pandas.core.groupby.DataFrameGroupBy.mean RT03\
+        -i pandas.core.groupby.DataFrameGroupBy.median SA01\
+        -i pandas.core.groupby.DataFrameGroupBy.min SA01\
+        -i pandas.core.groupby.DataFrameGroupBy.nth PR02\
+        -i pandas.core.groupby.DataFrameGroupBy.nunique RT03,SA01\
+        -i pandas.core.groupby.DataFrameGroupBy.ohlc SA01\
+        -i pandas.core.groupby.DataFrameGroupBy.plot PR02,SA01\
+        -i pandas.core.groupby.DataFrameGroupBy.prod SA01\
+        -i pandas.core.groupby.DataFrameGroupBy.rank RT03\
+        -i pandas.core.groupby.DataFrameGroupBy.resample RT03\
+        -i pandas.core.groupby.DataFrameGroupBy.sem SA01\
+        -i pandas.core.groupby.DataFrameGroupBy.skew RT03\
+        -i pandas.core.groupby.DataFrameGroupBy.sum SA01\
+        -i pandas.core.groupby.DataFrameGroupBy.transform RT03\
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+        -i pandas.core.groupby.SeriesGroupBy.aggregate RT03\
+        -i pandas.core.groupby.SeriesGroupBy.apply RT03\
+        -i pandas.core.groupby.SeriesGroupBy.cummax RT03\
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+        -i pandas.core.groupby.SeriesGroupBy.cumprod RT03\
+        -i pandas.core.groupby.SeriesGroupBy.cumsum RT03\
+        -i pandas.core.groupby.SeriesGroupBy.filter PR01,RT03,SA01\
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+        -i pandas.core.groupby.SeriesGroupBy.groups SA01\
+        -i pandas.core.groupby.SeriesGroupBy.indices SA01\
+        -i pandas.core.groupby.SeriesGroupBy.is_monotonic_decreasing SA01\
+        -i pandas.core.groupby.SeriesGroupBy.is_monotonic_increasing SA01\
+        -i pandas.core.groupby.SeriesGroupBy.max SA01\
+        -i pandas.core.groupby.SeriesGroupBy.mean RT03\
+        -i pandas.core.groupby.SeriesGroupBy.median SA01\
+        -i pandas.core.groupby.SeriesGroupBy.min SA01\
+        -i pandas.core.groupby.SeriesGroupBy.nth PR02\
+        -i pandas.core.groupby.SeriesGroupBy.ohlc SA01\
+        -i pandas.core.groupby.SeriesGroupBy.plot PR02,SA01\
+        -i pandas.core.groupby.SeriesGroupBy.prod SA01\
+        -i pandas.core.groupby.SeriesGroupBy.rank RT03\
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+        -i pandas.core.groupby.SeriesGroupBy.sem SA01\
+        -i pandas.core.groupby.SeriesGroupBy.skew RT03\
+        -i pandas.core.groupby.SeriesGroupBy.sum SA01\
+        -i pandas.core.groupby.SeriesGroupBy.transform RT03\
+        -i pandas.core.resample.Resampler.__iter__ RT03,SA01\
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+        -i pandas.tseries.offsets.Micro.nanos SA01\
+        -i pandas.tseries.offsets.Micro.normalize GL08\
+        -i pandas.tseries.offsets.Micro.rule_code GL08\
+        -i pandas.tseries.offsets.Milli PR02\
+        -i pandas.tseries.offsets.Milli.copy SA01\
+        -i pandas.tseries.offsets.Milli.delta GL08\
+        -i pandas.tseries.offsets.Milli.freqstr SA01\
+        -i pandas.tseries.offsets.Milli.is_on_offset GL08\
+        -i pandas.tseries.offsets.Milli.kwds SA01\
+        -i pandas.tseries.offsets.Milli.n GL08\
+        -i pandas.tseries.offsets.Milli.name SA01\
+        -i pandas.tseries.offsets.Milli.nanos SA01\
+        -i pandas.tseries.offsets.Milli.normalize GL08\
+        -i pandas.tseries.offsets.Milli.rule_code GL08\
+        -i pandas.tseries.offsets.Minute PR02\
+        -i pandas.tseries.offsets.Minute.copy SA01\
+        -i pandas.tseries.offsets.Minute.delta GL08\
+        -i pandas.tseries.offsets.Minute.freqstr SA01\
+        -i pandas.tseries.offsets.Minute.is_on_offset GL08\
+        -i pandas.tseries.offsets.Minute.kwds SA01\
+        -i pandas.tseries.offsets.Minute.n GL08\
+        -i pandas.tseries.offsets.Minute.name SA01\
+        -i pandas.tseries.offsets.Minute.nanos SA01\
+        -i pandas.tseries.offsets.Minute.normalize GL08\
+        -i pandas.tseries.offsets.Minute.rule_code GL08\
+        -i pandas.tseries.offsets.MonthBegin PR02\
+        -i pandas.tseries.offsets.MonthBegin.copy SA01\
+        -i pandas.tseries.offsets.MonthBegin.freqstr SA01\
+        -i pandas.tseries.offsets.MonthBegin.is_on_offset GL08\
+        -i pandas.tseries.offsets.MonthBegin.kwds SA01\
+        -i pandas.tseries.offsets.MonthBegin.n GL08\
+        -i pandas.tseries.offsets.MonthBegin.name SA01\
+        -i pandas.tseries.offsets.MonthBegin.nanos GL08\
+        -i pandas.tseries.offsets.MonthBegin.normalize GL08\
+        -i pandas.tseries.offsets.MonthBegin.rule_code GL08\
+        -i pandas.tseries.offsets.MonthEnd PR02\
+        -i pandas.tseries.offsets.MonthEnd.copy SA01\
+        -i pandas.tseries.offsets.MonthEnd.freqstr SA01\
+        -i pandas.tseries.offsets.MonthEnd.is_on_offset GL08\
+        -i pandas.tseries.offsets.MonthEnd.kwds SA01\
+        -i pandas.tseries.offsets.MonthEnd.n GL08\
+        -i pandas.tseries.offsets.MonthEnd.name SA01\
+        -i pandas.tseries.offsets.MonthEnd.nanos GL08\
+        -i pandas.tseries.offsets.MonthEnd.normalize GL08\
+        -i pandas.tseries.offsets.MonthEnd.rule_code GL08\
+        -i pandas.tseries.offsets.Nano PR02\
+        -i pandas.tseries.offsets.Nano.copy SA01\
+        -i pandas.tseries.offsets.Nano.delta GL08\
+        -i pandas.tseries.offsets.Nano.freqstr SA01\
+        -i pandas.tseries.offsets.Nano.is_on_offset GL08\
+        -i pandas.tseries.offsets.Nano.kwds SA01\
+        -i pandas.tseries.offsets.Nano.n GL08\
+        -i pandas.tseries.offsets.Nano.name SA01\
+        -i pandas.tseries.offsets.Nano.nanos SA01\
+        -i pandas.tseries.offsets.Nano.normalize GL08\
+        -i pandas.tseries.offsets.Nano.rule_code GL08\
+        -i pandas.tseries.offsets.QuarterBegin PR02\
+        -i pandas.tseries.offsets.QuarterBegin.copy SA01\
+        -i pandas.tseries.offsets.QuarterBegin.freqstr SA01\
+        -i pandas.tseries.offsets.QuarterBegin.is_on_offset GL08\
+        -i pandas.tseries.offsets.QuarterBegin.kwds SA01\
+        -i pandas.tseries.offsets.QuarterBegin.n GL08\
+        -i pandas.tseries.offsets.QuarterBegin.name SA01\
+        -i pandas.tseries.offsets.QuarterBegin.nanos GL08\
+        -i pandas.tseries.offsets.QuarterBegin.normalize GL08\
+        -i pandas.tseries.offsets.QuarterBegin.rule_code GL08\
+        -i pandas.tseries.offsets.QuarterBegin.startingMonth GL08\
+        -i pandas.tseries.offsets.QuarterEnd PR02\
+        -i pandas.tseries.offsets.QuarterEnd.copy SA01\
+        -i pandas.tseries.offsets.QuarterEnd.freqstr SA01\
+        -i pandas.tseries.offsets.QuarterEnd.is_on_offset GL08\
+        -i pandas.tseries.offsets.QuarterEnd.kwds SA01\
+        -i pandas.tseries.offsets.QuarterEnd.n GL08\
+        -i pandas.tseries.offsets.QuarterEnd.name SA01\
+        -i pandas.tseries.offsets.QuarterEnd.nanos GL08\
+        -i pandas.tseries.offsets.QuarterEnd.normalize GL08\
+        -i pandas.tseries.offsets.QuarterEnd.rule_code GL08\
+        -i pandas.tseries.offsets.QuarterEnd.startingMonth GL08\
+        -i pandas.tseries.offsets.Second PR02\
+        -i pandas.tseries.offsets.Second.copy SA01\
+        -i pandas.tseries.offsets.Second.delta GL08\
+        -i pandas.tseries.offsets.Second.freqstr SA01\
+        -i pandas.tseries.offsets.Second.is_on_offset GL08\
+        -i pandas.tseries.offsets.Second.kwds SA01\
+        -i pandas.tseries.offsets.Second.n GL08\
+        -i pandas.tseries.offsets.Second.name SA01\
+        -i pandas.tseries.offsets.Second.nanos SA01\
+        -i pandas.tseries.offsets.Second.normalize GL08\
+        -i pandas.tseries.offsets.Second.rule_code GL08\
+        -i pandas.tseries.offsets.SemiMonthBegin PR02,SA01\
+        -i pandas.tseries.offsets.SemiMonthBegin.copy SA01\
+        -i pandas.tseries.offsets.SemiMonthBegin.day_of_month GL08\
+        -i pandas.tseries.offsets.SemiMonthBegin.freqstr SA01\
+        -i pandas.tseries.offsets.SemiMonthBegin.is_on_offset GL08\
+        -i pandas.tseries.offsets.SemiMonthBegin.kwds SA01\
+        -i pandas.tseries.offsets.SemiMonthBegin.n GL08\
+        -i pandas.tseries.offsets.SemiMonthBegin.name SA01\
+        -i pandas.tseries.offsets.SemiMonthBegin.nanos GL08\
+        -i pandas.tseries.offsets.SemiMonthBegin.normalize GL08\
+        -i pandas.tseries.offsets.SemiMonthBegin.rule_code GL08\
+        -i pandas.tseries.offsets.SemiMonthEnd PR02,SA01\
+        -i pandas.tseries.offsets.SemiMonthEnd.copy SA01\
+        -i pandas.tseries.offsets.SemiMonthEnd.day_of_month GL08\
+        -i pandas.tseries.offsets.SemiMonthEnd.freqstr SA01\
+        -i pandas.tseries.offsets.SemiMonthEnd.is_on_offset GL08\
+        -i pandas.tseries.offsets.SemiMonthEnd.kwds SA01\
+        -i pandas.tseries.offsets.SemiMonthEnd.n GL08\
+        -i pandas.tseries.offsets.SemiMonthEnd.name SA01\
+        -i pandas.tseries.offsets.SemiMonthEnd.nanos GL08\
+        -i pandas.tseries.offsets.SemiMonthEnd.normalize GL08\
+        -i pandas.tseries.offsets.SemiMonthEnd.rule_code GL08\
+        -i pandas.tseries.offsets.Tick GL08\
+        -i pandas.tseries.offsets.Tick.copy SA01\
+        -i pandas.tseries.offsets.Tick.delta GL08\
+        -i pandas.tseries.offsets.Tick.freqstr SA01\
+        -i pandas.tseries.offsets.Tick.is_on_offset GL08\
+        -i pandas.tseries.offsets.Tick.kwds SA01\
+        -i pandas.tseries.offsets.Tick.n GL08\
+        -i pandas.tseries.offsets.Tick.name SA01\
+        -i pandas.tseries.offsets.Tick.nanos SA01\
+        -i pandas.tseries.offsets.Tick.normalize GL08\
+        -i pandas.tseries.offsets.Tick.rule_code GL08\
+        -i pandas.tseries.offsets.Week PR02\
+        -i pandas.tseries.offsets.Week.copy SA01\
+        -i pandas.tseries.offsets.Week.freqstr SA01\
+        -i pandas.tseries.offsets.Week.is_on_offset GL08\
+        -i pandas.tseries.offsets.Week.kwds SA01\
+        -i pandas.tseries.offsets.Week.n GL08\
+        -i pandas.tseries.offsets.Week.name SA01\
+        -i pandas.tseries.offsets.Week.nanos GL08\
+        -i pandas.tseries.offsets.Week.normalize GL08\
+        -i pandas.tseries.offsets.Week.rule_code GL08\
+        -i pandas.tseries.offsets.Week.weekday GL08\
+        -i pandas.tseries.offsets.WeekOfMonth PR02,SA01\
+        -i pandas.tseries.offsets.WeekOfMonth.copy SA01\
+        -i pandas.tseries.offsets.WeekOfMonth.freqstr SA01\
+        -i pandas.tseries.offsets.WeekOfMonth.is_on_offset GL08\
+        -i pandas.tseries.offsets.WeekOfMonth.kwds SA01\
+        -i pandas.tseries.offsets.WeekOfMonth.n GL08\
+        -i pandas.tseries.offsets.WeekOfMonth.name SA01\
+        -i pandas.tseries.offsets.WeekOfMonth.nanos GL08\
+        -i pandas.tseries.offsets.WeekOfMonth.normalize GL08\
+        -i pandas.tseries.offsets.WeekOfMonth.rule_code GL08\
+        -i pandas.tseries.offsets.WeekOfMonth.week GL08\
+        -i pandas.tseries.offsets.WeekOfMonth.weekday GL08\
+        -i pandas.tseries.offsets.YearBegin PR02\
+        -i pandas.tseries.offsets.YearBegin.copy SA01\
+        -i pandas.tseries.offsets.YearBegin.freqstr SA01\
+        -i pandas.tseries.offsets.YearBegin.is_on_offset GL08\
+        -i pandas.tseries.offsets.YearBegin.kwds SA01\
+        -i pandas.tseries.offsets.YearBegin.month GL08\
+        -i pandas.tseries.offsets.YearBegin.n GL08\
+        -i pandas.tseries.offsets.YearBegin.name SA01\
+        -i pandas.tseries.offsets.YearBegin.nanos GL08\
+        -i pandas.tseries.offsets.YearBegin.normalize GL08\
+        -i pandas.tseries.offsets.YearBegin.rule_code GL08\
+        -i pandas.tseries.offsets.YearEnd PR02\
+        -i pandas.tseries.offsets.YearEnd.copy SA01\
+        -i pandas.tseries.offsets.YearEnd.freqstr SA01\
+        -i pandas.tseries.offsets.YearEnd.is_on_offset GL08\
+        -i pandas.tseries.offsets.YearEnd.kwds SA01\
+        -i pandas.tseries.offsets.YearEnd.month GL08\
+        -i pandas.tseries.offsets.YearEnd.n GL08\
+        -i pandas.tseries.offsets.YearEnd.name SA01\
+        -i pandas.tseries.offsets.YearEnd.nanos GL08\
+        -i pandas.tseries.offsets.YearEnd.normalize GL08\
+        -i pandas.tseries.offsets.YearEnd.rule_code GL08\
+        -i pandas.unique PR07\
+        -i pandas.util.hash_array PR07,SA01\
+        -i pandas.util.hash_pandas_object PR07,SA01 # There should be no backslash in the final line, please keep this comment in the last ignored function
+
+    RET=$(($RET + $?)) ; echo $MSG "DONE"
 
 fi
 
diff --git a/doc/source/user_guide/timeseries.rst b/doc/source/user_guide/timeseries.rst
index 0f38d90e18..ecdfb3c565 100644
--- a/doc/source/user_guide/timeseries.rst
+++ b/doc/source/user_guide/timeseries.rst
@@ -797,8 +797,6 @@ There are several time/date properties that one can access from ``Timestamp`` or
     timetz,"Returns datetime.time as local time with timezone information"
     dayofyear,"The ordinal day of year"
     day_of_year,"The ordinal day of year"
-    weekofyear,"The week ordinal of the year"
-    week,"The week ordinal of the year"
     dayofweek,"The number of the day of the week with Monday=0, Sunday=6"
     day_of_week,"The number of the day of the week with Monday=0, Sunday=6"
     weekday,"The number of the day of the week with Monday=0, Sunday=6"
@@ -812,6 +810,10 @@ There are several time/date properties that one can access from ``Timestamp`` or
     is_year_end,"Logical indicating if last day of year (defined by frequency)"
     is_leap_year,"Logical indicating if the date belongs to a leap year"
 
+.. note::
+
+   You can use ``DatetimeIndex.isocalendar().week`` to access week of year date information.
+
 Furthermore, if you have a ``Series`` with datetimelike values, then you can
 access these properties via the ``.dt`` accessor, as detailed in the section
 on :ref:`.dt accessors<basics.dt_accessors>`.
diff --git a/pandas/_libs/meson.build b/pandas/_libs/meson.build
index 7621915ebc..c27386743c 100644
--- a/pandas/_libs/meson.build
+++ b/pandas/_libs/meson.build
@@ -54,37 +54,25 @@ _intervaltree_helper = custom_target('intervaltree_helper_pxi',
         py, tempita, '@INPUT@', '-o', '@OUTDIR@'
     ]
 )
-
-_algos_pxi_dep = declare_dependency(sources: [_algos_take_helper, _algos_common_helper])
-_khash_pxi_dep = declare_dependency(sources: _khash_primitive_helper)
-_hashtable_pxi_dep = declare_dependency(
-    sources: [_hashtable_class_helper, _hashtable_func_helper]
-)
-_index_pxi_dep = declare_dependency(sources: _index_class_helper)
-_intervaltree_pxi_dep = declare_dependency(sources: _intervaltree_helper)
-_sparse_pxi_dep = declare_dependency(sources: _sparse_op_helper)
-
+_khash_primitive_helper_dep = declare_dependency(sources: _khash_primitive_helper)
 
 subdir('tslibs')
 
 libs_sources = {
     # Dict of extension name -> dict of {sources, include_dirs, and deps}
     # numpy include dir is implicitly included
-    'algos': {'sources': ['algos.pyx'],
-              'deps': [_khash_pxi_dep, _algos_pxi_dep]},
+    'algos': {'sources': ['algos.pyx', _algos_common_helper, _algos_take_helper], 'deps': _khash_primitive_helper_dep},
     'arrays': {'sources': ['arrays.pyx']},
     'groupby': {'sources': ['groupby.pyx']},
     'hashing': {'sources': ['hashing.pyx']},
-    'hashtable': {'sources': ['hashtable.pyx'],
-                  'deps': [_khash_pxi_dep, _hashtable_pxi_dep]},
-    'index': {'sources': ['index.pyx'],
-              'deps': [_khash_pxi_dep, _index_pxi_dep]},
+    'hashtable': {'sources': ['hashtable.pyx', _hashtable_class_helper, _hashtable_func_helper], 'deps': _khash_primitive_helper_dep},
+    'index': {'sources': ['index.pyx', _index_class_helper], 'deps': _khash_primitive_helper_dep},
     'indexing': {'sources': ['indexing.pyx']},
     'internals': {'sources': ['internals.pyx']},
-    'interval': {'sources': ['interval.pyx'],
-                 'deps': [_khash_pxi_dep, _intervaltree_pxi_dep]},
-    'join': {'sources': ['join.pyx'],
-             'deps': [_khash_pxi_dep]},
+    'interval': {'sources': ['interval.pyx', _intervaltree_helper],
+                 'deps': _khash_primitive_helper_dep},
+    'join': {'sources': ['join.pyx', _khash_primitive_helper],
+             'deps': _khash_primitive_helper_dep},
     'lib': {'sources': ['lib.pyx', 'src/parser/tokenizer.c']},
     'missing': {'sources': ['missing.pyx']},
     'pandas_datetime': {'sources': ['src/vendored/numpy/datetime/np_datetime.c',
@@ -95,7 +83,7 @@ libs_sources = {
                                   'src/parser/io.c',
                                   'src/parser/pd_parser.c']},
     'parsers': {'sources': ['parsers.pyx', 'src/parser/tokenizer.c', 'src/parser/io.c'],
-                'deps': [_khash_pxi_dep]},
+                'deps': _khash_primitive_helper_dep},
     'json': {'sources': ['src/vendored/ujson/python/ujson.c',
                          'src/vendored/ujson/python/objToJSON.c',
                          'src/vendored/ujson/python/JSONtoObj.c',
@@ -107,8 +95,7 @@ libs_sources = {
     'reshape': {'sources': ['reshape.pyx']},
     'sas': {'sources': ['sas.pyx']},
     'byteswap': {'sources': ['byteswap.pyx']},
-    'sparse': {'sources': ['sparse.pyx'],
-               'deps': [_sparse_pxi_dep]},
+    'sparse': {'sources': ['sparse.pyx', _sparse_op_helper]},
     'tslib': {'sources': ['tslib.pyx']},
     'testing': {'sources': ['testing.pyx']},
     'writers': {'sources': ['writers.pyx']}
diff --git a/scripts/validate_docstrings.py b/scripts/validate_docstrings.py
index b42deff66f..0057f97ffa 100755
--- a/scripts/validate_docstrings.py
+++ b/scripts/validate_docstrings.py
@@ -16,6 +16,7 @@ Usage::
 from __future__ import annotations
 
 import argparse
+import collections
 import doctest
 import importlib
 import json
@@ -65,6 +66,10 @@ ERROR_MSGS = {
     "EX04": "Do not import {imported_library}, as it is imported "
     "automatically for the examples (numpy as np, pandas as pd)",
 }
+ALL_ERRORS = set(NUMPYDOC_ERROR_MSGS).union(set(ERROR_MSGS))
+duplicated_errors = set(NUMPYDOC_ERROR_MSGS).intersection(set(ERROR_MSGS))
+assert not duplicated_errors, (f"Errors {duplicated_errors} exist in both pandas "
+                               "and numpydoc, should they be removed from pandas?")
 
 
 def pandas_error(code, **kwargs):
@@ -340,9 +345,8 @@ def get_all_api_items():
 def print_validate_all_results(
     output_format: str,
     prefix: str | None,
-    errors: list[str] | None,
     ignore_deprecated: bool,
-    ignore_errors: dict[str, list[str]] | None,
+    ignore_errors: dict[str, set[str]],
 ):
     if output_format not in ("default", "json", "actions"):
         raise ValueError(f'Unknown output_format "{output_format}"')
@@ -358,22 +362,28 @@ def print_validate_all_results(
     prefix = "##[error]" if output_format == "actions" else ""
     exit_status = 0
     for func_name, res in result.items():
-        for err_code, err_desc in res["errors"]:
-            is_not_requested_error = errors and err_code not in errors
-            is_ignored_error = err_code in ignore_errors.get(func_name, [])
-            if is_not_requested_error or is_ignored_error:
-                continue
-
+        error_messages = dict(res["errors"])
+        actual_failures = set(error_messages)
+        expected_failures = (ignore_errors.get(func_name, set())
+                             | ignore_errors.get("*", set()))
+        for err_code in actual_failures - expected_failures:
+            sys.stdout.write(
+                f'{prefix}{res["file"]}:{res["file_line"]}:'
+                f'{err_code}:{func_name}:{error_messages[err_code]}\n'
+            )
+            exit_status += 1
+        for err_code in ignore_errors.get(func_name, set()) - actual_failures:
             sys.stdout.write(
                 f'{prefix}{res["file"]}:{res["file_line"]}:'
-                f"{err_code}:{func_name}:{err_desc}\n"
+                f"{err_code}:{func_name}:"
+                "EXPECTED TO FAIL, BUT NOT FAILING\n"
             )
             exit_status += 1
 
     return exit_status
 
 
-def print_validate_one_results(func_name: str) -> None:
+def print_validate_one_results(func_name: str) -> int:
     def header(title, width=80, char="#") -> str:
         full_line = char * width
         side_len = (width - len(title) - 2) // 2
@@ -399,20 +409,45 @@ def print_validate_one_results(func_name: str) -> None:
         sys.stderr.write(header("Doctests"))
         sys.stderr.write(result["examples_errs"])
 
+    return len(result["errors"]) + len(result["examples_errs"])
+
+
+def _format_ignore_errors(raw_ignore_errors):
+    ignore_errors = collections.defaultdict(set)
+    if raw_ignore_errors:
+        for obj_name, error_codes in raw_ignore_errors:
+            # function errors "pandas.Series PR01,SA01"
+            if obj_name != "*":
+                if obj_name in ignore_errors:
+                    raise ValueError(
+                        f"Object `{obj_name}` is present in more than one "
+                        "--ignore_errors argument. Please use it once and specify "
+                        "the errors separated by commas.")
+                ignore_errors[obj_name] = set(error_codes.split(","))
+
+                unknown_errors = ignore_errors[obj_name] - ALL_ERRORS
+                if unknown_errors:
+                    raise ValueError(
+                        f"Object `{obj_name}` is ignoring errors {unknown_errors} "
+                        f"which are not known. Known errors are: {ALL_ERRORS}")
+
+            # global errors "PR02,ES01"
+            else:
+                ignore_errors["*"].update(set(error_codes.split(",")))
+
+        unknown_errors = ignore_errors["*"] - ALL_ERRORS
+        if unknown_errors:
+            raise ValueError(
+                f"Unknown errors {unknown_errors} specified using --ignore_errors "
+                "Known errors are: {ALL_ERRORS}")
 
-def validate_error_codes(errors):
-    overlapped_errors = set(NUMPYDOC_ERROR_MSGS).intersection(set(ERROR_MSGS))
-    assert not overlapped_errors, f"{overlapped_errors} is overlapped."
-    all_errors = set(NUMPYDOC_ERROR_MSGS).union(set(ERROR_MSGS))
-    nonexistent_errors = set(errors) - all_errors
-    assert not nonexistent_errors, f"{nonexistent_errors} don't exist."
+    return ignore_errors
 
 
 def main(
     func_name,
     output_format,
     prefix,
-    errors,
     ignore_deprecated,
     ignore_errors
 ):
@@ -420,31 +455,14 @@ def main(
     Main entry point. Call the validation for one or for all docstrings.
     """
     if func_name is None:
-        error_str = ", ".join(errors)
-        msg = f"Validate docstrings ({error_str})\n"
-    else:
-        msg = f"Validate docstring in function {func_name}\n"
-    sys.stdout.write(msg)
-
-    validate_error_codes(errors)
-    if ignore_errors is not None:
-        for error_codes in ignore_errors.values():
-            validate_error_codes(error_codes)
-
-    if func_name is None:
-        exit_status = print_validate_all_results(
+        return print_validate_all_results(
             output_format,
             prefix,
-            errors,
             ignore_deprecated,
             ignore_errors
         )
     else:
-        print_validate_one_results(func_name)
-        exit_status = 0
-    sys.stdout.write(msg + "DONE" + os.linesep)
-
-    return exit_status
+        return print_validate_one_results(func_name)
 
 
 if __name__ == "__main__":
@@ -474,14 +492,6 @@ if __name__ == "__main__":
         "of methods starting by this pattern. It is "
         "ignored if parameter function is provided",
     )
-    argparser.add_argument(
-        "--errors",
-        default=None,
-        help="comma separated "
-        "list of error codes to validate. By default it "
-        "validates all errors (ignored when validating "
-        "a single docstring)",
-    )
     argparser.add_argument(
         "--ignore_deprecated",
         default=False,
@@ -492,6 +502,7 @@ if __name__ == "__main__":
     )
     argparser.add_argument(
         "--ignore_errors",
+        "-i",
         default=None,
         action="append",
         nargs=2,
@@ -504,18 +515,11 @@ if __name__ == "__main__":
     )
     args = argparser.parse_args(sys.argv[1:])
 
-    args.errors = args.errors.split(",") if args.errors else None
-    if args.ignore_errors:
-        args.ignore_errors = {function: error_codes.split(",")
-                              for function, error_codes
-                              in args.ignore_errors}
-
     sys.exit(
         main(args.function,
              args.format,
              args.prefix,
-             args.errors,
              args.ignore_deprecated,
-             args.ignore_errors
+             _format_ignore_errors(args.ignore_errors),
              )
     )
diff --git a/web/pandas/community/benchmarks.md b/web/pandas/community/benchmarks.md
index ffce00be96..1e63832a5a 100644
--- a/web/pandas/community/benchmarks.md
+++ b/web/pandas/community/benchmarks.md
@@ -75,5 +75,5 @@ There is a quick summary here:
 
 The main benchmarks comparing dataframe tools that include pandas are:
 
-- [H2O.ai benchmarks](https://h2oai.github.io/db-benchmark/)
+- [DuckDB (former H2O.ai) benchmarks](https://duckdblabs.github.io/db-benchmark/)
 - [TPCH benchmarks](https://pola.rs/posts/benchmarks/)


Test patch:
diff --git a/scripts/tests/test_validate_docstrings.py b/scripts/tests/test_validate_docstrings.py
index 73bfb12316..72d5c03ab7 100644
--- a/scripts/tests/test_validate_docstrings.py
+++ b/scripts/tests/test_validate_docstrings.py
@@ -255,29 +255,28 @@ class TestValidator:
             ],
         )
 
-        exit_status_ignore_func = validate_docstrings.print_validate_all_results(
+        exit_status = validate_docstrings.print_validate_all_results(
             output_format="default",
             prefix=None,
-            errors=["ER01", "ER02"],
             ignore_deprecated=False,
-            ignore_errors={
-                "pandas.DataFrame.align": ["ER01"],
-                # ignoring an error that is not requested should be of no effect
-                "pandas.Index.all": ["ER03"]
-            }
+            ignore_errors={"*": {"ER03"}},
         )
+        # two functions * two not ignored errors
+        assert exit_status == 2 * 2
+
         exit_status = validate_docstrings.print_validate_all_results(
             output_format="default",
             prefix=None,
-            errors=["ER01", "ER02"],
             ignore_deprecated=False,
-            ignore_errors=None
+            ignore_errors={
+                "*": {"ER03"},
+                "pandas.DataFrame.align": {"ER01"},
+                # ignoring an error that is not requested should be of no effect
+                "pandas.Index.all": {"ER03"}
+            }
         )
-
-        # we have 2 error codes activated out of the 3 available in the validate results
-        # one run has a function to ignore, the other does not
-        assert exit_status == 2*2
-        assert exit_status_ignore_func == exit_status - 1
+        # two functions * two not global ignored errors - one function ignored error
+        assert exit_status == 2 * 2 - 1
 
 
 
@@ -399,11 +398,10 @@ class TestMainFunction:
             func_name="docstring1",
             prefix=None,
             output_format="default",
-            errors=[],
             ignore_deprecated=False,
             ignore_errors=None,
         )
-        assert exit_status == 0
+        assert exit_status == 3
 
     def test_exit_status_errors_for_validate_all(self, monkeypatch) -> None:
         monkeypatch.setattr(
@@ -430,7 +428,6 @@ class TestMainFunction:
             func_name=None,
             prefix=None,
             output_format="default",
-            errors=[],
             ignore_deprecated=False,
             ignore_errors=None,
         )
@@ -449,7 +446,6 @@ class TestMainFunction:
             func_name=None,
             output_format="default",
             prefix=None,
-            errors=[],
             ignore_deprecated=False,
             ignore_errors=None,
         )
@@ -474,7 +470,6 @@ class TestMainFunction:
             func_name=None,
             output_format="json",
             prefix=None,
-            errors=[],
             ignore_deprecated=False,
             ignore_errors=None,
         )
@@ -519,18 +514,16 @@ class TestMainFunction:
             func_name=None,
             output_format="default",
             prefix=None,
-            errors=["ER01"],
             ignore_deprecated=False,
-            ignore_errors=None,
+            ignore_errors={"*": {"ER02", "ER03"}},
         )
         assert exit_status == 3
 
         exit_status = validate_docstrings.main(
             func_name=None,
-            prefix=None,
             output_format="default",
-            errors=["ER03"],
+            prefix=None,
             ignore_deprecated=False,
-            ignore_errors=None,
+            ignore_errors={"*": {"ER01", "ER02"}},
         )
         assert exit_status == 1