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Merge remote-tracking branch 'upstream/main' into stata-read-dta110
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‎.github/ISSUE_TEMPLATE/pdep_vote.yaml

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@@ -0,0 +1,74 @@
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name: PDEP Vote
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description: Call for a vote on a PDEP
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title: "VOTE: "
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labels: [Vote]
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body:
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- type: markdown
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attributes:
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value: >
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As per [PDEP-1](https://pandas.pydata.org/pdeps/0001-purpose-and-guidelines.html), the following issue template should be used when a
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maintainer has opened a PDEP discussion and is ready to call for a vote.
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- type: checkboxes
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attributes:
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label: Locked issue
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options:
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- label: >
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I locked this voting issue so that only voting members are able to cast their votes or
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comment on this issue.
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required: true
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- type: input
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id: PDEP-name
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attributes:
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label: PDEP number and title
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placeholder: >
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PDEP-1: Purpose and guidelines
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validations:
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required: true
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- type: input
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id: PDEP-link
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attributes:
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label: Pull request with discussion
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description: e.g. https://github.com/pandas-dev/pandas/pull/47444
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validations:
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required: true
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- type: input
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id: PDEP-rendered-link
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attributes:
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label: Rendered PDEP for easy reading
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description: e.g. https://github.com/pandas-dev/pandas/pull/47444/files?short_path=7c449e6#diff-7c449e698132205b235c501f7e47ebba38da4d2b7f9492c98f16745dba787041
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validations:
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required: true
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- type: input
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id: PDEP-number-of-discussion-participants
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attributes:
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label: Discussion participants
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description: >
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You may find it useful to list or total the number of participating members in the
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PDEP discussion PR. This would be the maximum possible disapprove votes.
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placeholder: >
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14 voting members participated in the PR discussion thus far.
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- type: input
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id: PDEP-vote-end
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attributes:
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label: Voting will close in 15 days.
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description: The voting period end date. ('Voting will close in 15 days.' will be automatically written)
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- type: markdown
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attributes:
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value: ---
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- type: textarea
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id: Vote
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attributes:
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label: Vote
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value: |
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Cast your vote in a comment below.
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* +1: approve.
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* 0: abstain.
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* Reason: A one sentence reason is required.
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* -1: disapprove
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* Reason: A one sentence reason is required.
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A disapprove vote requires prior participation in the linked discussion PR.
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@pandas-dev/pandas-core
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validations:
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required: true

‎.pre-commit-config.yaml

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@@ -108,7 +108,7 @@ repos:
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types: [python]
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stages: [manual]
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additional_dependencies: &pyright_dependencies
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- [email protected].351
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- [email protected].352
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- id: pyright
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# note: assumes python env is setup and activated
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name: pyright reportGeneralTypeIssues

‎ci/code_checks.sh

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@@ -80,135 +80,49 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.CategoricalIndex.codes SA01" \
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-i "pandas.CategoricalIndex.ordered SA01" \
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-i "pandas.DataFrame.__dataframe__ SA01" \
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-i "pandas.DataFrame.__iter__ SA01" \
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-i "pandas.DataFrame.assign SA01" \
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-i "pandas.DataFrame.at_time PR01" \
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-i "pandas.DataFrame.bfill SA01" \
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-i "pandas.DataFrame.columns SA01" \
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-i "pandas.DataFrame.copy SA01" \
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-i "pandas.DataFrame.droplevel SA01" \
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-i "pandas.DataFrame.dtypes SA01" \
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-i "pandas.DataFrame.ffill SA01" \
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-i "pandas.DataFrame.first_valid_index SA01" \
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-i "pandas.DataFrame.get SA01" \
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-i "pandas.DataFrame.hist RT03" \
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-i "pandas.DataFrame.infer_objects RT03" \
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-i "pandas.DataFrame.keys SA01" \
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-i "pandas.DataFrame.kurt RT03,SA01" \
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-i "pandas.DataFrame.kurtosis RT03,SA01" \
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-i "pandas.DataFrame.last_valid_index SA01" \
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-i "pandas.DataFrame.max RT03" \
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-i "pandas.DataFrame.mean RT03,SA01" \
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-i "pandas.DataFrame.median RT03,SA01" \
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-i "pandas.DataFrame.min RT03" \
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-i "pandas.DataFrame.plot PR02,SA01" \
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-i "pandas.DataFrame.pop SA01" \
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-i "pandas.DataFrame.prod RT03" \
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-i "pandas.DataFrame.product RT03" \
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-i "pandas.DataFrame.reorder_levels SA01" \
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-i "pandas.DataFrame.sem PR01,RT03,SA01" \
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-i "pandas.DataFrame.skew RT03,SA01" \
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-i "pandas.DataFrame.sparse PR01,SA01" \
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-i "pandas.DataFrame.sparse.density SA01" \
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-i "pandas.DataFrame.sparse.from_spmatrix SA01" \
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-i "pandas.DataFrame.sparse.to_coo SA01" \
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-i "pandas.DataFrame.sparse.to_dense SA01" \
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-i "pandas.DataFrame.sparse PR01" \
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-i "pandas.DataFrame.std PR01,RT03,SA01" \
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-i "pandas.DataFrame.sum RT03" \
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-i "pandas.DataFrame.swaplevel SA01" \
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-i "pandas.DataFrame.to_feather SA01" \
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-i "pandas.DataFrame.to_markdown SA01" \
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-i "pandas.DataFrame.to_parquet RT03" \
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-i "pandas.DataFrame.var PR01,RT03,SA01" \
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-i "pandas.DatetimeIndex.ceil SA01" \
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-i "pandas.DatetimeIndex.date SA01" \
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-i "pandas.DatetimeIndex.day SA01" \
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-i "pandas.DatetimeIndex.day_name SA01" \
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-i "pandas.DatetimeIndex.day_of_year SA01" \
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-i "pandas.DatetimeIndex.dayofyear SA01" \
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-i "pandas.DatetimeIndex.floor SA01" \
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-i "pandas.DatetimeIndex.freqstr SA01" \
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-i "pandas.DatetimeIndex.hour SA01" \
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-i "pandas.DatetimeIndex.indexer_at_time PR01,RT03" \
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-i "pandas.DatetimeIndex.indexer_between_time RT03" \
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-i "pandas.DatetimeIndex.inferred_freq SA01" \
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-i "pandas.DatetimeIndex.is_leap_year SA01" \
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-i "pandas.DatetimeIndex.microsecond SA01" \
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-i "pandas.DatetimeIndex.minute SA01" \
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-i "pandas.DatetimeIndex.month SA01" \
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-i "pandas.DatetimeIndex.month_name SA01" \
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-i "pandas.DatetimeIndex.nanosecond SA01" \
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-i "pandas.DatetimeIndex.quarter SA01" \
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-i "pandas.DatetimeIndex.round SA01" \
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-i "pandas.DatetimeIndex.second SA01" \
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-i "pandas.DatetimeIndex.snap PR01,RT03,SA01" \
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-i "pandas.DatetimeIndex.std PR01,RT03" \
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-i "pandas.DatetimeIndex.time SA01" \
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-i "pandas.DatetimeIndex.timetz SA01" \
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-i "pandas.DatetimeIndex.snap PR01,RT03" \
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-i "pandas.DatetimeIndex.to_period RT03" \
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-i "pandas.DatetimeIndex.to_pydatetime RT03,SA01" \
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-i "pandas.DatetimeIndex.tz SA01" \
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-i "pandas.DatetimeIndex.tz_convert RT03" \
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-i "pandas.DatetimeIndex.year SA01" \
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-i "pandas.DatetimeTZDtype SA01" \
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-i "pandas.DatetimeTZDtype.tz SA01" \
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-i "pandas.DatetimeTZDtype.unit SA01" \
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-i "pandas.Grouper PR02,SA01" \
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-i "pandas.HDFStore.append PR01,SA01" \
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-i "pandas.HDFStore.get SA01" \
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-i "pandas.HDFStore.groups SA01" \
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-i "pandas.HDFStore.info RT03,SA01" \
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-i "pandas.HDFStore.keys SA01" \
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-i "pandas.HDFStore.put PR01,SA01" \
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-i "pandas.HDFStore.select SA01" \
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-i "pandas.HDFStore.walk SA01" \
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-i "pandas.Grouper PR02" \
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-i "pandas.Index PR07" \
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-i "pandas.Index.T SA01" \
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-i "pandas.Index.append PR07,RT03,SA01" \
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-i "pandas.Index.astype SA01" \
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-i "pandas.Index.copy PR07,SA01" \
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-i "pandas.Index.difference PR07,RT03,SA01" \
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-i "pandas.Index.drop PR07,SA01" \
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-i "pandas.Index.drop_duplicates RT03" \
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-i "pandas.Index.droplevel RT03,SA01" \
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-i "pandas.Index.dropna RT03,SA01" \
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-i "pandas.Index.dtype SA01" \
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-i "pandas.Index.duplicated RT03" \
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-i "pandas.Index.empty GL08" \
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-i "pandas.Index.equals SA01" \
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-i "pandas.Index.fillna RT03" \
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-i "pandas.Index.get_indexer PR07,SA01" \
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-i "pandas.Index.get_indexer_for PR01,SA01" \
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-i "pandas.Index.get_indexer_non_unique PR07,SA01" \
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-i "pandas.Index.get_loc PR07,RT03,SA01" \
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-i "pandas.Index.get_slice_bound PR07" \
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-i "pandas.Index.hasnans SA01" \
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-i "pandas.Index.identical PR01,SA01" \
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-i "pandas.Index.inferred_type SA01" \
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-i "pandas.Index.insert PR07,RT03,SA01" \
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-i "pandas.Index.intersection PR07,RT03,SA01" \
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-i "pandas.Index.item SA01" \
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-i "pandas.Index.join PR07,RT03,SA01" \
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-i "pandas.Index.map SA01" \
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-i "pandas.Index.memory_usage RT03" \
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-i "pandas.Index.name SA01" \
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-i "pandas.Index.names GL08" \
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-i "pandas.Index.nbytes SA01" \
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-i "pandas.Index.ndim SA01" \
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-i "pandas.Index.nunique RT03" \
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-i "pandas.Index.putmask PR01,RT03" \
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-i "pandas.Index.ravel PR01,RT03" \
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-i "pandas.Index.reindex PR07" \
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-i "pandas.Index.shape SA01" \
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-i "pandas.Index.size SA01" \
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-i "pandas.Index.slice_indexer PR07,RT03,SA01" \
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-i "pandas.Index.slice_locs RT03" \
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-i "pandas.Index.str PR01,SA01" \
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-i "pandas.Index.symmetric_difference PR07,RT03,SA01" \
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-i "pandas.Index.take PR01,PR07" \
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-i "pandas.Index.to_list RT03" \
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-i "pandas.Index.union PR07,RT03,SA01" \
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-i "pandas.Index.unique RT03" \
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-i "pandas.Index.view GL08" \
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-i "pandas.Int16Dtype SA01" \
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-i "pandas.Int32Dtype SA01" \
@@ -236,7 +150,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.MultiIndex.append PR07,SA01" \
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-i "pandas.MultiIndex.copy PR07,RT03,SA01" \
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-i "pandas.MultiIndex.drop PR07,RT03,SA01" \
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-i "pandas.MultiIndex.droplevel RT03,SA01" \
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-i "pandas.MultiIndex.dtypes SA01" \
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-i "pandas.MultiIndex.get_indexer PR07,SA01" \
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-i "pandas.MultiIndex.get_level_values SA01" \
@@ -277,7 +190,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.PeriodIndex.dayofyear SA01" \
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-i "pandas.PeriodIndex.days_in_month SA01" \
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-i "pandas.PeriodIndex.daysinmonth SA01" \
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-i "pandas.PeriodIndex.freqstr SA01" \
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-i "pandas.PeriodIndex.from_fields PR07,SA01" \
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-i "pandas.PeriodIndex.from_ordinals SA01" \
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-i "pandas.PeriodIndex.hour SA01" \
@@ -298,12 +210,10 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.RangeIndex.step SA01" \
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-i "pandas.RangeIndex.stop SA01" \
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-i "pandas.Series SA01" \
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-i "pandas.Series.T SA01" \
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-i "pandas.Series.__iter__ RT03,SA01" \
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-i "pandas.Series.add PR07" \
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-i "pandas.Series.at_time PR01" \
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-i "pandas.Series.backfill PR01,SA01" \
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-i "pandas.Series.bfill SA01" \
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-i "pandas.Series.case_when RT03" \
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-i "pandas.Series.cat PR07,SA01" \
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-i "pandas.Series.cat.add_categories PR01,PR02" \
@@ -316,67 +226,40 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.Series.cat.rename_categories PR01,PR02" \
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-i "pandas.Series.cat.reorder_categories PR01,PR02" \
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-i "pandas.Series.cat.set_categories PR01,PR02" \
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-i "pandas.Series.copy SA01" \
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-i "pandas.Series.div PR07" \
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-i "pandas.Series.droplevel SA01" \
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-i "pandas.Series.dt.as_unit PR01,PR02" \
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-i "pandas.Series.dt.ceil PR01,PR02,SA01" \
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-i "pandas.Series.dt.ceil PR01,PR02" \
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-i "pandas.Series.dt.components SA01" \
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-i "pandas.Series.dt.date SA01" \
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-i "pandas.Series.dt.day SA01" \
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-i "pandas.Series.dt.day_name PR01,PR02,SA01" \
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-i "pandas.Series.dt.day_of_year SA01" \
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-i "pandas.Series.dt.dayofyear SA01" \
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-i "pandas.Series.dt.day_name PR01,PR02" \
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-i "pandas.Series.dt.days SA01" \
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-i "pandas.Series.dt.days_in_month SA01" \
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-i "pandas.Series.dt.daysinmonth SA01" \
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-i "pandas.Series.dt.floor PR01,PR02,SA01" \
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-i "pandas.Series.dt.floor PR01,PR02" \
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-i "pandas.Series.dt.freq GL08" \
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-i "pandas.Series.dt.hour SA01" \
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-i "pandas.Series.dt.is_leap_year SA01" \
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-i "pandas.Series.dt.microsecond SA01" \
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-i "pandas.Series.dt.microseconds SA01" \
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-i "pandas.Series.dt.minute SA01" \
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-i "pandas.Series.dt.month SA01" \
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-i "pandas.Series.dt.month_name PR01,PR02,SA01" \
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-i "pandas.Series.dt.nanosecond SA01" \
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-i "pandas.Series.dt.month_name PR01,PR02" \
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-i "pandas.Series.dt.nanoseconds SA01" \
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-i "pandas.Series.dt.normalize PR01" \
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-i "pandas.Series.dt.quarter SA01" \
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-i "pandas.Series.dt.qyear GL08" \
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-i "pandas.Series.dt.round PR01,PR02,SA01" \
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-i "pandas.Series.dt.second SA01" \
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-i "pandas.Series.dt.round PR01,PR02" \
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-i "pandas.Series.dt.seconds SA01" \
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-i "pandas.Series.dt.strftime PR01,PR02" \
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-i "pandas.Series.dt.time SA01" \
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-i "pandas.Series.dt.timetz SA01" \
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-i "pandas.Series.dt.to_period PR01,PR02,RT03" \
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-i "pandas.Series.dt.total_seconds PR01" \
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-i "pandas.Series.dt.tz SA01" \
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-i "pandas.Series.dt.tz_convert PR01,PR02,RT03" \
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-i "pandas.Series.dt.tz_convert PR01,PR02" \
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-i "pandas.Series.dt.tz_localize PR01,PR02" \
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-i "pandas.Series.dt.unit GL08" \
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-i "pandas.Series.dt.year SA01" \
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-i "pandas.Series.dtype SA01" \
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-i "pandas.Series.dtypes SA01" \
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-i "pandas.Series.empty GL08" \
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-i "pandas.Series.eq PR07,SA01" \
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-i "pandas.Series.ffill SA01" \
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-i "pandas.Series.first_valid_index SA01" \
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-i "pandas.Series.floordiv PR07" \
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-i "pandas.Series.ge PR07,SA01" \
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-i "pandas.Series.get SA01" \
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-i "pandas.Series.gt PR07,SA01" \
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-i "pandas.Series.hasnans SA01" \
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-i "pandas.Series.infer_objects RT03" \
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-i "pandas.Series.is_monotonic_decreasing SA01" \
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-i "pandas.Series.is_monotonic_increasing SA01" \
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-i "pandas.Series.is_unique SA01" \
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-i "pandas.Series.item SA01" \
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-i "pandas.Series.keys SA01" \
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-i "pandas.Series.kurt RT03,SA01" \
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-i "pandas.Series.kurtosis RT03,SA01" \
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-i "pandas.Series.last_valid_index SA01" \
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-i "pandas.Series.le PR07,SA01" \
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-i "pandas.Series.list.__getitem__ SA01" \
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-i "pandas.Series.list.flatten SA01" \
@@ -389,8 +272,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.Series.mod PR07" \
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-i "pandas.Series.mode SA01" \
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-i "pandas.Series.mul PR07" \
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-i "pandas.Series.nbytes SA01" \
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-i "pandas.Series.ndim SA01" \
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-i "pandas.Series.ne PR07,SA01" \
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-i "pandas.Series.nunique RT03" \
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-i "pandas.Series.pad PR01,SA01" \
@@ -410,7 +291,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.Series.rtruediv PR07" \
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-i "pandas.Series.sem PR01,RT03,SA01" \
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-i "pandas.Series.shape SA01" \
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-i "pandas.Series.size SA01" \
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-i "pandas.Series.skew RT03,SA01" \
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-i "pandas.Series.sparse PR01,SA01" \
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-i "pandas.Series.sparse.density SA01" \
@@ -456,7 +336,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.Series.swaplevel SA01" \
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-i "pandas.Series.to_dict SA01" \
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-i "pandas.Series.to_frame SA01" \
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-i "pandas.Series.to_list RT03" \
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-i "pandas.Series.to_markdown SA01" \
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-i "pandas.Series.to_string SA01" \
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-i "pandas.Series.truediv PR07" \
@@ -479,14 +358,10 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.Timedelta.total_seconds SA01" \
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-i "pandas.Timedelta.view SA01" \
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-i "pandas.TimedeltaIndex.as_unit RT03,SA01" \
482-
-i "pandas.TimedeltaIndex.ceil SA01" \
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-i "pandas.TimedeltaIndex.components SA01" \
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-i "pandas.TimedeltaIndex.days SA01" \
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-i "pandas.TimedeltaIndex.floor SA01" \
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-i "pandas.TimedeltaIndex.inferred_freq SA01" \
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-i "pandas.TimedeltaIndex.microseconds SA01" \
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-i "pandas.TimedeltaIndex.nanoseconds SA01" \
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-i "pandas.TimedeltaIndex.round SA01" \
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-i "pandas.TimedeltaIndex.seconds SA01" \
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-i "pandas.TimedeltaIndex.to_pytimedelta RT03,SA01" \
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-i "pandas.Timestamp PR07,SA01" \

‎doc/source/development/community.rst

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@@ -100,6 +100,8 @@ The pandas mailing list `[email protected] <mailto://pandas-dev@python
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conversations and to engage people in the wider community who might not
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be active on the issue tracker but we would like to include in discussions.
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Join the mailing list and view the archives `here <https://mail.python.org/mailman/listinfo/pandas-dev>`_.
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.. _community.slack:
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Community slack

‎doc/source/development/contributing_codebase.rst

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@@ -557,11 +557,12 @@ is being raised, using ``pytest.raises`` instead.
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Testing a warning
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^^^^^^^^^^^^^^^^^
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Use ``tm.assert_produces_warning`` as a context manager to check that a block of code raises a warning.
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Use ``tm.assert_produces_warning`` as a context manager to check that a block of code raises a warning
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and specify the warning message using the ``match`` argument.
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.. code-block:: python
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with tm.assert_produces_warning(DeprecationWarning):
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with tm.assert_produces_warning(DeprecationWarning, match="the warning message"):
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pd.deprecated_function()
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If a warning should specifically not happen in a block of code, pass ``False`` into the context manager.

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