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‎ci/code_checks.sh

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@@ -16,12 +16,18 @@
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set -uo pipefail
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[[ -z "$1" || "$1" == "code" || "$1" == "doctests" || "$1" == "docstrings" || "$1" == "single-docs" || "$1" == "notebooks" ]] || \
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if [[ -v 1 ]]; then
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CHECK=$1
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else
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# script will fail if it uses an unset variable (i.e. $1 is not provided)
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CHECK=""
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fi
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[[ -z "$CHECK" || "$CHECK" == "code" || "$CHECK" == "doctests" || "$CHECK" == "docstrings" || "$CHECK" == "single-docs" || "$CHECK" == "notebooks" ]] || \
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{ echo "Unknown command $1. Usage: $0 [code|doctests|docstrings|single-docs|notebooks]"; exit 9999; }
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BASE_DIR="$(dirname $0)/.."
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RET=0
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CHECK=$1
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### CODE ###
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if [[ -z "$CHECK" || "$CHECK" == "code" ]]; then
@@ -59,110 +65,28 @@ fi
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### DOCSTRINGS ###
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if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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MSG='Validate docstrings (EX01, EX02, EX04, GL01, GL02, GL03, GL04, GL05, GL06, GL07, GL09, GL10, PR03, PR04, PR05, PR06, PR08, PR09, PR10, RT01, RT02, RT04, RT05, SA02, SA03, SA04, SS01, SS02, SS03, SS04, SS05, SS06)' ; echo $MSG
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$BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=EX01,EX02,EX04,GL01,GL02,GL03,GL04,GL05,GL06,GL07,GL09,GL10,PR03,PR04,PR05,PR06,PR08,PR09,PR10,RT01,RT02,RT04,RT05,SA02,SA03,SA04,SS01,SS02,SS03,SS04,SS05,SS06
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MSG='Validate docstrings (EX01, EX04, GL01, GL02, GL03, GL04, GL05, GL06, GL07, GL09, GL10, PR03, PR04, PR05, PR06, PR08, PR09, PR10, RT01, RT02, RT04, RT05, SA02, SA03, SA04, SS01, SS02, SS03, SS04, SS05, SS06)' ; echo $MSG
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$BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=EX01,EX04,GL01,GL02,GL03,GL04,GL05,GL06,GL07,GL09,GL10,PR03,PR04,PR05,PR06,PR08,PR09,PR10,RT01,RT02,RT04,RT05,SA02,SA03,SA04,SS01,SS02,SS03,SS04,SS05,SS06
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RET=$(($RET + $?)) ; echo $MSG "DONE"
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MSG='Partially validate docstrings (EX03)' ; echo $MSG
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$BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=EX03 --ignore_functions \
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pandas.Series.dt.day_name \
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pandas.Series.str.len \
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pandas.Series.cat.set_categories \
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pandas.Series.plot.bar \
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pandas.Series.plot.hist \
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pandas.Series.plot.line \
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pandas.Series.to_sql \
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pandas.Series.to_latex \
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pandas.errors.CategoricalConversionWarning \
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pandas.errors.ChainedAssignmentError \
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pandas.errors.ClosedFileError \
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pandas.errors.DatabaseError \
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pandas.errors.IndexingError \
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pandas.errors.InvalidColumnName \
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pandas.errors.NumExprClobberingError \
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pandas.errors.PossibleDataLossError \
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pandas.errors.PossiblePrecisionLoss \
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pandas.errors.SettingWithCopyError \
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pandas.errors.SettingWithCopyWarning \
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pandas.errors.SpecificationError \
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pandas.errors.UndefinedVariableError \
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pandas.errors.ValueLabelTypeMismatch \
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pandas.Timestamp.ceil \
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pandas.Timestamp.floor \
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pandas.Timestamp.round \
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pandas.read_pickle \
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pandas.ExcelWriter \
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pandas.read_json \
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pandas.io.json.build_table_schema \
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pandas.DataFrame.to_latex \
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pandas.io.formats.style.Styler.to_latex \
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pandas.read_parquet \
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pandas.DataFrame.to_sql \
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pandas.read_stata \
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pandas.core.resample.Resampler.pipe \
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pandas.core.resample.Resampler.fillna \
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pandas.core.resample.Resampler.interpolate \
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pandas.plotting.scatter_matrix \
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pandas.pivot \
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pandas.merge_asof \
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pandas.wide_to_long \
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pandas.Index.rename \
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pandas.Index.droplevel \
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pandas.Index.isin \
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pandas.CategoricalIndex.set_categories \
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pandas.MultiIndex.names \
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pandas.MultiIndex.droplevel \
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pandas.IndexSlice \
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pandas.DatetimeIndex.month_name \
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pandas.DatetimeIndex.day_name \
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pandas.core.window.rolling.Rolling.corr \
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pandas.Grouper \
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pandas.core.groupby.SeriesGroupBy.apply \
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pandas.core.groupby.DataFrameGroupBy.apply \
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pandas.core.groupby.SeriesGroupBy.transform \
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pandas.core.groupby.SeriesGroupBy.pipe \
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pandas.core.groupby.DataFrameGroupBy.pipe \
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pandas.core.groupby.DataFrameGroupBy.describe \
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pandas.core.groupby.DataFrameGroupBy.idxmax \
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pandas.core.groupby.DataFrameGroupBy.idxmin \
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pandas.core.groupby.DataFrameGroupBy.value_counts \
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pandas.core.groupby.SeriesGroupBy.describe \
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pandas.core.groupby.DataFrameGroupBy.boxplot \
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pandas.core.groupby.DataFrameGroupBy.hist \
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pandas.io.formats.style.Styler.map \
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pandas.io.formats.style.Styler.apply_index \
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pandas.io.formats.style.Styler.map_index \
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pandas.io.formats.style.Styler.format \
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pandas.io.formats.style.Styler.format_index \
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pandas.io.formats.style.Styler.relabel_index \
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pandas.io.formats.style.Styler.hide \
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pandas.io.formats.style.Styler.set_td_classes \
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pandas.io.formats.style.Styler.set_tooltips \
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pandas.io.formats.style.Styler.set_uuid \
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pandas.io.formats.style.Styler.pipe \
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pandas.io.formats.style.Styler.highlight_between \
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pandas.io.formats.style.Styler.highlight_quantile \
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pandas.io.formats.style.Styler.background_gradient \
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pandas.io.formats.style.Styler.text_gradient \
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pandas.DataFrame.values \
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pandas.DataFrame.loc \
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pandas.DataFrame.iloc \
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pandas.DataFrame.groupby \
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pandas.DataFrame.describe \
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pandas.DataFrame.skew \
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pandas.DataFrame.var \
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pandas.DataFrame.idxmax \
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pandas.DataFrame.idxmin \
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pandas.DataFrame.last \
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pandas.DataFrame.pivot \
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pandas.DataFrame.sort_values \
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pandas.DataFrame.tz_convert \
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pandas.DataFrame.tz_localize \
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pandas.DataFrame.plot.bar \
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pandas.DataFrame.plot.hexbin \
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pandas.DataFrame.plot.hist \
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pandas.DataFrame.plot.line \
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pandas.DataFrame.hist \
89+
pandas.io.formats.style.Styler.text_gradient
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RET=$(($RET + $?)) ; echo $MSG "DONE"
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fi

‎doc/source/development/contributing.rst

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@@ -19,7 +19,7 @@ Bug reports and enhancement requests
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====================================
2020

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Bug reports and enhancement requests are an important part of making pandas more stable and
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are curated though Github issues. When reporting and issue or request, please select the `appropriate
22+
are curated though Github issues. When reporting an issue or request, please select the `appropriate
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category and fill out the issue form fully <https://github.com/pandas-dev/pandas/issues/new/choose>`_
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to ensure others and the core development team can fully understand the scope of the issue.
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‎doc/source/development/contributing_docstring.rst

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Finally, docstrings can also be appended to with the ``doc`` decorator.
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In this example, we'll create a parent docstring normally (this is like
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``pandas.core.generic.NDFrame``. Then we'll have two children (like
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``pandas.core.generic.NDFrame``). Then we'll have two children (like
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``pandas.core.series.Series`` and ``pandas.core.frame.DataFrame``). We'll
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substitute the class names in this docstring.
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‎doc/source/reference/series.rst

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:toctree: api/
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Series.align
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Series.case_when
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Series.drop
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Series.droplevel
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Series.drop_duplicates

‎doc/source/user_guide/io.rst

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.. code-block:: python
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storage_options = {"client_kwargs": {"endpoint_url": "http://127.0.0.1:5555"}}}
1707+
storage_options = {"client_kwargs": {"endpoint_url": "http://127.0.0.1:5555"}}
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df = pd.read_json("s3://pandas-test/test-1", storage_options=storage_options)
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More sample configurations and documentation can be found at `S3Fs documentation
@@ -3015,14 +3015,15 @@ Read in the content of the "books.xml" as instance of ``StringIO`` or
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Even read XML from AWS S3 buckets such as NIH NCBI PMC Article Datasets providing
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Biomedical and Life Science Jorurnals:
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3018-
.. ipython:: python
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:okwarning:
3018+
.. code-block:: python
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3021-
df = pd.read_xml(
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"s3://pmc-oa-opendata/oa_comm/xml/all/PMC1236943.xml",
3023-
xpath=".//journal-meta",
3024-
)
3025-
df
3020+
>>> df = pd.read_xml(
3021+
... "s3://pmc-oa-opendata/oa_comm/xml/all/PMC1236943.xml",
3022+
... xpath=".//journal-meta",
3023+
...)
3024+
>>> df
3025+
journal-id journal-title issn publisher
3026+
0 Cardiovasc Ultrasound Cardiovascular Ultrasound 1476-7120 NaN
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With `lxml`_ as default ``parser``, you access the full-featured XML library
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that extends Python's ElementTree API. One powerful tool is ability to query

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