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.github/actions/setup-conda/action.yml

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@@ -9,6 +9,8 @@ runs:
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- name: Install ${{ inputs.environment-file }}
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uses: mamba-org/setup-micromamba@v1
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with:
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# Pinning to avoid 2.0 failures
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micromamba-version: '1.5.10-0'
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environment-file: ${{ inputs.environment-file }}
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environment-name: test
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condarc-file: ci/.condarc

ci/code_checks.sh

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@@ -74,8 +74,29 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.Period.ordinal GL08" \
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-i "pandas.RangeIndex.from_range PR01,SA01" \
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-i "pandas.RangeIndex.step SA01" \
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-i "pandas.Series.cat.add_categories PR01,PR02" \
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-i "pandas.Series.cat.as_ordered PR01" \
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-i "pandas.Series.cat.as_unordered PR01" \
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-i "pandas.Series.cat.remove_categories PR01,PR02" \
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-i "pandas.Series.cat.remove_unused_categories PR01" \
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-i "pandas.Series.cat.rename_categories PR01,PR02" \
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-i "pandas.Series.cat.reorder_categories PR01,PR02" \
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-i "pandas.Series.cat.set_categories PR01,PR02" \
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-i "pandas.Series.dt.as_unit PR01,PR02" \
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-i "pandas.Series.dt.ceil PR01,PR02" \
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-i "pandas.Series.dt.day_name PR01,PR02" \
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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.month_name PR01,PR02" \
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-i "pandas.Series.dt.normalize PR01" \
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-i "pandas.Series.dt.round PR01,PR02" \
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-i "pandas.Series.dt.strftime PR01,PR02" \
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-i "pandas.Series.dt.to_period PR01,PR02" \
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-i "pandas.Series.dt.total_seconds PR01" \
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-i "pandas.Series.dt.tz_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.pad PR01,SA01" \
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-i "pandas.Series.sparse.fill_value SA01" \
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-i "pandas.Series.sparse.from_coo PR07,SA01" \
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-i "pandas.Series.sparse.npoints SA01" \
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-i "pandas.Series.sparse.sp_values SA01" \
@@ -84,43 +105,27 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.Timedelta.max PR02" \
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-i "pandas.Timedelta.min PR02" \
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-i "pandas.Timedelta.resolution PR02" \
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-i "pandas.Timedelta.to_timedelta64 SA01" \
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-i "pandas.TimedeltaIndex.to_pytimedelta RT03,SA01" \
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-i "pandas.Timestamp.max PR02" \
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-i "pandas.Timestamp.min PR02" \
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-i "pandas.Timestamp.nanosecond GL08" \
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-i "pandas.Timestamp.resolution PR02" \
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-i "pandas.Timestamp.tzinfo GL08" \
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-i "pandas.Timestamp.year GL08" \
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-i "pandas.api.types.is_dict_like PR07,SA01" \
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-i "pandas.api.types.is_file_like PR07,SA01" \
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-i "pandas.api.types.is_float PR01,SA01" \
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-i "pandas.api.types.is_float_dtype SA01" \
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-i "pandas.api.types.is_hashable PR01,RT03,SA01" \
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-i "pandas.api.types.is_int64_dtype SA01" \
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-i "pandas.api.types.is_integer PR01,SA01" \
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-i "pandas.api.types.is_interval_dtype SA01" \
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-i "pandas.api.types.is_iterator PR07,SA01" \
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-i "pandas.api.types.is_list_like SA01" \
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-i "pandas.api.types.is_named_tuple PR07,SA01" \
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-i "pandas.api.types.is_object_dtype SA01" \
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-i "pandas.api.types.is_re PR07,SA01" \
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-i "pandas.api.types.is_re_compilable PR07,SA01" \
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-i "pandas.api.types.pandas_dtype PR07,RT03,SA01" \
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-i "pandas.arrays.ArrowExtensionArray PR07,SA01" \
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-i "pandas.arrays.BooleanArray SA01" \
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-i "pandas.arrays.DatetimeArray SA01" \
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-i "pandas.arrays.IntegerArray SA01" \
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-i "pandas.arrays.IntervalArray.left SA01" \
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-i "pandas.arrays.IntervalArray.length SA01" \
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-i "pandas.arrays.IntervalArray.mid SA01" \
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-i "pandas.arrays.IntervalArray.right SA01" \
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-i "pandas.arrays.NumpyExtensionArray SA01" \
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-i "pandas.arrays.SparseArray PR07,SA01" \
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-i "pandas.arrays.TimedeltaArray PR07,SA01" \
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-i "pandas.core.groupby.DataFrameGroupBy.__iter__ RT03,SA01" \
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-i "pandas.core.groupby.DataFrameGroupBy.agg RT03" \
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-i "pandas.core.groupby.DataFrameGroupBy.aggregate RT03" \
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-i "pandas.core.groupby.DataFrameGroupBy.boxplot PR07,RT03,SA01" \
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-i "pandas.core.groupby.DataFrameGroupBy.get_group RT03,SA01" \
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-i "pandas.core.groupby.DataFrameGroupBy.groups SA01" \
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-i "pandas.core.groupby.DataFrameGroupBy.plot PR02" \
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-i "pandas.core.groupby.DataFrameGroupBy.sem SA01" \
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-i "pandas.core.groupby.SeriesGroupBy.__iter__ RT03,SA01" \
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-i "pandas.core.groupby.SeriesGroupBy.agg RT03" \
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-i "pandas.core.groupby.SeriesGroupBy.aggregate RT03" \
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-i "pandas.core.groupby.SeriesGroupBy.get_group RT03,SA01" \
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-i "pandas.core.groupby.SeriesGroupBy.groups SA01" \
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-i "pandas.core.groupby.SeriesGroupBy.indices SA01" \
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-i "pandas.core.groupby.SeriesGroupBy.plot PR02" \
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-i "pandas.core.groupby.SeriesGroupBy.sem SA01" \
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-i "pandas.core.resample.Resampler.__iter__ RT03,SA01" \
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-i "pandas.core.resample.Resampler.ffill RT03" \
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-i "pandas.core.resample.Resampler.get_group RT03,SA01" \
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-i "pandas.core.resample.Resampler.groups SA01" \
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-i "pandas.core.resample.Resampler.indices SA01" \
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-i "pandas.core.resample.Resampler.transform PR01,RT03,SA01" \
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-i "pandas.errors.AttributeConflictWarning SA01" \
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-i "pandas.errors.CSSWarning SA01" \
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-i "pandas.errors.CategoricalConversionWarning SA01" \
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-i "pandas.errors.ChainedAssignmentError SA01" \
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-i "pandas.errors.DataError SA01" \
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-i "pandas.errors.DuplicateLabelError SA01" \
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-i "pandas.errors.EmptyDataError SA01" \
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-i "pandas.errors.IntCastingNaNError SA01" \
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-i "pandas.errors.InvalidIndexError SA01" \
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-i "pandas.errors.InvalidVersion SA01" \
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-i "pandas.errors.NullFrequencyError SA01" \
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-i "pandas.errors.NumExprClobberingError SA01" \
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-i "pandas.errors.NumbaUtilError SA01" \
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-i "pandas.errors.OutOfBoundsTimedelta SA01" \
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-i "pandas.tseries.offsets.SemiMonthBegin.normalize GL08" \
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-i "pandas.tseries.offsets.SemiMonthBegin.rule_code GL08" \
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-i "pandas.tseries.offsets.SemiMonthEnd SA01" \
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-i "pandas.tseries.offsets.SemiMonthEnd.day_of_month GL08" \
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-i "pandas.tseries.offsets.SemiMonthEnd.is_on_offset GL08" \
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-i "pandas.tseries.offsets.SemiMonthEnd.n GL08" \

doc/source/development/contributing.rst

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branch and update your development environment to reflect any changes to the various packages that
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are used during development.
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If using :ref:`mamba <contributing.mamba>`, run:
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If using :ref:`conda <contributing.conda>`, run:
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.. code-block:: shell
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git checkout main
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git fetch upstream
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git merge upstream/main
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mamba activate pandas-dev
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mamba env update -f environment.yml --prune
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conda activate pandas-dev
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conda env update -f environment.yml --prune
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If using :ref:`pip <contributing.pip>` , do:
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doc/source/development/contributing_codebase.rst

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.. warning::
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* Please be aware that the above commands will use the current python environment. If your python packages are older/newer than those installed by the pandas CI, the above commands might fail. This is often the case when the ``mypy`` or ``numpy`` versions do not match. Please see :ref:`how to setup the python environment <contributing.mamba>` or select a `recently succeeded workflow <https://github.com/pandas-dev/pandas/actions/workflows/code-checks.yml?query=branch%3Amain+is%3Asuccess>`_, select the "Docstring validation, typing, and other manual pre-commit hooks" job, then click on "Set up Conda" and "Environment info" to see which versions the pandas CI installs.
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* Please be aware that the above commands will use the current python environment. If your python packages are older/newer than those installed by the pandas CI, the above commands might fail. This is often the case when the ``mypy`` or ``numpy`` versions do not match. Please see :ref:`how to setup the python environment <contributing.conda>` or select a `recently succeeded workflow <https://github.com/pandas-dev/pandas/actions/workflows/code-checks.yml?query=branch%3Amain+is%3Asuccess>`_, select the "Docstring validation, typing, and other manual pre-commit hooks" job, then click on "Set up Conda" and "Environment info" to see which versions the pandas CI installs.
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.. _contributing.ci:
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doc/source/development/contributing_environment.rst

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To use the :ref:`mamba <contributing.mamba>`-based compilers, you will need to install the
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To use the :ref:`conda <contributing.conda>`-based compilers, you will need to install the
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Developer Tools using ``xcode-select --install``.
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If you prefer to use a different compiler, general information can be found here:
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https://devguide.python.org/setup/#macos
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**Linux**
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For Linux-based :ref:`mamba <contributing.mamba>` installations, you won't have to install any
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additional components outside of the mamba environment. The instructions
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below are only needed if your setup isn't based on mamba environments.
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For Linux-based :ref:`conda <contributing.conda>` installations, you won't have to install any
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additional components outside of the conda environment. The instructions
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below are only needed if your setup isn't based on conda environments.
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Some Linux distributions will come with a pre-installed C compiler. To find out
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.. _contributing.mamba:
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.. _contributing.conda:
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Option 1: using mamba (recommended)
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Option 1: using conda (recommended)
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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* Install miniforge to get `mamba <https://mamba.readthedocs.io/en/latest/installation/mamba-installation.html>`_
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* Make sure your mamba is up to date (``mamba update mamba``)
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* Create and activate the ``pandas-dev`` mamba environment using the following commands:
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* Install miniforge to get `conda <https://github.com/conda-forge/miniforge?tab=readme-ov-file#download>`_
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* Create and activate the ``pandas-dev`` conda environment using the following commands:
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.. code-block:: none
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.. code-block:: bash
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mamba env create --file environment.yml
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mamba activate pandas-dev
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conda env create --file environment.yml
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conda activate pandas-dev
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.. _contributing.pip:
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doc/source/development/maintaining.rst

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- Git repo with a `new tag <https://github.com/pandas-dev/pandas/tags>`_
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- Source distribution in a `GitHub release <https://github.com/pandas-dev/pandas/releases>`_
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- Pip packages in the `PyPI <https://pypi.org/project/pandas/>`_
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- Conda/Mamba packages in `conda-forge <https://anaconda.org/conda-forge/pandas>`_
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- Conda packages in `conda-forge <https://anaconda.org/conda-forge/pandas>`_
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The process for releasing a new version of pandas is detailed next section.
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doc/source/getting_started/index.rst

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:columns: 12 12 6 6
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pandas is part of the `Anaconda <https://docs.continuum.io/anaconda/>`__
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distribution and can be installed with Anaconda or Miniconda:
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pandas can be installed via conda from `conda-forge <https://anaconda.org/conda-forge/pandas>`__.
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++++++++++++++++++++++
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