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‎.github/workflows/code-checks.yml‎

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steps:
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- name: Checkout
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uses: actions/checkout@v5
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uses: actions/checkout@v6
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fetch-depth: 0
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steps:
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- name: Checkout
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uses: actions/checkout@v5
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uses: actions/checkout@v6
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fetch-depth: 0
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steps:
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- name: Checkout
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uses: actions/checkout@v5
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uses: actions/checkout@v6
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fetch-depth: 0
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‎.github/workflows/codeql.yml‎

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- python
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steps:
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- uses: actions/checkout@v5
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- uses: actions/checkout@v6
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- uses: github/codeql-action/init@v4
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with:
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languages: ${{ matrix.language }}

‎.github/workflows/docbuild-and-upload.yml‎

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steps:
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- name: Checkout
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uses: actions/checkout@v5
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uses: actions/checkout@v6
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‎.github/workflows/package-checks.yml‎

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steps:
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- name: Checkout
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uses: actions/checkout@v5
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uses: actions/checkout@v6
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cancel-in-progress: true
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steps:
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uses: actions/checkout@v5
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uses: actions/checkout@v6
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fetch-depth: 0
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‎.github/workflows/unit-tests.yml‎

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- name: Checkout
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uses: actions/checkout@v5
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uses: actions/checkout@v6
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fetch-depth: 0
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- name: Checkout
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uses: actions/checkout@v5
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uses: actions/checkout@v6
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Linux-32-bit:
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runs-on: ubuntu-24.04
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container:
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image: quay.io/pypa/manylinux2014_i686
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image: quay.io/pypa/manylinux_2_28_i686
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options: --platform linux/386
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steps:
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- name: Checkout pandas Repo
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PYTEST_TARGET: pandas
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- uses: actions/checkout@v6
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uses: actions/checkout@v5
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uses: actions/checkout@v6
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‎.github/workflows/wheels.yml‎

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sdist_file: ${{ steps.save-path.outputs.sdist_name }}
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uses: actions/checkout@v6
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IS_SCHEDULE_DISPATCH: ${{ github.event_name == 'schedule' || github.event_name == 'workflow_dispatch' }}
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uses: actions/checkout@v6
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‎.gitignore‎

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.noseids
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.ipynb_checkpoints
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.tags
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tags
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.cache/
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.vscode/
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‎ci/code_checks.sh‎

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-i "pandas.Period.freq GL08" \
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-i "pandas.Period.ordinal GL08" \
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-i "pandas.errors.IncompatibleFrequency SA01,SS06,EX01" \
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-i "pandas.errors.InvalidVersion GL08" \
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-i "pandas.api.extensions.ExtensionArray.value_counts EX01,RT03,SA01" \
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-i "pandas.api.typing.DataFrameGroupBy.plot PR02" \
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-i "pandas.api.typing.SeriesGroupBy.plot PR02" \
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-i "pandas.api.typing.Resampler.quantile PR01,PR07" \
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-i "pandas.arrays.NumpyExtensionArray GL08" \
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-i "pandas.tseries.offsets.BDay PR02,SA01" \
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-i "pandas.tseries.offsets.BHalfYearBegin.is_on_offset GL08" \
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-i "pandas.tseries.offsets.BHalfYearBegin.n GL08" \

‎doc/source/whatsnew/v3.0.0.rst‎

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- Bug in :meth:`.DataFrameGroupBy.groups` and :meth:`.SeriesGroupby.groups` that would not respect groupby argument ``dropna`` (:issue:`55919`)
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- Bug in :meth:`.DataFrameGroupBy.median` where nat values gave an incorrect result. (:issue:`57926`)
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- Bug in :meth:`.DataFrameGroupBy.quantile` when ``interpolation="nearest"`` is inconsistent with :meth:`DataFrame.quantile` (:issue:`47942`)
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- Bug in :meth:`.DataFrameGroupBy.sum` and :meth:`.SeriesGroupby.groups` returning ``NaN`` on overflow. These methods now returns ``inf`` or ``-inf`` on overflow. (:issue:`60303`)
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- Bug in :meth:`.DataFrameGroupBy` reductions where non-Boolean values were allowed for the ``numeric_only`` argument; passing a non-Boolean value will now raise (:issue:`62778`)
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- Bug in :meth:`.Resampler.interpolate` on a :class:`DataFrame` with non-uniform sampling and/or indices not aligning with the resulting resampled index would result in wrong interpolation (:issue:`21351`)
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- Bug in :meth:`.Series.rolling` when used with a :class:`.BaseIndexer` subclass and computing min/max (:issue:`46726`)
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- Bug in :meth:`DataFrameGroupby.transform` and :meth:`SeriesGroupby.transform` with a reducer and ``observed=False`` that coerces dtype to float when there are unobserved categories. (:issue:`55326`)
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- Bug in :meth:`Rolling.apply` for ``method="table"`` where column order was not being respected due to the columns getting sorted by default. (:issue:`59666`)
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- Bug in :meth:`Rolling.apply` where the applied function could be called on fewer than ``min_period`` periods if ``method="table"``. (:issue:`58868`)
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- Bug in :meth:`Rolling.sem` computing incorrect results because it divided by ``sqrt((n - 1) * (n - ddof))`` instead of ``sqrt(n * (n - ddof))``. (:issue:`63180`)
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- Bug in :meth:`Rolling.skew` incorrectly computing skewness for windows following outliers due to numerical instability. The calculation now properly handles catastrophic cancellation by recomputing affected windows (:issue:`47461`)
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- Bug in :meth:`Series.resample` could raise when the date range ended shortly before a non-existent time. (:issue:`58380`)
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- Bug in :meth:`Series.resample` raising error when resampling non-nanosecond resolutions out of bounds for nanosecond precision (:issue:`57427`)

‎pandas/_libs/groupby.pyx‎

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)
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from libc.math cimport (
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sqrt,
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from libc.stdlib cimport (
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# NB: this does not use 'compensation' like the non-object
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# track does.
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# and non-integer track does.
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if nobs[lab, j] == 1:
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# GH#53606
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# Handle float overflow
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if (
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# GH#53606; GH#60303
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# which would lead to results being NaN instead
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# of +/- infinity. We cannot use util.is_nan
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compensation[lab, j] = 0
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compensation[lab, j].real = 0
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if uses_mask:

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