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.github/CODEOWNERS

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@@ -10,10 +10,8 @@ doc/source/development @noatamir
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# pandas
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pandas/_libs/ @WillAyd
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pandas/_libs/tslibs/* @MarcoGorelli
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pandas/_typing.py @Dr-Irv
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pandas/core/groupby/* @rhshadrach
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pandas/core/tools/datetimes.py @MarcoGorelli
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pandas/io/excel/* @rhshadrach
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pandas/io/formats/style.py @attack68
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pandas/io/formats/style_render.py @attack68

.github/actions/run-tests/action.yml

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@@ -14,7 +14,7 @@ runs:
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if: failure()
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- name: Upload coverage to Codecov
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uses: codecov/codecov-action@v4
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uses: codecov/codecov-action@v5
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with:
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flags: unittests
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name: codecov-pandas

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

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@@ -7,7 +7,7 @@ runs:
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using: composite
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steps:
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- name: Install ${{ inputs.environment-file }}
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uses: mamba-org/setup-micromamba@v1
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uses: mamba-org/setup-micromamba@v2
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with:
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environment-file: ${{ inputs.environment-file }}
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environment-name: test

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

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@@ -59,6 +59,10 @@ jobs:
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- name: Build documentation
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run: doc/make.py --warnings-are-errors
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- name: Build the interactive terminal
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working-directory: web/interactive_terminal
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run: jupyter lite build
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- name: Build documentation zip
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run: doc/make.py zip_html
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.github/workflows/wheels.yml

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@@ -153,7 +153,7 @@ jobs:
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run: echo "sdist_name=$(cd ./dist && ls -d */)" >> "$GITHUB_ENV"
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- name: Build wheels
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uses: pypa/cibuildwheel@v2.22.0
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uses: pypa/cibuildwheel@v2.23.2
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with:
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package-dir: ./dist/${{ startsWith(matrix.buildplat[1], 'macosx') && env.sdist_name || needs.build_sdist.outputs.sdist_file }}
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env:

.pre-commit-config.yaml

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@@ -1,4 +1,4 @@
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minimum_pre_commit_version: 2.15.0
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minimum_pre_commit_version: 4.0.0
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exclude: ^LICENSES/|\.(html|csv|svg)$
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# reserve "manual" for relatively slow hooks which we still want to run in CI
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default_stages: [
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skip: [pyright, mypy]
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repos:
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- repo: https://github.com/astral-sh/ruff-pre-commit
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rev: v0.9.4
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rev: v0.11.4
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hooks:
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- id: ruff
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args: [--exit-non-zero-on-fix]
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exclude: ^pandas/tests/frame/test_query_eval.py
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- id: ruff
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# TODO: remove autofixe-only rules when they are checked by ruff
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# TODO: remove autofix only rules when they are checked by ruff
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name: ruff-selected-autofixes
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alias: ruff-selected-autofixes
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files: ^pandas
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- id: ruff-format
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exclude: ^scripts|^pandas/tests/frame/test_query_eval.py
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- repo: https://github.com/jendrikseipp/vulture
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rev: 'v2.14'
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rev: v2.14
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hooks:
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- id: vulture
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entry: python scripts/run_vulture.py
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- id: trailing-whitespace
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args: [--markdown-linebreak-ext=md]
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- repo: https://github.com/PyCQA/isort
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rev: 6.0.0
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rev: 6.0.1
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hooks:
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- id: isort
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- repo: https://github.com/asottile/pyupgrade
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- id: sphinx-lint
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args: ["--enable", "all", "--disable", "line-too-long"]
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- repo: https://github.com/pre-commit/mirrors-clang-format
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rev: v19.1.7
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rev: v20.1.0
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hooks:
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- id: clang-format
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files: ^pandas/_libs/src|^pandas/_libs/include
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args: [-i]
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types_or: [c, c++]
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- repo: https://github.com/trim21/pre-commit-mirror-meson
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rev: v1.7.0
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rev: v1.7.2
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hooks:
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- id: meson-fmt
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args: ['--inplace']

Dockerfile

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@@ -13,5 +13,5 @@ COPY requirements-dev.txt /tmp
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RUN python -m pip install -r /tmp/requirements-dev.txt
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RUN git config --global --add safe.directory /home/pandas
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ENV SHELL "/bin/bash"
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ENV SHELL="/bin/bash"
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CMD ["/bin/bash"]

asv_bench/benchmarks/frame_methods.py

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self.df = DataFrame(np.random.randn(1000, 100))
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self.s = Series(np.arange(1028.0))
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self.df2 = DataFrame({i: self.s for i in range(1028)})
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self.df2 = DataFrame(dict.fromkeys(range(1028), self.s))
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self.df3 = DataFrame(np.random.randn(1000, 3), columns=list("ABC"))
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def time_apply_user_func(self):

asv_bench/benchmarks/indexing_engines.py

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@@ -67,6 +67,14 @@ class NumericEngineIndexing:
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def setup(self, engine_and_dtype, index_type, unique, N):
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engine, dtype = engine_and_dtype
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if (
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index_type == "non_monotonic"
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and dtype in [np.int16, np.int8, np.uint8]
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and unique
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):
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# Values overflow
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raise NotImplementedError
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if index_type == "monotonic_incr":
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if unique:
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arr = np.arange(N * 3, dtype=dtype)
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engine, dtype = engine_and_dtype
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dtype = dtype.lower()
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if (
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index_type == "non_monotonic"
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and dtype in ["int16", "int8", "uint8"]
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and unique
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):
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# Values overflow
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raise NotImplementedError
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if index_type == "monotonic_incr":
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if unique:
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arr = np.arange(N * 3, dtype=dtype)

asv_bench/benchmarks/rolling.py

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["DataFrame", "Series"],
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[("rolling", {"window": 10}), ("rolling", {"window": 1000}), ("expanding", {})],
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["int", "float"],
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["median", "mean", "max", "min", "std", "count", "skew", "kurt", "sum", "sem"],
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[
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"median",
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"mean",
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"max",
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"min",
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"std",
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"count",
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"skew",
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"kurt",
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"sum",
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"sem",
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"nunique",
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],
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)
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param_names = ["constructor", "window_kwargs", "dtype", "method"]
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