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.github/CODEOWNERS

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@@ -9,7 +9,6 @@ doc/cheatsheet @Dr-Irv
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doc/source/development @noatamir
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# pandas
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pandas/_libs/ @WillAyd
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pandas/_typing.py @Dr-Irv
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pandas/core/groupby/* @rhshadrach
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pandas/io/excel/* @rhshadrach

.github/ISSUE_TEMPLATE/feature_request.yaml

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attributes:
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label: Feature Description
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description: >
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Please describe how the new feature would be implemented, using psudocode if relevant.
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Please describe how the new feature would be implemented, using pseudocode if relevant.
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placeholder: >
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Add a new parameter to DataFrame, to_series, to return a Series if possible.
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.pre-commit-config.yaml

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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: v0.9.9
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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: 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']

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):

ci/code_checks.sh

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-i "pandas.Series.dt PR01" `# Accessors are implemented as classes, but we do not document the Parameters section` \
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-i "pandas.Period.freq GL08" \
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-i "pandas.Period.ordinal GL08" \
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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.resolution PR02" \
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-i "pandas.core.groupby.DataFrameGroupBy.plot PR02" \
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-i "pandas.core.groupby.SeriesGroupBy.plot PR02" \
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-i "pandas.core.resample.Resampler.quantile PR01,PR07" \

ci/deps/actions-310-minimum_versions.yaml

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- numpy=1.23.5
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# optional dependencies
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- beautifulsoup4=4.11.2
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- beautifulsoup4=4.12.3
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- blosc=1.21.3
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- bottleneck=1.3.6
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- fastparquet=2023.10.0
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- fsspec=2022.11.0
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- fastparquet=2024.2.0
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- fsspec=2024.2.0
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- html5lib=1.1
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- hypothesis=6.84.0
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- gcsfs=2022.11.0
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- jinja2=3.1.2
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- gcsfs=2024.2.0
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- jinja2=3.1.3
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- lxml=4.9.2
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- matplotlib=3.6.3
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- numba=0.56.4
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- numexpr=2.8.4
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- matplotlib=3.8.3
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- numba=0.59.0
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- numexpr=2.9.0
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- odfpy=1.4.1
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- qtpy=2.3.0
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- openpyxl=3.1.0
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- openpyxl=3.1.2
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- psycopg2=2.9.6
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- pyarrow=10.0.1
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- pymysql=1.0.2
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- pymysql=1.1.0
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- pyqt=5.15.9
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- pyreadstat=1.2.0
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- pyreadstat=1.2.6
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- pytables=3.8.0
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- python-calamine=0.1.7
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- pytz=2023.4
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- pyxlsb=1.0.10
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- s3fs=2022.11.0
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- scipy=1.10.0
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- s3fs=2024.2.0
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- scipy=1.12.0
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- sqlalchemy=2.0.0
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- tabulate=0.9.0
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- xarray=2022.12.0
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- xarray=2024.1.1
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- xlrd=2.0.1
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- xlsxwriter=3.0.5
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- zstandard=0.19.0
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- xlsxwriter=3.2.0
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- zstandard=0.22.0
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- pip:
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- adbc-driver-postgresql==0.10.0

ci/deps/actions-310.yaml

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# optional dependencies
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- beautifulsoup4>=4.11.2
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- beautifulsoup4>=4.12.3
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- blosc>=1.21.3
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- bottleneck>=1.3.6
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- fastparquet>=2023.10.0
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- fsspec>=2022.11.0
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- fastparquet>=2024.2.0
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- fsspec>=2024.2.0
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- html5lib>=1.1
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- hypothesis>=6.84.0
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- gcsfs>=2022.11.0
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- jinja2>=3.1.2
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- gcsfs>=2024.2.0
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- jinja2>=3.1.3
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- lxml>=4.9.2
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- matplotlib>=3.6.3
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- numba>=0.56.4
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- numexpr>=2.8.4
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- matplotlib>=3.8.3
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- numba>=0.59.0
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- numexpr>=2.9.0
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- odfpy>=1.4.1
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- qtpy>=2.3.0
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- openpyxl>=3.1.0
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- openpyxl>=3.1.2
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- psycopg2>=2.9.6
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- pyarrow>=10.0.1
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- pymysql>=1.0.2
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- pymysql>=1.1.0
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- pyqt>=5.15.9
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- pyreadstat>=1.2.0
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- pyreadstat>=1.2.6
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- pytables>=3.8.0
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- python-calamine>=0.1.7
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- pytz>=2023.4
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- pyxlsb>=1.0.10
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- s3fs>=2022.11.0
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- scipy>=1.10.0
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- s3fs>=2024.2.0
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- scipy>=1.12.0
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- sqlalchemy>=2.0.0
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- tabulate>=0.9.0
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- xarray>=2022.12.0, <=2024.9.0
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- xarray>=2024.1.1, <=2024.9.0
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- xlrd>=2.0.1
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- xlsxwriter>=3.0.5
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- zstandard>=0.19.0
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- xlsxwriter>=3.2.0
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- zstandard>=0.22.0
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- pip:
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- adbc-driver-postgresql>=0.10.0

ci/deps/actions-311-downstream_compat.yaml

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- numpy
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# optional dependencies
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- beautifulsoup4>=4.11.2
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- beautifulsoup4>=4.12.3
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- blosc>=1.21.3
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- bottleneck>=1.3.6
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- fastparquet>=2023.10.0
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- fsspec>=2022.11.0
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- fastparquet>=2024.2.0
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- fsspec>=2024.2.0
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- html5lib>=1.1
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- hypothesis>=6.84.0
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- gcsfs>=2022.11.0
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- jinja2>=3.1.2
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- gcsfs>=2024.2.0
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- jinja2>=3.1.3
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- lxml>=4.9.2
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- matplotlib>=3.6.3
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- numba>=0.56.4
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- numexpr>=2.8.4
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- matplotlib>=3.8.3
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- numba>=0.59.0
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- numexpr>=2.9.0
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- odfpy>=1.4.1
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- qtpy>=2.3.0
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- openpyxl>=3.1.0
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- openpyxl>=3.1.2
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- psycopg2>=2.9.6
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- pyarrow>=10.0.1
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- pymysql>=1.0.2
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- pymysql>=1.1.0
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- pyqt>=5.15.9
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- pyreadstat>=1.2.0
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- pyreadstat>=1.2.6
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- pytables>=3.8.0
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- python-calamine>=0.1.7
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- pytz>=2023.4
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- pyxlsb>=1.0.10
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- s3fs>=2022.11.0
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- scipy>=1.10.0
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- s3fs>=2024.2.0
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- scipy>=1.12.0
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- sqlalchemy>=2.0.0
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- tabulate>=0.9.0
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- xarray>=2022.12.0, <=2024.9.0
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- xarray>=2024.1.1, <=2024.9.0
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- xlrd>=2.0.1
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- xlsxwriter>=3.0.5
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- zstandard>=0.19.0
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- xlsxwriter>=3.2.0
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- zstandard>=0.22.0
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# downstream packages
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- botocore

ci/deps/actions-311.yaml

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- beautifulsoup4>=4.11.2
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- beautifulsoup4>=4.12.3
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- blosc>=1.21.3
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- bottleneck>=1.3.6
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- fastparquet>=2023.10.0
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- fsspec>=2022.11.0
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- fastparquet>=2024.2.0
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- fsspec>=2024.2.0
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- html5lib>=1.1
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- hypothesis>=6.84.0
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- gcsfs>=2022.11.0
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- jinja2>=3.1.2
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- gcsfs>=2024.2.0
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- jinja2>=3.1.3
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- lxml>=4.9.2
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- matplotlib>=3.6.3
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- numba>=0.56.4
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- numexpr>=2.8.4
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- matplotlib>=3.8.3
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- numba>=0.59.0
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- numexpr>=2.9.0
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- odfpy>=1.4.1
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- qtpy>=2.3.0
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- pyqt>=5.15.9
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- openpyxl>=3.1.0
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- openpyxl>=3.1.2
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- psycopg2>=2.9.6
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- pyarrow>=10.0.1
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- pymysql>=1.0.2
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- pyreadstat>=1.2.0
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- pymysql>=1.1.0
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- pyreadstat>=1.2.6
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- pytables>=3.8.0
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- python-calamine>=0.1.7
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- pytz>=2023.4
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- pyxlsb>=1.0.10
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- s3fs>=2022.11.0
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- scipy>=1.10.0
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- s3fs>=2024.2.0
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- scipy>=1.12.0
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- sqlalchemy>=2.0.0
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- tabulate>=0.9.0
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- xarray>=2022.12.0, <=2024.9.0
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- xarray>=2024.1.1, <=2024.9.0
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- xlrd>=2.0.1
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- xlsxwriter>=3.0.5
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- zstandard>=0.19.0
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- xlsxwriter>=3.2.0
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- zstandard>=0.22.0
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- adbc-driver-postgresql>=0.10.0

ci/deps/actions-312.yaml

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- beautifulsoup4>=4.11.2
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- beautifulsoup4>=4.12.3
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- blosc>=1.21.3
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- bottleneck>=1.3.6
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- fastparquet>=2023.10.0
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- fsspec>=2022.11.0
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- fastparquet>=2024.2.0
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- fsspec>=2024.2.0
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- html5lib>=1.1
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- hypothesis>=6.84.0
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- gcsfs>=2022.11.0
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- jinja2>=3.1.2
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- gcsfs>=2024.2.0
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- jinja2>=3.1.3
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- lxml>=4.9.2
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- matplotlib>=3.6.3
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- numba>=0.56.4
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- numexpr>=2.8.4
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- matplotlib>=3.8.3
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- numba>=0.59.0
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- numexpr>=2.9.0
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- odfpy>=1.4.1
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- qtpy>=2.3.0
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- pyqt>=5.15.9
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- openpyxl>=3.1.0
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- openpyxl>=3.1.2
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- psycopg2>=2.9.6
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- pyarrow>=10.0.1
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- pymysql>=1.0.2
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- pyreadstat>=1.2.0
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- pymysql>=1.1.0
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- pyreadstat>=1.2.6
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- pytables>=3.8.0
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- python-calamine>=0.1.7
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- pytz>=2023.4
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- pyxlsb>=1.0.10
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- s3fs>=2022.11.0
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- scipy>=1.10.0
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- s3fs>=2024.2.0
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- scipy>=1.12.0
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- sqlalchemy>=2.0.0
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- tabulate>=0.9.0
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- xarray>=2022.12.0, <=2024.9.0
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- xarray>=2024.1.1, <=2024.9.0
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- xlrd>=2.0.1
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- xlsxwriter>=3.0.5
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- zstandard>=0.19.0
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- xlsxwriter>=3.2.0
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- zstandard>=0.22.0
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- pip:
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- adbc-driver-postgresql>=0.10.0

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