pandas-plink

Pandas-plink is a Python package for reading PLINK binary file format and realized relationship matrices (PLINK or GCTA). The file reading is taken place via lazy loading, meaning that it saves up memory by actually reading only the genotypes that are actually accessed by the user.

Notable changes can be found at the CHANGELOG.md.

Install

It can be installed using pip:

pip install pandas-plink

Alternatively it can be intalled via conda:

conda install -c conda-forge pandas-plink

Usage

It is as simple as

>>> from pandas_plink import read_plink1_bin
>>> G = read_plink1_bin("chr11.bed", "chr11.bim", "chr11.fam", verbose=False)
>>> print(G)
<xarray.DataArray 'genotype' (sample: 14, variant: 779)>
dask.array<shape=(14, 779), dtype=float64, chunksize=(14, 779)>
Coordinates:
  * sample   (sample) object 'B001' 'B002' 'B003' ... 'B012' 'B013' 'B014'
  * variant  (variant) object '11_316849996' '11_316874359' ... '11_345698259'
    father   (sample) <U1 '0' '0' '0' '0' '0' '0' ... '0' '0' '0' '0' '0' '0'
    fid      (sample) <U4 'B001' 'B002' 'B003' 'B004' ... 'B012' 'B013' 'B014'
    gender   (sample) <U1 '0' '0' '0' '0' '0' '0' ... '0' '0' '0' '0' '0' '0'
    i        (sample) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13
    iid      (sample) <U4 'B001' 'B002' 'B003' 'B004' ... 'B012' 'B013' 'B014'
    mother   (sample) <U1 '0' '0' '0' '0' '0' '0' ... '0' '0' '0' '0' '0' '0'
    trait    (sample) <U2 '-9' '-9' '-9' '-9' '-9' ... '-9' '-9' '-9' '-9' '-9'
    a0       (variant) <U1 'C' 'G' 'G' 'C' 'C' 'T' ... 'T' 'A' 'C' 'A' 'A' 'T'
    a1       (variant) <U1 'T' 'C' 'C' 'T' 'T' 'A' ... 'C' 'G' 'T' 'G' 'C' 'C'
    chrom    (variant) <U2 '11' '11' '11' '11' '11' ... '11' '11' '11' '11' '11'
    cm       (variant) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0
    pos      (variant) int64 157439 181802 248969 ... 28937375 28961091 29005702
    snp      (variant) <U9 '316849996' '316874359' ... '345653648' '345698259'
>>> print(G.sel(sample="B003", variant="11_316874359").values)
0.0
>>> print(G.a0.sel(variant="11_316874359").values)
G
>>> print(G.sel(sample="B003", variant="11_316941526").values)
2.0
>>> print(G.a1.sel(variant="11_316941526").values)
C

Portions of the genotype will be read as the user access them.

Covariance matrices can also be read very easily. Example:

>>> from pandas_plink import read_rel
>>> K = read_rel("plink2.rel.bin")
>>> print(K)
<xarray.DataArray (sample_0: 10, sample_1: 10)>
array([[ 0.885782,  0.233846, -0.186339, -0.009789, -0.138897,  0.287779,
         0.269977, -0.231279, -0.095472, -0.213979],
       [ 0.233846,  1.077493, -0.452858,  0.192877, -0.186027,  0.171027,
         0.406056, -0.013149, -0.131477, -0.134314],
       [-0.186339, -0.452858,  1.183312, -0.040948, -0.146034, -0.204510,
        -0.314808, -0.042503,  0.296828, -0.011661],
       [-0.009789,  0.192877, -0.040948,  0.895360, -0.068605,  0.012023,
         0.057827, -0.192152, -0.089094,  0.174269],
       [-0.138897, -0.186027, -0.146034, -0.068605,  1.183237,  0.085104,
        -0.032974,  0.103608,  0.215769,  0.166648],
       [ 0.287779,  0.171027, -0.204510,  0.012023,  0.085104,  0.956921,
         0.065427, -0.043752, -0.091492, -0.227673],
       [ 0.269977,  0.406056, -0.314808,  0.057827, -0.032974,  0.065427,
         0.714746, -0.101254, -0.088171, -0.063964],
       [-0.231279, -0.013149, -0.042503, -0.192152,  0.103608, -0.043752,
        -0.101254,  1.423033, -0.298255, -0.074334],
       [-0.095472, -0.131477,  0.296828, -0.089094,  0.215769, -0.091492,
        -0.088171, -0.298255,  0.910274, -0.024663],
       [-0.213979, -0.134314, -0.011661,  0.174269,  0.166648, -0.227673,
        -0.063964, -0.074334, -0.024663,  0.914586]])
Coordinates:
  * sample_0  (sample_0) object 'HG00419' 'HG00650' ... 'NA20508' 'NA20753'
  * sample_1  (sample_1) object 'HG00419' 'HG00650' ... 'NA20508' 'NA20753'
    fid       (sample_1) object 'HG00419' 'HG00650' ... 'NA20508' 'NA20753'
    iid       (sample_1) object 'HG00419' 'HG00650' ... 'NA20508' 'NA20753'
>>> print(K.values)
[[ 0.89  0.23 -0.19 -0.01 -0.14  0.29  0.27 -0.23 -0.10 -0.21]
 [ 0.23  1.08 -0.45  0.19 -0.19  0.17  0.41 -0.01 -0.13 -0.13]
 [-0.19 -0.45  1.18 -0.04 -0.15 -0.20 -0.31 -0.04  0.30 -0.01]
 [-0.01  0.19 -0.04  0.90 -0.07  0.01  0.06 -0.19 -0.09  0.17]
 [-0.14 -0.19 -0.15 -0.07  1.18  0.09 -0.03  0.10  0.22  0.17]
 [ 0.29  0.17 -0.20  0.01  0.09  0.96  0.07 -0.04 -0.09 -0.23]
 [ 0.27  0.41 -0.31  0.06 -0.03  0.07  0.71 -0.10 -0.09 -0.06]
 [-0.23 -0.01 -0.04 -0.19  0.10 -0.04 -0.10  1.42 -0.30 -0.07]
 [-0.10 -0.13  0.30 -0.09  0.22 -0.09 -0.09 -0.30  0.91 -0.02]
 [-0.21 -0.13 -0.01  0.17  0.17 -0.23 -0.06 -0.07 -0.02  0.91]]

Please, refer to the pandas-plink documentation for more information.

Authors

Danilo Horta

License

This project is licensed under the MIT License.

Metadata

Release files for pandas-plink 2.3.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pandas-plink 2.3.2
File	Size	Uploaded
pandas_plink-2.3.2.tar.gz	18.4 kB	May 12, 2025	Details

Built distributions (wheels)

Table of built distributions (wheels) for pandas-plink 2.3.2
File	Interpreter	ABI	Platform	Reset
pandas_plink-2.3.2-pp310-pypy310_pp73-win_amd64.whl 55.8 kB May 12, 2025	PyPy 3.10	PyPy 3.10 7.3	Windows x86-64	Details
pandas_plink-2.3.2-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux_2_5_x86_64.manylinux1_x86_64.manylinux2014_x86_64.whl 83.3 kB May 12, 2025	PyPy 3.10	PyPy 3.10 7.3	Linux glibc 2.5+ x86-64, Linux glibc 2.17+ x86-64	Details
pandas_plink-2.3.2-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 46.4 kB May 12, 2025	PyPy 3.10	PyPy 3.10 7.3	Linux glibc 2.17+ ARM64	Details
pandas_plink-2.3.2-pp310-pypy310_pp73-macosx_14_0_arm64.whl 43.0 kB May 12, 2025	PyPy 3.10	PyPy 3.10 7.3	macOS 14.0+ ARM64	Details
pandas_plink-2.3.2-pp310-pypy310_pp73-macosx_13_0_x86_64.whl 42.1 kB May 12, 2025	PyPy 3.10	PyPy 3.10 7.3	macOS 13.0+ x86-64	Details
pandas_plink-2.3.2-cp312-cp312-win_amd64.whl 49.2 kB May 12, 2025	CPython 3.12	CPython 3.12	Windows x86-64	Details
pandas_plink-2.3.2-cp312-cp312-musllinux_1_2_x86_64.whl 77.4 kB May 12, 2025	CPython 3.12	CPython 3.12	Linux musl 1.2+ x86-64	Details
pandas_plink-2.3.2-cp312-cp312-musllinux_1_2_aarch64.whl 42.1 kB May 12, 2025	CPython 3.12	CPython 3.12	Linux musl 1.2+ ARM64	Details
pandas_plink-2.3.2-cp312-cp312-manylinux_2_17_x86_64.manylinux_2_5_x86_64.manylinux1_x86_64.manylinux2014_x86_64.whl 79.4 kB May 12, 2025	CPython 3.12	CPython 3.12	Linux glibc 2.17+ x86-64, Linux glibc 2.5+ x86-64	Details
pandas_plink-2.3.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 42.4 kB May 12, 2025	CPython 3.12	CPython 3.12	Linux glibc 2.17+ ARM64	Details
pandas_plink-2.3.2-cp312-cp312-macosx_14_0_arm64.whl 40.1 kB May 12, 2025	CPython 3.12	CPython 3.12	macOS 14.0+ ARM64	Details
pandas_plink-2.3.2-cp312-cp312-macosx_13_0_x86_64.whl 39.4 kB May 12, 2025	CPython 3.12	CPython 3.12	macOS 13.0+ x86-64	Details
pandas_plink-2.3.2-cp311-cp311-win_amd64.whl 40.9 kB May 12, 2025	CPython 3.11	CPython 3.11	Windows x86-64	Details
pandas_plink-2.3.2-cp311-cp311-musllinux_1_2_x86_64.whl 59.4 kB May 12, 2025	CPython 3.11	CPython 3.11	Linux musl 1.2+ x86-64	Details
pandas_plink-2.3.2-cp311-cp311-musllinux_1_2_aarch64.whl 42.0 kB May 12, 2025	CPython 3.11	CPython 3.11	Linux musl 1.2+ ARM64	Details
pandas_plink-2.3.2-cp311-cp311-manylinux_2_17_x86_64.manylinux_2_5_x86_64.manylinux1_x86_64.manylinux2014_x86_64.whl 60.6 kB May 12, 2025	CPython 3.11	CPython 3.11	Linux glibc 2.5+ x86-64, Linux glibc 2.17+ x86-64	Details
pandas_plink-2.3.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 42.1 kB May 12, 2025	CPython 3.11	CPython 3.11	Linux glibc 2.17+ ARM64	Details
pandas_plink-2.3.2-cp311-cp311-macosx_14_0_arm64.whl 34.6 kB May 12, 2025	CPython 3.11	CPython 3.11	macOS 14.0+ ARM64	Details
pandas_plink-2.3.2-cp311-cp311-macosx_13_0_x86_64.whl 34.2 kB May 12, 2025	CPython 3.11	CPython 3.11	macOS 13.0+ x86-64	Details
pandas_plink-2.3.2-cp310-cp310-win_amd64.whl 32.3 kB May 12, 2025	CPython 3.10	CPython 3.10	Windows x86-64	Details
pandas_plink-2.3.2-cp310-cp310-musllinux_1_2_x86_64.whl 41.6 kB May 12, 2025	CPython 3.10	CPython 3.10	Linux musl 1.2+ x86-64	Details
pandas_plink-2.3.2-cp310-cp310-musllinux_1_2_aarch64.whl 41.9 kB May 12, 2025	CPython 3.10	CPython 3.10	Linux musl 1.2+ ARM64	Details
pandas_plink-2.3.2-cp310-cp310-manylinux_2_17_x86_64.manylinux_2_5_x86_64.manylinux1_x86_64.manylinux2014_x86_64.whl 42.2 kB May 12, 2025	CPython 3.10	CPython 3.10	Linux glibc 2.5+ x86-64, Linux glibc 2.17+ x86-64	Details
pandas_plink-2.3.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 42.1 kB May 12, 2025	CPython 3.10	CPython 3.10	Linux glibc 2.17+ ARM64	Details
pandas_plink-2.3.2-cp310-cp310-macosx_14_0_arm64.whl 29.2 kB May 12, 2025	CPython 3.10	CPython 3.10	macOS 14.0+ ARM64	Details
pandas_plink-2.3.2-cp310-cp310-macosx_13_0_x86_64.whl 29.0 kB May 12, 2025	CPython 3.10	CPython 3.10	macOS 13.0+ x86-64	Details

Total release size: 1.2 MB

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Upload date	May 12, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
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Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

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Artifact

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Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

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Release files / pandas_plink-2.3.2-cp312-cp312-musllinux_1_2_aarch64.whl

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Provenance

Identity

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Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

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Provenance

Identity

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Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

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Release files / pandas_plink-2.3.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl

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Provenance

Identity

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Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

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Provenance

Identity

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Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

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Provenance

Identity

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Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

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Release files / pandas_plink-2.3.2-cp311-cp311-win_amd64.whl

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Provenance

Identity

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Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

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Uploaded via	`twine/6.1.0 CPython/3.12.9`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

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Release files / pandas_plink-2.3.2-cp311-cp311-musllinux_1_2_aarch64.whl

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Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

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Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

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Release files / pandas_plink-2.3.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl

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Provenance

Identity

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Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

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Release files / pandas_plink-2.3.2-cp311-cp311-macosx_14_0_arm64.whl

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Provenance

Identity

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Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

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Release files / pandas_plink-2.3.2-cp311-cp311-macosx_13_0_x86_64.whl

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Provenance

Identity

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Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

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Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.12.9`

Provenance

Identity

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Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

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Release files / pandas_plink-2.3.2-cp310-cp310-musllinux_1_2_x86_64.whl

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SHA-256 checksum How to use checksums	`f6d8c5697ba46e911c9662754f7afd6196da1dfc1790d8da81d84ad9f0f84b29`
BLAKE2b-256 checksum How to use checksums	`d7b1f13b885b489069689474c4806caef28b0c70824a8671e07f40d31a2ad9fd`
Upload date	May 12, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.12.9`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

Workflow

Publishing configuration: github.com/limix/pandas-plink/blob/865f5a52719602e55dae034444ec7a22fe01e653/.github/workflows/release.yml
Publishing logs: github.com/limix/pandas-plink/actions/runs/14972848007/attempts/1

Artifact

Subject: pandas_plink-2.3.2-cp310-cp310-musllinux_1_2_x86_64.whl
SHA-256 checksum: f6d8c5697ba46e911c9662754f7afd6196da1dfc1790d8da81d84ad9f0f84b29 Verifying attestations

Release files / pandas_plink-2.3.2-cp310-cp310-musllinux_1_2_aarch64.whl

Download URL	pandas_plink-2.3.2-cp310-cp310-musllinux_1_2_aarch64.whl
Size	41.9 kB
Tags	CPython 3.10 Linux musl 1.2+ ARM64
SHA-256 checksum How to use checksums	`078daac8507b1ac8cbf08c703d97c412ebf687ef22d8b13b244d4ee940a43485`
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Upload date	May 12, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.12.9`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

Workflow

Publishing configuration: github.com/limix/pandas-plink/blob/865f5a52719602e55dae034444ec7a22fe01e653/.github/workflows/release.yml
Publishing logs: github.com/limix/pandas-plink/actions/runs/14972848007/attempts/1

Artifact

Subject: pandas_plink-2.3.2-cp310-cp310-musllinux_1_2_aarch64.whl
SHA-256 checksum: 078daac8507b1ac8cbf08c703d97c412ebf687ef22d8b13b244d4ee940a43485 Verifying attestations

Release files / pandas_plink-2.3.2-cp310-cp310-manylinux_2_17_x86_64.manylinux_2_5_x86_64.manylinux1_x86_64.manylinux2014_x86_64.whl

Download URL	pandas_plink-2.3.2-cp310-cp310-manylinux_2_17_x86_64.manylinux_2_5_x86_64.manylinux1_x86_64.manylinux2014_x86_64.whl
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Tags	CPython 3.10 Linux glibc 2.17+ x86-64 Linux glibc 2.5+ x86-64
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Upload date	May 12, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.12.9`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

Workflow

Publishing configuration: github.com/limix/pandas-plink/blob/865f5a52719602e55dae034444ec7a22fe01e653/.github/workflows/release.yml
Publishing logs: github.com/limix/pandas-plink/actions/runs/14972848007/attempts/1

Artifact

Subject: pandas_plink-2.3.2-cp310-cp310-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl
SHA-256 checksum: 62a4b4b289f7c8b9221e4ba34aa8bcf504195f388aa4287384fe7aaeb52cda04 Verifying attestations

Release files / pandas_plink-2.3.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl

Download URL	pandas_plink-2.3.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Size	42.1 kB
Tags	CPython 3.10 Linux glibc 2.17+ ARM64
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Upload date	May 12, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.12.9`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

Workflow

Publishing configuration: github.com/limix/pandas-plink/blob/865f5a52719602e55dae034444ec7a22fe01e653/.github/workflows/release.yml
Publishing logs: github.com/limix/pandas-plink/actions/runs/14972848007/attempts/1

Artifact

Subject: pandas_plink-2.3.2-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl
SHA-256 checksum: 854e4d66e21b6aff9d2054f48d058af7115d5510e262ac55d6a2fe876676806b Verifying attestations

Release files / pandas_plink-2.3.2-cp310-cp310-macosx_14_0_arm64.whl

Download URL	pandas_plink-2.3.2-cp310-cp310-macosx_14_0_arm64.whl
Size	29.2 kB
Tags	CPython 3.10 macOS 14.0+ ARM64
SHA-256 checksum How to use checksums	`d1d81c57c4b17a37e86b4f17b4335db93b0a7482932f05c9719573aa816def7a`
BLAKE2b-256 checksum How to use checksums	`1f5f3094443bb99cfb5b40e253e83c4431feb524b431c98c96923824509cde28`
Upload date	May 12, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.12.9`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

Workflow

Publishing configuration: github.com/limix/pandas-plink/blob/865f5a52719602e55dae034444ec7a22fe01e653/.github/workflows/release.yml
Publishing logs: github.com/limix/pandas-plink/actions/runs/14972848007/attempts/1

Artifact

Subject: pandas_plink-2.3.2-cp310-cp310-macosx_14_0_arm64.whl
SHA-256 checksum: d1d81c57c4b17a37e86b4f17b4335db93b0a7482932f05c9719573aa816def7a Verifying attestations

Release files / pandas_plink-2.3.2-cp310-cp310-macosx_13_0_x86_64.whl

Download URL	pandas_plink-2.3.2-cp310-cp310-macosx_13_0_x86_64.whl
Size	29.0 kB
Tags	CPython 3.10 macOS 13.0+ x86-64
SHA-256 checksum How to use checksums	`8772ce3dc3c54960633e610f1735c526497ac5a40dbb717dafa45294d35fb037`
BLAKE2b-256 checksum How to use checksums	`0d4e4ec332f464f1e103ef75eca397d065bc6b7bd1145d7bd8feb1b8015d79cc`
Upload date	May 12, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.12.9`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/limix/pandas-plink
Publishing commit: github.com/limix/pandas-plink/tree/865f5a52719602e55dae034444ec7a22fe01e653

Workflow

Publishing configuration: github.com/limix/pandas-plink/blob/865f5a52719602e55dae034444ec7a22fe01e653/.github/workflows/release.yml
Publishing logs: github.com/limix/pandas-plink/actions/runs/14972848007/attempts/1

Artifact

Subject: pandas_plink-2.3.2-cp310-cp310-macosx_13_0_x86_64.whl
SHA-256 checksum: 8772ce3dc3c54960633e610f1735c526497ac5a40dbb717dafa45294d35fb037 Verifying attestations