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Polars is a blazingly fast DataFrames library implemented in Rust using Apache Arrow(2) as memory model.

copied from cf-staging / polars
Type Size Name Uploaded Downloads Labels
conda 11.7 MB | osx-arm64/polars-0.18.1-py311h0563b04_0.conda  1 year and 5 months ago 205 main
conda 12.5 MB | osx-64/polars-0.18.1-py38h9a7126c_0.conda  1 year and 5 months ago 266 main
conda 12.9 MB | win-64/polars-0.18.1-py310h87d50f1_0.conda  1 year and 5 months ago 244 main
conda 12.9 MB | win-64/polars-0.18.1-py38h4900a04_0.conda  1 year and 5 months ago 241 main
conda 11.6 MB | osx-arm64/polars-0.18.1-py39haff01fd_0.conda  1 year and 5 months ago 195 main
conda 12.5 MB | osx-64/polars-0.18.1-py310h3461e44_0.conda  1 year and 5 months ago 281 main
conda 12.5 MB | osx-64/polars-0.18.1-py39h80c48a4_0.conda  1 year and 5 months ago 260 main
conda 11.5 MB | osx-arm64/polars-0.18.1-py310had9acf8_0.conda  1 year and 5 months ago 198 main
conda 12.9 MB | win-64/polars-0.18.1-py311hc37eb10_0.conda  1 year and 5 months ago 261 main
conda 12.5 MB | osx-64/polars-0.18.1-py38h7510fb3_0.conda  1 year and 5 months ago 259 main
conda 12.5 MB | osx-64/polars-0.18.1-py39hf33989b_0.conda  1 year and 5 months ago 260 main
conda 12.8 MB | win-64/polars-0.18.1-py39hf21820d_0.conda  1 year and 5 months ago 433 main
conda 12.6 MB | osx-64/polars-0.18.1-py311h299eb51_0.conda  1 year and 5 months ago 259 main
conda 11.6 MB | osx-arm64/polars-0.18.1-py38hd0c8013_0.conda  1 year and 5 months ago 188 main
conda 14.6 MB | linux-64/polars-0.18.1-py39h9fdd4d6_0.conda  1 year and 5 months ago 1210 main
conda 14.6 MB | linux-64/polars-0.18.1-py38h0cc4f7c_0.conda  1 year and 5 months ago 971 main
conda 14.6 MB | linux-64/polars-0.18.1-py39he9b4010_0.conda  1 year and 5 months ago 1138 main
conda 14.6 MB | linux-64/polars-0.18.1-py310hcb5633a_0.conda  1 year and 5 months ago 1284 main
conda 14.6 MB | linux-64/polars-0.18.1-py38hc484311_0.conda  1 year and 5 months ago 989 main
conda 14.7 MB | linux-64/polars-0.18.1-py311h46250e7_0.conda  1 year and 5 months ago 1045 main

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