Support reading from and writing to Arrow files #415
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This requires overriding `Arrow.DictEncoding` so that an `Arrow.DictEncoded` with a `CategoricalArray` dictionary with one entry per level is created. This is the only way to ensure that indexing the Arrow column gives `CategoricalValue` objects. In practice such columns will most often be used after conversion to `CategoricalArray` via `copy`, `DataFrame`, etc. Apparently, pandas do not allow reading the resulting file if the array allows for missing values as it does not accept `missing` in the dictionary. Instead it would need missing entries to be coded via null indices, which is less efficient.
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Failure on 32-bit seems due to an |
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@nalimilan feel like adding some arch checks to disable testing/the extension defining any methods on 32bit? |
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Done! I also bumped the minimal Julia version to 1.6 as packages fail to install on 1.0 (which is super old anyway). |
palday
reviewed
Apr 30, 2025
palday
reviewed
Apr 30, 2025
palday
reviewed
Apr 30, 2025
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I'm not an org member so I can't approve but LGTM! |
Co-authored-by: Phillip Alday <palday@users.noreply.github.com>
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Thanks! |
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This requires overriding
Arrow.DictEncodingso that anArrow.DictEncodedwith aCategoricalArraydictionary with one entry per level is created. This is the only way to ensure that indexing the Arrow column givesCategoricalValueobjects. In practice such columns will most often be used after conversion toCategoricalArrayviacopy,DataFrame, etc.Apparently, pandas do not allow reading the resulting file if the array allows for missing values as it does not accept
missingin the dictionary. Instead it would need missing entries to be coded via null indices, which is less efficient.