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  • Feature request xarray.Dataset.from_dask_dataframe · 2 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
739576721 https://github.com/pydata/xarray/issues/3929#issuecomment-739576721 https://api.github.com/repos/pydata/xarray/issues/3929 MDEyOklzc3VlQ29tbWVudDczOTU3NjcyMQ== shoyer 1217238 2020-12-06T22:36:32Z 2020-12-06T22:36:32Z MEMBER

It sounds like making this work well would require xarray to support "unknown" dimension sizes throughout the codebase. This would be a nice feature to have, but indeed would likely require pervasive changes.

The other option would be to explicitly compute the shape when converting from dask dataframes, by calling dask_dataframe.shape[0].compute(). This would probably be more straightforward to implement but could potentially be pretty expensive in speed/memory.

(xref https://github.com/data-apis/array-api/issues/97)

 
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   Feature request xarray.Dataset.from_dask_dataframe 593029940
739395190 https://github.com/pydata/xarray/issues/3929#issuecomment-739395190 https://api.github.com/repos/pydata/xarray/issues/3929 MDEyOklzc3VlQ29tbWVudDczOTM5NTE5MA== keewis 14808389 2020-12-05T20:13:58Z 2020-12-05T20:44:42Z MEMBER

Thanks for investigating and working on this, @AyrtonB.

I indeed think this is the correct place to discuss this: your use case can probably be implemented by converting to a Dataset and then calling Dataset.to_array. Actually, we currently implement most methods on DataArray objects by converting to a temporary single-variable Dataset, calling the equivalent Dataset method and then converting the result back to a DataArray.

 
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   Feature request xarray.Dataset.from_dask_dataframe 593029940

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