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  • fujiisoup · 2 ✖

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  • sparse and other duck array issues · 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
565757852 https://github.com/pydata/xarray/issues/3245#issuecomment-565757852 https://api.github.com/repos/pydata/xarray/issues/3245 MDEyOklzc3VlQ29tbWVudDU2NTc1Nzg1Mg== fujiisoup 6815844 2019-12-14T22:14:03Z 2019-12-14T22:14:03Z MEMBER

What is the best way to save sparse array into a disc?

One naive way would be to use stack -> reset_index, but it flattened coordinates and if there is another variable that depends on these coordinates, they will be also flattened and may consume a lot of space.

 
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   sparse and other duck array issues 484240082
554795681 https://github.com/pydata/xarray/issues/3245#issuecomment-554795681 https://api.github.com/repos/pydata/xarray/issues/3245 MDEyOklzc3VlQ29tbWVudDU1NDc5NTY4MQ== fujiisoup 6815844 2019-11-17T22:38:51Z 2019-11-17T22:38:51Z MEMBER

Do we arrive at the consensus here for API to change the sparse or numpy array? xref #3542

To make it sparse array, to_sparse() would be better? How about or as_sparse()? + to_sparse() is probably consistent to todense() method + as_sparse() sounds similar to sparse's function, e.g. sparse.as_coo

To change the backend back from sparse array, to_dense() would be better? FYI, sparse uses todense().

I personally like as_sparse or as_numpy (or as_dense?), which sounds similar to as_type, which gives xarray object not dtype itself.

 
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   sparse and other duck array issues 484240082

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