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  • Dataset.from_records()? · 3 ✖

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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
840809933 https://github.com/pydata/xarray/issues/2824#issuecomment-840809933 https://api.github.com/repos/pydata/xarray/issues/2824 MDEyOklzc3VlQ29tbWVudDg0MDgwOTkzMw== max-sixty 5635139 2021-05-13T20:20:52Z 2021-05-13T20:20:52Z MEMBER

For any future travelers who come across this: a slight twist on the patterns above is xr.Dataset({name: (("dim",), my_recarray[name]) for name in my_recarray.dtype.names}) — the data will be loaded on a single dimension, and then .set_index(dim=['a','b']) can be used to set the appropriate indexes vs variables.

 
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   Dataset.from_records()? 423016453
474686642 https://github.com/pydata/xarray/issues/2824#issuecomment-474686642 https://api.github.com/repos/pydata/xarray/issues/2824 MDEyOklzc3VlQ29tbWVudDQ3NDY4NjY0Mg== shoyer 1217238 2019-03-20T05:09:10Z 2019-03-20T05:09:10Z MEMBER

We could potentially pick dimension names automatically, but it's not an entirely obvious this to do since passing a dict of numpy arrays into the xarray.Dataset constructor isn't supported (but I guess we could support that).

 
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   Dataset.from_records()? 423016453
474645059 https://github.com/pydata/xarray/issues/2824#issuecomment-474645059 https://api.github.com/repos/pydata/xarray/issues/2824 MDEyOklzc3VlQ29tbWVudDQ3NDY0NTA1OQ== shoyer 1217238 2019-03-20T01:13:36Z 2019-03-20T01:13:36Z MEMBER

Turning a record array into a dict of arrays is pretty straightforward, e.g., arrays = {name: my_recarray[name] for name in my_recarray.dtype.names}

You could then pass this into xr.Dataset, but you'll also have to set dimension names.

 
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   Dataset.from_records()? 423016453

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