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  • Conversion to pandas for zero-dimensional Data(Set|Array) · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
879685814 https://github.com/pydata/xarray/issues/5598#issuecomment-879685814 https://api.github.com/repos/pydata/xarray/issues/5598 MDEyOklzc3VlQ29tbWVudDg3OTY4NTgxNA== martinitus 7611856 2021-07-14T08:05:37Z 2021-07-14T08:05:37Z NONE

I'm not a pandas expert, but maybe one can create a dummy index that enforces the size=1 constraint. E.g. an index which only supports one value (e.g. None or zero). That could potentially be used to fix the round-trip.

Also potentially related: #5202 (also contains discussions about the multiindex/dataset handling)

 
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   Conversion to pandas for zero-dimensional Data(Set|Array) 943112510
879276594 https://github.com/pydata/xarray/issues/5598#issuecomment-879276594 https://api.github.com/repos/pydata/xarray/issues/5598 MDEyOklzc3VlQ29tbWVudDg3OTI3NjU5NA== shoyer 1217238 2021-07-13T17:40:13Z 2021-07-13T17:40:13Z MEMBER

to_dataframe() always returns a DataFrame with an index based on coordinate values. I guess we could return a trivial integer index, but this feels a little weird/non-consistent to me particularly because it breaks round-tripping. On the other hand, it is basically exactly what pandas does.

One compromise might be adding an index=False option to to_dataframe() (e.g., ds.to_dataframe(index=False)), which would always create a trivial index (rather than a MultiIndex) and thus obviously break round-tripping.

 
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   Conversion to pandas for zero-dimensional Data(Set|Array) 943112510

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