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  • shoyer · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
234685394 https://github.com/pydata/xarray/issues/907#issuecomment-234685394 https://api.github.com/repos/pydata/xarray/issues/907 MDEyOklzc3VlQ29tbWVudDIzNDY4NTM5NA== shoyer 1217238 2016-07-23T00:09:21Z 2016-07-23T00:09:21Z MEMBER

Does array.coords[dim] = array.coords[dim].values.astype(str) work? In theory, I think it should...

 
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   unstack() treats string coords as objects 166441031
234434065 https://github.com/pydata/xarray/issues/907#issuecomment-234434065 https://api.github.com/repos/pydata/xarray/issues/907 MDEyOklzc3VlQ29tbWVudDIzNDQzNDA2NQ== shoyer 1217238 2016-07-22T01:50:06Z 2016-07-22T01:50:22Z MEMBER

This is a tricky one to fix. Stack is not the only operation that can convert string arrays to dtype=object -- reindex and align also do this.

The challenge is that NumPy does not support variable width strings or strings with missing values. Hence, we end up with dtype=object arrays.

In this particular case, we could preserve the string dtype by keeping track of the original dtype of the arrays at go into a MultiIndex as metadata, similar to how we currently use PandasIndexAdapter to preserve the original dtype on arrays converted into non-multi indexes.

 
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   unstack() treats string coords as objects 166441031

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