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  • ebrevdo · 1 ✖

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  • OpenDAP loaded Dataset has lon/lats with type 'object'. · 1 ✖

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  • CONTRIBUTOR · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
36484363 https://github.com/pydata/xarray/issues/39#issuecomment-36484363 https://api.github.com/repos/pydata/xarray/issues/39 MDEyOklzc3VlQ29tbWVudDM2NDg0MzYz ebrevdo 1794715 2014-03-03T06:21:33Z 2014-03-03T06:21:33Z CONTRIBUTOR

Indices also have an .inferred_type getter. unfortunately it doesn't seem to return true type names...

In [13]: pandas.Index([1,2,3]).inferred_type Out[13]: 'integer'

In [14]: pandas.Index([1,2,3.5]).inferred_type Out[14]: 'mixed-integer-float'

In [15]: pandas.Index(["ab","cd"]).inferred_type Out[15]: 'string'

In [16]: pandas.Index(["ab","cd",3]).inferred_type Out[16]: 'mixed-integer'

On Sun, Mar 2, 2014 at 10:14 PM, Stephan Hoyer notifications@github.comwrote:

This is because coordinates are loaded as pandas.Index objects... which don't always faithfully preserve the type of the underlying object (see pydata/pandas#6471 https://github.com/pydata/pandas/issues/6471).

I believe serialization should still work though thanks to a work around I added for dtype=object. Do let me know if this is not the case. One solution to make this less awkward would be to wrap pandas.Index in something that keeps track of the dtype of the original arguments for use in mathematical expression.

Reply to this email directly or view it on GitHubhttps://github.com/akleeman/xray/issues/39#issuecomment-36484122 .

 
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   OpenDAP loaded Dataset has lon/lats with type 'object'. 28600785

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