html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/39#issuecomment-36484363,https://api.github.com/repos/pydata/xarray/issues/39,36484363,MDEyOklzc3VlQ29tbWVudDM2NDg0MzYz,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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