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/738#issuecomment-178297275,https://api.github.com/repos/pydata/xarray/issues/738,178297275,MDEyOklzc3VlQ29tbWVudDE3ODI5NzI3NQ==,1217238,2016-02-02T01:32:27Z,2016-02-02T01:32:27Z,MEMBER,"Unfortunately, NumPy has no integer type that can support missing values. This leaves us in a difficult situation for integer types. So, we've copied the approach from pandas of upcasting integers to floats when we need to add NaNs:
http://pandas.pydata.org/pandas-docs/stable/gotchas.html#nan-integer-na-values-and-na-type-promotions
http://xarray.pydata.org/en/stable/computation.html#missing-values (this could use a reference to the aforementioned pandas docs)

Conversion from complex to object is certainly not what we want, though, because NaN is a perfectly valid complex number. A fix to `_maybe_promote` _should_ take care of that:
https://github.com/pydata/xarray/blob/v0.7.0/xarray/core/common.py#L412

A contribution here would definitely be appreciated! We have made some improvements to complex number support recently but it definitely gets less use.
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