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/pull/554#issuecomment-137182315,https://api.github.com/repos/pydata/xarray/issues/554,137182315,MDEyOklzc3VlQ29tbWVudDEzNzE4MjMxNQ==,277579,2015-09-02T17:37:14Z,2015-09-02T17:37:14Z,CONTRIBUTOR,"OK. Thanks for clarifying :+1: 
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,103966239
https://github.com/pydata/xarray/pull/554#issuecomment-137178766,https://api.github.com/repos/pydata/xarray/issues/554,137178766,MDEyOklzc3VlQ29tbWVudDEzNzE3ODc2Ng==,1217238,2015-09-02T17:25:08Z,2015-09-02T17:25:08Z,MEMBER,"> One question still: what is the point of applying .real or .imag to dataset ? As far as I understand xray.Dataset might be inhomogeneous (a mix of non homogeneous datatypes).
> It doe make sense for xray.Dataarray though.

If every data variable in your Dataset has numeric values, `.real` and `.imag` are perfectly well defined. If not, you'll get an error message when you try to use them. This is similar to the case for other operations that only work on numbers (e.g., binary arithmetic).

My two cents is that `.real` and `.imag` would also be appropriate for `pandas.DataFrame`, even though they only make sense for certain dtypes.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,103966239
https://github.com/pydata/xarray/pull/554#issuecomment-137026637,https://api.github.com/repos/pydata/xarray/issues/554,137026637,MDEyOklzc3VlQ29tbWVudDEzNzAyNjYzNw==,277579,2015-09-02T10:48:17Z,2015-09-02T10:51:12Z,CONTRIBUTOR,"This is great ! Thanks!
One question still: what is the point of applying `.real` or `.imag` to dataset ?
As far as I understand xray.Dataset might be inhomogeneous (a mix of non homogeneous datatypes).
It doe make sense for xray.Dataarray though.
Maybe I was misleading by reporting incorrectly a pandas dataframe bug https://github.com/pydata/pandas/issues/10921#issuecomment-137022416 ?
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