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/3972#issuecomment-613845875,https://api.github.com/repos/pydata/xarray/issues/3972,613845875,MDEyOklzc3VlQ29tbWVudDYxMzg0NTg3NQ==,9948595,2020-04-15T06:36:48Z,2020-04-15T06:36:48Z,CONTRIBUTOR,"OK PR done #3973
Sorry I forgot to create a new branch... hope that's OK.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,599993415
https://github.com/pydata/xarray/pull/2924#issuecomment-487329592,https://api.github.com/repos/pydata/xarray/issues/2924,487329592,MDEyOklzc3VlQ29tbWVudDQ4NzMyOTU5Mg==,9948595,2019-04-28T00:21:15Z,2019-04-28T00:21:15Z,CONTRIBUTOR,"No problem. Thanks for xarray! 

Just a question. I put a guard in to test just for tuples (because that's what was breaking for me) but it seems to me that `_nan_minmax_object` should just return `utils.to_0d_object_array(data)`
unconditionally at that point no? It's a max or a min right.

Wasn't sure.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,437956917
https://github.com/pydata/xarray/pull/2924#issuecomment-487298047,https://api.github.com/repos/pydata/xarray/issues/2924,487298047,MDEyOklzc3VlQ29tbWVudDQ4NzI5ODA0Nw==,9948595,2019-04-27T16:04:45Z,2019-04-27T16:04:45Z,CONTRIBUTOR,Oops... I usually use black -- which I turned off since it would really have stuffed the code :),"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,437956917
https://github.com/pydata/xarray/issues/2923#issuecomment-487291300,https://api.github.com/repos/pydata/xarray/issues/2923,487291300,MDEyOklzc3VlQ29tbWVudDQ4NzI5MTMwMA==,9948595,2019-04-27T14:38:12Z,2019-04-27T14:38:12Z,CONTRIBUTOR,"Seems that the problem begins when
`xarray.core.nanops._nan_minmax_object` converts the max index value (2,99) tuple (which is correct)
to `np.array((0,99), dtype='O')` which is not because np.array converts this from dims=() to dims=(2,).

Which is now incorrect. Interesting... how do you tell numpy to create a 0 dimension array with a tuple?
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,437940426