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/2649#issuecomment-451658134,https://api.github.com/repos/pydata/xarray/issues/2649,451658134,MDEyOklzc3VlQ29tbWVudDQ1MTY1ODEzNA==,6360066,2019-01-05T14:03:14Z,2019-01-05T14:03:14Z,NONE,"Thanks, I have applied the fix and now it works. ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,396063731
https://github.com/pydata/xarray/issues/1346#issuecomment-290822179,https://api.github.com/repos/pydata/xarray/issues/1346,290822179,MDEyOklzc3VlQ29tbWVudDI5MDgyMjE3OQ==,6360066,2017-03-31T20:31:56Z,2017-03-31T20:31:56Z,NONE,"Thanks all guys for the replies. 
@Aegaeon I get the same your results with bottleneck...
@shoyer The point is that I haven't decided the use of float32 and — yes — using `.astype(np.float64)` solves the issue...the point is that is not an expected behaviour, with such standard dataset I would not expect any problem related to numerical precision...","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,218459353
https://github.com/pydata/xarray/issues/1346#issuecomment-290692479,https://api.github.com/repos/pydata/xarray/issues/1346,290692479,MDEyOklzc3VlQ29tbWVudDI5MDY5MjQ3OQ==,6360066,2017-03-31T11:53:12Z,2017-03-31T11:53:12Z,NONE,"Ok, I am on MacOS:
- Python 2.7.13 from Macports
- Dask 0.14.1 from Macports
- xarray from GitHub ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,218459353