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/1882#issuecomment-365697240,https://api.github.com/repos/pydata/xarray/issues/1882,365697240,MDEyOklzc3VlQ29tbWVudDM2NTY5NzI0MA==,244887,2018-02-14T18:17:53Z,2018-02-14T18:17:53Z,CONTRIBUTOR,"> Xarray for Scalable Scientific Data Analysis

Nice title! 

I know xarray has its origins and most of its current users in the earth science domains, and so I would expect much of the core of an xarray tutorial to involve various geo* flavored data, but since SciPy has attendees from so many different backgrounds it could be useful to try to survey the scope of work being done with xarray right now. I imagine there must be other users in astronomy, physics, biology and perhaps even quantitative civics/demography that could have interesting snippets to share. 

For my part, I am using xarray to work with microscopy data in a biological context, and would be happy to share a snippet or two. 

","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,293913247