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/133#issuecomment-56313445,https://api.github.com/repos/pydata/xarray/issues/133,56313445,MDEyOklzc3VlQ29tbWVudDU2MzEzNDQ1,2062210,2014-09-21T21:29:11Z,2014-09-21T21:29:11Z,NONE,"Happy to test it out for you.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,33639540
https://github.com/pydata/xarray/issues/133#issuecomment-56258103,https://api.github.com/repos/pydata/xarray/issues/133,56258103,MDEyOklzc3VlQ29tbWVudDU2MjU4MTAz,2062210,2014-09-20T06:05:19Z,2014-09-20T06:05:19Z,NONE,"@shoyer I love this suggested enhancement. If I could use xray and CDAT interchangeably, then I'd add xray into my workflow immediately (I'd image many other people would too, as CDAT has a fairly large user base).

The first thing I'd say is that you don't need to install all of [UV-CDAT](http://uvcdat.llnl.gov/) to get the useful modules. Instead, people have developed cdat-lite, which strips away all the visualisation stuff associated with UV-CDAT and just leaves the core convenience functions for calculating climatologies etc (i.e. it strips away the UV bit and just leaves the CDAT).

With the emergence of conda and binstar, it's now very easy to install cdat-lite with Anaconda. This page should be all you need: https://binstar.org/ajdawson/cdat-lite
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,33639540