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/623#issuecomment-147451867,https://api.github.com/repos/pydata/xarray/issues/623,147451867,MDEyOklzc3VlQ29tbWVudDE0NzQ1MTg2Nw==,2443309,2015-10-12T16:24:14Z,2015-10-12T16:24:14Z,MEMBER,"@j08lue - 

> But this works only on data that is already loaded into memory (e.g. with .load()), as illustrated in this gist. I assume that this constraint is due to the netCDF backend (in this case netCDF4) not supporting irregular slicing. Once loaded, the operation is performed on NumPy arrays, I guess?

We've recently addressed this in netCDF4 (issue: https://github.com/Unidata/netcdf4-python/issues/467, PR: https://github.com/Unidata/netcdf4-python/issues/469).  

> Now the first thing is that it took me quite a while to figure out why this worked in some cases and not in others. Perhaps the IndexError that is thrown by the backend could be caught to give more hints on this? Or add a note in the Docs about this?

We've also added a more descriptive error message on the xray end (#593, #595).  These changes will be available in xray 0.6.1 which should be released soon (blocked by read the docs bug).

As for your actual feature request.  Maybe you could show us some sample code that does what you're looking for?
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