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/118#issuecomment-42638962,https://api.github.com/repos/pydata/xarray/issues/118,42638962,MDEyOklzc3VlQ29tbWVudDQyNjM4OTYy,1217238,2014-05-09T07:04:36Z,2014-05-09T07:04:36Z,MEMBER,"OK, I just merged a fix into master.

Unfortunately, it's not terribly useful to be able to have arrays decoded as `netCDF4.datetime` objects, because it's not possible to use them with label based indexing, as they are not hashable (see Unidata/netcdf4-python#255).

Just out of curiosity, why do you usually convert `netCDF4.datetime` objects into real datetime objects? I'm guessing it's not because you want objects you can put in a dictionary?

If there is a better type than `netCDF4.datetime` to use for decoded dates, I'm definitely willing to consider it. As I said before, we don't make much use of non-standard dates.

It's also certainly possible (in principle) to keep around another array with the original, encoded dates. Right now all the decoding according to CF conventions is done in one large function with no options, but I would love for it to be more flexible and modular.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,33112594
https://github.com/pydata/xarray/issues/118#issuecomment-42591663,https://api.github.com/repos/pydata/xarray/issues/118,42591663,MDEyOklzc3VlQ29tbWVudDQyNTkxNjYz,1217238,2014-05-08T19:04:17Z,2014-05-08T19:04:17Z,MEMBER,"Ouch! Thanks for filing the report and providing the sample file -- I will take a look.

For now, turn off automatic date decoding by calling `xray.open_dataset('sample_for_xray.nc', decode_cf=False)`.

I'm _guessing_ that part of the trouble might be that numpy and pandas provide poor support for alternative calendars (and honestly, I haven't tested them very much). I attempted to fall back on making arrays of python datetime objects, but in this case it looks like that didn't work -- somehow things got converted in a numpy native datetime64 array anyways.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,33112594