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-42785413,https://api.github.com/repos/pydata/xarray/issues/118,42785413,MDEyOklzc3VlQ29tbWVudDQyNzg1NDEz,2443309,2014-05-11T22:26:54Z,2014-05-11T22:26:54Z,MEMBER,"@shoyer - my experience is that the dummy `netCDF4.datetime` objects don't play nice with setting up a `pandas` time index, so a intermediate conversion step is necessary.  I haven't looked into why this is exactly.

I just tried the new decoding and it seems to work.
","{""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-42598104,https://api.github.com/repos/pydata/xarray/issues/118,42598104,MDEyOklzc3VlQ29tbWVudDQyNTk4MTA0,2443309,2014-05-08T19:54:54Z,2014-05-08T19:54:54Z,MEMBER,"Thanks, the `decode_cf` keyword should get me around the problem for now.  

I've made a habit of always directly converting my `netCDF4.datetime` to true `datetime.datetime` objects immediately, since netCDF4 only returns real datetime objects for the Gregorian calendars. 

``` python
f = netCDF4.Dataset('sample_for_xray.nc') 
decoded_times = netCDF4.num2date(f.variables['time'][:], 
                                 f.variables['time'].units, 
                                 f.variables['time'].calendar)
for i, t in enumerate(decoded_times):
    decoded_times[i] = datetime.datetime(*t.timetuple()[:6])
```

The important piece to remember if this is done is that you have to be very picky about how you calculate timedeltas between these dates since they think they are on the Gregorian calendar.  I usually just keep an ordinal based time array around for that reason.  
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,33112594