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/pull/59#issuecomment-37505097,https://api.github.com/repos/pydata/xarray/issues/59,37505097,MDEyOklzc3VlQ29tbWVudDM3NTA1MDk3,1217238,2014-03-13T06:58:15Z,2014-03-13T06:58:15Z,MEMBER,"If you're sure that 'time' is stored as `pandas.DatetimeIndex` (e.g., you use a standard calendar and all dates within roughly 1700-2300), you can do those comparisons with `ds['time'].index`, which even lets you compare to strings: `ds['time'].index > '2014-01-01'`. But I agree it would be nice to have a general `to_datetime` method like pandas. If we already wrote this functionality (and it was somewhat tricky), we might as well expose it to users.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,29067976
https://github.com/pydata/xarray/pull/59#issuecomment-37434012,https://api.github.com/repos/pydata/xarray/issues/59,37434012,MDEyOklzc3VlQ29tbWVudDM3NDM0MDEy,1217238,2014-03-12T16:58:56Z,2014-03-12T16:58:56Z,MEMBER,"So I think the unfortunate reality is that np.datetime64 is still our best option. Otherwise we are left with dates as Python objects, which is painfully slow.
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