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/1399#issuecomment-300072972,https://api.github.com/repos/pydata/xarray/issues/1399,300072972,MDEyOklzc3VlQ29tbWVudDMwMDA3Mjk3Mg==,102827,2017-05-09T06:26:36Z,2017-05-09T06:26:36Z,CONTRIBUTOR,Okay. I will try to come up with a PR within the next days.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,226549366
https://github.com/pydata/xarray/issues/1399#issuecomment-299819380,https://api.github.com/repos/pydata/xarray/issues/1399,299819380,MDEyOklzc3VlQ29tbWVudDI5OTgxOTM4MA==,102827,2017-05-08T09:32:58Z,2017-05-08T09:32:58Z,CONTRIBUTOR,"Hmm... The ""nanosecond""-issue seems to need a fix very much at the foundation. As long as pandas and xarray rely on `datetime64[ns]` you cannot avoid nanoseconds, right? `pd.to_datetime()` [forces the conversion to nanoscends ](https://github.com/pandas-dev/pandas/blob/c8dafb5a7ae9fe42b9d15c47082a6fb139e78b5d/pandas/core/tools/timedeltas.py#L156)even if you pass integers but for a time `unit` different to `ns`. This does not make me as nervous as Fabien since my data is always quite recent, but I see that this is far from ideal for a tool for climate scientists.

An intermediate fix (@shoyer, do you actually want one?) that I could think of for the performance issue right now would be to do the conversion to `datetime64[ns]` depending on the time unit, e.g.

- multiply raw values (most likely floats) with number of nanoseconds in time `unit` for units smaller then days (or hours?) and use these values as integers in `pd.to_datetime()`
- else, fall back to using netCDF4/netcdftime for months and years (as suggested by shoyer) casting the raw values to floats

The only thing that bothers me is that I am not sure if the ""number of nanoseconds"" is always the same in every day or hour in the view of `datetime64`, due to leap seconds or other particularities.

@shoyer: Does this sound reasonable or did I forget to take into account any side effects?
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