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  • .item() on a DataArray with dtype='datetime64[ns]' returns int · 4 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
565183733 https://github.com/pydata/xarray/issues/3256#issuecomment-565183733 https://api.github.com/repos/pydata/xarray/issues/3256 MDEyOklzc3VlQ29tbWVudDU2NTE4MzczMw== dopplershift 221526 2019-12-12T20:57:56Z 2019-12-12T20:57:56Z CONTRIBUTOR

Yeah, it's not much shorter, but it's a much easier concept for new users to grasp, IMO.

 
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   .item() on a DataArray with dtype='datetime64[ns]' returns int 484699415
564633712 https://github.com/pydata/xarray/issues/3256#issuecomment-564633712 https://api.github.com/repos/pydata/xarray/issues/3256 MDEyOklzc3VlQ29tbWVudDU2NDYzMzcxMg== jthielen 3460034 2019-12-11T16:50:33Z 2019-12-11T16:50:33Z CONTRIBUTOR

Would it make sense to add something to the dt accessor, such as_datetime? @dopplershift's example would still be somewhat verbose, but it seems more sensible:

python times[0].dt.as_datetime().item()

 
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   .item() on a DataArray with dtype='datetime64[ns]' returns int 484699415
563511116 https://github.com/pydata/xarray/issues/3256#issuecomment-563511116 https://api.github.com/repos/pydata/xarray/issues/3256 MDEyOklzc3VlQ29tbWVudDU2MzUxMTExNg== dopplershift 221526 2019-12-10T01:00:00Z 2019-12-10T01:00:00Z CONTRIBUTOR

Well it'd be nice to have something, because what we have to do right now is: python times[0].values.astype('datetime64[ms]').astype('O') which is an abomination and terrible for teaching.

 
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   .item() on a DataArray with dtype='datetime64[ns]' returns int 484699415
524516807 https://github.com/pydata/xarray/issues/3256#issuecomment-524516807 https://api.github.com/repos/pydata/xarray/issues/3256 MDEyOklzc3VlQ29tbWVudDUyNDUxNjgwNw== shoyer 1217238 2019-08-24T03:58:15Z 2019-08-24T03:58:15Z MEMBER

This is basically a direct manifestation of this NumPy bug: https://github.com/numpy/numpy/issues/12550

We could potentially had a workaround in xarray but it would be good to figure out the NumPy fix first, so we can be consistent.

 
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   .item() on a DataArray with dtype='datetime64[ns]' returns int 484699415

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