issue_comments: 1008312049
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| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
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| https://github.com/pydata/xarray/pull/5876#issuecomment-1008312049 | https://api.github.com/repos/pydata/xarray/issues/5876 | 1008312049 | IC_kwDOAMm_X848GZ7x | 6628425 | 2022-01-09T14:51:33Z | 2022-01-09T17:53:08Z | MEMBER | @dcherian @mathause @andersy005 given a DataArray of times with missing values, do you have any thoughts on what the preferred result of One option would be to return ``` In [3]: times = [np.datetime64("NaT"), np.datetime64("2000-01-01")] In [4]: da = xr.DataArray(times, dims=["x"]) In [5]: da.dt.season Out[5]: <xarray.DataArray 'season' (x: 2)> array([nan, 'DJF'], dtype=object) Dimensions without coordinates: x ``` This would be somewhat in line with how pandas handles this in other contexts (e.g. https://github.com/pydata/xarray/pull/5876#discussion_r734447120). But this sort of awkwardly returns a DataArray of mixed types. Another option, and this is how @pierreloicq implemented things originally, would be to simply return a string label for missing values, e.g.
As I've thought about this more, this feels nicer, because the types are consistent and "season" is just a category label, and |
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