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  • numpy datetime conversion with DataArray is not working · 3 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1081869682 https://github.com/pydata/xarray/issues/6412#issuecomment-1081869682 https://api.github.com/repos/pydata/xarray/issues/6412 IC_kwDOAMm_X85AfAVy spencerkclark 6628425 2022-03-29T13:25:46Z 2022-03-29T13:25:46Z MEMBER

I agree this should be better documented.

Here when I want to retrieve the year of datetime, instead of casting back to an array of object & using datetime.year, it's handy to use built-in numpy datetime64 conversion.

The recommended way to extract datetime components, like the year, is to use the DatetimeAccessor. For example if you have a DataArray of datetime-like values (whether they are of type np.datetime64[ns] or cftime.datetime) you can do something like this:

da.dt.year

and it will return a DataArray containing the year of each datetime (for more information see the "Datetime components" section of the documentation).

 
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   numpy datetime conversion with DataArray is not working 1180565228
1081859463 https://github.com/pydata/xarray/issues/6412#issuecomment-1081859463 https://api.github.com/repos/pydata/xarray/issues/6412 IC_kwDOAMm_X85Ae92H jules-ch 43635101 2022-03-29T13:16:43Z 2022-03-29T13:18:37Z NONE

I'm using xarray on a Dataset & it's convenient for me to make calculation using DataArray. Here when I want to retrieve the year of datetime, instead of casting back to an array of object & using datetime.year, it's handy to use built-in numpy datetime64 conversion.

It's really confusing astype is not working like numpy does. If you want to keep this behavious maybe add a warning in the docs and log a warning aswell.

 
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   numpy datetime conversion with DataArray is not working 1180565228
1078904879 https://github.com/pydata/xarray/issues/6412#issuecomment-1078904879 https://api.github.com/repos/pydata/xarray/issues/6412 IC_kwDOAMm_X85ATsgv spencerkclark 6628425 2022-03-25T10:59:49Z 2022-03-25T10:59:49Z MEMBER

This is a common point of confusion, but is in fact expected. Xarray intentionally converts any np.datetime64 type to np.datetime64[ns]. The primary motivation is compatibility with pandas, which xarray relies on for time indexing and other time-related operations through things like pandas.DatetimeIndex or the pandas.Series.dt accessor (see, e.g., discussion in https://github.com/pydata/xarray/issues/789).

May I ask what your reason is for requiring a lower-precision datetime type? In xarray we have tried to provide alternatives (e.g. through cftime) for use-cases like longer date ranges.

 
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   numpy datetime conversion with DataArray is not working 1180565228

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