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id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
982973379 MDU6SXNzdWU5ODI5NzMzNzk= 5750 datetime64 data type in arrays is always 'datetime64[ns]' sjsmith757 45645265 open 0     2 2021-08-30T16:25:07Z 2021-08-31T14:37:26Z   NONE      

I think this is probably an enhancement request, but there doesn't seem to be any documentation related to this and it doesn't really match the behavior I would expect. From what I can tell, xarray doesn't support datetime arrays with units other than [ns]. For example,

times = np.arange(np.datetime64('2005-01'),np.datetime64('2007-01'),np.timedelta64(1,'M')) xrtimes = xr.DataArray(times,dims=['time'],coords={'time':times},name='time')

I would expect xrtimes.dtype to return dtype('<M8[M]') as times.dtype does, but instead it returns dtype('<M8[ns]'). Even looking at xrtimes.indexes['time'] to ensure it isn't just a problem with the repr, the dtype is listed as 'datetime64[ns]'. Trying to do xrtimes.astype('datetime64[M]') does nothing. It would be nice if this didn't simply silently fail, or if there were some documentation explaining that datetime64 objects have to be in units of ns.

In an ideal world, it would be nice if xarray supported datetime units other than ns, but I understand with internals that may be more trouble than its worth...

I'm using xarray=0.19.0 pandas=1.3.1 numpy=1.21.1

 
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     xarray 13221727 issue

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