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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
1563104480 I_kwDOAMm_X85dKxTg 7493 Interoperability with Pandas 2.0 non-nanosecond datetime khider 11758571 open 0     18 2023-01-30T19:55:00Z 2024-02-24T15:53:12Z   NONE      

Is your feature request related to a problem?

As mentioned in this post on the Pangeo discourse, Pandas 2.0 will fully support non-nanosecond datetime as indices. The motivation for this work was the paleogeosciences; a community who needs to represent time in millions of years. One of the biggest motivator is also to facilitate paleodata - model comparison. Enter xarray!

Below is a snippet of code to create a Pandas Series with a non-nanosecond datetime and export to xarray (this works). However, most of the interesting functionalities of xarray don't seem to support this datetime out-of-box:

```import numpy as np import pandas as pd import xarray as xr

pds = pd.Series([10, 12, 11, 9], index=np.array(['-2000-01-01', '-2005-01-01', '-2008-01-01', '-2009-01-01']).astype('M8[s]')) xra = pds.to_xarray() xra.plot() #matplotlib error xra.sel(index='-2009-01-01', method='nearest') To test, you will need the Pandas nightly built: pip uninstall pandas -y pip install --pre --extra-index https://pypi.anaconda.org/scipy-wheels-nightly/simple pandas>1.9 ```

Describe the solution you'd like

Work towards an integration of the new datetimes with xarray, which will support users beyond the paleoclimate community

Describe alternatives you've considered

No response

Additional context

No response

 
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     xarray 13221727 issue

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