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,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](https://discourse.pangeo.io/t/pandas-dtypes-now-free-from-nanosecond-limitation/3106) 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_","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7493/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue