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
756425955,MDU6SXNzdWU3NTY0MjU5NTU=,4648,Comprehensive benchmarking suite,2448579,open,0,,,6,2020-12-03T18:01:57Z,2023-06-15T16:56:00Z,,MEMBER,,,,"I think a good ""infrastructure"" target for the NASA OSS call would be to expand our benchmarking suite (https://pandas.pydata.org/speed/xarray/#/)

AFAIK running these in a useful manner on CI is still unsolved (please correct me if I'm wrong). But we can always run it on an NCAR machine using a cron job.

Thoughts?

cc @scottyhq

A quick survey of work needed (please append):
- [ ] indexing & slicing #3382 #2799 #2227
- [ ] DataArray construction  #4744 
- [ ] attribute access #4741, #4742
- [ ] property access #3514
- [ ] reindexing? https://github.com/pydata/xarray/issues/1385#issuecomment-297539517
- [x] alignment #3755, #7738 
- [ ] assignment #1771
- [ ] coarsen
- [x] groupby #659 #7795 #7796
- [x] resample #4498 #7795
- [ ] weighted #4482 #3883
- [ ] concat #7824
- [ ] merge
- [ ] open_dataset, open_mfdataset #1823
- [ ] stack / unstack
- [ ] apply_ufunc?
- [x] interp #4740 #7843
- [ ] reprs  #4744
- [x] to_(dask)_dataframe #7844 #7474

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