html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/pull/3925#issuecomment-925694605,https://api.github.com/repos/pydata/xarray/issues/3925,925694605,IC_kwDOAMm_X843LPqN,4160723,2021-09-23T10:37:07Z,2021-09-23T10:37:07Z,MEMBER,"In #5692 it is possible to perform selection using non-dimension coordinates with an index, although there's no easy way yet to set an index for such coordinates (this will be done in a follow-up PR by updating the API of `set_index`).  ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,592312709
https://github.com/pydata/xarray/pull/3925#issuecomment-794116358,https://api.github.com/repos/pydata/xarray/issues/3925,794116358,MDEyOklzc3VlQ29tbWVudDc5NDExNjM1OA==,4160723,2021-03-09T16:23:17Z,2021-03-09T16:23:17Z,MEMBER,"> pandas is 1000x faster than NumPy if the index is pre-existing, but 100x slower if the index is new. That's a 1e5 fold slow-down!

> I think users will appreciate the flexibility, but if there's some way we warn users that they really should set the index ahead of time when they are doing repeating indexing that could also be welcome.

I think it's a good use case for some kind of `EphemeralIndex` (or `BasicIndex` or `NumpyIndex`) once the explicit index refactoring is done, along with some good documentation on which index to choose for which purpose.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,592312709