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
2177359290,PR_kwDOAMm_X85pJtWE,8817,Update documentation for clarity,13053829,closed,0,,,3,2024-03-09T19:03:19Z,2024-03-09T22:33:19Z,2024-03-09T22:33:16Z,CONTRIBUTOR,,0,pydata/xarray/pulls/8817,Closes #8794 ,"{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8817/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull
2159674260,I_kwDOAMm_X86AugOU,8794,Difficult to convert `pd.DataFrame` to `Dataset` with multi-index,13053829,closed,0,,,2,2024-02-28T19:17:14Z,2024-03-09T22:33:17Z,2024-03-09T22:33:17Z,CONTRIBUTOR,,,,"### What is your issue?

## No direct way to create multi-index dataset

Unless I'm missing something, there is no easy way to convert a Pandas dataframe to a dataset with a multi-index. For example, `xr.Dataset.from_dataframe` automatically converts any Pandas multi-index into separate dimensions.

## Workaround is inefficient

One workaround is doing `xr.Dataset.from_dataframe(df).stack(...)` however this is very inefficient for sparse multi-indices.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8794/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue