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
651101286,MDU6SXNzdWU2NTExMDEyODY=,4203,.to_xarray(): a 9Mb dataframe requires 30Gb ram ,15280721,closed,0,,,6,2020-07-05T16:29:08Z,2020-07-08T04:39:21Z,2020-07-07T16:46:38Z,NONE,,,,"```python
ds1 = df.set_index(['lat','lon']).stack()
ds1.index.names = ['lat', 'lon', 'time']
ds1 = ds1.sort_index()
ds1.columns = ['T']

xr.Dataset(ds1)
```





I tried to transform a [dataset](https://drive.google.com/file/d/1oGTUi2RKVbN__zbJBRsN2eQ3hOGD4C7z/view?usp=sharing) with 2D latitude and longitude  into Xarray dataset, however I failed to do so, because ram error occurred during process.

I also tried to set lat and lon as coordination directly, however it is complex to plotting and conducting geographic manipulation in the following work. This dataset is a non-rectangular area, lat and lon can not be replaced by the corner values.
 

In all, I hope this data can be transformed into xarray and resampled into traditional rectangle data, which can be easily dealt with.

Any codes and suggestions are sincerely welcomed. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4203/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue