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/issues/3580#issuecomment-561261583,https://api.github.com/repos/pydata/xarray/issues/3580,561261583,MDEyOklzc3VlQ29tbWVudDU2MTI2MTU4Mw==,8881170,2019-12-03T17:02:39Z,2019-12-03T17:02:39Z,CONTRIBUTOR,"I can't seem to replicate this issue for some reason. I have the same versions of `xarray`, `numpy`, and `netCDF4` installed. 

```python-traceback
IndexError: The indexing operation you are attempting to perform is not valid on netCDF4.Variable object. Try loading your data into memory first by calling .load().
```

This implies that it's having issues slicing numpy-style with a dask array. I bet if you load it into memory and slice that way it'll work. But at ~22GB you might not be able to do that.

The preferred way to slice in `xarray` is to use `.sel()` and `.isel()` to leverage the label-aware nature of `xarray`. So you should have no problem doing this operation explicitly with the following:

`fullda['sst'].isel(M=0, S=0, X=0, Y=0)`. You of course don't need to slice the `L` dimension since you are taking the full thing, but the equivalent notation there is :`fullda['sst'].isel(L=slice(0, None))`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,529644880