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/3768#issuecomment-586123705,https://api.github.com/repos/pydata/xarray/issues/3768,586123705,MDEyOklzc3VlQ29tbWVudDU4NjEyMzcwNQ==,1217238,2020-02-14T06:52:27Z,2020-02-14T06:52:27Z,MEMBER,"The model of how indexing with non-DataArray objects is described here under [vectorized indexing](https://xarray.pydata.org/en/stable/indexing.html#vectorized-indexing): “Slices or sequences/arrays without named-dimensions are treated as if they have the same dimension which is indexed along”

For better or worse, xarray doesn’t have any way to distinguish between “meaningful” and “default” dimension names. This means that a DataArray without explicitly named dimensions will indeed broadcast differently (e.g., in either arithmetic or indexing) than unlabeled NumPy arrays.

These were intentional design choices: we like our name based broadcasting rules better than NumPy’s positional rules. And for the most part, the default dimension names like `dim_0` are just there so a user can see how they need to change their data instead of getting an error message.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,564555854