issue_comments: 418778596

Thanks for the report!

This was actually a somewhat intentional omission in xarray, but if would not be particularly difficult to add in this feature if we want it. At the very least, we should note this deviation somewhere in the docs.

There are two potentially problematic aspects to the pandas behavior: 1. It means that you cannot count on indexing a dataframe with its own index to return something equivalent to the original dataframe, e.g., consider df.loc[['a', 'a']] in your example, which returns a dataframe with 4 rows. 2. More generally, it means you can't count on indexing a dataframe with an array to return an object of the same size as the indexer. This is particularly problematic for xarray, because we support vectorized indexing with multi-dimensional indexers. I don't know how we could define a multi-dimensional equivalent of this -- what shape should the result have if you indexed with a multi-dimensional array instead, e.g., da.loc[{"dim_0": xr.DataArray([['a']]}]? With multiple dimensions involved, it's not clear where the extra introduced dimensions should go.

Now that you bring this up, I wonder how the existing supporting for indexing like da.loc[{"dim_0": "a"}] would work if there are other multi-dimensional indexers. I don't know if we have test coverage for this...