issue_comments: 420444668

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https://github.com/pydata/xarray/issues/2399#issuecomment-420444668 https://api.github.com/repos/pydata/xarray/issues/2399 420444668 MDEyOklzc3VlQ29tbWVudDQyMDQ0NDY2OA== 6815844 2018-09-11T22:16:32Z 2018-09-11T22:16:32Z MEMBER

Sorry that I couldn't join the discussion here.

Thanks, @horta, for giving the nice document. We tried to use the consistent terminology in the docs, but I agree that it would be nice to have a list of the definitions. I think it might be better to discuss in another issue. See #2410.

For loc and sel issues. One thing I don't agree is

The result of d.loc[i] is equal to d.sel(x=i). Also, it seems reasonable to expect the its result should be the same as d0.sel(x=i) for d0 given by

As xarray inherits not only from pandas but also from numpy's multi-dimensional array. That is, we need to be very consistent with the resultant shape of indexing. It would be confusing if a selection from different dimensional arrays becomes the same.

I do think that handling duplicate matches with indexing is an important use-case. This comes up with nearest neighbor matching as well -- it would be useful to be able to return the full set of matches within a given distance, not just the nearest match.

I also think that what is lacking in xarray is this functionality. Any interest to help us for this?

 
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