issue_comments: 523155674

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https://github.com/pydata/xarray/issues/3224#issuecomment-523155674 https://api.github.com/repos/pydata/xarray/issues/3224 523155674 MDEyOklzc3VlQ29tbWVudDUyMzE1NTY3NA== 1217238 2019-08-20T19:13:16Z 2019-08-20T19:13:16Z MEMBER

I appreciate how this could be convenient, but I am concerned about adding more complexity to xarray's merge code, which is already pretty complex and hard to maintain. My refactor in https://github.com/pydata/xarray/pull/3234 is the first time that code has been touched in quite a while and I don't think anyone (other than myself) has made contributions to that part of xarray.

To solve your use-case, what about either: 1. Converting observations into a MultiIndex over individual and subtissue, or 2. Creating separate individual/subtissue dimensions and storing the data the data in the form of a sparse array

Then you could do this sort of data munging with normal indexing/alignment/merging, e.g., python tissue_1 = ds.sel(subtissue="Whole_Blood").rename({k: k + ':1' for k in ds}) tissue_2 = ds.sel(subtissue="Adipose_Subcutaneous").rename({k: k + ':2' for k in ds}) merged = tissue_1.merge(tissue_2) # would have dimensions [gene, individual]

 
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