issue_comments: 1058577301

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https://github.com/pydata/xarray/issues/5030#issuecomment-1058577301 https://api.github.com/repos/pydata/xarray/issues/5030 1058577301 IC_kwDOAMm_X84_GJuV 35968931 2022-03-03T22:35:08Z 2022-03-03T22:37:16Z MEMBER

For datatree, you could apply the reduction with the set-intersection of provided dims and dims present in a node (if that's the right term).

I specifically want the user to be able to choose between different behaviours with a flag, but you're right that I could just deal with this at the datatree level instead of here. That would make a fair amount of sense, and it would cover Julius' use-case (via encouraging him to store his models in a tree, so that for ds in model_datasets would become a loop over nodes in a tree).

My concern is that we could conceivably adding missing_dims to any function that takes a dim argument, which is pretty much the whole API.

Do you think that's a problem though? We added keep_attrs to even more of the API than this would cover. Specifically I would want to add it to the REDUCE_METHODS, the NAN_REDUCE_METHODS, and the NAN_CUM_METHODS (so {"all", "any", "max", "min", "mean", "prod", "sum", "std", "var", "median", "cumsum", "cumprod"}).

I'm fine with doing it either here or in datatree personally.

 
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