issue_comments: 748483357

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https://github.com/pydata/xarray/issues/4714#issuecomment-748483357 https://api.github.com/repos/pydata/xarray/issues/4714 748483357 MDEyOklzc3VlQ29tbWVudDc0ODQ4MzM1Nw== 14808389 2020-12-19T14:41:47Z 2020-12-19T14:41:47Z MEMBER

reindex does not have to be changed since we can just call e.g. ffill with the dim parameter for this to work: python arr.reindex(...).ffill(dim="dim")

This really depends on how you intend to use the result of the indexing. For example, if you don't really need the big matrix, you could just convert the DataArray to a Dataset where the sensor dimension is the names of the variables (using to_dataset(dim="sensor"), or construct it that way). If you do need the matrix, this might be slightly better (you still end up allocating a T * (S + n) array): python arr.reindex(sensor=["A", "B", "C"]).sel({"sensor": ..., "time": ...}, method="ffill") but if you really care about the memory allocated at once, you might be better off using dask: python arr.chunk({"time": 100}).reindex(...).sel(...)

If all of that is not an option, I guess we might be able add a method_kwargs parameter (not sure if there is a better option, though).

 
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