issue_comments: 748483357

This data as json

html_url	issue_url	id	node_id	user	created_at	updated_at	author_association	body	reactions	performed_via_github_app	issue
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).	{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }		771382653