github: issue_comments: 1 row where issue = 1128759050 and user = 6574622 sorted by updated

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id	html_url	issue_url	node_id	user	created_at	updated_at ▲	author_association	body	reactions	performed_via_github_app	issue
1034098265	https://github.com/pydata/xarray/issues/6259#issuecomment-1034098265	https://api.github.com/repos/pydata/xarray/issues/6259	IC_kwDOAMm_X849oxZZ	d70-t 6574622	2022-02-09T19:05:44Z	2022-02-09T19:05:44Z	CONTRIBUTOR	This sounds like it could theoretically be handled using intake derived datasets. To be fair, derived datasets are probably still in their early stages. But the basic idea would be to apply arbitrary transformations to a dataset after it has been opened (e.g. with `decode_cf=False`) and represent the outcome of this transformation as an entry in the catalog. A suitable transformation function might be something like: `python def fix_calendar(ds): ds.time.calendar = "proleptic_gregorian" return xr.decode_cf(ds)` ... but maybe it is still more convenient or useful to handle it in xarray directly (e.g. I don't know if stac has a similar approach).	{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }		Be able to override calendar in `open_dataset`/`open_mfdataset`/etc OR include another calendar name 1128759050

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