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/6259#issuecomment-1034098265,https://api.github.com/repos/pydata/xarray/issues/6259,1034098265,IC_kwDOAMm_X849oxZZ,6574622,2022-02-09T19:05:44Z,2022-02-09T19:05:44Z,CONTRIBUTOR,"This sounds like it could theoretically be handled using [intake derived datasets](https://intake.readthedocs.io/en/latest/transforms.html?highlight=transform#barebone-example). 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}",,1128759050