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  • Open mfdataset with long time axis · 2 ✖

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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
914653049 https://github.com/pydata/xarray/pull/5767#issuecomment-914653049 https://api.github.com/repos/pydata/xarray/issues/5767 IC_kwDOAMm_X842hH95 mathause 10194086 2021-09-07T21:53:44Z 2021-09-07T21:53:44Z MEMBER

Maybe something like this:

python attrs = dict(units="days since 1850-01-01", calendar="proleptic_gregorian") ds1 = xr.Dataset(coords=dict(time=("time", [164678], attrs))) xr.conventions.decode_cf(ds1)

(or you can directly create two time arrays as suggested by @TomNicholas )

 
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   Open mfdataset with long time axis 988426640
913094980 https://github.com/pydata/xarray/pull/5767#issuecomment-913094980 https://api.github.com/repos/pydata/xarray/issues/5767 IC_kwDOAMm_X842bLlE mathause 10194086 2021-09-05T06:31:41Z 2021-09-05T06:31:41Z MEMBER

I like the idea. I would still raise an error, though.Maybe: "Found a mix of pandas and cftime datetime data types. Re-opening the data with the option use_cftime=True may fix this issue." That would be less magic and should tell the users what's going wrong. In addition we would not need an additional keyword argument. I expect a merge_by_coords operation to be typically fairly early in the analysis pipeline.

 
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   Open mfdataset with long time axis 988426640

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