issue_comments: 1531050846

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https://github.com/pydata/xarray/issues/7790#issuecomment-1531050846 https://api.github.com/repos/pydata/xarray/issues/7790 1531050846 IC_kwDOAMm_X85bQfte 5821660 2023-05-02T08:04:45Z 2023-05-03T04:20:11Z MEMBER

As in #7098, citing @dcherian:

I think the real solution here is to explicitly handle NaNs during the decoding step. We do want these to be NaT in the output.

There are three more issues revealed here when using datetime64:

  • if _FillValue is set in encoding, it has to be of same type/resolution as the times in the array
  • If _FillValue is provided, we need to provide dtype and units to which fit our data, eg. if the _FillValue is referenced to unix-epoch the unit's should be equivalent
  • when encoding in the presence of NaT the data array is converted to floating point with NaN, which is problematic for the subsequent conversion to int64
 
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