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  • jjhelmus · 2 ✖

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  • Read NetCDF files with multiple values in missing_value attribute · 2 ✖

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  • CONTRIBUTOR · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
122332344 https://github.com/pydata/xarray/issues/471#issuecomment-122332344 https://api.github.com/repos/pydata/xarray/issues/471 MDEyOklzc3VlQ29tbWVudDEyMjMzMjM0NA== jjhelmus 1050278 2015-07-17T16:23:34Z 2015-07-17T16:23:34Z CONTRIBUTOR

Sounds like a good solution. I'll work on a PR.

 
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   Read NetCDF files with multiple values in missing_value attribute 94966000
122294746 https://github.com/pydata/xarray/issues/471#issuecomment-122294746 https://api.github.com/repos/pydata/xarray/issues/471 MDEyOklzc3VlQ29tbWVudDEyMjI5NDc0Ng== jjhelmus 1050278 2015-07-17T14:30:15Z 2015-07-17T14:30:15Z CONTRIBUTOR

Yes, the two values in the missing_value attribute indicate two classes of data (not collected vs below minimum detectable threshold) and these data can be access by setting mask_and_scale=False but this also results in a valid data being returned without scaling which makes it less useful.

My question is how should xray should handle these cases? Either replace all instances of the values in missing_value with NaN or raise a error message stating that multiple missing_values are not supported similar? I'd be happy to create a PR implementing either case.

 
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   Read NetCDF files with multiple values in missing_value attribute 94966000

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