id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
175188832,MDU6SXNzdWUxNzUxODg4MzI=,997,"Discovered conflicting _FillValue and missing_value, but both are NaN",204523,closed,0,,,0,2016-09-06T08:29:01Z,2016-09-07T16:20:24Z,2016-09-07T16:20:24Z,CONTRIBUTOR,,,,"When a variable contains both attributes and both are `NaN` the comparison fails. This happens when with `engine='netcdf4'` and not with `engine='h5netcdf`.

Example file: ftp://anon-ftp.ceda.ac.uk/neodc/esacci/aerosol/data/MERIS_ALAMO/L3/v2.2/DAILY/2008/01/20080101-ESACCI-L3C_AEROSOL-AOD-MERIS_ENVISAT-ALAMO-fv2.2.nc

```
ncdump -h 20080101-ESACCI-L3C_AEROSOL-AOD-MERIS_ENVISAT-ALAMO-fv2.2.nc
netcdf \20080101-ESACCI-L3C_AEROSOL-AOD-MERIS_ENVISAT-ALAMO-fv2.2 {
dimensions:
        latitude = 180 ;
        longitude = 360 ;
variables:
        float AOD550(latitude, longitude) ;
                AOD550:_FillValue = NaNf ;
                AOD550:long_name = ""Mean Effective Aerosol Optical Thickness at 550nm over ocean - Best solution"" ;
                AOD550:standard_name = ""atmosphere_optical_thickness_due_to_ambient_aerosol"" ;
                AOD550:units = ""1"" ;
                AOD550:coordinates = ""latitude longitude"" ;
                AOD550:valid_range = -3.402823e+38f, 3.402823e+38f ;
                AOD550:missing_value = NaNf ;
}
```

```
>>> import xarray as xr
>>> ds = xr.open_dataset('20080101-ESACCI-L3C_AEROSOL-AOD-MERIS_ENVISAT-ALAMO-fv2.2.nc', engine='h5netcdf', decode_cf=False)
>>> ds.variables['AOD550'].attrs['_FillValue']
array([ nan], dtype=float32)
>>> ds.variables['AOD550'].attrs['missing_value']
array([ nan], dtype=float32)
>>> type(ds.variables['AOD550'].attrs['missing_value'])
<class 'numpy.ndarray'>
>>> xr.core.utils.equivalent(ds.variables['AOD550'].attrs['_FillValue'], ds.variables['AOD550'].attrs['missing_value'])
True
>>>
```

```
>>> ds = xr.open_dataset('20080101-ESACCI-L3C_AEROSOL-AOD-MERIS_ENVISAT-ALAMO-fv2.2.nc', engine='netcdf4', decode_cf=False) 
>>> ds.variables['AOD550'].attrs['_FillValue']
nan
>>> ds.variables['AOD550'].attrs['missing_value']
nan
>>> type(ds.variables['AOD550'].attrs['missing_value'])
<class 'numpy.float32'>
>>> xr.core.utils.equivalent(ds.variables['AOD550'].attrs['_FillValue'], ds.variables['AOD550'].attrs['missing_value'])
False
>>>
```
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