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/2368#issuecomment-419166240,https://api.github.com/repos/pydata/xarray/issues/2368,419166240,MDEyOklzc3VlQ29tbWVudDQxOTE2NjI0MA==,1828519,2018-09-06T16:54:43Z,2018-09-06T16:55:11Z,CONTRIBUTOR,"@rabernat For the groups NetCDF files I had in mind the NASA L1B data files for the satellite instrument VIIRS onboard Suomi-NPP and NOAA-20 satellites. You can see an example file [here](https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/5110/VNP02IMG/2018/008/VNP02IMG.A2018008.0000.001.2018061001540.nc).

The summary of the ncdump is:

```
netcdf VNP02IMG.A2018008.0000.001.2018061001540 {
dimensions:
        number_of_scans = 202 ;
        number_of_lines = 6464 ;
        number_of_pixels = 6400 ;
        number_of_LUT_values = 65536 ;

... lots of global attributes ...

group: scan_line_attributes {
  variables:
        double scan_start_time(number_of_scans) ;
                scan_start_time:long_name = ""Scan start time (TAI93)"" ;
                scan_start_time:units = ""seconds"" ;
                scan_start_time:_FillValue = -999.9 ;
                scan_start_time:valid_min = 0. ;
                scan_start_time:valid_max = 2000000000. ;
... lots of other variables in this group ...

group: observation_data {
  variables:
        ushort I04(number_of_lines, number_of_pixels) ;
                I04:long_name = ""I-band 04 earth view radiance"" ;
                I04:units = ""Watts/meter^2/steradian/micrometer"" ;
                I04:_FillValue = 65535US ;
                I04:valid_min = 0US ;
                I04:valid_max = 65527US ;
                I04:scale_factor = 6.104354e-05f ;
                I04:add_offset = 0.0016703f ;
                I04:flag_values = 65532US, 65533US, 65534US ;
                I04:flag_meanings = ""Missing_EV Bowtie_Deleted Cal_Fail"" ;

```

When I first started out with xarray I assumed I would be able to do something like:

```
import xarray as xr
nc = xr.open_dataset('VNP02IMG.A2018008.0000.001.2018061001540.nc')
band_data = nc['observation_data/I04']
```

Which I can't do, but can do with the python netcdf4 library:

```
In [7]: from netCDF4 import Dataset

In [8]: nc = Dataset('VNP02IMG.A2018008.0000.001.2018061001540.nc')

In [9]: nc['observation_data/I04']
Out[9]: 
<class 'netCDF4._netCDF4.Variable'>
```

I understand that I can provide the `group` keyword to `open_dataset` but then I have to open the file twice if I want to get the global attributes. So any interface I had set up in my code to pass around one object with all of the file contents won't work. That isn't xarray's fault and shouldn't necessarily be something xarray has to solve, but it is a type of NetCDF4 file that is valid and can't be read ""perfectly"" with xarray.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,350899839
https://github.com/pydata/xarray/issues/2368#issuecomment-413849756,https://api.github.com/repos/pydata/xarray/issues/2368,413849756,MDEyOklzc3VlQ29tbWVudDQxMzg0OTc1Ng==,1828519,2018-08-17T12:26:42Z,2018-08-17T12:26:42Z,CONTRIBUTOR,This is mentioned elsewhere (can't find the issue right now) and may be out of scope for this issue but I'm going to say it anyway: opening a NetCDF file with groups was not as easy as I wanted it to be when first starting out with xarray.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,350899839