issue_comments

@BorjaEst I don't think I ever pushed anything up, sorry. Probably best to start a new one.

@BorjaEst I haven't opened a PR for this 🙂

@dcherian Thanks for the review, I've made those changes

@dcherian thanks! I've tried overriding with .attrs["coordinates"] = None, .attrs["coordinates"] = "" and .attrs["coordinates"] = False but that doesn't seem to work either. Would be great if that worked and would solve my problem!

I had a go at working on this, as mentioned in #5448 it could be a fix in https://github.com/pydata/xarray/blob/ce01f42134962b63d453657c5cb649ebf152283d/xarray/conventions.py#L707

I couldn't see how to fix it in there but tried a fix at the end of https://github.com/pydata/xarray/blob/ce01f42134962b63d453657c5cb649ebf152283d/xarray/conventions.py#L813 for bounds and coordinate variables. See below: ```python def cf_encoder(variables, attributes): """ Encode a set of CF encoded variables and attributes. Takes a dicts of variables and attributes and encodes them to conform to CF conventions as much as possible. This includes masking, scaling, character array handling, and CF-time encoding.

Parameters
----------
variables : dict
    A dictionary mapping from variable name to xarray.Variable
attributes : dict
    A dictionary mapping from attribute name to value

Returns
-------
encoded_variables : dict
    A dictionary mapping from variable name to xarray.Variable,
encoded_attributes : dict
    A dictionary mapping from attribute name to value

See Also
--------
decode_cf_variable, encode_cf_variable
"""

# add encoding for time bounds variables if present.
_update_bounds_encoding(variables)

new_vars = {k: encode_cf_variable(v, name=k) for k, v in variables.items()}

# Remove attrs from bounds variables (issue #2921)
for var in new_vars.values():
    bounds = var.attrs["bounds"] if "bounds" in var.attrs else None
    if bounds and bounds in new_vars:
        # see http://cfconventions.org/cf-conventions/cf-conventions.html#cell-boundaries
        for attr in [
            "units",
            "standard_name",
            "axis",
            "positive",
            "calendar",
            "long_name",
            "leap_month",
            "leap_year",
            "month_lengths",
        ]:
            if attr in new_vars[bounds].attrs and attr in var.attrs:
                if new_vars[bounds].attrs[attr] == var.attrs[attr]:
                    new_vars[bounds].attrs.pop(attr)
        # remove _FillValue for bounds
        if new_vars[bounds].attrs.get("_FillValue"):
             new_vars[bounds].attrs["_FillValue"] = None


# remove _FillValue for coordinate variables as missing values are not permitted
# a coordinate variable is a one-dimensional variable with the same name as its dimension
# see coordinate variable in http://cfconventions.org/cf-conventions/cf-conventions.html#terminology
for var in new_vars.keys():
    if new_vars[var].dims == (var,) and new_vars[var].attrs.get("_FillValue"):
        new_vars[var].attrs["_FillValue"] = None

return new_vars, attributes

```

tests to add into test_conventions.py could be something like:

```python def test_fill_value_none_for_coordinate_variables(): # need to be floats so _FillValue is added temp = 273.15 + 25 * np.random.randn(2, 2) lon = [0.0, 5.0] lat = [10.0, 20.0]

ds = Dataset({'temperature': (['lat', 'lon'], temp)},
            coords={'lat': lat,
                    'lon': lon})

ds['lat'].attrs = {
    'standard_name': 'latitude',
    'long_name': 'latitude',
    'units': 'degrees_north',
    'axis': 'Y'}
ds['lon'].attrs = {
    'standard_name': 'longitude',
    'long_name': 'longitude',
    'units': 'degrees_east',
    'axis': 'X'}
ds['temperature'].attrs = {
    'standard_name': 'air_temperature',
    'units': 'K'}


v, _ = conventions.cf_encoder(ds.variables, ds.attrs)

assert v["lat"].attrs['_FillValue'] is None
assert v["lon"].attrs['_FillValue'] is None
# check _FillValue still inserted for temperature
assert v["temperature"].attrs['_FillValue'] is not None

def test_fill_value_none_for_bounds_variables(): # need to be floats so _FillValue is added temp = 273.15 + 25 * np.random.randn(2, 2) lat_bnds = np.arange(4.0).reshape((2, 2)) lon = [0.0, 5.0] lat = [10.0, 20.0]

ds = Dataset({'temperature': (['lat', 'lon'], temp), 
              'lat_bnds': (['lat', 'nbnds'], lat_bnds),
              'lon_bnds': (['lon', 'nbnds'], lat_bnds)},
            coords={'lat': lat,
                    'lon': lon})


ds['lat'].attrs = {
    'standard_name': 'latitude',
    'long_name': 'latitude',
    'units': 'degrees_north',
    'axis': 'Y',
    'bounds': 'lat_bnds'}
ds['lon'].attrs = {
    'standard_name': 'longitude',
    'long_name': 'longitude',
    'units': 'degrees_east',
    'axis': 'X',
    'bounds': 'lon_bnds'}
ds['temperature'].attrs = {
    'standard_name': 'air_temperature',
    'units': 'K'}

v, _ = conventions.cf_encoder(ds.variables, ds.attrs)
assert v["lat_bnds"].attrs['_FillValue'] is None
assert v["lon_bnds"].attrs['_FillValue'] is None

```

but I couldn't quite get this to work, with some tests in test_backends.py failing. I could see that the fill value is being added in by maybe_default_fill_value in conventions.py so maybe it would be better to skip coordinate variable and bounds here. I can't really spend anymore time on this but putting it here in case its useful.