issue_comments: 654015589

Ok, so for now I roll with this:

```python def shrink_dataarray(da, dims=None): """remove nodata borders from spatial dims of dataarray""" dims = set(dims) if dims else set(da.dims)

if len(dims) != 2:
    raise IndexError

# non-spatial dims (carry over, only shrink spatial dims)
nsd = set(da.dims) - dims
nsd_indexers = {d: range(len(da[d])) for d in nsd}

indexers = {d: (da.count(dim=dims - set([d])|nsd).cumsum() != 0) * 
               (da.count(dim=dims - set([d])|nsd)[::-1].cumsum()[::-1] != 0)
            for d in dims}

indexers.update(nsd_indexers)

return da.isel(**indexers)

```

Is it possible to identify non-spatial dims with plain xarray dataarrays (non cf-xarray)? And is there maybe a way to detect unlimited dims (usually the time dim)?