It is great that xarray supports dimensions without coords, but sometimes I think it would be useful to be able to easily opt into autogenerated coords from 0 to n-1. This can be useful to obtain DataArrays for pointwise indexing:

```python import xarray as xr ds = xr.Dataset()

a list of selected indices for each layer

ds['selected'] = (['layer', 'selected-i'], [ [0, 1, 2], [1, 5, 3], ])

normally, concatenation would drop layer data

print(xr.concat(ds['selected'], dim='selected-i'))

<xarray.DataArray 'selected' (selected-i: 6)>

array([0, 1, 2, 1, 5, 3])

Dimensions without coordinates: selected-i

if you generate coords from 0 to n-1 for layer, however, the resulting DataArray

contains 'layer' indices for use in pointwise indexing

print(xr.concat(ds .assign_coords(layer=list(range(ds.sizes['layer']))) ['selected'], dim='selected-i'))

<xarray.DataArray 'selected' (selected-i: 6)>

array([0, 1, 2, 1, 5, 3])

Coordinates:

layer (selected-i) int64 0 0 0 1 1 1

Dimensions without coordinates: selected-i

```

My issue with the above is that layer=list(range(ds.sizes['layer'])) is verbose and fails to be DRY. My thought for such an API is that xarray could maybe have a special constant for auto-assignment, usable in any method that takes input coords:

python print(xr.concat(ds .assign_coords(layer=xr.AUTO) ['selected'], dim='selected-i'))

(Additionally, perhaps xr.AUTO could be a function/class, so that xr.AUTO(start) produces indices starting at start.)