issue_comments

My mental model of what's happening may not be correct. I did want sel(), isel(), and squeeze() to all operate the same way (and maybe someday even work on non-dim coordinates!). Replacing squeeze() with isel() in my initial example gives the same failure, which I would want it to work:

``` import numpy as np import xarray as xr

arr1 = xr.DataArray(np.zeros((1,5)), dims=['y', 'x'], coords={'e': ('y', [10])}) arr2 = arr1.isel(y=0).expand_dims('y') xr.testing.assert_identical(arr1, arr2) ```

``` AssertionError: Left and right DataArray objects are not identical

Differing coordinates: L e (y) int64 10 R e int64 10 ```

The non-dim coordinate e has forgotten that it was associated with y. I'd prefer that this association remained.

Where it gets really interesting is in the following example where the non-dim coordinate moves from one dim to another. I understand the logic here (since the isel() were done in a way that correlates 'y' and 'z'). In my proposal, this would not happen without explicit user intervention -- which may actually be desired here (it's sorta surprising):

``` import numpy as np import xarray as xr

arr = xr.DataArray(np.zeros((2, 2, 5)), dims=['z', 'y', 'x'], coords={'e': ('y', [10, 20])}) print(arr.coords) print()

arr0 = arr.isel(z=0,y=0) arr1 = arr.isel(z=1,y=1)

arr_concat = xr.concat([arr0, arr1], 'z') print(arr_concat.coords) ```

``` Coordinates: e (y) int64 10 20

Coordinates: e (z) int64 10 20 ```

One problem with this -- at least for now -- is that xarray currently doesn't allow coordinates on DataArray objects to have dimensions that don't appear on the DataArray itself.

Ah, then that would be the desire here.

It might also be surprising that this would make squeeze('y') inconsistent with isel(y=0)

The suggestion here is that both of these would behave the same. The MCVE was just for the squeeze case, but I expect that isel and sel would both allow non-dim coords to maintain the reference to their original dim (even if it becomes a non-dim coord itself).

I'm not a huge fan of adding arguments for a case that rarely comes up (I presume). 

One difference in your example is that the 'e' coord is never based on 'y', so I would not want it expanded -- so I'd still like that test to pass.

The case I'm interested in is where the non-dimension coords are based on existing dimension coords that gets squeezed.

So in this example: ``` import numpy as np import xarray as xr

arr1 = xr.DataArray(np.zeros((1,5)), dims=['y', 'x'], coords={'y': [42], 'e': ('y', [10])}) arr1.squeeze() ```

The squeezed array looks like:

<xarray.DataArray (x: 5)> array([0., 0., 0., 0., 0.]) Coordinates: y int64 42 e int64 10 Dimensions without coordinates: x

What I think would be more useful:

<xarray.DataArray (x: 5)> array([0., 0., 0., 0., 0.]) Coordinates: y int64 42 e (y) int64 10 <---- Note the (y) Dimensions without coordinates: x