issue_comments

Thanks @max-sixty. Contrary to my warning about not doing a PR, I couldn't help myself and dug in a bit. It turns out that string coordinates aren't the problem, it's when the coordinate isn't in sorted order. For example, @chrisroat's original example doesn't error if the coordinate is ["G", "R"] instead of ["R", "G"]. A more concrete WIP test:

```python def test_stack_groupby_unsorted_coord(): data = [[0, 1], [2, 3]] data_flat = [0, 1, 2, 3] dims = ["y", "x"] y_vals = [2, 3]

# "y" coord is in sorted order, and everything works
arr = xr.DataArray(data, dims=dims, coords={"y": y_vals})
actual1 = arr.stack(z=["y", "x"]).groupby("z").first()
midx = pd.MultiIndex.from_product([[2, 3], [0, 1]], names=dims)
expected1 = xr.DataArray(data_flat, dims=["z"], coords={"z": midx})
xr.testing.assert_equal(actual1, expected1)

# Now "y" coord is NOT in sorted order, and the bug appears
arr = xr.DataArray(data, dims=dims, coords={"y": y_vals[::-1]})
actual2 = arr.stack(z=["y", "x"]).groupby("z").first()
midx = pd.MultiIndex.from_product([[3, 2], [0, 1]], names=dims)
expected2 = xr.DataArray(data_flat, dims=["z"], coords={"z": midx})
xr.testing.assert_equal(actual2, expected2)

test_stack_groupby_str_coords() yieldspython

AssertionError Traceback (most recent call last)

[...]

AssertionError: Left and right DataArray objects are not equal

Differing values: L array([2, 3, 0, 1]) R array([0, 1, 2, 3]) Differing coordinates: L * z (z) MultiIndex - z_leve...(z) int64 2 2 3 3 - z_leve...(z) int64 0 1 0 1 R * z (z) MultiIndex - y (z) int64 3 3 2 2 - x (z) int64 0 1 0 1 ```

I'll return to this tomorrow, in the meantime if this triggers any thoughts about the best path forward, that would be much appreciated!

Notice that the string coordinate also gets reordered alphabetically: in @chrisroat 's example above, the coord goes from ['R', 'G'] to ['G', 'R'].

@max-sixty I can't promise a PR anytime soon, but if/when I do manage, where would be a good starting point? Perhaps here where the _level_ names are introduced: https://github.com/pydata/xarray/blob/009aa66620b3437cf0de675013fa7d1ff231963c/xarray/core/dataset.py#L251-L256

Edit: actually maybe here: https://github.com/pydata/xarray/blob/9eec56c833da6dca02c3e6c593586fd201a534a0/xarray/core/variable.py#L2237-L2249

Here's a quick and dirty workaround that works at least for my use case. arr_orig is the original DataArray from which arr_unstacked_bad was generated via a stack/groupby/apply/unstack chain yielding the _level_0 etc. dims, with the stack call having been arr_orig.stack(**{dim_of_stack: dims_stacked}). Likely excessively convoluted and YMMV.

```python def fix_unstacked_dims(arr_unstacked_bad, arr_orig, dim_of_stack, dims_stacked): """Workaround for xarray bug involving stacking str-based coords.

C.f. https://github.com/pydata/xarray/issues/3287

"""
dims_not_stacked = [dim for dim in arr_orig.dims if dim not in dims_stacked]
stacked_dims_after_unstack = [dim for dim in arr_unstacked_bad.dims 
                              if dim not in dims_not_stacked]
dims_mapping = {d1: d2 for d1, d2 in zip(stacked_dims_after_unstack, dims_stacked)}
arr_unstacked_bad = arr_unstacked_bad.rename(dims_mapping)

arr_out = arr_orig.copy(deep=True)
arr_out.values = arr_unstacked_bad.transpose(*arr_orig.dims).values
return arr_out.assign_coords(arr_orig.coords)

```

Same or different problem as https://github.com/pydata/xarray/issues/1483?

I just bumped into this problem as well. xarray 0.15.0. Expected behavior? Bug?