issue_comments

This one is failing on CI / ubuntu-latest py3.9 bare-minimum, is it taking a path without flox installed perhaps?

``` __ TestDataArrayGroupBy.testgroupby_fastpath_for_monotonic ___ [gw2] linux -- Python 3.9.16 /home/runner/micromamba-root/envs/xarray-tests/bin/python

self = <xarray.tests.test_groupby.TestDataArrayGroupBy object at 0x7fbd9f461c10>

def test_groupby_fastpath_for_monotonic(self):
    # Fixes https://github.com/pydata/xarray/issues/6220
    index = [1, 2, 3, 4, 7, 9, 10]
    array = DataArray(np.arange(len(index)), [("idx", index)])
    array_rev = array.copy().assign_coords({"idx": index[::-1]})
    fwd = array.groupby("idx", squeeze=False)
    rev = array_rev.groupby("idx", squeeze=False)

    for gb in [fwd, rev]:
        assert all([isinstance(elem, slice) for elem in gb._group_indices])

    assert_identical(fwd.sum(), array)

  assert_identical(rev.sum(), array_rev.sortby("idx"))

E AssertionError: Left and right DataArray objects are not identical E
E Differing values: E L E array([0, 1, 2, 3, 4, 5, 6]) E R E array([6, 5, 4, 3, 2, 1, 0]) E Differing coordinates: E L * idx (idx) int64 10 9 7 4 3 2 1 E R * idx (idx) int64 1 2 3 4 7 9 10 ```

TO check the fastpath we'd want to both get the right answer and make sure that _group_indices is filled with slices: https://github.com/pydata/xarray/blob/4f3128bb7266d1a6fdeaf20718ea3f8286fe041e/xarray/core/groupby.py#L422-L430

Thanks @JoelJaeschke!

The intent was to change the code in _unique_and_monotonic here

A good test would be make sure you get the same answer when grouping a DataArray of ones by a monotonically increasing variable (e.g. [1, 1, 2, 2, 3, 3, 3]) and the decreasing variable( e.g. [3, 3, 3, 2, 2, 1, 1])