isel with 0d dask array index fails

[johnomotani]

What happened:
If a 0d dask array is passed as an argument to isel(), an error occurs because dask arrays do not have a .item() method. I came across this when trying to use the result of da.argmax() from a dask-backed array to select from the DataArray.

What you expected to happen:
isel() returns the value at the index contained in the 0d dask array.

Minimal Complete Verifiable Example:

import dask.array as daskarray
import numpy as np
import xarray as xr

a = daskarray.from_array(np.linspace(0., 1.))
da = xr.DataArray(a, dims="x")

x_selector = da.argmax(dim=...)

da_max = da.isel(x_selector)

Anything else we need to know?:

I think the problem is here

xarray/xarray/core/variable.py

Lines 546 to 548 in a198218

	key = tuple(
	k.data.item() if isinstance(k, Variable) and k.ndim == 0 else k for k in key
	)

and k.values.item() or int(k.data) would fix my issue, but I don't know the reason for using .item() in the first place, so I'm not sure if either of these would have some undesirable side-effect.

May be related to #2511, but from the code snippet above, I think this is a specific issue of 0d dask arrays rather than a generic dask-indexing issue like #2511.

I'd like to fix this because it breaks the nice new features of argmin() and argmax() if the DataArray is dask-backed.

Environment:

Output of xr.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.7.6 | packaged by conda-forge | (default, Jun 1 2020, 18:57:50)
[GCC 7.5.0]
python-bits: 64
OS: Linux
OS-release: 5.4.0-42-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: en_GB.UTF-8
libhdf5: 1.10.5
libnetcdf: 4.7.4

xarray: 0.16.0
pandas: 1.0.5
numpy: 1.18.5
scipy: 1.4.1
netCDF4: 1.5.3
pydap: None
h5netcdf: None
h5py: 2.10.0
Nio: None
zarr: None
cftime: 1.2.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: 2.19.0
distributed: 2.21.0
matplotlib: 3.2.2
cartopy: None
seaborn: None
numbagg: None
pint: 0.13
setuptools: 49.2.0.post20200712
pip: 20.1.1
conda: 4.8.3
pytest: 5.4.3
IPython: 7.15.0
sphinx: None