id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
490037439,MDU6SXNzdWU0OTAwMzc0Mzk=,3282,Silent value assignment failure in open_zarr Dataset due to hidden mode='r',6475152,open,0,,,0,2019-09-05T22:23:46Z,2020-03-29T10:33:20Z,,NONE,,,,"Hello Xarray devs,

Thanks for your work on this fantastic package.  I'm a new user, and the subtleties of different data stores are unfamiliar to me.  I got tripped up by the fact that Zarr stores are (silently) read-only, and I think it would be helpful if this were more prominent in the docstring or [zarr section](https://xarray.pydata.org/en/stable/io.html#zarr) of the docs.

When I try to assign values to parts of a local Zarr-backed Dataset, I get a silent failure:

```python
In [142]: ds = xr.open_zarr('tmp.zarr', chunks=None)

In [143]: selector = dict(time='2014-06-06T01:00:00', azimuth=0, frequency=0.0)

In [144]: ds['counts'].loc[selector].values
Out[144]: array(4294967295, dtype=uint32)

# try to assign a value here, like the example in the docs: 
# In [55]: ds['empty'].loc[dict(lon=260, lat=30)] = 100
In [145]: ds['counts'].loc[selector].values = 0

# just get the same value back
In [146]: ds['counts'].loc[selector].values
Out[146]: array(4294967295, dtype=uint32)

```

The answer seems to be buried in the `open_zarr` source code:

```python
    ...
    # Zarr supports a wide range of access modes, but for now xarray either
    # reads or writes from a store, never both. For open_zarr, we only read
    mode = 'r'
    zarr_store = ZarrStore.open_group(store, mode=mode,
                                      synchronizer=synchronizer,
                                      group=group, consolidated=consolidated)
    ...
```

#### Expected Output

Assignment that follows the examples [in the documentation](https://xarray.pydata.org/en/stable/indexing.html#assigning-values-with-indexing).

1.  I think that mentioning `mode='r'` in the `open_zarr` docstring would be the most helpful.
2.  A description of this and the reasoning behind why zarr datasets are read-only would be helpful in the [zarr section](https://xarray.pydata.org/en/stable/io.html#zarr) of the docs.
3.  Optionally, a note in the [indexing and assignment](https://xarray.pydata.org/en/stable/indexing.html#assigning-values-with-indexing) that not all store backends support assignment would also be helpful.

I'm happy to make a PR on 1 & 3, but I'm not familiar with the reasoning behind why stores are never mixed-mode.

Thanks again!


#### Output of ``xr.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.7.3 | packaged by conda-forge | (default, Mar 27 2019, 15:43:19)
[Clang 4.0.1 (tags/RELEASE_401/final)]
python-bits: 64
OS: Darwin
OS-release: 16.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: None
libnetcdf: None

xarray: 0.12.3
pandas: 0.24.2
numpy: 1.16.3
scipy: 1.3.0
netCDF4: None
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: 2.3.1
cftime: None
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: 1.2.2
distributed: 1.28.1
matplotlib: 3.1.0
cartopy: None
seaborn: None
numbagg: None
setuptools: 41.0.1
pip: 19.1
conda: None
pytest: None
IPython: 7.5.0
sphinx: None
</details>
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