issues: 977149831

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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
977149831 MDU6SXNzdWU5NzcxNDk4MzE= 5732 Coordinates implicitly created when passing a DataArray as coord to Dataset constructor 4160723 open 0     3 2021-08-23T15:20:37Z 2021-08-24T14:18:09Z   MEMBER      

I stumbled on this while working on #5692. Is this intended behavior or unwanted side effect?

What happened:

Create a new Dataset by passing a DataArray object as coordinate also add the DataArray coordinates to the dataset:

```python

foo = xr.DataArray([1.0, 2.0, 3.0], coords={"x": [0, 1, 2]}, dims="x") ds = xr.Dataset(coords={"foo": foo}) ds <xarray.Dataset> Dimensions: (x: 3) Coordinates: * x (x) int64 0 1 2 foo (x) float64 1.0 2.0 3.0 Data variables: empty ```

What you expected to happen:

The behavior above seems a bit counter-intuitive to me. I would rather expect no additional coordinates auto-magically added to the dataset, i.e. only one foo coordinate in this example:

```python

ds <xarray.Dataset> Dimensions: (x: 3) Coordinates: foo (x) float64 1.0 2.0 3.0 Data variables: empty ```

Environment:

Output of <tt>xr.show_versions()</tt> INSTALLED VERSIONS ------------------ commit: None python: 3.8.6 | packaged by conda-forge | (default, Nov 27 2020, 19:17:44) [Clang 11.0.0 ] python-bits: 64 OS: Darwin OS-release: 20.3.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: None LOCALE: (None, 'UTF-8') libhdf5: 1.10.6 libnetcdf: 4.7.4 xarray: 0.19.0 pandas: 1.1.5 numpy: 1.21.1 scipy: 1.7.0 netCDF4: 1.5.5.1 pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.3.1 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: 2021.07.2 distributed: 2021.07.2 matplotlib: 3.3.3 cartopy: 0.19.0.post1 seaborn: None numbagg: None pint: None setuptools: 49.6.0.post20201009 pip: 20.3.1 conda: None pytest: 6.1.2 IPython: 7.25.0 sphinx: 3.3.1 
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