issues: 342426261

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342426261 MDU6SXNzdWUzNDI0MjYyNjE= 2299 Confusing behaviour with MultiIndex 1882397 closed 0 6815844   1 2018-07-18T17:41:12Z 2018-08-13T22:16:31Z 2018-08-13T22:16:31Z NONE      

Dataset allows assignment of new variables with dimension names that are used in a MultiIndex, even if the lengths do not match the existing coordinate.

```python a = pd.DataFrame({'a': [1, 2], 'b': [3, 4]}).unstack('a') a.index.names = ['dim0', 'dim1'] a.index.name = 'stacked_dim'

b = xr.Dataset(coords={'dim0': ['a', 'b'], 'dim1': [0, 1]}) b = b.stack(dim_stacked=['dim0', 'dim1']) assert(len(b.dim0) == 4)

This should raise an errors because the length is != 4

b['c'] = (('dim0',), [10, 11]) b Instead, it reports `dim0` as a new dimension without coordinates: <xarray.Dataset> Dimensions: (dim0: 2, dim_stacked: 4) Coordinates: * dim_stacked (dim_stacked) MultiIndex - dim0 (dim_stacked) object 'a' 'a' 'b' 'b' - dim1 (dim_stacked) int64 0 1 0 1 Dimensions without coordinates: dim0 Data variables: c (dim0) int64 10 11 ```

Similar cases of coordinates that aren't used do raise an error: python ds = xr.Dataset() ds.coords['a'] = [1, 2, 3] ds = ds.sel(a=1) ds['b'] = (('a',), [1, 2]) ds

Output of xr.show_versions()

``` INSTALLED VERSIONS ------------------ commit: None python: 3.6.5.final.0 python-bits: 64 OS: Darwin OS-release: 17.7.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: en_GB.UTF-8 LANG: None LOCALE: en_GB.UTF-8 xarray: 0.10.7 pandas: 0.23.2 numpy: 1.14.5 scipy: 1.1.0 netCDF4: 1.4.0 h5netcdf: None h5py: 2.8.0 Nio: None zarr: None bottleneck: 1.2.1 cyordereddict: None dask: 0.18.1 distributed: 1.22.0 matplotlib: 2.2.2 cartopy: None seaborn: 0.8.1 setuptools: 39.2.0 pip: 10.0.1 conda: 4.5.8 pytest: 3.6.2 IPython: 6.4.0 sphinx: 1.7.5 ``` 
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