issue_comments: 369294450

If you're OK creating a new Dataset, it works to remove any variables using a dimension, e.g., ``` In [25]: test_dataset = xr.Dataset(dict( ...: empty_array=xr.DataArray([], dims='a'), ...: populated_array=xr.DataArray([1], {'b':['1']}, 'b') ...: )) ...:

In [26]: test_dataset Out[26]: <xarray.Dataset> Dimensions: (a: 0, b: 1) Coordinates: * b (b) <U1 '1' Dimensions without coordinates: a Data variables: empty_array (a) float64 populated_array (b) int64 1

In [27]: test_dataset.drop('empty_array') Out[27]: <xarray.Dataset> Dimensions: (b: 1) Coordinates: * b (b) <U1 '1' Data variables: populated_array (b) int64 1 ```

You're right that this doesn't work to remove dimensions from existing datasets (e.g., with del). But this isn't specific to dimensions of length 0 -- you can't delete any dimensions. At best, you can delete a coordinate variable corresponding to a dimension: ``` In [46]: test_dataset Out[46]: <xarray.Dataset> Dimensions: (a: 0, b: 1) Coordinates: * b (b) <U1 '1' Dimensions without coordinates: a Data variables: empty_array (a) float64 populated_array (b) int64 1

In [47]: del test_dataset['b']

In [48]: test_dataset Out[48]: <xarray.Dataset> Dimensions: (a: 0, b: 1) Dimensions without coordinates: a, b Data variables: empty_array (a) float64 populated_array (b) int64 1

In [49]: del test_dataset['populated_array']

In [50]: test_dataset Out[50]: <xarray.Dataset> Dimensions: (a: 0, b: 1) Dimensions without coordinates: a, b Data variables: empty_array (a) float64 ```

Is there a way to remove a dimension (and possibly then all data variables which depend on it)?

This used to be possible in the xarray data model prior to v0.9.0. del should to delete a dimension corresponding to a coordinate variable and all other associated variables.

When we made coordinates optional, I updated del to only delete data/coordinate variables. This made sense, but meant there is now no way to get rid of dimensions.

I'd like to suggest two possible fixes: 1. Update del dataset[key] to remove all "orphaned" dimensions that don't correspond to a dimension on any variable. This would enforce the invariant "all dimensions on a dataset correspond to a dimension on one of its variables." If there are other places where we violate this invariant those should be fixed, too. 2. Update Dataset.dims to allow deleting elements. Deleting a dimension on a dataset means all associated variables are also deleted.