html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/1949#issuecomment-369315468,https://api.github.com/repos/pydata/xarray/issues/1949,369315468,MDEyOklzc3VlQ29tbWVudDM2OTMxNTQ2OA==,17178478,2018-02-28T17:27:10Z,2018-02-28T17:27:38Z,NONE,"The drop technique seems reasonable, if a bit long-winded for the programmatic case (loop over all dimensions, find any that are empty -> loop over all variables, drop any that contain those empty dimensions).
As an addition, if the empty dimension also has an associated empty coordinate then it requires an extra step to get rid of it:
``` python
In [21]: test_dataset = xr.Dataset(dict(
...: empty_array=xr.DataArray([], dims='a', coords={'a':[]}),
...: populated_array=xr.DataArray([1], {'b':['1']}, 'b')
...: ))
In [22]: test_dataset
Out[22]:
Dimensions: (a: 0, b: 1)
Coordinates:
* a (a) float64
* b (b)
Dimensions: (a: 0, b: 1)
Coordinates:
* a (a) float64
* b (b)
Dimensions: (b: 1)
Coordinates:
* b (b)