TST: add test to ensure that df.groupby() returns the missing categories when grouping on 2 pd.Categoricals
- [x] closes #23865
- [x] closes #27075 
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`

1) _New Tests Addeded_
#23865 #27075 both reported that when df.groupby was called and `by` was set to more than one pd.Categorical column, that any missing categories were not returned, even when observed=False. This issue was fixed in #29690. This Pull Request adds tests to make sure that this correct behaviour is enforced by tests. 

2) _New Bug Found_
Testing did reveal one further issue: DataFrameGroupBy.count() returns NaN for missing Categories, when it should return a count of 0.  SeriesGroupBy.count() does return 0, which is the expected behaviour. I have raised an issue for this bug (#35028 ) and marked the test with an xfail. When the bug is fixed, the xfail will cause the tests to fail, and the xfail can be removed. 

3) _Existing Test Changed as it had the Wrong Expected Result_
A similar issue was reported for .sum() in #31422: missing categories return a sum of NaN when they should return a sum of 0. There was a mistake on the existing test for SeriesGroupBy.sum(), as it said the expected output was NaN (see below) when it should have been 0.
https://github.com/pandas-dev/pandas/blob/0159cba6eb14983ab7eaf38ff138c3c397a6fe3b/pandas/tests/groupby/test_categorical.py#L1315

I have changed this so that the expected output is 0 (this is inline with the comment here: https://github.com/pandas-dev/pandas/issues/31422#issuecomment-579826193 ) and marked the tests for .sum() with xfail. When the bug is addressed, the xfail will cause the tests to fail, and the xfails can be removed. 