test groupby.indices for multiple groupby and mix of types
Creates tests for GH26859

- [X] closes #26859
- [X] tests added / passed
- [X] passes `black pandas`
- [X] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry

Does this warrant an entry in whatsnew?
> Thanks @alexifm for the PR!
> 
> Some comments. More generally the second function is a lot to take in, wondering if it can be simplified somehow

yea, probably can just run the groupby on all the columns and remove the parametrization.  I'd have to check again if there was anything special about 1 vs multiple fields in a groupby.  Or perhaps split into two simpler tests? > yea, probably can just run the groupby on all the columns and remove the parametrization. I'd have to check again if there was anything special about 1 vs multiple fields in a groupby. 

Unless they're direct replicas of each other we likely want to test both

>Or perhaps split into two simpler tests?

i'd say split into two tests @arw2019 
> Unless they're direct replicas of each other we likely want to test both

The difference is whether the keys are tuples or not:
```
>>> df.groupby(['a', 'b']).indices
{('a', Timestamp('2018-01-01 00:00:00')): array([0]),
 ('b', Timestamp('2018-02-01 00:00:00')): array([1]),
 ('c', Timestamp('2018-03-01 00:00:00')): array([2])}

>>> df.groupby(['a']).indices
{'a': array([0]), 'b': array([1]), 'c': array([2])}
```
So nearly identical behavior but subtly different.  I split the tests but can bring them back together. @alexifm can you merge master and update to comments This pull request is stale because it has been open for thirty days with no activity. Please update or respond to this comment if you're still interested in working on this. closing as stale. if you want to continue, pls ping and can re-open.