Aggregation with 'any' always returns True
Using 'any' as aggregation function (and 'all' as well) to find groups where at least one value is True seems like an intuitive way, but it doesn't work right now:

```
In [12]: DataFrame({'a': [0, 1], 'b': [True, False]}).groupby('a').agg(any)
Out[12]: 
      b
a      
0  True
1  True
```

This is the case where this issue came up: I have a dataset with seasons (continuous integers) and a boolean column (e.g. called 'success'). Now I want to select all data from seasons that have at least one True in the boolean column. Right now the best way to do it that I can think of would be:
1. Select rows where success == True.
2. Group them by season and aggregate with a function returning True regardless of the input.
3. Join the result back into the dataset on season.
4. Perform fillna(False).

Being able to just apply 'any' would cut the process down to two steps. Also, if there is another, better way to do this operation, I’d be grateful to hear about it.
