added support for selecting multiple nth values
I'm not 100% sure this is the best way to implement this, but I think it'd be nice for GroupBy.nth() to support selecting multiple values. For instance if we have

```
df = DataFrame(1, index=pd.date_range(start='1/1/2013', end='6/30/2014', freq='B'), columns=['a', 'b'])
```

and currently we can easily get the nth entry for each month by:

```
df.groupby((df.index.year, df.index.month)).nth(0)
```

however we can't easily get, for instance, the first 5 entries for each group without having a more complex loop in the user code. If nth() accepts a list of integers we would be able to simply do

```
df.groupby((df.index.year, df.index.month)).nth(range(5))
```

This PR makes the above work when there's no dropna. I can't quite figure out the section where dropna is handled, and therefore I'm currently requiring that no dropna be passed when n is a list of values. I'm happy to improve this and also enhance the tests. Please let me know your feedback. Thanks. 

FYI this is prob useful

but u know you can do .head(5) for first 5 entries
 Ah indeed ... head() and tail() can cover some of these cases. This is probably still useful for the general case though. 
 can you add an example of this to: http://pandas-docs.github.io/pandas-docs-travis/groupby.html#taking-the-nth-row-of-each-group (maybe right after this). Also ok with forming a sub-sectin of the the 'nth' usages
 Good idea - I added an example to groupby.html, also added a few more unit tests. Thanks. 
 @mortada thanks for this. I forgot to have you put in a release note.

can you do a quick PR with a release note for this (use the PR number), in the enhancements section. and add the example as well. thanks
 sure happy to do that
