EHN: Add filter methods to SeriesGroupBy, DataFrameGroupBy GH919

closes #919

I have been using Wes' workaround (see #919) for filtering groups. Finally, for brevity's sake, I wrote a real filter method. In the one simple case I checked, it performs faster than the workaround.

On a small (~10) Series:

    In [7]: %timeit grouped.filter(lambda x: x.mean() > 10)  # my method
    1000 loops, best of 3: 346 us per loop

    In [8]: %timeit grouped.obj[grouped.transform(lambda x: x.mean() > 10)]  # workaround
    1000 loops, best of 3: 462 us per loop

On a large (1000000) Series:

    In [18]: %timeit grouped.filter(lambda x: x.mean() > 0) # my method
    1 loops, best of 3: 213 ms per loop

    In [19]: %timeit grouped.obj[grouped.transform(lambda x: x.mean() > 0)]
    1 loops, best of 3: 696 ms per loop

This PR only handles Series, and I included one simple test. If I am on the right track, I'll write one for DataFrames also and write additional tests. If this is a job for Cython, I'm out of my depth, but I think numpy is sufficient. Does this look OK?