API: Expose groupby API for fast custom calculations
Currently code such as:
`df.groupby(['col1', 'col2']).mean()`

Is heavily optimized as it has access to the internal blocks and can use a cython based function to execute. If a custom calculation is required (for example root-mean-squared-error) then the only current option is to use:
`df.groupby(['col1', 'col2']).apply(my_func)`

It would be good to be able to supply a cythonized or numba jit compiled function which is given the numpy arrays for each group or even all the blocks so the looping can all happen in the compiled function.

The other current alternative is to take the values of the dataframe and implement your own grouping but I feel pandas already has this bit covered well.