Feature request: add a count_uniques function on dataframes
I find myself writing this utility over and over in my usual work:

``` python
def count_uniques(df, groupby, unique_on):
    """Takes a dataframe, groups it by groupby, and counts the unique 
    values of unique_on."""
    return df.groupby(groupby).agg({unique_on: lambda x: len(x.unique())})
```

This is easiest to explain by example. Suppose I had a dataframe with two columns, both with repeated values, and I want to count the number of unique values in one column rela

``` python
In [1]: from analysis import count_uniques

In [2]: import pandas as pd

In [3]: df = pd.DataFrame(pd.np.array([['CBS', 'Old Spice'],
       ['ABC', 'Budweiser'],
       ['CBS', 'Budweiser'],
       ['CBS', 'Budweiser'],
       ['ESPN', 'Burger King'],
       ['Disney', 'Budweiser'],
       ['ESPN', None]]), columns=["Channel", "Advertiser"])

In [4]: count_uniques(df, "Channel", "Advertiser")
Out[4]: 
         Advertiser
Channel            
ABC               1
CBS               2
Disney            1
ESPN              2

In [5]: count_uniques(df, "Advertiser", "Channel")
Out[5]: 
             Channel
Advertiser          
Budweiser          3
Burger King        1
Old Spice          1
```

I feel like I should be able to call this right off of the dataframe, as `df.count_uniques("Advertiser", "Channel")`. My particular implementation of the function is not optimized whatsoever and I'm pretty confident there are speedier ways to do this calculation.
