API/ENH: idxmax groupby API
from [SO](http://stackoverflow.com/questions/26701849/pandas-groupby-and-finding-maximum-in-groups-returning-value-and-count)

Thinking that this is a nice general idiom that might deserve a function: 

`df.loc[df.groupby(level='host').idxmax()['no']]`

maybe:
a) `df.groupby(level='host').idxmax(loc='no')` ? (e.g. have the idxmin/idxmin) functions take a 'loc' argument. or is this bending the api a big much?
b) `df.groupby(level='host').loc('no').idxmax()`
c) `df.groupby(level='hist').loc[lambda x: x.idxmax()['no']]`
d) `df.groupby(level='hist').loc('no','idxmax')`

```
df_logfile = pd.DataFrame({ 
    'host' : ['this.com', 'this.com', 'this.com', 'that.com', 'other.net', 
              'other.net', 'other.net'],
    'service' : ['mail', 'mail', 'web', 'mail', 'mail', 'web', 'web' ] })

df = df_logfile.groupby(['host','service'])['service'].agg({'no':'count'})
mask = df.groupby(level=0).agg('idxmax')
df_count = df.loc[mask['no']]
df_count = df_count.reset_index()

# yields
        host service  no
0  other.net     web   2
1   that.com    mail   1
2   this.com    mail   2
```
