best practice for combining partial string indexing + regular mask?
Consider the simple example as follows

```
import pandas as pd

dataframe = pd.DataFrame({'time' : [pd.to_datetime('2016-06-06'),
                                    pd.to_datetime('2016-06-06'),
                                    pd.to_datetime('2016-06-07'),
                                    pd.to_datetime('2016-06-08')],
                            'value' : [1,2,3,4],
                            'group' : ['A','B','A','B']})

dataframe.set_index('time', inplace = True)

dataframe
Out[13]: 
           group  value
time                   
2016-06-06     A      1
2016-06-06     B      2
2016-06-07     A      3
2016-06-08     B      4
```

Now I want to use all the cool partial string indexing functions, but also be able to filter on other variables. The solution I come up with is the syntax

`dataframe.loc[dataframe['group'] == 'A'].loc['2016-06-06']`

which looks really horrible with the two `loc` combined. Is that the correct pandonic way to do so (while keeping the index?) I have read and read again the documentation but I cannot find the answer.

Thanks!