Extra Bin with Pandas Resample in 0.11.0
I've got a pandas data frame defined like this, using pandas 0.11.0:

```
    last_4_weeks_range = pandas.date_range(                                
            start=datetime.datetime(2001, 5, 4), periods=28)               
    last_4_weeks = pandas.DataFrame(                                       
        [{'REST_KEY': 1, 'DLY_TRN_QT': 80, 'DLY_SLS_AMT': 90,              
            'COOP_DLY_TRN_QT': 30, 'COOP_DLY_SLS_AMT': 20}] * 28 +         
        [{'REST_KEY': 2, 'DLY_TRN_QT': 70, 'DLY_SLS_AMT': 10,              
            'COOP_DLY_TRN_QT': 50, 'COOP_DLY_SLS_AMT': 20}] * 28,          
        index=last_4_weeks_range.append(last_4_weeks_range))               
    last_4_weeks.sort(inplace=True)
```

and when I go to resample it:

```
In [265]: last_4_weeks.resample('7D', how='sum')
Out[265]: 
            COOP_DLY_SLS_AMT  COOP_DLY_TRN_QT  DLY_SLS_AMT  DLY_TRN_QT  REST_KEY
2001-05-04               280              560          700        1050        21
2001-05-11               280              560          700        1050        21
2001-05-18               280              560          700        1050        21
2001-05-25               280              560          700        1050        21
2001-06-01                 0                0            0           0         0
```

I end up with an extra empty bin I wouldn't expect to see -- 2001-06-01. I wouldn't expect that bin to be there, as my 28 days are evenly divisible into the 7 day resample I'm performing. I've tried messing around with the closed kwarg, but I can't escape that extra bin.  This seems like a bug, and it messes up my mean calculations when I try to do 

```
In [266]: last_4_weeks.groupby('REST_KEY').resample('7D', how='sum').mean(level=0)
Out[266]: 
          COOP_DLY_SLS_AMT  COOP_DLY_TRN_QT  DLY_SLS_AMT  DLY_TRN_QT  REST_KEY
REST_KEY                                                                      
1                      112              168          504         448       5.6
2                      112              280           56         392      11.2
```

as the numbers are being divided by 5 rather than 4.  (I also wouldn't expect REST_KEY to show up in the aggregation columns as it's part of the groupby, but that's really a smaller problem.)
