BUG: TimeGrouper outputs different result by column order

closes #6764

`TimeGrouper` may output incorrect results depending on the target column order. The problem seems to be caused by 2 parts.
- `TimeGrouper._get_time_bins` and related methods expects sorted values input.
- `BinGrouper.get_iterator` expects sorted data input. 

```
>>> df = pd.DataFrame({'Branch' : 'A A A A A A A B'.split(),
                   'Buyer': 'Carl Mark Carl Carl Joe Joe Joe Carl'.split(),
                   'Quantity': [1,3,5,1,8,1,9,3],
                   'Date' : [
                    datetime(2013,1,1,13,0), datetime(2013,1,1,13,5),
                    datetime(2013,10,1,20,0), datetime(2013,10,2,10,0),
                    datetime(2013,10,1,20,0), datetime(2013,10,2,10,0),
                    datetime(2013,12,2,12,0), datetime(2013,12,2,14,0),]})

# correct
>>> df.groupby([pd.Grouper(freq='1M',key='Date'),'Buyer']).sum()
                  Quantity
Date       Buyer          
2013-01-31 Carl          1
           Mark          3
2013-10-31 Carl          6
           Joe           9
2013-12-31 Carl          3
           Joe           9

[6 rows x 1 columns]

>>> df_sorted = df.sort('Quantity')          # change "Date" column unsorted
# incorrect
>>> df_sorted.groupby([pd.Grouper(freq='1M',key='Date'),'Buyer']).sum()
                  Quantity
Date       Buyer          
2013-01-31 Carl          1
2013-10-31 Carl          1
           Joe           1
           Mark          3
2013-12-31 Carl          8
           Joe          17

[6 rows x 1 columns]

>>> df_sorted.groupby([pd.Grouper(freq='1M',key='Date', sort=True),'Buyer']).sum()
# same incorrect result
```

```
# correct
>>> df.groupby([pd.Grouper(freq='6M',key='Date'),'Buyer']).sum()
                  Quantity
Date       Buyer          
2013-01-31 Carl          1
           Mark          3
2014-01-31 Carl          9
           Joe          18

[4 rows x 1 columns]

# incorrect
>>> df_sorted.groupby([pd.Grouper(freq='6M',key='Date'),'Buyer']).sum()
                  Quantity
Date       Buyer          
2013-01-31 Carl          1
2014-01-31 Carl          9
           Joe          18
           Mark          3

[4 rows x 1 columns]
```