ENH: pivot_table can now accept Grouper
`pivot_table` can accept `Grouper` by `index` and `columns` kw.

```
>>> 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(2013,11,1,13,0), datetime(2013,9,1,13,5),
              datetime(2013,10,1,20,0), datetime(2013,10,2,10,0),
              datetime(2013,11,1,20,0), datetime(2013,10,2,10,0),
              datetime(2013,10,2,12,0), datetime(2013,12,5,14,0)],
    'PayDay' : [datetime(2013,10,4,0,0), datetime(2013,10,15,13,5),
                datetime(2013,9,5,20,0), datetime(2013,11,2,10,0),
                datetime(2013,10,7,20,0), datetime(2013,9,5,10,0),
                datetime(2013,12,30,12,0), datetime(2013,11,20,14,0),]})

>>> pd.pivot_table(df, index=pd.Grouper(freq='M', key='Date'),
                     columns=pd.Grouper(freq='M', key='PayDay'),
                     values='Quantity', aggfunc=np.sum)
PayDay      2013-09-30  2013-10-31  2013-11-30  2013-12-31
Date                                                      
2013-09-30         NaN           3         NaN         NaN
2013-10-31           6         NaN           1           9
2013-11-30         NaN           9         NaN         NaN
2013-12-31         NaN         NaN           3         NaN
```

Looks usefull at first glance!
- Can you in the future first open an issue to propose the functionality? (unless there is already one?) In this case I personally think it is useful functionality, but if we would decide this is out of scope for pandas (or some other reason to not include it), it would be a bit pity for your efforts in the PR.
- Can you also add something to the docs (somewhere in reshaping.rst)
- I suppose this is only usefull for datetime-like columns? Maybe explain this better then?
 @sinhrks ping when you update
 @jreback @jorisvandenbossche Updated the points and rebased. Pls check?
 @jreback docs are OK now for me. But I don't really have a judgement on the implemenation. OK for you?
 thanks @sinhrks 
