Multiindexing slicing of dates
Should I be able to [slice like](http://pandas.pydata.org/pandas-docs/dev/indexing.html#advanced-indexing-with-hierarchical-index) follows:

```
In [1]: df
Out[1]:
          report_date  item_id  views category
0 2013-06-01 00:00:00        2      3        a
1 2013-06-01 00:00:00        2      2        b
2 2013-06-01 00:00:00        5     16        a
3 2013-06-01 00:00:00        2      4        c
4 2013-06-01 00:00:00        2      5        d

In [2]: pivot = df.pivot_table(values=['views'], rows=['report_date','item_id'], aggfunc='sum')

In [3]: pivot
Out[3]:
                     views
report_date item_id
2013-06-01  2           14
            5           16

In [4]: pivot.ix[('2013-6-01', 3):('2013-06-1', 6)]
Out[4]:
                     views
report_date item_id
2013-06-01  5           16
```

But if I try and slice from outside any of the ranges, I get an exception:

```
In [21]: pivot.ix[('2013-6-01',3):('2013-06-02', 6)]
---------------------------------------------------------------------------
Exception                                 Traceback (most recent call last)
<ipython-input-21-390c2ec15fd2> in <module>()
----> 1 pivot.ix[('2013-6-01',3):('2013-06-02', 6)]

/Users/234BroadWalk/pandas/pandas/core/indexing.pyc in __getitem__(self, key)
     46             return self._getitem_tuple(key)
     47         else:
---> 48             return self._getitem_axis(key, axis=0)
     49
     50     def _get_label(self, label, axis=0):

/Users/234BroadWalk/pandas/pandas/core/indexing.pyc in _getitem_axis(self, key, axis)
    390         labels = self.obj._get_axis(axis)
    391         if isinstance(key, slice):
--> 392             return self._get_slice_axis(key, axis=axis)
    393         elif _is_list_like(key) and not (isinstance(key, tuple) and
    394                                          isinstance(labels, MultiIndex)):

/Users/234BroadWalk/pandas/pandas/core/indexing.pyc in _get_slice_axis(self, slice_obj, axis)
    652         else:
    653             try:
--> 654                 indexer = labels.slice_indexer(start, stop, slice_obj.step)
    655             except Exception:
    656                 if _is_index_slice(slice_obj):

/Users/234BroadWalk/pandas/pandas/core/index.pyc in slice_indexer(self, start, end, step)
   1199         This function assumes that the data is sorted, so use at your own peril
   1200         """
-> 1201         start_slice, end_slice = self.slice_locs(start, end)
   1202
   1203         # return a slice

/Users/234BroadWalk/pandas/pandas/core/index.pyc in slice_locs(self, start, end, strict)
   2276             if not isinstance(end, tuple):
   2277                 end = end,
-> 2278             end_slice = self._partial_tup_index(end, side='right')
   2279
   2280         return start_slice, end_slice

/Users/234BroadWalk/pandas/pandas/core/index.pyc in _partial_tup_index(self, tup, side)
   2293             if lab not in lev:
   2294                 if not lev.is_type_compatible(lib.infer_dtype([lab])):
-> 2295                     raise Exception('Level type mismatch: %s' % lab)
   2296
   2297                 # short circuit

Exception: Level type mismatch: 2013-06-02
```

see [this SO question](http://stackoverflow.com/questions/17035108/filtering-based-on-the-rows-data-after-creating-a-pivot-table-in-python-pandas).
