Stacking with MultiIndex column DataFrame throws an error
Stacking this particular MultiIndex column DataFrame throws an error:

```
import pandas as pd
from StringIO import StringIO

csv = StringIO("""ID,NAME,DATE,VAR1
1,a,03-JAN-2013,69
1,a,04-JAN-2013,77
1,a,05-JAN-2013,75
2,b,03-JAN-2013,69
2,b,04-JAN-2013,75
2,b,05-JAN-2013,72""")

df = pd.read_csv(csv, index_col=['DATE', 'ID'], parse_dates=['DATE'])
df.columns.name = 'Params'

In [11]: df.unstack('ID').resample('W-THU')
Out[11]: 
Params      VAR1      
ID             1     2
DATE                  
2013-01-03    69  69.0
2013-01-10    76  73.5
```

It looks like you ought to be able to stack this over `'ID'`, but it throws an error:

```
In [12]: df.unstack('ID').resample('W-THU').stack('ID')
---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-12-e61b475b7bed> in <module>()
----> 1 df.unstack('ID').resample('W-THU').stack('ID')

/Library/Python/2.7/site-packages/pandas/core/frame.pyc in stack(self, level, dropna)
   3950             return result
   3951         else:
-> 3952             return stack(self, level, dropna=dropna)
   3953 
   3954     def unstack(self, level=-1):

/Library/Python/2.7/site-packages/pandas/core/reshape.pyc in stack(frame, level, dropna)
    443 
    444     if isinstance(frame.columns, MultiIndex):
--> 445         return _stack_multi_columns(frame, level=level, dropna=True)
    446     elif isinstance(frame.index, MultiIndex):
    447         new_levels = list(frame.index.levels)

/Library/Python/2.7/site-packages/pandas/core/reshape.pyc in _stack_multi_columns(frame, level, dropna)
    504         # can make more efficient?
    505         if loc.stop - loc.start != levsize:
--> 506             chunk = this.ix[:, this.columns[loc]]
    507             chunk.columns = level_vals.take(chunk.columns.labels[-1])
    508             value_slice = chunk.reindex(columns=level_vals).values

/Library/Python/2.7/site-packages/pandas/core/indexing.pyc in __getitem__(self, key)
     32                 pass
     33 
---> 34             return self._getitem_tuple(key)
     35         else:
     36             return self._getitem_axis(key, axis=0)

/Library/Python/2.7/site-packages/pandas/core/indexing.pyc in _getitem_tuple(self, tup)
    222                 continue
    223 
--> 224             retval = retval.ix._getitem_axis(key, axis=i)
    225 
    226         return retval

/Library/Python/2.7/site-packages/pandas/core/indexing.pyc in _getitem_axis(self, key, axis)
    340                 raise ValueError('Cannot index with multidimensional key')
    341 
--> 342             return self._getitem_iterable(key, axis=axis)
    343         elif axis == 0:
    344             is_int_index = _is_integer_index(labels)

/Library/Python/2.7/site-packages/pandas/core/indexing.pyc in _getitem_iterable(self, key, axis)
    406             # this is not the most robust, but...
    407             if (isinstance(labels, MultiIndex) and
--> 408                     not isinstance(keyarr[0], tuple)):
    409                 level = 0
    410             else:

/Library/Python/2.7/site-packages/pandas/core/index.pyc in __getitem__(self, key)
   1745             retval = []
   1746             for lev, lab in zip(self.levels, self.labels):
-> 1747                 if lab[key] == -1:
   1748                     retval.append(np.nan)
   1749                 else:

IndexError: index out of bounds
```

_Taken from this [SO question](http://stackoverflow.com/questions/15617496/resampling-a-multi-index-dataframe)._
