0.12.0 to_hdf() error on a multi-index DataFrame
I have the following DataFrame:

```
portfolio_data
```

> <class 'pandas.core.frame.DataFrame'>
> MultiIndex: 45846 entries, (2013-06-28, 000312) to (2013-07-01, Y8565N10)
> Data columns (total 12 columns):
> market_cap          45843  non-null values
> alpha               45778  non-null values
> gics_code           45843  non-null values
> investable          45846  non-null values
> issuer_country      45789  non-null values
> msci_country        32667  non-null values
> return_daily        44373  non-null values
> universe            45846  non-null values
> weight_benchmark    45846  non-null values
> weight_portfolio    45846  non-null values
> weight_active       45846  non-null values
> country             45846  non-null values
> dtypes: bool(2), float64(7), object(3)

```
portfolio_data.index[0]
```

> (datetime.date(2013, 6, 28), '000312')

I get the following error while

```
portfolio_data.to_hdf(OUTPUT_FILE_NAME_PORTFOLIO, OUTPUT_NAME_PORTFOLIO, mode='w', table=True)
```

> ---
> 
> TypeError                                 Traceback (most recent call last)
> C:\Python27\lib\site-packages\IPython\utils\py3compat.pyc in execfile(fname, glob, loc)
>     169             else:
>     170                 filename = fname
> --> 171             exec compile(scripttext, filename, 'exec') in glob, loc
>     172     else:
>     173         def execfile(fname, *where):
> 
> M:\Projects\PortfolioAnalytics\Code\Python\attribution\TopContributors.py in <module>()
>     487     if logger.isEnabledFor(logging.DEBUG):
>     488         logger.debug('Storing data for the portfolio into {} ...'.format(OUTPUT_FILE_NAME_PORTFOLIO))
> --> 489     portfolio_data.to_hdf(OUTPUT_FILE_NAME_PORTFOLIO, OUTPUT_NAME_PORTFOLIO, mode='w', table=True)
>     490 
>     491     logger.info('Finished {}.'.format(MODULE_NAME))
> 
> C:\Python27\lib\site-packages\pandas\core\generic.pyc in to_hdf(self, path_or_buf, key, *_kwargs)
>     519         """ activate the HDFStore """
>     520         from pandas.io import pytables
> --> 521         return pytables.to_hdf(path_or_buf, key, self, *_kwargs)
>     522 
>     523     def to_clipboard(self):
> 
> C:\Python27\lib\site-packages\pandas\io\pytables.pyc in to_hdf(path_or_buf, key, value, mode, complevel, complib, append, **kwargs)
>     192     if isinstance(path_or_buf, basestring):
>     193         with get_store(path_or_buf, mode=mode, complevel=complevel, complib=complib) as store:
> --> 194             f(store)
>     195     else:
>     196         f(path_or_buf)
> 
> C:\Python27\lib\site-packages\pandas\io\pytables.pyc in <lambda>(store)
>     188         f = lambda store: store.append(key, value, *_kwargs)
>     189     else:
> --> 190         f = lambda store: store.put(key, value, *_kwargs)
>     191 
>     192     if isinstance(path_or_buf, basestring):
> 
> C:\Python27\lib\site-packages\pandas\io\pytables.pyc in put(self, key, value, table, append, *_kwargs)
>     583         encoding : default None, provide an encoding for strings
>     584         """
> --> 585         self._write_to_group(key, value, table=table, append=append, *_kwargs)
>     586 
>     587     def remove(self, key, where=None, start=None, stop=None):
> 
> C:\Python27\lib\site-packages\pandas\io\pytables.pyc in _write_to_group(self, key, value, index, table, append, complib, encoding, *_kwargs)
>     921             raise ValueError('Compression not supported on non-table')
>     922 
> --> 923         s.write(obj = value, append=append, complib=complib, *_kwargs)
>     924         if s.is_table and index:
>     925             s.create_index(columns = index)
> 
> C:\Python27\lib\site-packages\pandas\io\pytables.pyc in write(self, obj, data_columns, *_kwargs)
>    3251                 data_columns.insert(0, n)
>    3252         self.levels = obj.index.names
> -> 3253         return super(AppendableMultiFrameTable, self).write(obj=obj.reset_index(), data_columns=data_columns, *_kwargs)
>    3254 
>    3255     def read(self, columns=None, **kwargs):
> 
> C:\Python27\lib\site-packages\pandas\io\pytables.pyc in write(self, obj, axes, append, complib, complevel, fletcher32, min_itemsize, chunksize, expectedrows, *_kwargs)
>    2983         self.create_axes(axes=axes, obj=obj, validate=append,
>    2984                          min_itemsize=min_itemsize,
> -> 2985                          *_kwargs)
>    2986 
>    2987         if not self.is_exists:
> 
> C:\Python27\lib\site-packages\pandas\io\pytables.pyc in create_axes(self, axes, obj, validate, nan_rep, data_columns, min_itemsize, **kwargs)
>    2715                 self.values_axes.append(col)
>    2716             except (NotImplementedError, ValueError, TypeError), e:
> -> 2717                 raise e
>    2718             except (Exception), detail:
>    2719                 raise Exception("cannot find the correct atom type -> [dtype->%s,items->%s] %s" % (b.dtype.name, b.items, str(detail)))
> 
> TypeError: [date] is not implemented as a table column
