BUG: groupby with datetime columns
```
df=pd.DataFrame(
    [[75,1,'2013-07-15',],
     [44,3,'2014-04-02',],
     [15,2,'2013-05-23',],
     [93,1,'2014-04-04',]] ,columns=['Sales','Store','Date'])

df.Date=pd.to_datetime(df.Date)
gb=df.groupby('Store')
gb.apply(lambda df: pd.Series([1,2,3]))
```

**KeyError: "['Date'] not in index"**
If I comment out `to_datetime(df.Date)`  to use string type for date, then it works fine.

---
### more details follows:

INSTALLED VERSIONS
python: 3.4.3.final.0
pandas: 0.17.0

---

KeyError                                  Traceback (most recent call last)
<ipython-input-109-45118450dd9c> in <module>()
      8 df.Date=pd.to_datetime(df.Date)
      9 gb=df.groupby('Store')
---> 10 gb.apply(lambda df: pd.Series([1,2,3]))

......I omit the intermediate traces for succinct.

/Users/apple/miniconda3/lib/python3.4/site-packages/pandas/core/indexing.py in _convert_to_indexer(self, obj, axis, is_setter)
   1119                 mask = check == -1
   1120                 if mask.any():
-> 1121                     raise KeyError('%s not in index' % objarr[mask])
   1122 
   1123                 return _values_from_object(indexer)

KeyError: "['Date'] not in index"
