Series (DataFrame column) inplace interpolate UnboundLocalError
Hello, I recently stumbled across this:

``` python
df1 = pd.DataFrame({'a':[1.,2.,3.,4.,nan,6,7,8]}, dtype='<f4')
df1.a.interpolate(inplace=True, downcast=None)


---------------------------------------------------------------------------
UnboundLocalError                         Traceback (most recent call last)
<ipython-input-9-bf0994f72664> in <module>()
----> 1 df1.a.interpolate(inplace=True, downcast=None)

C:\Program Files\Python27\lib\site-packages\pandas\core\generic.pyc in interpolate(self, method, axis, limit, inplace, downcast, **kwargs)
   2304         if axis == 1:
   2305             res = res.T
-> 2306         return res
   2307 
   2308     #----------------------------------------------------------------------

UnboundLocalError: local variable 'res' referenced before assignment
```

The problem arises with setting inplace to True regardless of 'downcast'. 

But speaking of which: running interpolate() without any options, I would excpect to keep data types by default! I often chunk through datasets and glue them together with to_hdf. It took me a while to figure out that a float column in one chunk had just zeros in it so interpolate downcasted it to int => to_hdf raised on appending.

Thx in advance
