BUG: Fix groupby duplicate column

Though having duplicated column names in a dataframe is never a good idea, it may happen, and that shouldn't confuse groupby() with a meaningless message. Currently
```python
>>> obj=pd.DataFrame(columns=["A","B","A", "C"], data=[range(4), range(2,6), range(0, 8, 2)])
>>> obj.groupby("A").mean()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "pandas/core/generic.py", line 2846, in groupby
    sort=sort, group_keys=group_keys, squeeze=squeeze)
  File "pandas/core/groupby.py", line 1173, in groupby
    return klass(obj, by, **kwds)
  File "pandas/core/groupby.py", line 390, in __init__
    level=level, sort=sort)
  File "pandas/core/groupby.py", line 2086, in _get_grouper
    ping = Grouping(group_axis, gpr, obj=obj, name=name, level=level, sort=sort)
  File "pandas/core/groupby.py", line 1925, in __init__
    self.grouper = self.index.map(self.grouper)
  File "pandas/core/index.py", line 1524, in map
    return self._arrmap(self.values, mapper)
  File "generated.pyx", line 2203, in pandas.algos.arrmap_int64 (pandas/algos.c:72274)
TypeError: 'DataFrame' object is not callable
```
This patch fixes that.
```python
>>> obj.groupby("A").mean()
     B  C
A A      
0 2  1  3
  4  2  6
2 4  3  5
```
Thanks.
need to use ``self.assertTrue`` rather than bare asserts