Performance of Series vs ndarray?
I didn't expect using `pandas.Series` to be almost 4 times slower for some common operations:

``` python
In [161]: a = np.arange(100)

In [162]: b = pandas.Series(a)

In [163]: %timeit abs(a).sum()
100000 loops, best of 3: 7.06 us per loop

In [164]: %timeit abs(b).sum()
10000 loops, best of 3: 27.4 us per loop

In [166]: %timeit abs(a)
1000000 loops, best of 3: 1.43 us per loop

In [167]: %timeit abs(b)
100000 loops, best of 3: 4.33 us per loop
```
