List of objects to numpy array

A trial case:

In [765]: class Keypoints(object):
    def __init__(self):
        self.pt=[1.,2.]
   .....:         
In [766]: keypoints=[Keypoints() for i in xrange(1000)]
In [767]: cd=np.array([k.pt for k in keypoints])
In [768]: cd
Out[768]: 
array([[ 1.,  2.],
       [ 1.,  2.],
       [ 1.,  2.],
       ..., 
       [ 1.,  2.],
       [ 1.,  2.],
       [ 1.,  2.]])
In [769]: cd_x=cd[:,0]

In timeit tests, the keypoints step takes just as long as the cd calculation, 1ms.

But the 2 simpler iterations

cd_x=np.array([k.pt[0] for k in keypoints])
cd_y=np.array([k.pt[1] for k in keypoints])

takes half the time. I was expecting the single iteration to save time. But in these simple cases, the comprehension itself takes only half of the time, the rest is creating the array.

In [789]: timeit [k.pt[0] for k in keypoints]
10000 loops, best of 3: 136 us per loop
In [790]: timeit np.array([k.pt[0] for k in keypoints])
1000 loops, best of 3: 282 us per loop