Why does random.shuffle fail on numpy lists?

I have an array of row vectors, upon which I run random.shuffle:

#!/usr/bin/env python                                                                                                                                                                                                                                                

import random
import numpy as np

zzz = np.array([[0.1, 0.2, 0.3, 0.4, 0.5],
                [0.6, 0.7, 0.8, 0.9, 1. ]])

iterations = 100000
f = 0
for _ in range(iterations):
    random.shuffle(zzz)
    if np.array_equal(zzz[0], zzz[1]):
        print(zzz)
        f += 1

print(float(f)/float(iterations))

Between 99.6 and 100% of the time, using random.shuffle on zzz returns a list with the same elements in it, e.g.:

$ ./test.py
...
[[ 0.1  0.2  0.3  0.4  0.5]
 [ 0.1  0.2  0.3  0.4  0.5]]
0.996

Using numpy.random.shuffle appears to pass this test and shuffle row vectors correctly. I'm curious to know why random.shuffle fails.