How to rearrange array based upon index array

You can simply use your "index" list directly, as, well, an index array:

>>> arr = np.array([10, 20, 30, 40, 50])
>>> idx = [1, 0, 3, 4, 2]
>>> arr[idx]
array([20, 10, 40, 50, 30])

It tends to be much faster if idx is already an ndarray and not a list, even though it'll work either way:

>>> %timeit arr[idx]
100000 loops, best of 3: 2.11 µs per loop
>>> ai = np.array(idx)
>>> %timeit arr[ai]
1000000 loops, best of 3: 296 ns per loop

for those whose index is 2d array, you can use map function. Here is an example:

a = np.random.randn(3, 3)
print(a)
print(np.argsort(a))

print(np.array(list(map(lambda x, y: y[x], np.argsort(a), a))))

the output is

[[-1.42167035  0.62520498  2.02054623]
 [-0.17966393 -0.01561566  0.24480554]
 [ 1.10568543  0.00298402 -0.71397599]]
[[0 1 2]
 [0 1 2]
 [2 1 0]]
[[-1.42167035  0.62520498  2.02054623]
 [-0.17966393 -0.01561566  0.24480554]
 [-0.71397599  0.00298402  1.10568543]]