Are numpy arrays really faster than python lists? Yes they are

numpy_array.py

import numpy as np
import timeit

std_arr = list(range(0,10000))
np_arr = np.array(std_arr)
#np_arr_vec = np.vectorize(lambda n: (n * 31) / 31)

def operate_on_std_array():
    for index,elem in enumerate(std_arr):
        std_arr[index] = elem * 31
        std_arr[index] = elem / 31
    return std_arr

def operate_on_np_arr():
    global np_arr
    np_arr *= 31
    np_arr //= 31 # integer division, not double
    return np_arr


import time
def test_time(f):
    count = 100
    start = time.time()
    for i in range(count):
        f()
    dur = time.time() - start
    return dur

print('standard operation', test_time(operate_on_std_array))
print('numpy operation', test_time(operate_on_np_arr))