python numpy || numpy || why numpy || series

Published: 10 December 2018
on channel: CSE TECH'S

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import time
import numpy as np

size_of_vec = 1000

def pure_python_version():
t1 = time.time()
X = range(size_of_vec)
Y = range(size_of_vec)
Z = [X[i] + Y[i] for i in range(len(X)) ]
return time.time() - t1

def numpy_version():
t1 = time.time()
X = np.arange(size_of_vec)
Y = np.arange(size_of_vec)
Z = X + Y
return time.time() - t1

t1 = pure_python_version()
t2 = numpy_version()
print(t1, t2)
print("Numpy is in this example " + str(t1/t2) + " faster!")
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import numpy as np
import time
import sys
let's declare the size
Size = 100000
Creating two lists
list1 = range(Size)
list2 = range(Size)
Creating two NumPy arrays
arr1 = np.arange(Size)
arr2 = np.arange(Size)
Calculating time for Python list
start = time.time()
result = [(x ,y) for x, y in zip(list1, list2)]
print("Time for Python List in msec: ", (time.time() - start) * 1000)
Calculating time for NumPy array
start = time.time()
result = arr1 ,arr2
print("Time for NumPy array in msec: ", (time.time()- start) * 1000)
print("\nThis means NumPy array is faster than Python List")
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