What is numpy array vectorization?

What is numpy array vectorization?

Numpy array vectorization is a technique that allows you to perform operations on entire arrays without using explicit loops, which can significantly speed up computations.

Can you give me an example of how to use vectorization in numpy?

Sure! For instance, if you want to add two arrays element-wise, you can do it like this:

import numpy as np

a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
result = a + b  # This will give you array([5, 7, 9])

What are the benefits of using vectorization?

The main benefits include improved performance, cleaner code, and reduced memory usage since operations are applied in bulk rather than iteratively.

Are there any limitations to vectorization?

Yes, vectorization may not be suitable for all types of operations, especially those that require complex logic or depend on previous results.