In this section, we will see how to create and load NumPy arrays.
First, there are several NumPy functions for creating common types of arrays. For example, np.zeros(shape) creates an array containing only zeros. The shape argument is a tuple giving the size of every axis. Hence, np.zeros((3, 4)) creates an array of size (3, 4) (note the double parentheses, because we pass a tuple to the function).
Here are some further examples:
In [1]: import numpy as np print("ones", np.ones(5)) print("arange", np.arange(5)) print("linspace", np.linspace(0., 1., 5)) print("random", np.random.uniform(size=3)) print("custom", np.array([2, 3, 5])) Out[1]: ones [ 1. 1. 1. 1. 1.] arange [0 1 2 3 4] linspace [ 0. 0.25 0.5 0.75 1. ] random [ 0.68361911 0.33585308 0.70733934] custom [2 3 5]
The np.arange() and np.linspace() functions create arrays with regularly spaced numbers. The np...