Uniform random with random() in NumPy

Introduction

We use uniform random numbers to get values that are equally likely anywhere in a range. This helps when we want to simulate random events or test ideas with random data.

When simulating rolling a fair dice many times.

When picking random points inside a square or rectangle.

When testing how a program behaves with random inputs.

When creating random samples for experiments.

When generating random colors or positions in a game.

Syntax

NumPy

numpy.random.random(size=None)

size is optional and decides how many random numbers you get.

The numbers are between 0 (inclusive) and 1 (exclusive).

Examples

Get one random number between 0 and 1.

NumPy

import numpy as np
x = np.random.random()
print(x)

Get an array of 5 random numbers between 0 and 1.

NumPy

import numpy as np
arr = np.random.random(5)
print(arr)

Get a 2 by 3 matrix of random numbers between 0 and 1.

NumPy

import numpy as np
matrix = np.random.random((2,3))
print(matrix)

Sample Program

This program shows how to get one random number, an array of random numbers, and a matrix of random numbers using numpy.random.random().

NumPy

import numpy as np

# Generate one random number
one_num = np.random.random()
print(f"One random number: {one_num}")

# Generate 4 random numbers in an array
arr = np.random.random(4)
print("Array of 4 random numbers:", arr)

# Generate a 3x2 matrix of random numbers
matrix = np.random.random((3, 2))
print("3x2 matrix of random numbers:")
print(matrix)

Important Notes

Each time you run the code, the random numbers will change.

You can set a seed with np.random.seed(number) to get the same random numbers every time, which helps with testing.

Summary

Uniform random numbers are equally likely anywhere between 0 and 1.

Use numpy.random.random() to get these numbers.

You can get one number, an array, or a matrix by changing the size parameter.