Python - Random Number using Gaussian Distribution

Python - Generate Random Float using Gaussian distribution

To generate a random floating point number using Gaussian distribution in Python, use gauss() function of Python random package.

In this tutorial, we shall learn how to generate a random floating point number based on Gaussian distribution with specified mean and standard deviation.

Syntax of random.guass()

Following is the syntax of gauss() function in random module.

f = random.gauss(mu, sigma)

where

ParameterDescription
mu[Mandatory] Mean of Gaussian distribution.
sigma[Mandatory] Standard Deviation of Gaussian distribution.

gauss() function returns a random floating point value based on the given mean and standard deviation for the Gaussian distribution.

Examples

1. Generate float value using Gaussian Distribution

In this example, we shall use random.gauss() function to generate a random floating point number based on the Gaussian distribution with mean of 2 and standard deviation of 0.5.

Python Program

import random

mu = 2
sigma = 0.5
randomnumber = random.gauss(mu, sigma)
print(randomnumber)

Output

2.2072072627475663

2. Generate float using Gaussian distribution with a standard deviation of 0.1

In this example, we shall use random.gauss() function to generate a random floating point number based on the Gaussian distribution with mean of 0 and standard deviation of 0.1.

Python Program

import random

mu = 0
sigma = 0.1
randomnumber = random.gauss(mu, sigma)
print(randomnumber)

Output

-0.040644379382734665

Summary

In this tutorial of Python Examples, we learned how to generate a random floating point number using Gaussian distribution, with the help of well detailed example programs.

Python Libraries