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 – random.guass()

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

f = random.gauss(mu, sigma)

where

Parameter	Description
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.

Example 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 2 and standard deviation of 0.5.

Python Program

import random

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

Run

Output

2.2072072627475663

Example 2

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)

Run

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.