# Python – Random Number using Gaussian Distribution

Contents

## 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

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)``````
Run Code Copy

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)``````
Run Code Copy

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.

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