# random.gauss() function in Python

`random` module is used to generate random numbers in Python. Not actually random, rather this is used to generate pseudo-random numbers. That implies that these randomly generated numbers can be determined.

## random.gauss()

`gauss() ` is an inbuilt method of the `random` module. It is used to return a random floating point number with gaussian distribution.

Syntax : random.gauss(mu, sigma)

Parameters :
mu : mean
sigma : standard deviation

Returns : a random gaussian distribution floating number

Example 1:

 `# import the random module ` `import` `random ` ` `  `# determining the values of the parameters ` `mu ``=` `100` `sigma ``=` `50` ` `  `# using the gauss() method ` `print``(random.gauss(mu, sigma)) `

Output :

`127.80261974806497`

Example 2: We can generate the number multiple times and plot a graph to observe the gaussian distribution.

 `# import the required libraries  ` `import` `random  ` `import` `matplotlib.pyplot as plt  ` `   `  `# store the random numbers in a   ` `# list  ` `nums ``=` `[]  ` `mu ``=` `100` `sigma ``=` `50` `   `  `for` `i ``in` `range``(``100``):  ` `    ``temp ``=` `random.gauss(mu, sigma) ` `    ``nums.append(temp)  ` `       `  `# plotting a graph  ` `plt.plot(nums)  ` `plt.show() `

Output : Example 3: We can create a histogram to observe the density of the gaussian distribution.

 `# import the required libraries  ` `import` `random  ` `import` `matplotlib.pyplot as plt  ` `   `  `# store the random numbers in a list  ` `nums ``=` `[]  ` `mu ``=` `100` `sigma ``=` `50` `   `  `for` `i ``in` `range``(``10000``):  ` `    ``temp ``=` `random.gauss(mu, sigma)  ` `    ``nums.append(temp)  ` `       `  `# plotting a graph  ` `plt.hist(nums, bins ``=` `200``)  ` `plt.show() `

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