random.weibullvariate() function in Python

Last Updated : 26 May, 2020

`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.weibullvariate()

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

Syntax : random.weibullvariate(alpha, beta)

Parameters :
alpha : scale parameter
beta : shape parameter

Returns : a random Weibull distribution floating number

Example 1:

 `# import the random module ` `import` `random ` ` `  `# determining the values of the parameters ` `alpha ``=` `1` `beta ``=` `1.5` ` `  `# using the weibullvariate() method ` `print``(random.weibullvariate(alpha, beta)) `

Output :

`0.7231214446591137`

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

 `# import the required libraries  ` `import` `random  ` `import` `matplotlib.pyplot as plt  ` `   `  `# store the random numbers in a   ` `# list  ` `nums ``=` `[]  ` `alpha ``=` `1` `beta ``=` `1.5` `   `  `for` `i ``in` `range``(``100``):  ` `    ``temp ``=` `random.weibullvariate(alpha, beta) ` `    ``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 Weibull distribution.

 `# import the required libraries  ` `import` `random  ` `import` `matplotlib.pyplot as plt  ` `   `  `# store the random numbers in a list  ` `nums ``=` `[]  ` `alpha ``=` `1` `beta ``=` `1.5` `   `  `for` `i ``in` `range``(``10000``):  ` `    ``temp ``=` `random.weibullvariate(alpha, beta)  ` `    ``nums.append(temp)  ` `       `  `# plotting a graph  ` `plt.hist(nums, bins ``=` `200``)  ` `plt.show() `

Output :