# random.expovariate() 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.expovariate()

`expovariate() ` is an inbuilt method of the `random` module. It is used to return a random floating point number with exponential distribution.
Syntax : random.expovariate(lambda) Parameters : lambda : a non zero value Returns : a random exponential distribution floating number if the parameter is positive, the results range from 0 to positive infinity if the parameter is negative, the results range from 0 to negative infinity
Example 1:
 `# import the random module ``import` `random `` ` `# determining the values of the parameter ``lambda` `=` `1.5`` ` `# using the expovariate() method ``print``(random.expovariate(``lambda``)) `

Output :
`0.22759592233982198`
Example 2: We can generate the number multiple times and plot a graph to observe the exponential distribution.
 `# import the required libraries  ``import` `random  ``import` `matplotlib.pyplot as plt  ``   ` `# store the random numbers in a   ``# list  ``nums ``=` `[]  ``alpha ``=` `3``   ` `for` `i ``in` `range``(``100``):  ``    ``temp ``=` `random.paretovariate(alpha) ``    ``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 exponential distribution.
 `# import the required libraries  ``import` `random  ``import` `matplotlib.pyplot as plt  ``   ` `# store the random numbers in a list  ``nums ``=` `[]  ``lambda` `=` `1.5``   ` `for` `i ``in` `range``(``10000``):  ``    ``temp ``=` `random.expovariate(``lambda``) ``    ``nums.append(temp)  ``       ` `# plotting a graph  ``plt.hist(nums, bins ``=` `200``)  ``plt.show() `

Output :

Previous
Next