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# 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 :

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