numpy.random.exponential() in Python
Last Updated :
15 Jul, 2020
With the help of numpy.random.exponential() method, we can get the random samples from exponential distribution and returns the numpy array of random samples by using this method.
exponential distribution
Syntax : numpy.random.exponential(scale=1.0, size=None)
Return : Return the random samples of numpy array.
Example #1 :
In this example we can see that by using numpy.random.exponential() method, we are able to get the random samples of exponential distribution and return the samples of numpy array.
Python3
import numpy as np
import matplotlib.pyplot as plt
gfg = np.random.exponential( 3.45 , 10000 )
count, bins, ignored = plt.hist(gfg, 14 , density = True )
plt.show()
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Output :
Example #2 :
Python3
import numpy as np
import matplotlib.pyplot as plt
gfg = np.random.exponential( 101.123 , 10000 )
gfg1 = np.random.exponential(gfg, 10000 )
count, bins, ignored = plt.hist(gfg1, 14 , density = True )
plt.show()
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Output :
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