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numpy.random.standard_cauchy() in 1Python

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With the help of numpy.random.standard_cauchy() method, we can see get the random samples from a standard cauchy distribution and return the random samples.

Standard cauchy distribution

Syntax : numpy.random.standard_cauchy(size=None)

Return : Return the random samples as numpy array.

Example #1 :

In this example we can see that by using numpy.random.standard_cauchy() method, we are able to get the random samples of standard cauchy distribution and generate the random samples from it.

Python3




# import numpy
import numpy as np
import matplotlib.pyplot as plt
  
# Using standard_cauchy() method
gfg = np.random.standard_cauchy(100000)
  
gfg = gfg[(gfg>-25) & (gfg<25)]
plt.hist(gfg, bins = 100, density = True)
plt.show()


Output :

Example #2 :

Python3




# import numpy
import numpy as np
import matplotlib.pyplot as plt
  
# Using standard_cauchy() method
gfg = np.random.standard_cauchy(100000)
gfg1 = np.random.power([gfg>0], 100000)
  
plt.hist(gfg1, bins = 100, density = True)
plt.show()


Output :



Last Updated : 18 Aug, 2020
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