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numpy.random.standard_normal() in Python
  • Last Updated : 18 Aug, 2020

With the help of numpy.random.standard_normal() method, we can get the random samples from standard normal distribution and return the random samples as numpy array by using this method.

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

Return : Return the random samples as numpy array.

Example #1 :

In this example we can see that by using numpy.random.standard_normal() method, we are able to get the random samples of standard normal distribution.



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# import numpy
import numpy as np
import matplotlib.pyplot as plt
  
# Using standard_normal() method
gfg = np.random.standard_normal(5000)
  
plt.hist(gfg, bins = 50, density = True)
plt.show()

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Output :

Example #2 :

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# import numpy
import numpy as np
import matplotlib.pyplot as plt
  
# Using standard_normal() method
gfg = np.random.standard_normal(10000)
  
plt.hist(gfg, bins = 100, density = True)
plt.show()

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Output :

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