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.
Python3
# 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() |
Output :
Example #2 :
Python3
# 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() |
Output :