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