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numpy.random.choice() in Python

  • Difficulty Level : Expert
  • Last Updated : 15 Jul, 2020

With the help of choice() method, we can get the random samples of one dimensional array and return the random samples of numpy array.

Syntax : numpy.random.choice(a, size=None, replace=True, p=None)

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Parameters:



1) a – 1-D array of numpy having random samples.

2) size – Output shape of random samples of numpy array.

3) replace – Whether the sample is with or without replacement.

4) p – The probability attach with every samples in a. 

Output : Return the numpy array of random samples.

Example #1 :

In this example we can see that by using choice() method, we are able to get the random samples of numpy array, it can generate uniform or non-uniform samples by using this method.

Python3




# import choice
import numpy as np
import matplotlib.pyplot as plt
  
# Using choice() method
gfg = np.random.choice(13, 5000)
  
count, bins, ignored = plt.hist(gfg, 25, density = True)
plt.show()

Output :

Example #2 :

Python3




# import choice
import numpy as np
import matplotlib.pyplot as plt
  
# Using choice() method
gfg = np.random.choice(5, 1000, p =[0.2, 0.1, 0.3, 0.4, 0])
  
count, bins, ignored = plt.hist(gfg, 14, density = True)
plt.show()

Output :




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