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)
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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