Python Numpy random choice()
Description :
Example :
NumPy generally stands for Numerical Python and it is a general purpose array processing package.it always provides a high performance multidimensional array object. Numpy is usually for creating an array of n dimensions.
Method Name :numpy.random.choice(a, size=None, replace=True, p=None)
Description :The choice() method, we can get the random samples of one dimensional array and return the random samples of numpy array. The random choice() method always returns a randomly selected element from a non-empty sequence but An empty sequence as an argument raises an IndexError.This function is not accessible directly, so we need to import a random module and then we need to call this function using the random static object.
In this article, I will tell you about the parameter and its description
Parameter Name: a
Description :1-D array of numpy having random samples.
Parameter Name: size
Description :Output shape of random samples of numpy array.
Parameter Name: replace
Description : Whether the sample is with or without replacement.
Parameter Name: p
Description :The probability attach with every sample in array
Return : Return the numpy array of random samples.
The first step would be to give syntax
command:
numpy.random.choice(a, size=None, replace=True, p=None)
Example :
Code :
# 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 :
Example :Code :
# 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 :
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