np.random.float
numpy.random.uniform(low=0.0, high=1.0, size=None)np.random.float
numpy.random.uniform(low=0.0, high=1.0, size=None)np.random.seed
import numpy as np
np.random.seed(42)
random_numbers = np.random.random(size=4)
random_numberspython select random subset from numpy array
fruits = ['apple', 'banana', 'orange', 'grape']
subset_size = int(0.7 * len(fruits))
np.random.choice(fruits, subset_size, replace=False)
# array(['grape', 'banana'], dtype='<U6')numpy.random.choice
>>> np.random.choice(5, 3, p=[0.1, 0, 0.3, 0.6, 0])
array([3, 3, 0])random choice sampling numpy
>>> np.random.choice(5, 3, replace=False)
array([3,1,0])
>>> #This is equivalent to np.random.permutation(np.arange(5))[:3]numpy random for string
>>> aa_milne_arr = ['pooh', 'rabbit', 'piglet', 'Christopher']
>>> np.random.choice(aa_milne_arr, 5, p=[0.5, 0.1, 0.1, 0.3])
array(['pooh', 'pooh', 'pooh', 'Christopher', 'piglet'],
dtype='|S11')
fruits = ['apple', 'banana', 'orange', 'grape']
subset_size = int(0.7 * len(fruits))
np.random.choice(fruits, subset_size, replace=False)
# array(['grape', 'banana'], dtype='<U6')Copyright © 2021 Codeinu
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