Np.random.choice

Np.random.float

numpy.random.uniform(low=0.0, high=1.0, size=None)

Source: docs.scipy.org

Np.random.seed

import numpy as np
np.random.seed(42)
random_numbers = np.random.random(size=4)
random_numbers

Source: datacamp.com

Python 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')

Source: docs.scipy.org

Np.random.choice

np.random.choice(5, 3, replace=False, p=[0.1, 0, 0.3, 0.6, 0])
array([2, 3, 0]) # random

Source: numpy.org

Np.random.choice

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'], # random
      dtype='<U11')

Source: numpy.org

Np.random.choice

np.random.choice(5, 3)
array([0, 3, 4]) # random
>>> #This is equivalent to np.random.randint(0,5,3)

Source: numpy.org

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