Random choice sampling numpy

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

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]

Source: docs.scipy.org

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')

Source: docs.scipy.org

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