NumPy - random.randint() function

The NumPy random.randint() function returns random integers drawn from low (inclusive) to high (exclusive), in a given shape.

Syntax

numpy.random.randint(low, high=None, size=None, dtype='l')

Parameters

`low`	`Required.` Specify lowest (signed) integer to be drawn from the distribution (unless high=None, in which case this parameter is one above the highest such integer).
`high`	`Optional.` If provided, one above the largest (signed) integer to be drawn from the distribution (see above for behavior if high=None).
`size`	`Optional.` Specify output shape. If the given shape is, e.g., (m, n, k), then m n * k* samples are drawn. Default is None, in which case a single value is returned.
`dtype`	`Optional.` Specify desired dtype of the result.

Return Value

Returns random int values from the appropriate distribution in given shape, or a single such random int if size not provided.

Example:

In the example below, random.randint() function is used to generate random integers in a given shape. As high=None in this example, samples are drawn from [0, low).

import numpy as np

x = np.random.randint(3, size=(10))
y = np.random.randint(3, size=(3, 3))

#printing x
print("x =", x)

#printing y
print("y =")
print(y)

The output of the above code will be:

x = [2 1 2 2 2 0 0 2 1 0]
y =
[[1 0 1]
 [0 0 0]
 [2 2 0]]

Example:

When high is provided, integer samples are drawn from [low, high).

import numpy as np

x = np.random.randint(3, 10, (10))
y = np.random.randint(3, 10, (3, 3))

#printing x
print("x =", x)

#printing y
print("y =")
print(y)

The output of the above code will be:

x = [9 7 4 3 6 3 3 9 4 7]
y =
[[7 6 7]
 [4 6 8]
 [4 3 4]]

❮ NumPy - Random