Python:NumPy randint()

randint() is a function from NumPy’s random module that generates random integers. It can generate a single integer or an array of integers within a specified range, making it useful for simulations, testing, and randomized operations.

Syntax

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

Parameters:

• low (int): Lowest (inclusive) integer to be drawn.
• high (int, optional): One above the highest integer to be drawn. If not provided, integers are drawn from the range [0, low).
• size (int or tuple of ints, optional): Output shape. If None, a single integer is returned.
• dtype (data-type, optional): Desired data type of the output. Default is int.

Return value:

• out (int or ndarray): Random integer(s) from the specified range.
  • If size is None, returns a single integer.
  • If size is specified, returns a NumPy array of the given shape.

Example

This example generates a random integer (0-9) and an array of 5 random integers (1-5):

import numpy as np
np.random.seed(15)

# Single random integer from 0 to 9
single_int = np.random.randint(10)
print(single_int)

# Array of 5 random integers from 1 to 5
arr = np.random.randint(1, 6, size=5)
print(arr)

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The output for this code will be:

8
[5 1 5 4 4]

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Note: Exact output values may vary depending on NumPy version, but the format will be as shown.

Here:

• np.random.seed(15) ensures reproducible results.
• np.random.randint(10) generates a single integer between 0 and 9.
• np.random.randint(1, 6, size=5) generates an array of 5 integers between 1 and 5.

Codebyte Example

This codebyte sample generates a single random integer and a 2×3 array of random integers from specified ranges, ensuring reproducible results using a fixed random seed:

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• np.random.seed(42) ensures the code produces the same results every time.
• size=(2, 3) generates a 2D array with 2 rows and 3 columns of random integers.