Random sampling in numpy | randint() function

The numpy.random.randint() function is used to generate random integers within a specified range. It allows you to create arrays of any shape filled with random integer values, making it useful in simulations, testing, and numerical experiments.

Example:

Input: Generate integers between 0 and 5
Output: [3 1 4 0 2]

Explanation: Each value is a random integer from the interval [0, 5).

Syntax

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

Parameters:

• low: lowest integer that can appear in the output.
• high(Optional): Upper limit (exclusive). If omitted, range becomes [0, low).
• size(Optional): Shape of the output array (e.g., 5, (2,3), (2,3,4)).
• dtype(Optional): Data type of the returned numbers. Default is integer.

Examples

Example 1: This example generates five random integers between 0 and 4, stored in a one-dimensional array.

import numpy as np
arr = np.random.randint(0, 5, size=5)
print(arr)

[2 2 3 3 4]

Example 2: This example creates a 2×3 matrix of random integers ranging from 0 to 9.

import numpy as np
arr = np.random.randint(0, 10, size=(2, 3))
print(arr)

[[7 9 8]
 [9 1 1]]

Explanation:

• size=(2, 3): creates 2 rows and 3 columns.
• 0 to 10: upper limit 10 is excluded.

Example 3: This example produces a 3D array (2×2×4) with values between 5 and 15.

import numpy as np
arr = np.random.randint(5, 15, size=(2, 2, 4))
print(arr)

[[[ 8  7 12 12]
  [ 6 13 13  6]]

 [[11  6  6  7]
  [ 7  9  6  8]]]