Generate Random Numbers From the Uniform Distribution using NumPy

NumPy provides the random.uniform() function to generate random numbers from a uniform distribution. In a uniform distribution, every number within the specified range has an equal probability of being selected.

In this simple example, we generate a single random number between 0 and 1 using numpy.random.uniform().

import numpy as np
num = np.random.uniform()
print(num)

0.17507289334250875

Syntax

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

Parameters:

• low (float, optional): Lower bound (default 0.0, inclusive).
• high (float, optional): Upper bound (default 1.0, exclusive).
• size (int or tuple, optional): Output shape. If None, returns a single value.

Returns: out (ndarray or float) Random samples from a uniform distribution in [low, high).

Examples

Example 1: In this example, we generate an array of 4 random numbers from the default range [0, 1).

import numpy as np
r = np.random.uniform(size=4)
print(r)

[0.66863102 0.68088668 0.22748931 0.57169974]

Example 2: This code generates a 1D array of 5 random numbers between 0.0 and 1.0.

import numpy as np
arr = np.random.uniform(0.0, 1.0, 5)
print(arr)

[0.44138756 0.10759472 0.58152145 0.17274268 0.37231619]

Example 3: Here we generate random numbers in a custom range [10, 20) with size 3.

import numpy as np
arr = np.random.uniform(10, 20, 3)
print(arr)

[15.32145976 19.64183948 15.41500478]