Generate Random Float numbers in Python using random() and Uniform() functions

In this article, I will show you how to generate random float numbers in Python. This article will help you to generate a random float number between 0 and 1. Also, you will learn to generate a random float number between any range.

Goals of this lesson. In this lesson, you’ll learn how to:

• Generate random float numbers in Python
• Generate a random float number between a float range
• Generate a random floating-point number with two precision in python.
• Produce a secure random float number.
• Use a numpy.random package to generate a random array of float numbers.

random.random() to generate a random floating-point number

Let see how to use the random.random() function of a random module to get a random float number. The random.random() function generates a random float number uniformly in the semi-open range [0.0, 1.0). Let see this with an example.

import random

print("Random float number is ", random.random())
print("Random float number is ", random.random())
print("Random float number is ", random.random())

Output: Run Online

Printing random float number  0.8504482249878023
Printing random float number  0.5769147269189085
Printing random float number  0.7774750819971197

Note: A random.random() function can only provide float numbers between 0.1. to 1.0. What if you want a random float number between any two numbers? We can use  random.uniform().

random.uniform() to get a random float number between a float range

Suppose you want to generate a random float number between 10.5 to 99.5 or from 50 to 550.50. You can do this using a random.uniform() function. The random.uniform() function returns a random floating-point number between the given range. Let see now how to use it.

Syntax of random.uniform()

random.uniform(start, stop)

The random.uniform() function returns a random floating-point number N such that start <= N <= stop.

• In simple word, if start <= stop the random.uniform function generates a random float number which is greater than or equal to the start number and less than or equal to the stop number.
• If  stop <= start, the random.uniform function generates a random float number which is greater than or equal to the stop number and less than or equal to the start number.
• For example, you can generate a random float number between 10 to 100 and also from 100 to 10. Both treated the same.

Note: The end-point value stop may or may not be included in the range depending on floating-point rounding.

Arguments

• A random.uniform function has two arguments and both the arguments are compulsory.
• If you miss any of them, you will get a TypeError: uniform() missing 1 required positional argument.

random.uniform() function Examples to get a random float number between float range

Let see how to use the random.uniform() function to get a random float number between the given range.

import random
print("Random float number between given range is ", random.uniform(10.5,100.5))
print("Random float number between given range is ", random.uniform(10.5,100.5))

print("Random float number between 10 and 100 is ", random.uniform(10,100))
print("Random float number between 10 and 100 is ", random.uniform(10,100))

print("Random float number between 100 and 50 is ", random.uniform(100,50))
print("Random float number between 100 and 50 is ", random.uniform(100,50))

Output: Run Online

Random float number between given range is  15.774675259307998
Random float number between given range is  40.20762839321159

Random float number between 10 and 100 is  10.091116283165412
Random float number between 10 and 100 is  94.51261450871945

Random float number between 100 and 50 is  79.38837140752604
Random float number between 100 and 50 is  85.31946104301423

Generate a floating-point random number with two precision

As you can see the above examples generated a random float number but with 15 decimal digits. So how to generate a random float number with limited decimal digits.

You can use the round() function to round the float number. Use the round function with the random.random and random.uniform function to limit float number precision to two decimal places. Let see this with an example program.

import random

print("Printing random float number with two decimal places is ", round(random.random(), 2))
print("Random float number between 2.5 and 22.5 with two decimal places is ", round(random.uniform(2.5,22.5), 2))

Output:

Printing random float number with two decimal places is  0.8
Random float number between 2.5 and 22.5 with two decimal places is  9.5

Difference between random.uniform() and random.random()

• The random.random() function takes no parameters while random.uniform() takes two parameters, i.e., start and stop.
• The random.random() function generates a random float number between 0.0 to 1.0, but never return upper bound. I.e., It never returns 1.0. On the other side random.uniform(start, stop) generates a random float number between the start and stop number. Due to the rounding effect, it can return a stop number.

Generate a cryptographically secure random float number

Note: Above all methods are not cryptographically secure. To cryptographically secure random output use random.SystemRandom() class. Refer to How to Cryptographically secure random data in python for more details.

Example

import random

secure_random = random.SystemRandom()
randomfloat = secure_random.random()
print("Secure random float number is ", randomfloat)

randomfloat = secure_random.uniform(12.5, 77.5)
print("Secure random float number is ", randomfloat)

Output: Run Online

Secure random float number is  0.800760229291861
Secure random float number is  35.0470859352744

Use Numpy.random to generate a random array of float numbers

NumPy isn’t a part of a standard python library. However, it has various functions to generate a random array of float numbers. Python’s NumPy module has a numpy.random package to generate random data.

You can install NumPy using pip command. Let see how to use those.

Printing a random float number using a numpy

import numpy

random_float = numpy.random.randn()
print("printing random float number using a numpy \n")
print(random_float,"\n")

Output: Run Online

printing random float number using a numpy 
0.833280610141848

Generate a random float number using a numpy between any float range

import numpy

random_float_number = numpy.random.uniform(49.5, 99.5)
print("random float array in [49.5, 99.5] \n", random_float_number,"\n")

Output:

random float array in [49.5, 99.5] 
 59.11713060647423

Use a numpy.random.rand() to create an n-dimensional array of float numbers and populate it with random samples from a uniform distribution over [0, 1).

import numpy

random_float_array = numpy.random.rand(2,3)
print("printing random float array 2X3 \n")
print(random_float_array,"\n")

Output: Run Online

printing random float array 2X3

[[0.34344184 0.8833125  0.76322675]
 [0.17844326 0.7717775  0.86237081]]

Use a numpy.random.uniform() to create an n-dimensional array of float numbers between any float range.

import numpy

#2 X 2 dimensional float array  within 77.5 to 125.5
random_float_array = numpy.random.uniform(75.5, 125.5, size=(2, 2))
print("random float array in [77.5, 125.5] \n", random_float_array,"\n")

Output: Run Online

random float array in [77.5, 125.5] 
 [[107.50697835 123.84889979]
 [106.26566127 101.92179508]] 

Next Steps

To practice what you learned in this article, I have created a Python random data generation Quiz and Exercise project.

Let me know your comments and feedback in the section below.