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

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

Also, you will learn how to generate a floating point random number with two precision in python. Produce a cryptographically 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() method to get random float number. The random.random()  method returns the next random floating point number in the range between o. 1 to 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:  Execute Online

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

Note:  random() method 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() method. The uniform() method returns a random floating point number between the given range. Let see now how to use the uniform() method in Python.

Syntax of random.uniform()

random.uniform(start, stop)

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

• In simple word, if start <= stop  uniform method 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 uniform method 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

• Uniform method 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() method Examples to get a random float number between float range

Let see how to use the uniform() method 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:  Execute 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

As you can see in the output every time we got a different random float number between 10 to 100.

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.

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() method takes no parameters while random.uniform() takes two parameters, i.e., start and stop.
• The random() method 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 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:  Execute 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. You can install NumPy using a 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:  Execute 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:  Execute 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:  Execute 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.