THE WORLD'S LARGEST WEB DEVELOPER SITE

Python Tutorial

Python HOME Python Intro Python Get Started Python Syntax Python Comments Python Variables Python Data Types Python Numbers Python Casting Python Strings Python Booleans Python Operators Python Lists Python Tuples Python Sets Python Dictionaries Python If...Else Python While Loops Python For Loops Python Functions Python Lambda Python Arrays Python Classes/Objects Python Inheritance Python Iterators Python Scope Python Modules Python Dates Python JSON Python RegEx Python PIP Python Try...Except Python User Input Python String Formatting

File Handling

Python File Handling Python Read Files Python Write/Create Files Python Delete Files

Python NumPy

NumPy Intro NumPy Getting Started NumPy Creating Arrays NumPy Array Indexing NumPy Array Slicing NumPy Data Types NumPy Copy vs View NumPy Array Shape NumPy Array Reshape NumPy Array Iterating NumPy Array Join NumPy Array Split NumPy Array Search NumPy Array Sort NumPy Array Filter NumPy Random

Machine Learning

Getting Started Mean Median Mode Standard Deviation Percentile Data Distribution Normal Data Distribution Scatter Plot Linear Regression Polynomial Regression Multiple Regression Scale Train/Test Decision Tree

Python MySQL

MySQL Get Started MySQL Create Database MySQL Create Table MySQL Insert MySQL Select MySQL Where MySQL Order By MySQL Delete MySQL Drop Table MySQL Update MySQL Limit MySQL Join

Python MongoDB

MongoDB Get Started MongoDB Create Database MongoDB Create Collection MongoDB Insert MongoDB Find MongoDB Query MongoDB Sort MongoDB Delete MongoDB Drop Collection MongoDB Update MongoDB Limit

Python Reference

Python Overview Python Built-in Functions Python String Methods Python List Methods Python Dictionary Methods Python Tuple Methods Python Set Methods Python File Methods Python Keywords Python Exceptions Python Glossary

Module Reference

Random Module Requests Module Math Module cMath Module

Python How To

Remove List Duplicates Reverse a String Add Two Numbers

Python Examples

Python Examples Python Exercises Python Quiz Python Certificate

Random Numbers in NumPy


What is a Random Number?

Random number does NOT mean a different number every time. Random means something that can not be predicted logically.

Pseudo Random and True Random.

Computers work on programs, and programs are definitive set of instructions. So it means there must be some algorithm to generate a random number as well.

If there is a program to generate random number it can be predicted, thus it is not truly random.

Random numbers generated through a generation algorithm are called pseudo random.

Can we make truly random numbers?

Yes. In order to generate a truly random number on our computers we need to get the random data from some outside source. This outside source is generally our keystrokes, mouse movements, data on network etc.

We do not need truly random numbers, unless its related to security (e.g. encryption keys) or the basis of application is the randomness (e.g. Digital roulette wheels).

In this tutorial we will be using pseudo random numbers.


Generate Random Number

NumPy offers the random module to work with random numbers.

Example

Generate a random integer from 0 to 100:

from numpy import random

x = random.randint(100)

print(x)
Try it Yourself »

Generate Random Float

The random module's rand() method returns a random float between 0 and 1.

Example

Generate a random float from 0 to 1:

from numpy import random

x = random.rand()

print(x)
Try it Yourself »

Generate Random Array

In NumPy we work with arrays, and you can use the two methods from the above examples to make random arrays.

Integers

The randint() method takes a size parameter where you can specify the shape of an array.

Example

Generate a 1-D array containing 5 random integers from 0 to 100:

from numpy import random

x=random.randint(100, size=(5))

print(x)
Try it Yourself »

Example

Generate a 2-D array with 3 rows, each row containing 5 random integers from 0 to 100:

from numpy import random

x = random.randint(100, size=(3, 5))

print(x)
Try it Yourself »

Floats

The rand() method also allows you to specify the shape of the array.

Example

Generate a 1-D array containing 5 random floats:

from numpy import random

x = random.rand(5)

print(x)
Try it Yourself »

Example

Generate a 2-D array with 3 rows, each row containing 5 random numbers:

from numpy import random

x = random.rand(3, 5)

print(x)
Try it Yourself »

Generate Random Number From Array

The choice() method allows you to generate a random value based on an array of values.

The choice() method takes an array as a parameter and randomly returns one of the values.

Example

Return one of the values in an array:

from numpy import random

x = random.choice([3, 5, 7, 9])

print(x)
Try it Yourself »

The choice() method also allows you to return an array of values.

Add a size parameter to specify the shape of the array.

Example

Generate a 2-D array that consists of the values in the array parameter (3, 5, 7, and 9):

from numpy import random

x = random.choice([3, 5, 7, 9], size=(3, 5))

print(x)
Try it Yourself »