TechBeamersTechBeamers
  • Learn ProgrammingLearn Programming
    • Python Programming
      • Python Basic
      • Python OOP
      • Python Pandas
      • Python PIP
      • Python Advanced
      • Python Selenium
    • Python Examples
    • Selenium Tutorials
      • Selenium with Java
      • Selenium with Python
    • Software Testing Tutorials
    • Java Programming
      • Java Basic
      • Java Flow Control
      • Java OOP
    • C Programming
    • Linux Commands
    • MySQL Commands
    • Agile in Software
    • AngularJS Guides
    • Android Tutorials
  • Interview PrepInterview Prep
    • SQL Interview Questions
    • Testing Interview Q&A
    • Python Interview Q&A
    • Selenium Interview Q&A
    • C Sharp Interview Q&A
    • PHP Interview Questions
    • Java Interview Questions
    • Web Development Q&A
  • Self AssessmentSelf Assessment
    • Python Test
    • Java Online Test
    • Selenium Quiz
    • Testing Quiz
    • HTML CSS Quiz
    • Shell Script Test
    • C/C++ Coding Test
Search
  • Python Multiline String
  • Python Multiline Comment
  • Python Iterate String
  • Python Dictionary
  • Python Lists
  • Python List Contains
  • Page Object Model
  • TestNG Annotations
  • Python Function Quiz
  • Python String Quiz
  • Python OOP Test
  • Java Spring Test
  • Java Collection Quiz
  • JavaScript Skill Test
  • Selenium Skill Test
  • Selenium Python Quiz
  • Shell Scripting Test
  • Latest Python Q&A
  • CSharp Coding Q&A
  • SQL Query Question
  • Top Selenium Q&A
  • Top QA Questions
  • Latest Testing Q&A
  • REST API Questions
  • Linux Interview Q&A
  • Shell Script Questions
© 2024 TechBeamers. All Rights Reserved.
Reading: A Beginner’s Guide to Python Random Sampling
Font ResizerAa
TechBeamersTechBeamers
Font ResizerAa
  • Python
  • SQL
  • C
  • Java
  • Testing
  • Selenium
  • Agile Concepts Simplified
  • Linux
  • MySQL
  • Python Quizzes
  • Java Quiz
  • Testing Quiz
  • Shell Script Quiz
  • WebDev Interview
  • Python Basic
  • Python Examples
  • Python Advanced
  • Python OOP
  • Python Selenium
  • General Tech
Search
  • Programming Tutorials
    • Python Tutorial
    • Python Examples
    • Java Tutorial
    • C Tutorial
    • MySQL Tutorial
    • Selenium Tutorial
    • Testing Tutorial
  • Top Interview Q&A
    • SQL Interview
    • Web Dev Interview
  • Best Coding Quiz
    • Python Quizzes
    • Java Quiz
    • Testing Quiz
    • ShellScript Quiz
Follow US
© 2024 TechBeamers. All Rights Reserved.
Python AdvancedPython Tutorials

A Beginner’s Guide to Python Random Sampling

Last updated: Feb 04, 2024 12:35 am
By Meenakshi Agarwal
Share
9 Min Read
Python Random Sampling Explained with Examples
SHARE

Random sampling might sound complicated, but it’s a super useful skill when working with data in Python. It helps you pick out bits of information without going through everything. Python’s got this cool toolbox called the random module that makes random sampling a breeze. In this tutorial, we’re going to explore different ways to use it, with lots of examples and practical tips. By the end, you’ll be a pro at randomly picking elements, shuffling things around, and even simulating random processes.

Contents
1. Introduction to Random SamplingWhy Random Sampling is HandyQuick Look at Python’s random Toolbox2. Simple Random Samplingrandom.choice() – Grab a Random Thing3. Sampling Without Replacementrandom.sample() – Get Unique Stuff4. Sampling With Replacementrandom.choices() – Repeat the Fun5. Random Integer Generationrandom.randint() – Get Random Whole Numbers6. Random Float Generationrandom.uniform() – Grab Random Decimal Numbers7. Shuffling Sequencesrandom.shuffle() – Mix Things Up8. Seed for Reproducibilityrandom.seed() – Make It Happen Again9. Custom Probability Distributionsrandom.choices() with weights – Your Own Rules10. Monte Carlo SimulationSimulate Random Stuff11. Random Sampling in Pandassample() Method – Get Random in DataFrames

Follow our step-by-step guide to learn about random sampling in Python. Let’s begin with how to create random samples in Python.

1. Introduction to Random Sampling

Why Random Sampling is Handy

Random sampling helps us make sense of big sets of data without going crazy. Think of it as grabbing a bunch of random samples to understand the whole thing better. It’s like tasting a bit of soup to know if it needs more salt.

Quick Look at Python’s random Toolbox

Python’s got this cool toolbox called random that’s filled with tools for random stuff. It’s like a bag of tricks for grabbing things randomly, from numbers to items in a list.

2. Simple Random Sampling

random.choice() – Grab a Random Thing

Use random.choice() when you just want one thing randomly picked from a bunch of things. It’s like closing your eyes and pointing to something on a menu.

import random as rnd

samples = [0.1, 0.11, 0.111, 0.1111, 0.1111]
sample = rnd.choice(samples)

print("You randomly chose:", sample)

Here, random choice() picks one thing from the list of samples. Easy, right?

3. Sampling Without Replacement

random.sample() – Get Unique Stuff

If you need a few things, but each one has to be unique, use random.sample(). It’s like picking a few unique candies from a big jar.

import random as rnd

samples = [0.1, 0.12, 0.13, 0.13, 0.14]
sample = rnd.sample(samples, 3)

print("You got these unique things:", sample)

Here, random.sample() gives you a few unique things from the list samples.

4. Sampling With Replacement

random.choices() – Repeat the Fun

When it’s okay to pick the same thing more than once, use random.choices(). It’s like reaching into a bag of candies, taking one, and then putting it back for the next round.

import random as rnd

samples = [1/1, 1/2, 1/3, 1/4, 1/5]
sample = rnd.choices(samples, k=3)

print("You randomly got these, and maybe some twice:", sample)

Here, random.choices() lets you pick a few things, and it might choose the same thing more than once.

5. Random Integer Generation

random.randint() – Get Random Whole Numbers

For random whole numbers, use random.randint(). It’s like rolling a dice and getting a number between two others.

import random as rnd

rand_int = rnd.randint(1, 10)

print("You rolled the dice and got:", rand_int)

Here, random.randint() gives you a random number between 1 and 10.

6. Random Float Generation

random.uniform() – Grab Random Decimal Numbers

If you need random decimal numbers, use random.uniform(). It’s like guessing a number between two others, even if they’re not whole.

import random as rnd

rand_ft = rnd.uniform(0.0, 1.0)

print("You guessed a random decimal between 0.0 and 1.0:", rand_ft)

Here, random.uniform() gives you a random decimal between 0.0 and 1.0.

7. Shuffling Sequences

random.shuffle() – Mix Things Up

To mix up the order of things in a list, use random.shuffle(). It’s like shuffling a deck of cards.

import random as rnd

samples = [1, 11, 111, 1111, 1111]
rnd.shuffle(samples)

print("You shuffled the list and got:", samples)

Here, random.shuffle() mixes up the order of the list samples.

8. Seed for Reproducibility

random.seed() – Make It Happen Again

If you want to get the same random results every time, use random.seed(). It’s like setting a magic number so that your randomness is predictable.

import random as rnd

random.seed(42)
rand_int = rnd.randint(1, 10)

print("With the magic number 42, you got:", rand_int)

Here, random.seed(42) makes sure that you get the same random results every time you run the code.

9. Custom Probability Distributions

random.choices() with weights – Your Own Rules

When you want some things to be more likely than others, use random.choices() with the weights parameter. It’s like making a game where you’re more likely to roll a certain number.

import random as rnd

samples = [1**1, 2**2, 3**3, 4**4, 5**5]
weights = [0.1, 0.2, 0.3, 0.2, 0.2]

custom_dist = rnd.choices(samples, weights=weights, k=5)

print("You played a game with custom rules and got:", custom_dist)

Here, elements with higher weights are more likely to be chosen.

10. Monte Carlo Simulation

Simulate Random Stuff

Monte Carlo simulation is like playing around with randomness to get numerical results. A classic example is estimating the value of π by randomly throwing darts at a target.

import random as rnd

def estimate_pi(num_samples):
    inside_circle = 0

    for _ in range(num_samples):
        x = rnd.uniform(0, 1)
        y = rnd.uniform(0, 1)

        if x**2 + y**2 <= 1:
            inside_circle += 1

    return (inside_circle / num_samples) * 4

estd_pi = estimate_pi(100000)

print("You estimated the value of π and got:", estd_pi)

Here, the estimate_pi function uses random points to approximate the value of π.

11. Random Sampling in Pandas

sample() Method – Get Random in DataFrames

For random sampling in Pandas, use the sample() method on DataFrames. It’s like grabbing random rows or columns from a table.

import pandas as pd

# Assuming df is a DataFrame
df = pd.DataFrame({
    'A': range(1, 11),
    'B': range(11, 21),
    'C': range(21, 31)
})

rand_sample = df.sample(n=3, random_state=42)

print("You randomly picked these rows from your table:")
print(rand_sample)

Here, df.sample(n=3) randomly selects 3 rows from the DataFrame df.

Conclusion – Python Random Sampling

In this guide, we’ve covered the basics of random sampling in Python using the random module. From picking random elements to shuffling things around and even simulating random processes, Python’s got your back. Remember to choose the method that fits what you need, whether it’s unique elements, repeated elements, whole numbers, decimals, or even your own custom rules. And don’t forget to set a seed if you want to get the same random results every time. Now go out there and confidently use Python’s random sampling magic in your data adventures!

Happy Coding,
Team TechBeamers

You Might Also Like

How to Connect to PostgreSQL in Python

Generate Random IP Address (IPv4/IPv6) in Python

Python Remove Elements from a List

Selenium Python Extent Report Guide

10 Python Tricky Coding Exercises

TAGGED:Random Data Generation Made Easy
Meenakshi Agarwal Avatar
By Meenakshi Agarwal
Follow:
Hi, I'm Meenakshi Agarwal. I have a Bachelor's degree in Computer Science and a Master's degree in Computer Applications. After spending over a decade in large MNCs, I gained extensive experience in programming, coding, software development, testing, and automation. Now, I share my knowledge through tutorials, quizzes, and interview questions on Python, Java, Selenium, SQL, and C# on my blog, TechBeamers.com.
Previous Article Generate Random Numbers in Excel Using Multiple Ways How to Generate Random Numbers in Excel
Next Article AWS Interview Questions and Answers 25 AWS Interview Questions and Answers to Remember

Popular Tutorials

SQL Interview Questions List
50 SQL Practice Questions for Good Results in Interview
SQL Interview Nov 01, 2016
Demo Websites You Need to Practice Selenium
7 Sites to Practice Selenium for Free in 2024
Selenium Tutorial Feb 08, 2016
SQL Exercises with Sample Table and Demo Data
SQL Exercises – Complex Queries
SQL Interview May 10, 2020
Java Coding Questions for Software Testers
15 Java Coding Questions for Testers
Selenium Tutorial Jun 17, 2016
30 Quick Python Programming Questions On List, Tuple & Dictionary
30 Python Programming Questions On List, Tuple, and Dictionary
Python Basic Python Tutorials Oct 07, 2016
//
Our tutorials are written by real people who’ve put in the time to research and test thoroughly. Whether you’re a beginner or a pro, our tutorials will guide you through everything you need to learn a programming language.

Top Coding Tips

  • PYTHON TIPS
  • PANDAS TIPSNew
  • DATA ANALYSIS TIPS
  • SELENIUM TIPS
  • C CODING TIPS
  • GDB DEBUG TIPS
  • SQL TIPS & TRICKS

Top Tutorials

  • PYTHON TUTORIAL FOR BEGINNERS
  • SELENIUM WEBDRIVER TUTORIAL
  • SELENIUM PYTHON TUTORIAL
  • SELENIUM DEMO WEBSITESHot
  • TESTNG TUTORIALS FOR BEGINNERS
  • PYTHON MULTITHREADING TUTORIAL
  • JAVA MULTITHREADING TUTORIAL

Sign Up for Our Newsletter

Subscribe to our newsletter to get our newest articles instantly!

Loading
TechBeamersTechBeamers
Follow US
© 2024 TechBeamers. All Rights Reserved.
  • About
  • Contact
  • Disclaimer
  • Privacy Policy
  • Terms of Use
TechBeamers Newsletter - Subscribe for Latest Updates
Join Us!

Subscribe to our newsletter and never miss the latest tech tutorials, quizzes, and tips.

Loading
Zero spam, Unsubscribe at any time.
x