Python Practice for Beginners: 250 Hands-On Exercises: Python Practice for Beginners: 250 Hands-On Exercises From Basic Concepts to Mini-Projects: ... Active Learning (Micro Learning | Python)

 

Python Practice for Beginners: 250 Hands-On Exercises

Unlock the power of Python programming with this comprehensive exercise book designed for beginners and early-stage learners. "Python Practice for Beginners: 250 Hands-On Exercises" offers a unique, practical approach to mastering one of the world's most popular programming languages.

Key Features:
250 carefully crafted exercises covering essential Python concepts
Gradual progression from basic to more advanced topics
Detailed solutions and explanations for each exercise
Real-world applications to reinforce learning
Suitable for self-learners, students, and coding bootcamp participants


This book bridges the gap between theory and practice, providing you with the hands-on experience crucial for becoming proficient in Python. Each chapter focuses on specific aspects of Python, including:

1. Basic syntax and data types
2. Control structures and loops
3. Functions and modules
4. Object-oriented programming
5. File handling and data processing
6. Error handling and debugging
7. Introduction to popular Python libraries

Whether you're preparing for coding interviews, supplementing your coursework, or embarking on a self-learning journey, this book will help you build a solid foundation in Python programming. The exercises are designed to challenge your problem-solving skills and deepen your understanding of Python's capabilities.

Written by László Bocsó, a Microsoft Certified Trainer with years of experience in teaching programming, this book provides insights and best practices that go beyond basic syntax. You'll learn how to write clean, efficient, and Pythonic code while tackling real-world programming challenges.

By the end of this book, you'll have:
Gained confidence in writing Python code
Developed strong problem-solving skills B
Built a portfolio of 250 Python projects
Prepared yourself for more advanced Python topics

Start your Python journey today with "Python Practice for Beginners: 250 Hands-On Exercises" and transform yourself from a coding novice to a confident Python programmer. Perfect for self-study or as a complement to other learning resources, this book is your key to Python mastery.

Buy now and take the first step towards becoming a proficient Python programmer!

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Modern Python Cookbook: 130+ updated recipes for modern Python 3.12 with new techniques and tools

 

Enhance your Python skills with the third edition of Modern Python Cookbook with 130+ new and updated recipes covering Python 3.12, including new coverage on graphics, visualizations, dependencies, virtual environments, and more.

Purchase of the print or Kindle book includes a free eBook in PDF format

Key Features

• New chapters on type matching, data visualization, dependency management, and more
• Comprehensive coverage of Python 3.12 with updated recipes and techniques
• Provides practical examples and detailed explanations to solve real-world problems efficiently

Book Description

Python is the go-to language for developers, engineers, data scientists, and hobbyists worldwide. Known for its versatility, Python can efficiently power applications, offering remarkable speed, safety, and scalability. This book distills Python into a collection of straightforward recipes, providing insights into specific language features within various contexts, making it an indispensable resource for mastering Python and using it to handle real-world use cases.

The third edition of Modern Python Cookbook provides an in-depth look into Python 3.12, offering more than 140 new and updated recipes that cater to both beginners and experienced developers. This edition introduces new chapters on documentation and style, data visualization with Matplotlib and Pyplot, and advanced dependency management techniques using tools like Poetry and Anaconda. With practical examples and detailed explanations, this cookbook helps developers solve real-world problems, optimize their code, and get up to date with the latest Python features.

What you will learn

• Master core Python data structures, algorithms, and design patterns
• Implement object-oriented designs and functional programming features
• Use type matching and annotations to make more expressive programs
• Create useful data visualizations with Matplotlib and Pyplot
• Manage project dependencies and virtual environments effectively
• Follow best practices for code style and testing
• Create clear and trustworthy documentation for your projects

Who this book is for

This Python book is for web developers, programmers, enterprise programmers, engineers, and big data scientists. If you are a beginner, this book offers helpful details and design patterns for learning Python. If you are experienced, it will expand your knowledge base. Fundamental knowledge of Python programming and basic programming principles will be helpful

Table of Contents

1. Numbers, Strings, and Tuples
2. Statements and Syntax
3. Function Definitions
4. Built-In Data Structures Part 1: Lists and Sets
5. Built-In Data Structures Part 2: Dictionaries
6. User Inputs and Outputs
7. Basics of Classes and Objects
8. More Advanced Class Design
9. Functional Programming Features
10. Type Matching and Annotations
11. Input/Output, Physical Format, and Logical Layout
12. Graphics and Visualization with Jupyter Lab
13. Application Integration: Configuration
14. Application Integration: Combination
15. Testing
16. Dependencies and Virtual Environments
17. Documentation and Style

Hard Copy : Modern Python Cookbook: 130+ updated recipes for modern Python 3.12 with new techniques and tools

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Python for Algorithmic Trading Cookbook: Recipes for designing, building, and deploying algorithmic trading strategies with Python

 

Harness the power of Python libraries to transform freely available financial market data into algorithmic trading strategies and deploy them into a live trading environment

Key Features

• Follow practical Python recipes to acquire, visualize, and store market data for market research
• Design, backtest, and evaluate the performance of trading strategies using professional techniques
• Deploy trading strategies built in Python to a live trading environment with API connectivity
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

Discover how Python has made algorithmic trading accessible to non-professionals with unparalleled expertise and practical insights from Jason Strimpel, founder of PyQuant News and a seasoned professional with global experience in trading and risk management. This book guides you through from the basics of quantitative finance and data acquisition to advanced stages of backtesting and live trading.

Detailed recipes will help you leverage the cutting-edge OpenBB SDK to gather freely available data for stocks, options, and futures, and build your own research environment using lightning-fast storage techniques like SQLite, HDF5, and ArcticDB. This book shows you how to use SciPy and statsmodels to identify alpha factors and hedge risk, and construct momentum and mean-reversion factors. You’ll optimize strategy parameters with walk-forward optimization using vectorbt and construct a production-ready backtest using Zipline Reloaded. Implementing all that you’ve learned, you’ll set up and deploy your algorithmic trading strategies in a live trading environment using the Interactive Brokers API, allowing you to stream tick-level data, submit orders, and retrieve portfolio details.

By the end of this algorithmic trading book, you'll not only have grasped the essential concepts but also the practical skills needed to implement and execute sophisticated trading strategies using Python.

What you will learn

• Acquire and process freely available market data with the OpenBB Platform
• Build a research environment and populate it with financial market data
• Use machine learning to identify alpha factors and engineer them into signals
• Use VectorBT to find strategy parameters using walk-forward optimization
• Build production-ready backtests with Zipline Reloaded and evaluate factor performance
• Set up the code framework to connect and send an order to Interactive Brokers

Who this book is for

Python for Algorithmic Trading Cookbook equips traders, investors, and Python developers with code to design, backtest, and deploy algorithmic trading strategies. You should have experience investing in the stock market, knowledge of Python data structures, and a basic understanding of using Python libraries like pandas. This book is also ideal for individuals with Python experience who are already active in the market or are aspiring to be.

Table of Contents

1. Acquire Free Financial Market Data with Cutting-edge Python Libraries
2. Analyze and Transform Financial Market Data with pandas
3. Visualize Financial Market Data with Matplotlib, Seaborn, and Plotly Dash
4. Store Financial Market Data on Your Computer
5. Build Alpha Factors for Stock Portfolios
6. Vector-Based Backtesting with VectorBT
7. Event-Based Backtesting Factor Portfolios with Zipline Reloaded
8. Evaluate Factor Risk and Performance with Alphalens Reloaded
9. Assess Backtest Risk and Performance Metrics with Pyfolio
10. Set Up the Interactive Brokers Python API
11. Manage Orders, Positions, and Portfolios with the IB API

Hard Copy : Python for Algorithmic Trading Cookbook: Recipes for designing, building, and deploying algorithmic trading strategies with Python

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Python Playground: Coding Games and Projects for Kids and Beginners

 

Unlock the full potential of Python programming with " Python Playground: Coding Games and Projects for Kids and Beginners." Whether you're a beginner or an experienced coder, this book is your ultimate resource for learning and mastering the Python language.

Dive deep into the essentials of Python programming, starting with the basics and progressing to advanced topics. Learn how to write clean, efficient code with Python debugging techniques that help you identify and fix errors quickly. Ensure your code's reliability with thorough Python testing strategies that cover a variety of testing frameworks.

Explore the exciting world of Python web development and discover how to build robust web applications using popular frameworks like Django and Flask. If you're interested in creating visually appealing applications, our comprehensive coverage of Python GUI programming will guide you through developing user-friendly graphical interfaces with libraries like Tkinter and PyQt.

For those with a passion for gaming, the Python game development section provides insights into creating interactive games using Pygame and other game development tools. Every chapter is filled with practical examples and hands-on Python projects that reinforce your learning and enhance your skills.

" Python Playground: Coding Games and Projects for Kids and Beginners" is your go-to companion for all things Python, offering clear explanations, expert tips, and numerous resources to aid your Python learning journey. With Python, the possibilities are endless—start exploring them today!

Hard Copy : Python Playground: Coding Games and Projects for Kids and Beginners

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Python All-in-One For Dummies

 

Everything you need to know to get into Python coding, with 7 books in one

Python All-in-One For Dummies is your one-stop source for answers to all your Python questions. From creating apps to building complex web sites to sorting big data, Python provides a way to get the work done. This book is great as a starting point for those new to coding, and it also makes a perfect reference for experienced coders looking for more than the basics. Apply your Python skills to data analysis, learn to write AI-assisted code using GitHub CoPilot, and discover many more exciting uses for this top programming language.

• Get started coding in Python―even if you’re new to computer programming
• Reference all the essentials and the latest updates, so your code is air-tight
• Learn how Python can be a solution for large-scale projects and big datasets
• Accelerate your career path with this comprehensive guide to learning Python
• 
  

Experienced and would-be coders alike will love this easy-to-follow guide to learning and applying Python.

Hard Copy : Python All-in-One For Dummies

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Python, Javascript, Java, SQL, Linux: The Complete Coding and Developing Crash Course for Beginners (2024)

 

The Complete Coding and Developing Crash Course for Beginners - From Zero to Hero 2024

Are you a beginner struggling to get started with coding in 2024? Overwhelmed by learning new programming languages? Looking for an easy-to-understand guide to take you from novice to confident coder?

If yes, then keep reading.

In Python, JavaScript, Java, SQL, Linux, you won't just learn these skills; you'll master them. This comprehensive 5-in-1 guide is tailored for complete beginners, offering a bootcamp-style approach that simplifies learning with practical examples, hands-on exercises, and real-world applications.

Whether you're just starting out or looking to refine your skills, this course will boost your confidence as you tackle coding challenges and set you apart in the job market. This book breaks down complex concepts into easy-to-understand modules, making it the perfect resource for anyone aiming to become a proficient coder.

Here's a Sneak Peek of What You'll Master in this 5-in-1 guide:

Book 1 - Python Programming

• Basics: Learn variables, functions, loops, conditionals, and data types.
• Data Structures: Master sequences, tuples, lists, matrices, and dictionaries.
• Functions: Create and utilize functions effectively.
• OOP: Understand classes, methods, and OOP principles.
• Error Handling: Implement robust exception handling.
• File Operations: Handle file reading, writing, and manipulation.
• and so much more

Book 2 - JavaScript Programming

• Fundamentals: Understand values, types, and operators.
• Client-Side JavaScript: Learn advantages and limitations.
• Development Tools: Explore JavaScript tools and environments.
• Dynamic Web Pages: Create dynamic web pages.
• Advanced JavaScript: Dive into higher-level concepts.
• and so much more

Book 3 - Java Programming

• Basics: Learn about variables, data types, and syntax.
• OOP: Understand classes, objects, inheritance, and polymorphism.
• Java Standard Library: Utilize essential classes and methods.
• Exception Handling: Implement try-catch blocks.
• Development Tools: Explore tools and environments.
• and so much more

Book 4 - SQL

• Foundations: Learn SQL basics, including data types, statements, and clauses.
• Database Management: Create, modify, and manage databases and tables.
• Complex Queries: Execute joins, unions, and advanced queries.
• Performance Optimization: Optimize SQL queries.
• Data Integrity: Implement primary keys, foreign keys, and constraints.
• and so much more

Book 5 - Linux

• Basics: Understand Linux concepts and distributions.
• Command Line: Master Linux commands and shell scripting.
• System Administration: Manage users, groups, and file permissions.
• Networking: Configure and troubleshoot network settings.
• Security: Implement security measures and manage firewalls.
• and so much more

This isn't just a book. It's a career booster. ✅ Whether you're aiming for a new job or developing your own software, this guide has everything you need. Find practical advice and skills to propel your career, set you apart from peers, and make you an invaluable asset to any organization.

Hard Copy: Python, Javascript, Java, SQL, Linux: The Complete Coding and Developing Crash Course for Beginners (2024)

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Python Programming for Beginners: 4 Books in 1: No-Fail, Step-by-Step Guide to Master Python in 30 Days or Less: Packed with Examples, Exercises, and Case Studies

 

Dive deep into the future of programming with this comprehensive guide to Quantum Computing, Cloud Systems, Machine Learning, and VR Development.

Ever felt overwhelmed by the rapid advancements in programming and tech?

Looking to stay ahead in the tech world but unsure where to start?

Or perhaps you're seeking a robust, in-depth resource that covers the frontier areas of modern coding?

Your search ends here.

In a world increasingly driven by technology, it's not just about coding anymore; it's about coding for the platforms that will define the next decade.

Many are still in the dark about where the future of programming is headed, but with this book, you'll be light years ahead.

Encompassing a deep dive into the realms of Quantum Computing, Cloud Systems, Machine Learning, and VR Development, this book is tailored for those hungry for the next big thing.

With detailed insights, step-by-step tutorials, and an easy-to-grasp style, it bridges the gap between traditional coding knowledge and future tech.

Within these pages, here's a snapshot of what you'll uncover:

Quantum Revolution: Grasp the Fundamentals of Quantum Computing and its Game-Changing Implications

Above the Clouds: Navigating Modern Cloud Systems for Efficient and Scalable Programming

Minds and Machines: Delving into Machine Learning, AI, and the Promise they Hold

Reality 2.0: Dive into the World of VR Development and Shape Virtual Realities like Never Before
And a Universe More!

Imagine being able to converse confidently about quantum algorithms, or creating machine learning models that can predict the future, or designing immersive

VR experiences that feel more real than reality itself.

This four-in-one bundle doesn't just scratch the surface. It provides a deep understanding, empowering you to harness the opportunities of the next tech era.

★ Are you ready to leap into the future of programming and stand out in the tech universe? ★

Hard Copy: Python Programming for Beginners: 4 Books in 1: No-Fail, Step-by-Step Guide to Master Python in 30 Days or Less: Packed with Examples, Exercises, and Case Studies

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Clean Code in Python: Refactor your legacy code base

 

Getting the most out of Python to improve your codebase

Key Features

Save maintenance costs by learning to fix your legacy codebase

Learn the principles and techniques of refactoring

Apply microservices to your legacy systems by implementing practical techniques

Book Description

Python is currently used in many different areas such as software construction, systems administration, and data processing.

In all of these areas, experienced professionals can find examples of inefficiency, problems, and other perils, as a result of bad code. After reading this book, readers will understand these problems, and more importantly, how to correct them.

The book begins by describing the basic elements of writing clean code and how it plays an important role in Python programming. You will learn about writing efficient and readable code using the Python standard library and best practices for software design. You will learn to implement the SOLID principles in Python and use decorators to improve your code. The book delves more deeply into object oriented programming in Python and shows you how to use objects with descriptors and generators. It will also show you the design principles of software testing and how to resolve software problems by implementing design patterns in your code. In the final chapter we break down a monolithic application to a microservice one, starting from the code as the basis for a solid platform.

By the end of the book, you will be proficient in applying industry approved coding practices to design clean, sustainable and readable Python code.

What you will learn

Set up tools to effectively work in a development environment

Explore how the magic methods of Python can help us write better code

Examine the traits of Python to create advanced object-oriented design

Understand removal of duplicated code using decorators and descriptors

Effectively refactor code with the help of unit tests

Learn to implement the SOLID principles in Python

Hard Copy: Clean Code in Python: Refactor your legacy code base

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Prepare Data for Exploration

 

Mastering Data Preparation: A Review of Coursera's "Data Preparation" Course

In today’s data-driven world, the ability to handle and prepare data is a vital skill. Coursera’s Data Preparation course offers an excellent introduction to this fundamental process, providing learners with hands-on experience and practical knowledge in preparing data for analysis.

Why Data Preparation Matters

Before any analysis can begin, data must be cleaned, formatted, and organized. Messy or incomplete data can lead to inaccurate results and poor decisions. Proper data preparation ensures that your data is reliable and ready for analysis, making it one of the most important steps in the data science workflow.

What the Course Covers

The Data Preparation course on Coursera, part of a broader data science specialization, covers essential techniques to ensure that your data is in prime shape for analysis. Whether you’re working with large datasets or trying to make sense of small, incomplete ones, the course provides the tools needed to:

• Clean and format data: You’ll learn how to deal with missing values, outliers, and inconsistent formatting—common issues when working with raw data.
• Handle different data types: Learn how to work with various data types such as text, numeric, categorical, and date/time data.
• Data transformation: You’ll explore techniques for transforming data, such as normalization, standardization, and encoding categorical variables, making the data suitable for algorithms and further analysis.
• Explore datasets: The course also emphasizes the importance of exploratory data analysis (EDA), where you’ll learn to visualize and summarize data to uncover patterns, correlations, and trends.

Hands-on Learning Experience

What sets this course apart is the practical, hands-on learning experience. Using real-world datasets, you’ll get to apply the techniques you learn, ensuring you leave the course not only with theoretical knowledge but also the skills to execute data preparation in practice.

The exercises include working with Python libraries like pandas, numpy, and matplotlib—key tools for data manipulation and visualization.

Who Should Take This Course?

This course is designed for beginners in data science and those with some basic programming skills who want to strengthen their data preparation abilities. If you're familiar with Python and want to develop your data handling skills further, this course is a perfect fit.

Whether you’re a budding data scientist, a business analyst, or a professional looking to enhance your data analysis skills, this course will equip you with the essential knowledge needed to prepare data for any data analysis or machine learning project.

Final Thoughts

Data preparation is often an overlooked but crucial step in the data science process. Coursera’s Data Preparation course offers a structured, in-depth introduction to this essential skill, ensuring that your data is clean, organized, and ready for analysis. With a mix of theory and hands-on practice, this course is an excellent choice for anyone looking to improve their data-handling skills.

Join Free: Prepare Data for Exploration

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Visualizing Word Frequencies using Python

 

pip install wordcloud

import matplotlib.pyplot as plt

from wordcloud import WordCloud

text = input("Enter sentence for word cloud :")

wordcloud = WordCloud().generate(text)

plt.imshow(wordcloud, interpolation='bilinear')

plt.axis('off')    

plt.show()

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Learn to code with AI

 

What you'll learn

How to use AI to build web apps without any programming knowledge

How to deploy your web apps to the web

The very basics of HTML, CSS, and JavaScript

There are 3 modules in this course

Imagine waking up tomorrow as a web developer. What would you want to build?

With AI tools like ChatGPT, you're already a developer, regardless of your experience, if you know how to work with them.

So in this course, you'll build functional, interactive front-end projects while learning how to write effective prompts and debug and refine your code with the help of AI.

No coding experience needed! We'll focus on helping you prototype and build projects with AI's assistance, turning you from a non-coder into a capable problem solver.

By the end of this course, you'll have a collection of mini-projects, newly acquired skills, and a solid foundation to keep building with AI.

You'll work on various projects using HTML, CSS, and JavaScript. Let's do this!

Join for Free: Learn to code with AI

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AI for Everyday Life

 

What you'll learn

Craft an input and output using the prompt engineering methods for generative AI

Apply your knowledge of one prompt engineering method to a real-world scenario

Articulate two methods of prompt engineering for everyday uses.

There are 2 modules in this course

This course takes the mystery generative artificial intelligence (gen-AI) and explains its uses straightforward language for people who want to use it in their everyday lives. 

Knowing how to describe and use generative AI effectively is an Important skillset to successfully engaging in all types of personal communication, from social media posts to emails and blogs. Learners will gain a clear understanding what generative AI is and learn the fundamental skills required to use gen-AI ethically and effectively. Participants will be provided tested methods for prompting an AI Assistant, such as ChatGPT, Claude, and Gemini to yield useful results.

Join for Free: AI for Everyday Life

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Circle Marker on Map using Python

 

import folium

# Create map

m = folium.Map(location=[37.7749, -122.4194], zoom_start=13)

# Add a circle marker

folium.CircleMarker(

    location=[37.7749, -122.4194],

    radius=50,

    popup="San Francisco",

    color="blue",

    fill=True,

    fill_color="blue",

).add_to(m)

# Display map in Jupyter

m

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EQUILIBRIUM INDEX IN ARRAY in Python

 

The Equilibrium Index of an array is an index where the sum of the elements on the left side of the index is equal to the sum of the elements on the right side.

def find_equilibrium_index(arr):

    total_sum = sum(arr)

    left_sum = 0

    for i, num in enumerate(arr):

        total_sum -= num  

        

        if left_sum == total_sum:

            return i 

        

        left_sum += num  

    

    return -1  

# Example usage

arr = [1, 3, 5, 2, 2]

equilibrium_index = find_equilibrium_index(arr)

print(f"Equilibrium Index: {equilibrium_index}")

#source code --> clcoding.com

Equilibrium Index: 2

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Object-Oriented Programming in Python

 What you'll learn

Construct Python classes to encapsulate state and functionality

Instantiate objects and appropriately access attributes

Skills you'll practice

Software Engineering

Computer Programming

Python Programming

Object Oriented CSS

Inheritance Patterns

Learn, practice, and apply job-ready skills in less than 2 hours

Receive training from industry experts

Gain hands-on experience solving real-world job tasks

Build confidence using the latest tools and technologies

About this Guided Project

In this project, you will gain hands-on experience working with classes in Python to model real-world objects and systems. By the end, you will be able to utilize key object-oriented programming principles like inheritance and polymorphism.

We will build an interactive boxing match simulation using Python classes to represent different fighters. You will learn how to define class attributes, instantiate object instances, and customize behaviors through methods. The concepts covered translate to building all types of apps.

Join for Free: Object-Oriented Programming in Python

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Python Programming Projects Workbook for Kids: Master Python in 1 month with 150 Outrageously Fun Small Python Programs for Kids (Coding for Absolute Beginners)

 Python Workbook for Kids and Beginners with 150 Hands-On Small Python Projects

This is an interactive workbook which is a gateway to the exciting world of coding in Python.

⭐️ 1st BONUS: List of 10 Coding Projects to Practice

⭐️ 2nd BONUS: 15 Inspirational Quotes by Programmers

⭐️ 3rd BONUS: 10 Most Common Programming Errors and their Solutions

Structured as a comprehensive guide, this workbook takes young learners on a journey through Python programming, starting with the basics and gradually building up to more advanced concepts. Each chapter is meticulously crafted to provide a step-by-step approach to learning, making it easy for kids to follow along and grasp even the most complex topics.

What sets this workbook apart is its interactive format. Instead of passively reading through lessons, kids are encouraged to roll up their sleeves and dive into the coding exercises. With each program, they'll gain hands-on experience writing code, debugging errors, and seeing their creations come to life right before their eyes.

From simple programs like printing messages and performing basic math operations to more advanced projects like creating animations using the Turtle module, every exercise in this workbook is designed to be both educational and outrageously fun. As kids work their way through the exercises, they'll not only master Python programming but also develop critical thinking skills, problem-solving abilities, and a deep passion for coding.

Whether used in a classroom setting or as a self-paced learning resource at home, the "Python Programming Projects Workbook for Kids" is the perfect companion for young learners eager to embark on their coding journey. With its workbook format, interactive exercises, and playful approach to programming, this book transforms learning Python into an exciting adventure that kids won't want to put down.

As you work through the book, you’ll learn how to:

Write your first Python Program

5 Basic Python Concepts that are Essential to Success as a Beginner in Coding

Troubleshoot coding errors for each Python Concept

Build programs that allow users to create accounts and manage their own data

Create animations in Python using a module that draws objects on the screen, and responds to user pressing keys.

Answers to all questions in the workbook at the end of the book 

eBook: Python Programming Projects Workbook for Kids: Master Python in 1 month with 150 Outrageously Fun Small Python Programs for Kids (Coding for Absolute Beginners)

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Python Programming for Students and Beginners: Coding stories for high school students, kids, and new programmers

 

Unlock the World of Python Programming with Fun and Easy-to-Follow Stories!

Are you a high school student, a curious kid, or a beginner looking to dive into the world of coding? "Python Programming for Students and Beginners" is the perfect guide for you! This book takes you on an exciting journey through the basics of Python, using fun, relatable stories that make learning to code enjoyable and accessible.

Designed with students, kids, and new programmers in mind, this book breaks down complex programming concepts into simple, easy-to-understand lessons. You will follow along with coding stories that help you grasp the fundamentals of Python, all while building real-world skills.

What You will Learn:

Python Basics: Learn to install Python, understand variables and data types, and write your first program.

Fun Coding Stories: Enjoy coding adventures like creating your virtual pet, building a chatbot, and automating everyday tasks.

Problem-Solving: Learn to think like a programmer with hands-on exercises and examples that challenge creativity.

Real-World Skills: Explore how Python is used in web development, data science, game creation, and automation.

Who Is This Book For?

High School Students: If you are starting to code, this book will help you develop a solid foundation in Python.

Curious Kids: Fun and interactive coding stories will keep younger readers engaged while they learn programming.

New Programmers: Beginners of all ages will find this book easy to follow, with practical examples and step-by-step guides.

Why You will Love This Book:

Easy-to-Understand: No prior coding experience needed! Every chapter is written in clear, simple language that anyone can follow.

Hands-On Projects: Get ready to build real programs that solve problems and help you practice your skills.

Engaging Stories: Each coding lesson is designed as a fun story, keeping you entertained as you learn.

"Python Programming for Students and Beginners" is more than just a textbook—it is an adventure into the world of programming! Whether you’re learning for school, starting a new hobby, or curious about the power of Python, this book is your gateway to becoming a confident coder. 

eBook: Python Programming for Students and Beginners: Coding stories for high school students, kids, and new programmers

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Why is it not same in Python?

 

Explanation:

a = 0.2 + 0.4:

This line adds 0.2 and 0.4, resulting in 0.6.

However, due to floating-point precision limitations in computers, the actual value stored in a might be slightly different from the exact mathematical value of 0.6.

b = 0.6:

This line assigns the value 0.6 directly to b.

print(a == b):

This line compares the values of a and b. Since the values might differ slightly due to floating-point precision, the comparison evaluates to False.

a = 0.1 + 0.3:

This line adds 0.1 and 0.3, resulting in 0.4.

Again, due to floating-point precision, the actual value stored in a might be slightly different from the exact mathematical value of 0.4.

b = 0.4:

This line assigns the value 0.4 directly to b.

print(a == b):

This line compares the values of a and b. In this case, the values might be close enough within the floating-point precision, so the comparison evaluates to True.

Key Points:

Floating-point numbers are represented in binary format with limited precision, which can lead to slight inaccuracies when performing arithmetic operations.

Comparing floating-point numbers for exact equality can be unreliable due to these precision limitations.

If you need to compare floating-point numbers for equality, it's often better to check if they are within a certain tolerance range rather than expecting exact equality.

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Careful with chained operations

 

Let's break down the expressions one by one:

1. (False == False) in [False]

(False == False): This evaluates to True, because False is equal to False.

True in [False]: Now the expression becomes True in [False]. This checks if True is in the list [False].

The result is False because the list only contains False, not True.

So, the overall result of (False == False) in [False] is False.

2. False == (False in [False])

(False in [False]): This checks if False is in the list [False].

This is True because False is indeed in [False].

False == True: Now the expression becomes False == True.

This is False because False is not equal to True.

So, the overall result of False == (False in [False]) is False.

3. False == False in [False]

This is a chained comparison, equivalent to:

(False == False) and (False in [False])

False == False: This is True because False is equal to False.

False in [False]: This is True because False is in the list [False].

So, the overall result of False == False in [False] is True.

Summary of Results:

(False == False) in [False]: False

False == (False in [False]): False

False == False in [False]: True

Each expression behaves differently based on how the logical comparisons and list membership are evaluated.

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Convert PDF files to Excel files using Python

 

pip install pdfplumber pandas openpyxl

import pdfplumber

import pandas as pd

def pdf_to_excel(pdf_file, excel_file):

    

    with pdfplumber.open(pdf_file) as pdf:

        all_tables = []

        for page in pdf.pages:

            tables = page.extract_tables()

            for table in tables:

                if table:  

                    df = pd.DataFrame(table)

                    all_tables.append(df)

        if not all_tables:

            all_tables.append(pd.DataFrame([["No tables found"]]))

        with pd.ExcelWriter(excel_file, engine='openpyxl') as writer:

            for idx, df in enumerate(all_tables):

                df.to_excel(writer, sheet_name=f'Sheet{idx+1}', index=False)

pdf_to_excel('clcodingpdff.pdf', 'clcoding.xlsx')

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Create Audio Book using Python

 

from gtts import gTTS

import os

def create_audiobook(text_file, output_file):

    with open(text_file, 'r', encoding='utf-8') as file:

        text = file.read()

    tts = gTTS(text=text, lang='en')

    tts.save(output_file)

    print(f"Audiobook saved as {output_file}")

text_file = "clcodingtxt.txt"  

output_file = "audiobook.mp3"

create_audiobook(text_file, output_file)

os.system(f"start {output_file}")  

#source code --> clcoding.com

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Generate Emoji using Python

 

import emoji

def text_to_emoji(text):

    return emoji.emojize(text)

input_text = input("Enter text with emoji aliases : ")

converted_text = text_to_emoji(input_text)

print("Converted Text with Emojis:", converted_text)

#source code --> clcoding.com

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Python Program to Check Email Accounts Across Services

 

import subprocess

def check_email(email):

    result = subprocess.run(["holehe", email],

                            capture_output=True, text=True)

    return result.stdout

email = input("Enter the email: ")

response = check_email(email)

print(response)

#source code --> clcoding.com

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A Quick Guide to Learning Python: Easy Coding, Designed for Beginners | Free

 

Mastering a programming language requires understanding code and writing it effectively. This book offers quizzes to improve skills in reading and understanding code, while the exercises aim to improve writing code skills.

Each chapter starts with an explanation and code examples and is followed by exercises and quizzes, offering an opportunity for self-testing and understanding which level you achieved.

This book goes beyond the traditional approach by explaining Python syntaxes with real-world code examples. This approach makes learning exciting and ensures readers can apply their knowledge effectively. The included exercises and quizzes, along with their solutions, provide a guarantee to readers and empower them to create simple yet valuable programs.

Learning one computer language facilitates learning other computer languages. This principle arises from rules and logic that connect computer languages. A confirmation of this was when I was asked to teach the C# programming language at the University of Applied Science. Despite having no experience with C#, I dedicated a weekend to diving into the language and realized it wasn't fundamentally different from other object-oriented programming languages.

Python is also a language reliant on object-oriented programming principles. Our focus is real-world examples, enabling you to apply these concepts in your programming works. Learning programming is a communication tool with computers, as machines operate using their language defined by specific logical structures and sentences known as statements.

Free Kindle : A Quick Guide to Learning Python: Easy Coding, Designed for Beginners

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Create table using Python

 

Rich allows you to display data in well-formatted tables, useful for presenting data in a structured manner.

Use Case: Displaying tabular data in the terminal (e.g., database results, CSV data).

from rich.table import Table

from rich.console import Console

console = Console()

table = Table(title="User Data")

table.add_column("ID", justify="right", style="cyan", no_wrap=True)

table.add_column("Name", style="magenta")

table.add_column("Age", justify="right", style="green")

table.add_row("1", "Alice", "28")

table.add_row("2", "Bob", "32")

table.add_row("3", "Charlie", "22")

console.print(table)

      User Data       

┏━━━━┳━━━━━━━━━┳━━━━━┓

┃ ID ┃ Name    ┃ Age ┃

┡━━━━╇━━━━━━━━━╇━━━━━┩

│  1 │ Alice   │  28 │

│  2 │ Bob     │  32 │

│  3 │ Charlie │  22 │

└────┴─────────┴─────┘

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Rich – Display colorful, formatted console output using Python

 

pip install rich

from rich.console import Console

console = Console()

message = "Welcome to [bold magenta]clcoding.com[/bold magenta]"

style = "bold green"

console.print(message, style=style)

#clcoding.com

Welcome to clcoding.com

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Python Coding challenge - Day 244 | What is the output of the following Python Code?

 

In this code snippet:

s = 'clcoding'

index = s.find('z')

print(index)

s = 'clcoding': This assigns the string 'clcoding' to the variable s.

s.find('z'): The .find() method is used to search for the first occurrence of the specified substring 'z' in the string s. If the substring is found, it returns the index (position) of its first occurrence. If the substring is not found, .find() returns -1.

Since 'z' is not in the string 'clcoding', s.find('z') will return -1.

print(index): This prints the value of index, which in this case is -1.

Output:  -1

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