This student-friendly textbook encourages the development of programming skills through active practice by focusing on exercises that support hands-on learning. The Python Workbook provides a compendium of 186 exercises, spanning a variety of academic disciplines and everyday situations. Solutions to selected exercises are also provided, supported by brief annotations that explain the technique used to solve the problem, or highlight a specific point of Python syntax. This enhanced new edition has been thoroughly updated and expanded with additional exercises, along with concise introductions that outline the core concepts needed to solve them. The exercises and solutions require no prior background knowledge, beyond the material covered in a typical introductory Python programming course. Features: uses an accessible writing style and easy-to-follow structure; includes a mixture of classic exercises from the fields of computer science and mathematics, along with exercises that connect to other academic disciplines; presents the solutions to approximately half of the exercises; provides annotations alongside the solutions, which explain the approach taken to solve the problem and relevant aspects of Python syntax; offers a variety of exercises of different lengths and difficulties; contains exercises that encourage the development of programming skills using if statements, loops, basic functions, lists, dictionaries, files, and recursive functions. Undergraduate students enrolled in their first programming course and wishing to enhance their programming abilities will find the exercises and solutions provided in this book to be ideal for their needs.

While other textbooks devote their pages to explaining introductory programming concepts, The Python Workbook focuses exclusively on exercises, following the philosophy that computer programming is a skill best learned through experience and practice. Designed to support and encourage hands-on learning about programming, this student-friendly work contains 174 exercises, spanning a variety of academic disciplines and everyday situations. Solutions to selected exercises are also provided, supported by brief annotations that explain the technique used to solve the problem, or highlight specific points of Python syntax. No background knowledge is required to solve the exercises, beyond the material covered in a typical introductory Python programming course. Undergraduate students undergoing their first programming course and wishing to enhance their programming abilities will find the exercises and solutions provided in this book to be ideal for their needs.

This student-friendly textbook encourages the development of programming skills through active practice by focusing on exercises that support hands-on learning. The Python Workbook provides a compendium of 186 exercises, spanning a variety of academic disciplines and everyday situations. Solutions to selected exercises are also provided, supported by brief annotations that explain the technique used to solve the problem, or highlight a specific point of Python syntax. This enhanced new edition has been thoroughly updated and expanded with additional exercises, along with concise introductions that outline the core concepts needed to solve them. The exercises and solutions require no prior background knowledge, beyond the material covered in a typical introductory Python programming course. Features: uses an accessible writing style and easy-to-follow structure; includes a mixture of classic exercises from the fields of computer science and mathematics, along with exercises that connect to other academic disciplines; presents the solutions to approximately half of the exercises; provides annotations alongside the solutions, which explain the approach taken to solve the problem and relevant aspects of Python syntax; offers a variety of exercises of different lengths and difficulties; contains exercises that encourage the development of programming skills using if statements, loops, basic functions, lists, dictionaries, files, and recursive functions. Undergraduate students enrolled in their first programming course and wishing to enhance their programming abilities will find the exercises and solutions provided in this book to be ideal for their needs.

Python Workbook for Beginners with Hands-On ProjectsAre you looking for a hands-on approach to learn Python fast? Or perhaps you have just completed a Python course and are looking for practice questions to test your Python skills.Do you have problems with some Python concepts and are looking for a workbook to provide you with more questions and solutions to learn from?This workbook is for you.This book is designed to be the accompanying workbook for the book "Learn Python In One Day and Learn It Well (2nd Edition)" by the same author. It can also be used as a standalone workbook for you to test and improve your knowledge of the Python syntax.What this book offers...Carefully designed questionsEach question in this workbook is crafted to help you gradually build your programming skills, focusing on one or two concepts at a time and increasing in level of difficulty as we progress through the chapters.Clear and Easy to Understand SolutionsAll solutions in this book are extensively tested by a group of beta readers. The solutions provided are simplified as much as possible so that they can serve as examples for you to refer to when you are learning a new syntax.Two Projects to Consolidate Your LearningThis workbook also includes two projects at the end to help you consolidate your learning. While the individual chapters prior to the projects help you learn one concept at a time, these two projects require the application of multiple concepts covered in previous chapters and allow you to see how everything works together.What this book aims to do...This workbook is written with one goal in mind - to help new programmers overcome their initial obstacles to learning.A lot of times, when new programmers look at code written by other programmers, they tend to feel intimidated as a lot of the code looks complicated to them. A complete program written by other programmers incorporates many different concepts.The goal of this workbook is to isolate the different concepts so that new programmers can gradually gain competency in the fundamentals of the language before working on bigger projects at the end of the book. Programming does not have to be scary or frustrating when you take one step at a time.Ready to start practicing and building your Python skills? Click the BUY button now to download this workbook.Topics Covered: - Variables and Mathematical Operations in Python- Common data types, including integers, floats, strings- Lists, Tuples and Dictionaries- String Formatting- Accepting user inputs and displaying outputs- Comparison and Condition Statements- Control flow tools in Python- How to handle errors and exceptions- What are functions and modules?- How to define your own functions and modules- How to work with external files- Object Oriented Programming Concepts- Classes, Subclasses and Inheritance..and more...Click the BUY button now to start learning and practicing your Python skills. Learn it fast and learn it well.

The second edition of the best-selling Python for Kids—which brings you (and your parents) into the world of programming—has been completely updated to use the latest version of Python, along with tons of new projects! Python is a powerful programming language that’s easy to learn and fun to use! But books about programming in Python can be dull and that’s no fun for anyone. Python for Kids brings kids (and their parents) into the wonderful world of programming. Jason R. Briggs guides you through the basics, experimenting with unique (and hilarious) example programs featuring ravenous monsters, secret agents, thieving ravens, and more. New terms are defined; code is colored and explained; puzzles stretch the brain and strengthen understanding; and full-color illustrations keep you engaged throughout. By the end of the book, you’ll have programmed two games: a clone of the famous Pong, and “Mr. Stick Man Races for the Exit”—a platform game with jumps and animation. This second edition is revised and updated to reflect Python 3 programming practices. There are new puzzles to inspire you and two new appendices to guide you through Python’s built-in modules and troubleshooting your code. As you strike out on your programming adventure, you’ll learn how to: Use fundamental data structures like lists, tuples, and dictionaries Organize and reuse your code with functions and modules Use control structures like loops and conditional statements Draw shapes and patterns with Python’s turtle module Create games, animations, and other graphical wonders with tkinter Why should serious adults have all the fun? Python for Kids is your ticket into the amazing world of computer programming. Covers Python 3.x which runs on Windows, macOS, Linux, even Raspberry Pi

This workbook (which is the Part 1) has been specifically put together to help absolute beginners in Python to improve their programming skills. Contained in this eBook are over 70 questions and their answers/explanations on variables, strings, lists, tuples, operators, sets, if statements, loops, arrays, functions, and some other fundamental Python questions for beginners. So if you're an absolute beginner in the world of Python programming, you won't go wrong with making use of this workbook to improve your skills.

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms