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Python For Everyone, 3rd Edition

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Python For Everyone, 3rd Edition

Cay S. Horstmann, Rance D. Necaise

ISBN: 978-1-119-49853-7 December 2018

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Description

Python for Everyone, 3rd Edition is an introduction to programming designed to serve a wide range of student interests and abilities, focused on the essentials, and on effective learning. It is suitable for a first course in programming for computer scientists, engineers, and students in other disciplines. This text requires no prior programming experience and only a modest amount of high school algebra. Objects are used where appropriate in early chapters and students start designing and implementing their own classes in Chapter 9. New to this edition are examples and exercises that focus on various aspects of data science.

Related Resources

Just the Right Amount of Python:
The goal of this book is to teach good programming and computer science with Python as the means of instruction and not an end in itself. This edition accelerates the coverage of convenience operations for working with strings and lists.

Interactive Learning:
Interactive content is front and center, with immersive activities integrated with the text to foster in depth learning. Students don't just watch animations and code traces, they work on generating them right in the eText.

Integrated Live Coding:
Live code samples invite the reader to experiment and to learn programming constructs first hand. The activities provide instant feedback to show students what they did right and where they need to study more.

A Focus on Data Science:
The methods of data science are becoming so important that students in many disciplines, not just computer scientists, are eager to learn the fundamentals of programming. Python is uniquely positioned as the “go to” language for budding data scientists, due to its logical structure, interactive programming libraries that invite exploration, and a wealth of libraries for data manipulation.This edition provides examples and exercises that focus on various aspects of data science.

More Toolboxes:
Students are empowered to perform useful work such as statistical computations, drawing graphs and charts, sending e-mail, processing spreadsheets, and analyzing web pages. The libraries are placed in the context of computer science principles, and students learn how those principles apply to solving real-world problems. Many new end-of-chapter review and programming exercises have been added to the toolboxes, as well as additional toolboxes on turtle graphics and game
programming.