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    Read more about Python for Everybody: Exploring Data Using Python 3

    Python for Everybody: Exploring Data Using Python 3

    (14 reviews)

    Charles Severance, University of Michigan

    Copyright Year:

    ISBN 13: 9781530051120

    Publisher: Charles Severance

    Language: English

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    Reviewed by KYLE NASH, Assistant Professor of Management, Metropolitan State University on 2/18/24

    The book is deemed suitable for everyone interested in exploring Python, offering a clear and comprehensive explanation of fundamental concepts. It covers a wide range of topics, including regular expressions, databases, web services, and data... read more

    Reviewed by Bhanumathi Selvaraj, Adjunct Faculty, Bunker Hill Community College on 3/27/23

    The book is suitable for everybody who wants to explore Python language without any other programming background. It provides a comprehensive and clear explanation on the fundamental concepts of Python such as data types, data structures,... read more

    Reviewed by Diane Rhodes, Adjunct Instructor, Metropolitan State University of Denver on 2/25/23

    The book is structured to allow readers to learn at their own pace. Each chapter introduces new concepts and reinforces them through practical examples and exercises. The explanations are clear and concise, and the examples are well thought out... read more

    Reviewed by Youyou Tao, Assistant Professor, Loyola Marymount University on 2/25/22

    I've taught programming for about four years. The topics that I covered in my courses include fundamental concepts and topics in Python programming, web scraping, and Python for data analytics. I've struggled a long time to find a textbook that... read more

    Reviewed by Maira Monteiro, Assistant Professor, Seattle Pacific University on 1/3/22

    This is a great introductory textbook addressing the main aspects of Python. Topics are covered with up-to-the-point discussions and meaningful examples. It is a powerful resource for beginners in the topic, meaningfully supporting the Open... read more

    Reviewed by Micheline Al Harrack, Continuing Instructor, Marymount University on 11/19/21

    This text can be broken down into two parts: the first ten chapters constitute a comprehensive introduction to basic Python concepts while the remaining chapters explore topics related to data acquisition and visualization (web, databases, SQL).... read more

    Reviewed by Mya T. Bowen, Assistant Professor, Roxbury Community College on 6/17/21

    The text covers all areas and ideas of the subject appropriately and provides an effective glossary at the end of every chapter. read more

    Reviewed by Shahab Hussain, Adjunct Professor, North Shore Community College on 6/2/21

    This book presents majority of the Python Programming critical areas and explains with useful examples. read more

    Reviewed by Syeda Ferdous Begum, Professor, Middlesex Community College on 4/14/21, updated 4/20/21

    This book great for beginner programmer who does not know anything about programming. This text can be used in the computer science and information technology field. Even though it is targeted towards beginners, it contains advanced topics but... read more

    Reviewed by Sankardas Roy, Assistant Professor, Bowling Green State University on 1/31/21

    As the title suggests, the intended audience of this book is "everybody" who wants to explore Python for data analysis work. The book does cover the basics of Python programming, giving sufficient amount of subject details for a new programmer.... read more

    Reviewed by Kuuipo Walsh, Director, Oregon State University on 8/28/20

    Dr. Charles R. Severance's book introduces the fundamentals of Python programming in Chapters 1-10, without diving deeply into object-oriented programming. These chapters focus on code examples manipulating text and text files. Given the title, it... read more

    Reviewed by Joe Paris, Faculty, Linn-Benton Community College on 7/2/20

    This book is an approachable introduction to both Python the language and its application to information science -- namely retrieving, cleaning, and storing data for later analysis. Chapters two through ten are based heavily on Allen Downey and... read more

    Reviewed by Matt Bailey, Associate Professor, Bucknell University on 2/25/19

    The book is a comprehensive and approachable introduction to Python. The first nine chapters are terse, but comprehensive introduction to Python. Given the title, I had expected some discussion of the pandas Python package. It is more geared... read more

    Reviewed by Giancarlo Schrementi, Instructor, Hollins University on 5/21/18

    This book is a remix of the excellent Think Python book by Allen Downey. The book keeps the clarity of the original while including examples skewed towards data applications, particularly text processing. The remix adds chapters on regular... read more

    Table of Contents

    • 1 Why should you learn to write programs?
    • 2 Variables, expressions, and statements
    • 3 Conditional execution
    • 4 Functions
    • 5 Iteration
    • 6 Strings
    • 7 Files
    • 8 Lists
    • 9 Dictionaries
    • 10 Tuples
    • 11 Regular expressions
    • 12 Networked programs
    • 13 Using Web Services
    • 14 Object-Oriented Programming
    • 15 Using databases and SQL
    • 16 Visualizing data
    • A Contributions
    • B Copyright Detail

    Ancillary Material

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    About the Book

    I never seemed to find the perfect data-oriented Python book for my course, so I set out to write just such a book. Luckily at a faculty meeting three weeks before I was about to start my new book from scratch over the holiday break, Dr. Atul Prakash showed me the Think Python book which he had used to teach his Python course that semester. It is a well-written Computer Science text with a focus on short, direct explanations and ease of learning.The overall book structure has been changed to get to doing data analysis problems as quickly as possible and have a series of running examples and exercises about data analysis from the very beginning.

    Chapters 2–10 are similar to the Think Python book, but there have been major changes. Number-oriented examples and exercises have been replaced with data- oriented exercises. Topics are presented in the order needed to build increasingly sophisticated data analysis solutions. Some topics like try and except are pulled forward and presented as part of the chapter on conditionals. Functions are given very light treatment until they are needed to handle program complexity rather than introduced as an early lesson in abstraction. Nearly all user-defined functions have been removed from the example code and exercises outside of Chapter 4. The word “recursion”1 does not appear in the book at all.

    In chapters 1 and 11–16, all of the material is brand new, focusing on real-world uses and simple examples of Python for data analysis including regular expressions for searching and parsing, automating tasks on your computer, retrieving data across the network, scraping web pages for data, object-oriented programming, using web services, parsing XML and JSON data, creating and using databases using Structured Query Language, and visualizing data.

    The ultimate goal of all of these changes is a shift from a Computer Science to an Informatics focus is to only include topics into a first technology class that can be useful even if one chooses not to become a professional programmer.

    About the Contributors


    Charles Severance is a Clinical Associate Professor at the University of Michigan School of Information.

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