Topics: Coronavirus | AI | Data Science | Deep Learning | Machine Learning | Python | R | Statistics

KDnuggets Home » News » 2020 » May » Tutorials, Overviews » Python For Everybody: The Free eBook ( 20:n21 )

Gold BlogPython For Everybody: The Free eBook


Get back to fundamentals with this free eBook, Python For Everybody, approaching the learning of programming from a data analysis perspective.



Openshare twitter count:
0

It's a new week, which means it's also time to profile and share a new free eBook. This week we get back to basics with Python For Everybody, written by Charles R. Severance, a book intended to develop or strengthen your foundational Python programming skills.

Figure

 

Python For Everybody was written as an accompanying text for Python for Everybody Specialization on Coursera, Python for Everybody (2 courses) on edX, and Python for Everybody (2 courses) on FutureLearn, all of which were also created by the book's author.

This book is particularly suited to individuals looking to learn Python in the context of data science and data analytics, according to the author:

The goal of this book is to provide an Informatics-oriented introduction to programming. The primary difference between a computer science approach and the Informatics approach taken in this book is a greater focus on using Python to solve data analysis problems common in the world of Informatics.

First off, you should know that Python for Everybody uses Python 3, though an older version of the book using Python 2 is still available should you, for some reason, want to learn Python 2 (you should definitely not want to do so, however). It is also code-centric, not spending much time on programming theory but rather jumping right to implementation.

Simply put, Python For Everybody teaches you what you need to know about Python to get writing practically useful code right now, particularly from a data analysis perspective.

The book's table of contents are as follows:

  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 review of the Kindle version of this book on Amazon states the following:

I have not found a better beginner Python book out there. Plus, now that I am a professional Python programmer, I find myself constantly referring to this book to clarify certain points and reinforce understanding of basic principles. (I may be a professional, but I'm still a rookie.) I've purchased a few fat, expensive Python programming books with animals on the cover, but these tend to collect dust. In short, I have a new-found appreciation for this book and how much work went in to writing it. Thanks, Professor Severance!

And it's not the only positive review; 448 ratings of the book with an average of 4.6 out of 5 should tell you that many others have also found Python for Everybody useful. The consensus seems to be that the book quickly covers concepts, does so in an easily understandable manner, and jumps right into the corresponding code.

Aside from English, the book is also available in Spanish, Italian, Portuguese, and Chinese. You can find further information and links to these editions on the book's website.

Download the PDF here. You can optionally read the book as a series of interactive Jupyter notebooks here. If you like the book and want to support the author, paperback and electronic (Kindle) copies can be purchased on Amazon.

If you are new to data science and are looking to get a grip on one of the field's most dominant programming languages, freely-available Python for Everybody is a book that should be at the top of your list.

 
Related:


Sign Up

By subscribing you accept KDnuggets Privacy Policy