Doing Math with Python: Use Programming to Explore Algebra, Statistics, Calculus, and More!

by Amit Saha

In Doing Math with Python you'll learn to how to use the Python programming language as a tool to delve into math concepts. Python is easy to learn, and it's perfect for exploring topics like statistics, geometry, probability, and calculus. You’ll learn to write programs to find derivatives, solve equations graphically, manipulate algebraic expressions, even examine projectile motion.

Rather than crank through tedious calculations by hand, you'll learn how to use Python functions and modules to handle the number crunching while you focus on the principles behind the math. Exercises throughout teach fundamental programming concepts, like using functions, handling user input, and reading and manipulating data. As you learn to think computationally, you'll discover new ways to explore and think about math, and gain valuable programming skills that you can use to continue your study of math and computer science.

If you’re interested in math but have yet to dip into programming, you’ll find that Python makes it easy to go deeper into the subject—let Python handle the tedious work while you spend more time on the math.

Genres: Programming, Mathematics, Nonfiction, Computer Science, Computers, Reference, Technology

264 pages, Kindle Edition

First published March 1, 2015

Reviews

[Jake · Rating 5 out of 5]

This book is, undoubtedly, meant for a younger audience and is more of a cookbook of ideas than a textbook on the topic. That said, Amit gave a lot of ideas to write small hacks to automate my undergrad education. I kept thinking to myself, if only I had a netbook and SymPy when I was back in middle school, learning math would have been much more enjoyable.

The book really gave me a vibe, not unlike that which the maker community has with kids. It really shows you the immediate reward feedback loop of why learning this trade to automate or illuminate your mathematics is worth it. For this reason I plan on getting a copy for my nephews. I refuse to give books to others before reading them myself, and I'm glad I did. It was a real delight.

[Venkatesh-Prasad · Rating 4 out of 5]

The book provides a good introduction to SymPy and Matplotlib besides demonstrating how to use the stock features of Python libraries for basic number crunching and statistics. Folks who would like to use Python for numerical computations but haven't done so yet will find the book most helpful.

[William Schram · Rating 5 out of 5]

This book uses Python to teach basic High School Math. Now a lot of the stuff you do is through modules that already exist in Python. However, since you are able to manipulate the data and do other things like draw graphs, it presents a representation that is visible and more easily understood. Now the big thing about this is that it won't really be Earth-shattering unless you go and put in effort to do it. That goes for pretty much everything though I suppose.

The book guides you through installing Python and some other program that allows you to run your programs. It gives you basic grounding in IDLE, and allows you to use this program called Anaconda to run the programs you wrote. Anaconda is a bit like cmd.exe, and the other book I had recommended that I use Powershell, so I don't really have a preference yet. Challenges that are in the book have their answers online, or at least one way to do it.

This book assumes some grounding in Python and thus does not explain all of the notation that it uses. I still don't know what if __name__ == '__main__': is supposed to do, but taking it out ruins the code, so I put it in. Along the way it covers graphs, statistics, algebra, trigonometry, and calculus.

A very good reference for a beginner programmer, like me. If you are more advanced, you might become bored with what the author is talking about, since he doesn't delve too deep into the mysteries of Python.

Edit: Okay, I don't know how, but I missed the part in the book that explained if __name__ == '__main__':. Apparently it allows you to reuse blocks of code.

[Martin · Rating 4 out of 5]

A little more explanation of mathematical concepts at the end
would have been nice.

[Stephen · Rating 4 out of 5]

Very good book. Interesting applications of Python to plotting, statistics, and calculus. There's even a section covering chaos math and the Mandelbrot set. I recommend this book.

[MarkH · Rating 2 out of 5]

I wasn't a huge fan of this book. It was obviously written for someone with very little programming experience, but I still didn't think it was very good. I thought the code samples were subpar and there wasn't any depth to the topics. Not a lot of value was there beyond holding your hand as it walked you through the most basic of library functions.

[Alb85 · Rating 3 out of 5]

Libro che dà delle nozioni di base su come applicare i concetti matematici attraverso la programmazione in Python.

Il libro è breve e spiega come:
- scrivere e risolvere equazioni
- rappresentare nel piano cartesiano le equazioni
- disegnare figure geometriche
- scrivere e risolvere derivate ed integrali

[Craig Beyers · Rating 4 out of 5]

This book is a good introduction to Python, with some basic programming guidance included. It does not mention the free, downloadable Anaconda version of Python, probably because it was written and published prior to the Anaconda distribution availability.

[Poki · Rating 4 out of 5]

mmm maths

[Zee · Rating 4 out of 5]

8,5/10

Cuốn sách cơ bản nếu muốn tìm hiểu về Python (beginner) và việc viết toán bằng Python.
Mình khá thích cách trình bày của mấy cuốn kiểu này, siêu dễ hiểu.

[Stefan · Rating 4 out of 5]

A solid introduction to Python for all your math homework. Nice to see Python 3, but missed to introduce projects from vast Python ecosystem and open gates to higher math (or instill interest in it), however I guess the second wasn't the book main goal (hence 4 vs. 3 stars).