
Author 
Amit Saha 
ISBN10 
9781593276409 
Year 
2015 
Pages 
264 
Language 
en 
Publisher 
No Starch Press 
DOWNLOAD NOW
READ ONLINE
Doing Math with Python shows you how to use Python to delve into high school–level math topics like statistics, geometry, probability, and calculus. You’ll start with simple projects, like a factoring program and a quadraticequation solver, and then create more complex projects once you’ve gotten the hang of things. Along the way, you’ll discover new ways to explore math and gain valuable programming skills that you’ll use throughout your study of math and computer science. Learn how to: Describe your data with statistics, and visualize it with line graphs, bar charts, and scatter plots Explore set theory and probability with programs for coin flips, dicing, and other games of chance Solve algebra problems using Python’s symbolic math functions Draw geometric shapes and explore fractals like the Barnsley fern, the Sierpinski triangle, and the Mandelbrot set Write programs to find derivatives and integrate functions Creative coding challenges and applied examples help you see how you can put your new math and coding skills into practice. You’ll write an inequality solver, plot gravity’s effect on how far a bullet will travel, shuffle a deck of cards, estimate the area of a circle by throwing 100,000 “darts” at a board, explore the relationship between the Fibonacci sequence and the golden ratio, and more. Whether you’re interested in math but have yet to dip into programming or you’re a teacher looking to bring programming into the classroom, you’ll find that Python makes programming easy and practical. Let Python handle the grunt work while you focus on the math.

Author 
Amit Saha 
ISBN10 
9781593277192 
Year 
20150801 
Pages 
264 
Language 
en 
Publisher 
No Starch Press 
DOWNLOAD NOW
READ ONLINE
Doing Math with Python shows you how to use Python to delve into high school–level math topics like statistics, geometry, probability, and calculus. You’ll start with simple projects, like a factoring program and a quadraticequation solver, and then create more complex projects once you’ve gotten the hang of things. Along the way, you’ll discover new ways to explore math and gain valuable programming skills that you’ll use throughout your study of math and computer science. Learn how to: –Describe your data with statistics, and visualize it with line graphs, bar charts, and scatter plots –Explore set theory and probability with programs for coin flips, dicing, and other games of chance –Solve algebra problems using Python’s symbolic math functions –Draw geometric shapes and explore fractals like the Barnsley fern, the Sierpinski triangle, and the Mandelbrot set –Write programs to find derivatives and integrate functions Creative coding challenges and applied examples help you see how you can put your new math and coding skills into practice. You’ll write an inequality solver, plot gravity’s effect on how far a bullet will travel, shuffle a deck of cards, estimate the area of a circle by throwing 100,000 "darts" at a board, explore the relationship between the Fibonacci sequence and the golden ratio, and more. Whether you’re interested in math but have yet to dip into programming or you’re a teacher looking to bring programming into the classroom, you’ll find that Python makes programming easy and practical. Let Python handle the grunt work while you focus on the math. Uses Python 3

Author 
Amit Saha 
ISBN10 
9781593277192 
Year 
20150801 
Pages 
264 
Language 
en 
Publisher 
No Starch Press 
DOWNLOAD NOW
READ ONLINE
Doing Math with Python shows you how to use Python to delve into high school–level math topics like statistics, geometry, probability, and calculus. You’ll start with simple projects, like a factoring program and a quadraticequation solver, and then create more complex projects once you’ve gotten the hang of things. Along the way, you’ll discover new ways to explore math and gain valuable programming skills that you’ll use throughout your study of math and computer science. Learn how to: –Describe your data with statistics, and visualize it with line graphs, bar charts, and scatter plots –Explore set theory and probability with programs for coin flips, dicing, and other games of chance –Solve algebra problems using Python’s symbolic math functions –Draw geometric shapes and explore fractals like the Barnsley fern, the Sierpinski triangle, and the Mandelbrot set –Write programs to find derivatives and integrate functions Creative coding challenges and applied examples help you see how you can put your new math and coding skills into practice. You’ll write an inequality solver, plot gravity’s effect on how far a bullet will travel, shuffle a deck of cards, estimate the area of a circle by throwing 100,000 "darts" at a board, explore the relationship between the Fibonacci sequence and the golden ratio, and more. Whether you’re interested in math but have yet to dip into programming or you’re a teacher looking to bring programming into the classroom, you’ll find that Python makes programming easy and practical. Let Python handle the grunt work while you focus on the math. Uses Python 3

Author 
Mahesh Venkitachalam 
ISBN10 
9781593276041 
Year 
20151001 
Pages 
352 
Language 
en 
Publisher 
No Starch Press 
DOWNLOAD NOW
READ ONLINE
Python is a powerful programming language that’s easy to learn and fun to play with. But once you’ve gotten a handle on the basics, what do you do next? Python Playground is a collection of imaginative programming projects that will inspire you to use Python to make art and music, build simulations of realworld phenomena, and interact with hardware like the Arduino and Raspberry Pi. You’ll learn to use common Python tools and libraries like numpy, matplotlib, and pygame to do things like: *Generate Spirographlike patterns using parametric equations and the turtle module *Create music on your computer by simulating frequency overtones *Translate graphical images into ASCII art *Write an autostereogram program that produces 3D images hidden beneath random patterns *Make realistic animations with OpenGL shaders by exploring particle systems, transparency, and billboarding techniques *Construct 3D visualizations using data from CT and MRI scans *Build a laser show that responds to music by hooking up your computer to an Arduino Programming shouldn’t be a chore. Have some solid, geeky fun with Python Playground. The projects in this book are compatible with both Python 2 and 3.

Author 
J.C. Bautista 
ISBN10 
9781326017965 
Year 
20140913 
Pages 
268 
Language 
en 
Publisher 
Lulu.com 
DOWNLOAD NOW
READ ONLINE
"We have developed 120 Python programs and more than 110 illustrations in a work that will be useful both to students of science of the first university science courses, as well as high school students and teachers, and to anyone interested in Python programming intending to acquire new tools to expose mathematical concepts in a didactic and modern fashion....The book begins with a detailed introduction to Python, followed by ten chapters of mathematics with its corresponding Python programs, results and graphs."Cover.

Author 
Eric Matthes 
ISBN10 
9781593276034 
Year 
20151120 
Pages 
560 
Language 
en 
Publisher 
No Starch Press 
DOWNLOAD NOW
READ ONLINE
Learn Python—Fast! Python Crash Course is a fastpaced, thorough introduction to Python that will have you writing programs, solving problems, and making things that work in no time. In the first half of the book, you’ll learn about basic programming concepts, such as lists, dictionaries, classes, and loops, and practice writing clean and readable code with exercises for each topic. You’ll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you’ll put your new knowledge into practice with three substantial projects: a Space Invaders–inspired arcade game, data visualizations with Python’s superhandy libraries, and a simple web app you can deploy online. As you work through Python Crash Course you’ll learn how to: *Use powerful Python libraries and tools, including matplotlib, NumPy, and Pygal *Make 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progresses *Work with data to generate interactive visualizations *Create and customize Web apps and deploy them safely online *Deal with mistakes and errors so you can solve your own programming problems If you’ve been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code! Uses Python 2 and 3

Author 
John V. Guttag 
ISBN10 
9780262529624 
Year 
20160812 
Pages 
472 
Language 
en 
Publisher 
MIT Press 
DOWNLOAD NOW
READ ONLINE
The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization.

Author 
Christian Hill 
ISBN10 
9781107075412 
Year 
20160131 
Pages 
482 
Language 
en 
Publisher 
Cambridge University Press 
DOWNLOAD NOW
READ ONLINE
Learn to master basic programming tasks from scratch with reallife scientific examples in this complete introduction to Python.
Introduction to the Python computer language for mathematicians and scientists. Topics in scientific computation drawn from statistics, machine learning, mathematics, geometry, and the sciences. Target audience: students with calculus and linear algebra but no previous programming background. Includes over 300 exercises and projects for students.

Author 
Jesse M. Kinder 
ISBN10 
9781400873982 
Year 
20150701 
Pages 
160 
Language 
en 
Publisher 
Princeton University Press 
DOWNLOAD NOW
READ ONLINE
Python is a computer programming language that is rapidly gaining popularity throughout the sciences. A Student's Guide to Python for Physical Modeling aims to help you, the student, teach yourself enough of the Python programming language to get started with physical modeling. You will learn how to install an opensource Python programming environment and use it to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; and simulation. No prior programming experience is assumed. This tutorial focuses on fundamentals and introduces a wide range of useful techniques, including: Basic Python programming and scripting Numerical arrays Two and threedimensional graphics Monte Carlo simulations Numerical methods, including solving ordinary differential equations Image processing Animation Numerous code samples and exercises—with solutions—illustrate new ideas as they are introduced. Webbased resources also accompany this guide and include code samples, data sets, and more.

Author 
Hans Petter Langtangen 
ISBN10 
9783662498873 
Year 
20160728 
Pages 
922 
Language 
en 
Publisher 
Springer 
DOWNLOAD NOW
READ ONLINE
The book serves as a first introduction to computer programming of scientific applications, using the highlevel Python language. The exposition is example and problemoriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlabstyle" and procedural programming as well as objectoriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical onevariable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling realworld problems using objects and functions and embracing the objectoriented paradigm. ... Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011 This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012 “This fourth edition is a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in Python...” Joan Horvath, Computing Reviews, March 2015

Author 
Tony Ojeda 
ISBN10 
9781783980253 
Year 
20140925 
Pages 
396 
Language 
en 
Publisher 
Packt Publishing Ltd 
DOWNLOAD NOW
READ ONLINE
If you are an aspiring data scientist who wants to learn data science and numerical programming concepts through handson, realworld project examples, this is the book for you. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of data science projects, the steps in the data science pipeline, and the programming examples presented in this book. Since the book is formatted to walk you through the projects with examples and explanations along the way, no prior programming experience is required.

Author 
Ivan Idris 
ISBN10 
1849518939 
Year 
20121025 
Pages 
226 
Language 
en 
Publisher 
Packt Publishing Ltd 
DOWNLOAD NOW
READ ONLINE
Written in Cookbook style, the code examples will take your Numpy skills to the next level. This book will take Python developers with basic Numpy skills to the next level through some practical recipes.

Author 
Kyran Dale 
ISBN10 
9781491920541 
Year 
20160630 
Pages 
592 
Language 
en 
Publisher 
"O'Reilly Media, Inc." 
DOWNLOAD NOW
READ ONLINE
Learn how to turn raw data into rich, interactive web visualizations with the powerful combination of Python and JavaScript. With this handson guide, author Kyran Dale teaches you how build a basic dataviz toolchain with bestofbreed Python and JavaScript libraries—including Scrapy, Matplotlib, Pandas, Flask, and D3—for crafting engaging, browserbased visualizations. As a working example, throughout the book Dale walks you through transforming Wikipedia’s tablebased list of Nobel Prize winners into an interactive visualization. You’ll examine steps along the entire toolchain, from scraping, cleaning, exploring, and delivering data to building the visualization with JavaScript’s D3 library. If you’re ready to create your own webbased data visualizations—and know either Python or JavaScript— this is the book for you. Learn how to manipulate data with Python Understand the commonalities between Python and JavaScript Extract information from websites by using Python’s webscraping tools, BeautifulSoup and Scrapy Clean and explore data with Python’s Pandas, Matplotlib, and Numpy libraries Serve data and create RESTful web APIs with Python’s Flask framework Create engaging, interactive web visualizations with JavaScript’s D3 library

Author 
Yves Hilpisch 
ISBN10 
9781491945391 
Year 
20141211 
Pages 
606 
Language 
en 
Publisher 
"O'Reilly Media, Inc." 
DOWNLOAD NOW
READ ONLINE
The financial industry has adopted Python at a tremendous rate recently, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. This handson guide helps both developers and quantitative analysts get started with Python, and guides you through the most important aspects of using Python for quantitative finance. Using practical examples through the book, author Yves Hilpisch also shows you how to develop a fullfledged framework for Monte Carlo simulationbased derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks, with topics that include: Fundamentals: Python data structures, NumPy array handling, time series analysis with pandas, visualization with matplotlib, high performance I/O operations with PyTables, date/time information handling, and selected best practices Financial topics: mathematical techniques with NumPy, SciPy and SymPy such as regression and optimization; stochastics for Monte Carlo simulation, ValueatRisk, and CreditValueatRisk calculations; statistics for normality tests, meanvariance portfolio optimization, principal component analysis (PCA), and Bayesian regression Special topics: performance Python for financial algorithms, such as vectorization and parallelization, integrating Python with Excel, and building financial applications based on Web technologies