We will write a program, the numbers and formulas as input, perform some calculations, and then get out of the solution or drawing graphics. Some of these programs can provide powerful computing capabilities to solve some math problems. These programs can be obtained solution of the equation, we calculate the correlation between the data set, determine the maximum value of the function, and the like. In other programs, we will simulate real-life events, such as parabolic motion, tossing a coin or dice. Use the program to simulate such an event, so that we can use a simple method to better analyze and understand the things themselves.
Maybe you will find some without the aid of a computer program will be very difficult to explore the theme, for example, even in the best case, hand-drawn fractal images is an extremely tedious work, and if in the most difficult circumstances, this is simply an impossible task. With the computer program, we need to do is implement the relevant operation in a loop. I think you will find that in this "learning mathematics with Python" situations, learning programming and learning mathematics will become even more exciting, interesting and useful.
Today recommended this "Python mathematical programming" will be three themes - programming, mathematics and science together. More specifically, after studying this book, we will solve some problems through the high school level programming, such as processing units of measurement, research parabolic movement, calculate the mean, median and mode, determining the linear correlation coefficient, solving algebraic equations that describe pendulum motion, dice simulation game, create the geometry, find the limit functions, derivative and integral. This is a topic familiar to many people, but we do not have a pen and paper, but with a computer program to study them.
Who Should Read This Book
If you are learning program, you will like this book demonstrates the use of computational methods to solve the problem. Likewise, if you are a teacher, you can use this book to train students in the practical application of programming skills to do so to avoid a somewhat abstract computer science. This book assumes that the reader understand the basis for programming in Python 3, such as functions, function parameters, the concept of Python classes and objects, cycle. Appendix B covers other topics in this book Python procedures used, but this book does not cover these additional topics in detail. If you feel you need more background, I recommend reading Jason Briggs of Python for kids (No Starch Press, 2013).
What does this book have?
The book consists of seven chapters and two appendices. Readers gave the left a title challenge at the end of each chapter. I suggest you let go a try, because in the process of writing programs themselves will learn more. These challenges will require you to explore new themes, this is a great way to improve learning ability.
- Chapter 1, the digital processing. The chapter begins with basic math operations, the gradual deepening of the content requires a higher level of mathematical skills.
- Chapter 2, data visualization. This chapter uses matplotlib libraries generated by the graphics data.
- Chapter 3, the statistical characteristics of the data. This chapter will continue to explain the subject of processing data sets, including the basic statistical concepts: mean, median, mode, and linear correlation data set of variables. It will also cover how to handle CSV data file, which is a popular file format to distribute a variety of data sets.
- Chapter 4, with SymPy Packet Solutions algebra and symbolic mathematics problems. This chapter describes the use SymPy symbolic math library, starting from the representation and handling algebraic expressions, after the introduction of more complex issues, such as solving equations.
- Chapter 5, and a collection of probability. This chapter discusses the mathematical representation of a collection, then deep into discrete probability, will discuss analog uniform and non-uniform random events.
- Chapter 6, draw and fractal geometry. This chapter discusses the use of matplotlib drawing geometry, fractals and creating animations.
- Chapter 7, the solution calculus problem. This chapter discusses some of the mathematical functions in the Python standard library and SymPy library, and then describes how to solve calculus problems.
- Appendix A, software installation. Involving Python 3, matplotlib and SymPy installation under Microsoft Windows, Linux and Mac OS X platforms.
- Appendix B, Python theme overview. Python discusses some topics that may be helpful for beginners.
Sample chapter on probation:
