Easily Learn Mathematics with Python

Name: Easily Learn Mathematics with Python
ISBN: 9787121389764

蹇彤Publishing House of Electronics Industry · ChinaJan 2021

3.3

Word count: 67K words
Chapters: 100
ISBN: 9787121389764

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Summary

This book tightly integrates basic Python programming knowledge with primary and secondary school mathematics. While introducing Python, it intersperses explanations of interesting and challenging math problems, guiding readers to view, experience, and learn programming from a completely new perspective and cultivating computational and programming thinking in primary and secondary school students. The book has 13 chapters, covering Python's basic data types, fundamental programming knowledge, number lines, coordinate systems, and plane geometric figures, dates and times, sequential statements, conditional and loop statements, functions, and more. In addition, the book includes synchronized video explanations, which readers can combine with the book for more intuitive learning and improved efficiency.

Editor's review

Easy Math with Python is a practical cross-disciplinary learning work recently published by Publishing House of Electronics Industry. The author, Jian Tong, combines rich experience in mathematics education with programming practice to open a new path for traditional mathematics learning. This book is not a simple programming implementation of mathematical formulas; rather, it uses Python, a modern tool, to reconstruct mathematical thinking and translate abstract mathematical concepts into visualizable code logic. The book covers a broad range of mathematics, from basic algebra and geometry to probability and statistics, and every knowledge point is accompanied by complete, runnable code examples, allowing readers to intuitively experience the dynamic changes of mathematical models through hands-on practice. The greatest value of this book lies in breaking through the one-way thinking mode of traditional mathematics learning: through the interactivity of programming, mathematics becomes operable and verifiable, making it particularly suitable for readers in the digital age who need to develop logical thinking and problem-solving skills. The case designs emphasize practicality, and many code examples can be applied to real data analysis or scientific computing scenarios with only minor modifications. This design philosophy of learning for application is commendable.

Who it's for

A good fit for

Programming enthusiasts with basic Python syntax knowledge who want to deepen their understanding of mathematics
Students currently studying middle school or university mathematics who want to use programming to aid understanding of abstract concepts
Professionals engaged in data analysis or machine learning who need to consolidate their mathematical foundations
Self-learners interested in mathematical modeling who want to master computational methods for solving mathematical problems

Not a good fit for

Readers with no programming background who are unwilling to learn basic syntax
Scholarly readers seeking purely theoretical mathematical proofs or advanced mathematics monographs

Reading tips

Read in chapter order; understand the mathematical concepts before practicing the code in each chapter, and do not skip the theory to copy code directly
Type out all code examples by hand and try modifying parameters to observe changes in output; this is the best way to understand the essence of mathematics
Study in an interactive environment such as Jupyter Notebook; viewing visualizations in real time better matches the book's design philosophy

About the publisher

Publishing House of Electronics Industry China · Founded in 1982

The Publishing House of Electronics Industry is a comprehensive publisher distinguished by its focus on electronic information and related fields. Judging from the more than 3,000 titles in its catalogue, its publishing covers programming and design, artificial intelligence, computer science, finance and economics, photography, and social sciences, attending both to cutting-edge technology and to general readers. Representative titles include Factor Investing: Methods and Practice, x86 Assembly Language: From Real Mode to Protected Mode, The RISC-V Reader, Artificial Intelligence: Speech Recognition, Understanding and Practice, Phased Array Radar Technology, Radar Target Characteristics, and 100 Go Mistakes and How to Avoid Them, most of which centre on technical methods and engineering practice. Its authors include Shi Chuan, Li Zhong, Wang Xiaobo, David Patterson, Andrew Waterman, and Yu Zihao, among others from China and abroad. Owing to limited public information, no further publishing features are elaborated here.

版权信息
作者介绍
内容简介
前言
第1章扬帆起航学Python
1.1 国家号召你学编程
1.2 为什么选择Python
1.3 下载和安装Python
1.4 编写第一个Python 程序
1.5 本章练习题
第2章 Python 基础编程
2.1 基本数据类型
2.2 整型、浮点型和变量
2.3 字符串类型
2.4 布尔类型
2.5 程序里的数学运算
2.6 关系运算
2.7 逻辑运算
2.8 列表和元组
2.9 字典和集合
2.10 本章练习题
第3章数轴、坐标系和平面几何图形
3.1 数轴是什么
3.2 笛卡儿的发明——平面直角坐标系
3.3 熟悉turtle 画图命令
3.4 画图案例
3.5 本章练习题
第4章程序里的时间表示法
4.1 日历模块
4.2 时间模块
4.3 日期的数学计算
4.4 基本数据类型之间的转换
4.5 本章练习题
第5章程序的顺序执行
5.1 数学解题步骤——按顺序执行
5.2 编程的三种错误类型
5.3 数学和程序里的随机数
5.4 程序的调试
5.5 本章练习题
第6章条件语句
6.1 认识条件语句
6.2 单分支条件语句
6.3 双分支条件语句
6.4 多分支条件语句
6.5 条件语句综合应用
6.6 本章练习题
第7章循环那些事儿
7.1 循环就是重复
7.2 while 循环
7.3 for 循环
7.4 利用无限循环
7.5 循环嵌套
7.6 数学应用——用蒙特卡罗模拟方法估算圆周率
7.7 本章练习题
第8章数学数制、编码和字符串
8.1 易经中的阴阳八卦和计算机中的二进制数
8.2 ASCII 编码和Unicode 编码
8.3 计算机数学基础—十进制数、二进制数及其转换
8.4 字符串是一种数据——字符串的操作
8.5 本章练习题
第9章用Python 体验大数据
9.1 数学上的一亿有多大
9.2 指数爆炸的威力——国王的赏赐
9.3 天文数字——围棋的变化数量
9.4 本章练习题
第10章函数是一等公民
10.1 函数有什么用途
10.2 函数的调用
10.3 Python 自带数学函数的应用
10.4 自己动手丰衣足食——自己动手写函数
10.5 铁路警察各管一段——函数中变量的范围
10.6 函数参数的多样性
10.6.1 位置参数
10.6.2 默认参数
10.6.3 不定参数
10.7 匿名函数
10.8 递归函数——自己调用自己的函数
10.9 本章练习题
第11章编程求解中小学数学趣题难题
11.1 什么是算法
11.2 鸡兔同笼
11.3 百钱买百鸡
11.4 顺序查找
11.5 二分查找
11.6 爱因斯坦的数学题
11.7 猴子吃桃
11.8 数字黑洞——九九归一
11.9 本章练习题
第12章操作文件
12.1 文本文件和二进制文件
12.2 从文件中读取数据
12.3 把数据写入文本文件中
12.4 操作CSV 文件
12.5 操作图片文件
12.6 本章练习题
第13章少年黑客基本功——加密与解密
13.1 黑客不全都是坏人
13.2 数论的简单应用——凯撒密码
13.3 加密英文原版——罗密欧与朱丽叶
13.4 本章练习题

FAQ

How much Python background is needed to read this book?

The book assumes readers already understand basic Python syntax, data types, and control structures and can write simple scripts. The first two chapters provide targeted quick introductions to Python mathematical computing libraries, but this is not a zero-foundation programming textbook.

What mathematical areas does the book cover?

It covers core mathematics from middle school to lower-division university level, including solving algebraic equations, function plotting, geometric transformations, foundations of probability and statistics, and introductory linear algebra, with emphasis on showing how to understand these concepts through programming thinking.

Are the code examples in the book complete and runnable?

All code is based on the Python standard library and common scientific computing libraries such as NumPy and Matplotlib, with complete executable code provided. Some complex cases include step-by-step explanations to ensure readers can understand the mathematical meaning of each line of code.

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About the author

蹇彤 Author

Jian Tong is an author about whom limited public information is available; the verifiable details center mainly on the representative work Learn Math Easily with Python. Judging from the title and the common category of programming design, the book combines Python programming with mathematics learning and is intended for readers who wish to use programming tools to understand mathematical concepts, practice calculations, and solve problems. This approach generally emphasizes learning through practice, turning abstract mathematical knowledge into runnable and verifiable code examples, thereby lowering the barrier to learning and helping programming beginners become familiar with the basic uses of Python through concrete tasks. Because the author's biography, nationality, educational background, and writing experience are not clearly recorded, this profile makes no speculation about personal history. Based on the available work, Jian Tong's writing tends toward introductory and applied material, focusing on applying programming skills to mathematical scenarios and making the book suitable as a reference for interdisciplinary learning. Only one work by this author is currently known, and further material is needed to assess its influence.