Python Data Analysis and Visualization: From Beginner to Mastery

Name: Python Data Analysis and Visualization: From Beginner to Mastery
ISBN: 9787301310489

高博 / 刘冰 / 李力Peking University Press · ChinaAug 2025

3.4

Word count: 84K words
Chapters: 95
ISBN: 9787301310489

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Summary

Starting from zero, this book systematically introduces Python's applications in data processing and visual analysis. It is divided into 3 parts and 12 chapters, arranged as follows.

Part 1: Basics, Chapters 1–4. Chapter 1 Meet the Python: Getting Started with Python. Chapter 2 Sharpen Your Fangs and Load the Magazine: Preparing Your Work Environment. Chapter 3 One of Python's Basic Skills: The Python Language

Editor's review

This is an introductory Python data analysis book that starts from zero. Structurally it is divided into a basics part and subsequent content on data processing and visualization, following a sequence of first setting up the environment, then learning the language, and finally applying it to analysis tasks—an order that matches beginners' cognitive progression. Its strength lies in placing "data analysis" and "visualization" on the same learning chain: it first explains Python's basic syntax and work environment preparation, then gradually moves to using code to process data and present results, avoiding the awkwardness of learning only syntax without knowing how to use it. The book advances layer by layer by part and chapter, making it suitable as a course textbook or a self-study roadmap; readers can follow along chapter by chapter, or use the basics part as a quick-reference manual. Note that the value of a tool-oriented book lies in hands-on practice—reading without practicing makes true mastery difficult, so it is advisable to reproduce the code in a local environment while reading. Overall, it is suitable as a first systematic textbook for entering the field of data analysis, rather than a reference book on advanced algorithms or statistical theory.

Who it's for

A good fit for

Students and workplace newcomers with no programming background who want a systematic introduction to Python data analysis
Clerical and operations staff who need to process tabular data and create basic chart reports
University instructors selecting a textbook to organize an introductory data analysis course by part and chapter
Self-learners with some Excel experience who want to switch to code-based analysis tools

Not a good fit for

Advanced readers who already have Python basics and want to delve into machine learning or statistical modeling
Professionals expecting direct access to complex algorithm derivations and advanced visualization techniques

Reading tips

First set up the environment and type along with the examples in the order of the basics part, making sure each chapter's code runs before moving to the next
Replace the book's sample data with tables from your own work or studies; learning while practicing is more engaging
After each visualization chapter, try creating two or three different charts from the same dataset and compare the results
When you encounter an error, first review the environment configuration chapter; most beginner issues stem from version or dependency installation problems

About the publisher

Peking University Press China · Founded in 1979

Peking University Press is a comprehensive university press whose publishing areas cover classical literature, popular science, social culture, world history, Western philosophy, and culture. Its catalogue contains 6,031 titles, with representative books including A Dream of Red Mansions, Relativity: The Special and General Theory (15th Edition) (with Einstein's classic papers on unified field theory and other topics), Elements, Conics, The Aristocratic Families of the Eastern Jin, The Philosophy of Mythology (Volume I), The Philosophy of Mythology (Volume II), and The Origin of Continents and Oceans. Representative authors include Cao Xueqin, Zhou Ruchang, Albert Einstein, Euclid, Apollonius, Tian Yuqing, Schelling, and Xian Gang. The press has developed distinctive strengths in classical Chinese literature and in the translation of Western philosophical classics, while also covering scientific classics and social and cultural studies. As public information is limited, this description is based only on the books in the catalogue and offers no further extrapolation.

版权信息
前言大数据时代，Python数据分析与可视化之利器
第1篇基础篇
第1章认识大蟒：Python快速入门
1.1 什么是大蟒（Python）
1.2 Python是位“年轻的老同志”
1.3 Python语言有什么特点
1.4 Python语言的应用领域
新手问答
本章小结
第2章磨好利牙，子弹上膛：准备好工作环境
2.1 版本的比较与选择
2.2 在Windows上安装Python
2.3 在macOS上安装Python
2.4 选择合适的开发工具
2.5 安装所需的第三方组件（库）
新手问答
小试牛刀
本章小结
第3章大蟒的基本技能之一：Python语言基础
3.1 基本概念
3.2 数据类型
3.3 运算符
新手问答
小试牛刀
本章小结
第4章大蟒的基本技能之二：Python语言进阶
4.1 流程控制
4.2 异常处理
4.3 函数
4.4 面向对象编程
4.5 文件操作
新手问答
小试牛刀
本章小结
第2篇应用篇
第5章给大蟒找食：Python的数据存取操作
5.1 餐前小食：文本文件的数据存取
5.2 开胃菜：Excel文件的数据存取
5.3 主菜：写一个爬虫来收集网页数据
5.4 主菜：操作MySQL数据库
5.5 甜点：ORM框架
新手问答
小试牛刀
本章小结
第6章洗干净了再吃：使用Python预处理数据
6.1 清洗和预处理数据的原因及方法
6.2 使用Pandas预处理数据
新手问答
小试牛刀
本章小结
第7章有营养的食物：大数据分析及可视化基础知识
7.1 大数据的概念
7.2 大数据分析
7.3 使用NumPy和SciPy快速处理数据
新手问答
小试牛刀
本章小结
第8章大蟒神通之一：使用Matplotlib绘制基础图形
8.1 绘制简单图形
8.2 绘制高级图形
新手问答
小试牛刀
本章小结
第9章大蟒神通之二：使用Matplotlib美化和修饰图形
9.1 调整坐标轴和刻度
9.2 添加标题、图例和注释文本
9.3 设置线形和文本字体
9.4 使用颜色
9.5 划分画布
新手问答
小试牛刀
本章小结
第10章大蟒神通之三：数据可视化之3D图形应用
10.1 创建3D可视化图表
10.2 使用Matplotlib创建动画
新手问答
小试牛刀
本章小结
第11章大蟒神通之四：图像处理
11.1 使用Python Imaging Library处理图像
11.2 生成CAPTCHA图像
新手问答
小试牛刀
本章小结
第3篇实战篇
第12章综合案例：全国县级市天气预报的数据可视化分析
12.1 目标与计划
12.2 确定目标数据
12.3 试验抓取数据
12.4 保存数据入库
12.5 检查清理数据
12.6 绘制图形图表
本章小结
附录

FAQ

I have no programming background at all—can I keep up with this book?

Yes. The book starts from zero, first covering Python basics and work environment preparation, then gradually moving into language skills and data analysis content, with chapters arranged step by step. It is recommended to study in order and reproduce the code hands-on; do not skip the environment configuration section.

What software environment is needed for the book's content?

The book includes a dedicated chapter on preparing the work environment, which introduces the installation and configuration of the required tools. It is recommended to follow that chapter's steps strictly, pay attention to version compatibility, and check first whether dependencies are fully installed if problems arise.

What level can I reach after finishing the book?

You can master basic Python syntax and complete foundational analysis tasks such as data reading, processing, and common chart plotting, making it a good starting point for continued practice after the introduction. To delve into statistical modeling or machine learning, you will need additional specialized textbooks.

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About the author

高博 Author

Publicly available information about Gao Bo is quite limited. The reliable details come mainly from the several practical technical books he has published in the Chinese book market. Judging from the eight titles included in the collection, his writing centers on digital tools and programming applications, including beginner-oriented AI art tutorials, Python and R data analysis and visualization, Python network programming, and AI-powered office guides built around tools such as ChatGPT and DeepSeek. Another title, China's County-Level Economic Development under the Dual Carbon Goals, touches on financial and economic issues. Most of these books follow a "from beginner to mastery" approach, emphasizing operational steps and key techniques and extending into commercial practice, together forming a tutorial style that guides self-learners from basic to advanced levels.

刘冰 Author

Liu Bing is a Chinese author with a notably wide range of writing; public information about the author is limited, and biographical details remain incomplete. Ten works are held in the collection, covering biography, journalism practice, travel essays, literary appreciation, programming design, and machine learning. Among them are the biography Tan Sitong and the sports biography Messi: The Road of Legend (2018 New Edition); Journalism Practice Training reflects an interest in news operations; Walking the Roof of the World—Five Lessons on Dreams and Journeys leans toward inspiration and travel writing; and Guangzhou Study Travel Ancient Poetry Courseware combines local culture with the teaching of classical poetry. Technical works such as Python Data Analysis and Visualization from Beginner to Mastery and Bayesian Algorithms and Machine Learning extend the author's reach into programming and data science. Overall, Liu Bing's works combine knowledge popularization with practical training and address a variety of readerships.

李力 Author

Li Li: publicly available information is limited. It is known only that four of his works are held in this database, covering such diverse fields as film studies, programming design, and medicine. In film, his works Classical Film Image Analysis and Film Color Theory are included in the Peking University Film and Television Arts series, showing a sustained attention to image language and the use of color; the former focuses on image analysis, while the latter examines color in cinema, addressing specific topics within film and television arts research. In the technical field, he wrote Python Data Analysis and Visualization from Beginner to Mastery, aimed at beginners seeking an introduction and further study. In medicine, he contributed to Animal Models of Human Reproductive Diseases, which concerns experimental models in reproductive disease research. His writing spans art, technology, and medicine, with markedly different subject matter, emphasizing practical and methodological organization and serving as reference for learners and researchers in the relevant fields.