Python Full-Stack Development: Data Analysis

This book is the third of four volumes in the "Python Full-Stack Development" series, part of the "Tsinghua Developer Library · Python" series from Tsinghua University Press, compiled by Xia Zhengdong. The book has seven chapters organized around the complete data analysis workflow: from data collection, data cleaning, and data analysis to data visualization, using nearly 400 sample code snippets to connect the core technologies needed at each stage. Chapter 1 covers web crawlers, including HTTP fundamentals, the urllib and requests network request libraries, regular expressions and web parsing libraries, Selenium browser simulation, multiprocess and multithreaded crawlers, mobile app data scraping (Charles packet capture), the Scrapy framework, and distributed crawlers. Chapters 2 and 3 systematically introduce NumPy and Pandas respectively, covering array creation, indexing and iteration, broadcasting, universal functions and linear algebra, as well as Series, DataFrame, long-wide data transformation, arithmetic operations, statistical methods, function application, sorting and deduplication, and CSV/Excel file reading and writing. Chapters 4 to 6 focus on visualization, covering Matplotlib (line, column, bar, pie, scatter, histogram, area, box, violin, heatmap, and subplots), Seaborn (various statistical charts, clustered heatmaps, and regression plots), and pyecharts (options configuration items, chained calls, and various chart types). Chapter 7 builds on the complete workflow of data collection, storage and retrieval, cleaning, analysis, and visualization to organize a comprehensive project practice, helping readers integrate scattered knowledge points into runnable engineering practice. The book can serve as a reference for computer software developers and as a teaching reference for university programs in computer science, software engineering, artificial intelligence, information management, and related fields.