Practical Web Scraping for Data Science: Best Practices and Examples with Python

Title: Practical Web Scraping for Data Science: Best Practices and Examples with Python

Citation: vanden Broucke, S., & Baesens, B. (2018). Practical Web Scraping for Data Science: Best Practices and Examples with Python. Apress. ISBN 978-1-4842-3581-2, e-ISBN 978-1-4842-3582-9, https://doi.org/10.1007/978-1-4842-3582-9

Key Topics:

1. Introduction to Web Scraping: Definition, importance, and applications in data science.
2. Web Scraping Basics: HTTP, HTML, CSS, and using Python libraries like requests and Beautiful Soup.
3. Advanced Web Scraping: Handling forms, login screens, cookies, JavaScript-heavy websites, and web crawling.
4. Managerial and Legal Concerns: Legal aspects, best practices, and integrating web scraping into the data science workflow.

Summary:

"Practical Web Scraping for Data Science" by Seppe vanden Broucke and Bart Baesens is a comprehensive guide to web scraping tailored for data scientists. The book aims to provide a concise and modern approach to web scraping using Python, focusing on best practices and practical examples. It covers the basics of web scraping, including HTTP, HTML, and CSS, and delves into advanced topics such as handling JavaScript-heavy websites and web crawling. The book also addresses managerial and legal concerns, making it a valuable resource for data science practitioners, lecturers, and students.