Book Image

Hands-On Web Scraping with Python - Second Edition

By : Anish Chapagain
Book Image

Hands-On Web Scraping with Python - Second Edition

By: Anish Chapagain

Overview of this book

Web scraping is a powerful tool for extracting data from the web, but it can be daunting for those without a technical background. Designed for novices, this book will help you grasp the fundamentals of web scraping and Python programming, even if you have no prior experience. Adopting a practical, hands-on approach, this updated edition of Hands-On Web Scraping with Python uses real-world examples and exercises to explain key concepts. Starting with an introduction to web scraping fundamentals and Python programming, you’ll cover a range of scraping techniques, including requests, lxml, pyquery, Scrapy, and Beautiful Soup. You’ll also get to grips with advanced topics such as secure web handling, web APIs, Selenium for web scraping, PDF extraction, regex, data analysis, EDA reports, visualization, and machine learning. This book emphasizes the importance of learning by doing. Each chapter integrates examples that demonstrate practical techniques and related skills. By the end of this book, you’ll be equipped with the skills to extract data from websites, a solid understanding of web scraping and Python programming, and the confidence to use these skills in your projects for analysis, visualization, and information discovery.
Table of Contents (20 chapters)
1
Part 1:Python and Web Scraping
4
Part 2:Beginning Web Scraping
8
Part 3:Advanced Scraping Concepts
13
Part 4:Advanced Data-Related Concepts
16
Part 5:Conclusion

Summary

Generating and gathering information using different analysis techniques and using it for decision-making is a growing field. Fields such as business intelligence (BI), AI, and ML require, and use, various data analysis techniques. Python programming provides a great infrastructure for the processes of data collection, data processing, information abstraction, and knowledge discovery. Libraries such as pandas, NumPy, csv, json, and plotly are the core Python libraries of the overall systematic process.

A practical introduction to the concepts related to data mining, data analysis, EDA, and data visualization was the main agenda of this chapter.

In the next chapter, we will be learning about machine learning and web scraping.