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

Data Mining, Analysis, and Visualization

So far, we have learned about some of the core Python libraries and techniques regarding HTTP/HTTPS communication, reading content, browser automation, and more from a data extraction perspective.

Data is the new oil (we all agree about this), but solely obtaining or collecting data does not provide any significant value. Collected data is stored in files (JSON, CSV, and XML), databases, and more. Stored data needs to be identified, searched, arranged, cleaned, transformed, explored, or modeled using algorithms and can sometimes be used by many services and applications before there’s any profit from the information from it.

Various technologies and concepts are involved in identifying and collecting data and processing it in order to extract some value. Data analysis implements and executes logic and algorithms using data-related applications and tools to generate valuable information. Visualization, on the other hand, displays...