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

ML using scikit-learn

To develop a model, we need datasets. Web scraping is again the perfect technique to collect the desired data and store it in the relevant format. There are plenty of ML-related libraries and frameworks available in Python, and they are growing in number. scikit-learn is a Python library that addresses and helps to deal with the majority of supervised ML features.

scikit-learn is also known and used as sklearn. It is built upon numpy, scipy, and matplotlib. The library provides a large number of features related to ML aspects such as classification, clustering, regression, and preprocessing. We will explore beginner and intermediate concepts of the supervised learning type with regression using scikit-learn. You can also explore the sklearn user guide available at https://scikit-learn.org/stable/user_guide.html.

We have covered a lot of information about regression in previous sections of this chapter. Regression is a supervised learning technique that is...