You're reading from Practical Data Science with Python Learn tools and techniques from hands-on examples to extract insights from data

Product type Paperback

Published in Sep 2021

Publisher Packt

ISBN-13 9781801071970

Length 620 pages

Edition 1st Edition

Languages

Python

Tools

Excel

Concepts

Data Science

Author (1):

Nathan George

View More author details

Table of Contents (30) Chapters

Preface

1. Part I - An Introduction and the Basics

2. Introduction to Data Science FREE CHAPTER

3. Getting Started with Python

4. Part II - Dealing with Data

5. SQL and Built-in File Handling Modules in Python

6. Loading and Wrangling Data with Pandas and NumPy

7. Exploratory Data Analysis and Visualization

8. Data Wrangling Documents and Spreadsheets

9. Web Scraping

10. Part III - Statistics for Data Science

11. Probability, Distributions, and Sampling

12. Statistical Testing for Data Science

13. Part IV - Machine Learning

14. Preparing Data for Machine Learning: Feature Selection, Feature Engineering, and Dimensionality Reduction

15. Machine Learning for Classification

16. Evaluating Machine Learning Classification Models and Sampling for Classification

17. Machine Learning with Regression

18. Optimizing Models and Using AutoML

19. Tree-Based Machine Learning Models

20. Support Vector Machine (SVM) Machine Learning Models

21. Part V - Text Analysis and Reporting

22. Clustering with Machine Learning

23. Working with Text

24. Part VI - Wrapping Up

25. Data Storytelling and Automated Reporting/Dashboarding

26. Ethics and Privacy

27. Staying Up to Date and the Future of Data Science

28. Other Books You May Enjoy

29. Index

Parsing HTML from scraped pages

As we already saw, we can easily download a webpage in Python with urllib or the requests library. One thing to note is these libraries do not work with dynamic JavaScript content. For example, we can download and save the Packt home page:

res = rq.get('https://www.packtpub.com/')
with open('packt.html', 'wb') as f:
    f.write(res.content)

When we open it, it looks OK, except not all the content displays properly. For example, some of the icons are missing because they load dynamically with JavaScript. For gathering data from pages where JavaScript plays a heavy role, we can instead use other packages, like requests-html, Selenium, or the Scrapy package with the scrapy-splash plugin. The point is, you may notice some data missing when scraping data from pages. This could be due to JavaScript loading content, meaning you should try one of those other packages for scraping data from that page.

As our first example...