There is a wealth of data contained within publicly available web pages. How can you extract it and get it into a format suitable for further use and analysis? In this course, Extracting Data from HTML with R 3, you will learn how to scrape HTML content using R and transform it into valuable datasets. First, you will gain an understanding of techniques for targeting HTML elements that contain the data you want. Next, you will discover how to extract text and attributes, and wrangle the resulting content into a tidy dataset. Finally, you will explore methods for scaling up your scraping using various R tools. When you are finished with this course, you will have the skills and knowledge necessary to unlock valuable data contained in web content.
Author Name: Jesse Harris
Author Description:
Jesse has worked in technology and communications roles for over 20 years. He is a big fan of the R software ecosystem and loves good data visualizations, especially if they’re about sports. His hobbies include learning new languages and cheering for hockey teams whose best days are in the past. Jesse lives in Edmonton, Canada.

Table of Contents

• Course Overview
  1min
• Expanding Your Data Professional Toolset with Rvest
  11mins
• Exploring an HTML Document Object in R
  9mins
• Isolating Pieces of an HTML Document
  33mins
• Extracting Attributes and Text from HTML Elements
  22mins
• Scraping Multiple Pages
  18mins
• Extracting Data from HTML Tables
  14mins
• Wrapping Up
  7mins