Course Overview
This course shows you how to use R’s web scraping packages and functions to extract data from publicly available websites and online sources. You’ll learn how to read and parse HTML, select relevant elements from a webpage, and convert the results into clean, analysis-ready tables in R. The emphasis is on building practical, reusable scraping workflows using widely used tools in the R ecosystem.
Key Highlights:
– Web scraping with R packages: Use established R tools to download web pages, parse HTML, and extract text and tables.
– Selectors and page structure: Identify and target the right elements on a page (e.g., links, tables, headings, metadata).
– End-to-end workflow in R: Collect, clean, transform, and export scraped data in a tidy format.
– Hands-On Learning: Engage in practical exercises to scrape review data from online platforms and perform text manipulations.
This course includes a range of activities such as web-scraping demos, live-coding sessions, interactive quizzes, and practical exercises to work individually or in a group. Active participation and contribution are recommended. You’ll leave the course with working scripts you can adapt to your own data sources.
In this course we highlight the importance of prioritising the use of official APIs first. Web scraping is covered only when no suitable or dedicated API exists and more specifically for scientific, research and educational purposes. We also cover the areas of responsible web scraping such as respecting terms of service, copyright and server overload.
Places are limited to 15 participants.
