what is web-scraping fr?

This repository is a tutorial for learning how to scrape data from websites using R. It accompanies a workshop on the rvest package and teaches you how to automatically collect information from web pages and turn it into clean, organized tables. Instead of manually copying and pasting data from a site, you learn how to write code that does it for you. The lessons start with the basics of how a web page is structured and how to identify the specific pieces of a page you want to grab. It walks through using browser tools to pinpoint the data you need, then shows how to use rvest to extract that information and format it into a tidy data frame. Beyond the basics, it also covers how to scrape multiple pages at once, handle websites that load their content dynamically with JavaScript, and pull data from hidden or unofficial APIs that websites use behind the scenes. It even includes tips on using large language models to help with the process. This is ideal for data analysts, researchers, or anyone who uses R and needs to collect data that only exists on a website. For example, if you want to gather product prices from an online store, compile a list of contacts from a directory, or collect headlines from a news site, this tutorial shows you how to automate that work. It is designed for a hands-on audience, the materials include a slide deck and code you can run yourself. To follow along, you just need to install a couple of R packages and have a standard Chrome browser on your computer. The Chrome requirement specifically supports the sections on scraping dynamic, JavaScript-heavy sites.