Unique & Practical R Tool Tutorial 3 out 5 Series

 Scrape Websites with R (No Python Needed!)

Need Data from Websites? Stop Copy-Pasting Like It’s 1999!

Manually collecting data from websites is slow, boring, and error-prone. But guess what? R can scrape it for you—automatically.

Whether you’re tracking prices, scraping news, or gathering leads, I’ll show you how to extract data in seconds—no Python required!

Say goodbye to tedious data collection.

Why This Matters

Web scraping helps gather data for market research, competitor analysis, and more—without manual work.

Real-Life Example

Extracting product prices from an e-commerce site for a price comparison study.

R Code Example

R Tool

library(rvest)
library(dplyr)

# Scrape Amazon product prices
url <- "https://www.amazon.com/s?k=laptops"
page <- read_html(url)

product_names <- page %>% 
  html_nodes(".a-size-medium") %>% 
  html_text()

prices <- page %>% 
  html_nodes(".a-price-whole") %>% 
  html_text()

data.frame(Product = product_names, Price = prices)

Key Benefits

•  No need for Python (just R!)
•  Automate competitive pricing analysis
•  Use with ggplot2 for instant visualizations

Recommendations

• Respect robots.txt and avoid aggressive scraping

• Use RSelenium for dynamic pages

Try It Today: Pick a website, tweak the code, and watch R pull the data for you. No more manual work!

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