This project explores data scraped from the website Books to Scrape, an online catalog designed for web scraping practice. The goal is to collect book-related information such as titles, prices, genres, ratings, and availability, and perform a data analysis to uncover insights about pricing patterns and relationships among features.
Extract book data (title, price, rating, genre, availability) using web scraping techniques.
Clean, organize, and structure the scraped data into a usable format.
Explore pricing trends and relationships between genres, ratings, and book prices.
Visualize insights through clear, professional data visualizations.
Website: https://books.toscrape.com/
Description: A public website containing a catalog of books for web scraping exercises.
Data Collected:
Book title
Price
Star rating
Availability
Genre
Product link
A total of 1,000 books were scraped for this analysis.
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Collected data by scraping multiple pages from the website.
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Extracted HTML content using the requests library.
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Parsed book details using BeautifulSoup.
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Stored results in a pandas DataFrame for analysis.