The website 'books.toscrape.com' is an online platform for selling books. The scraping process involved extracting various data points such as book titles, prices, ratings, and URLs. The libraries used for web scraping include BeautifulSoup and Requests. The scraped data was then converted into a pandas DataFrame for further analysis.
- The BeautifulSoup library was utilized to parse the HTML content of the website.
- The Requests library was used to send HTTP requests and retrieve the website's HTML.
- The web scraping process involved iterating through multiple pages of the website and extracting relevant information such as book titles, prices, ratings, and URLs.
- The extracted data was stored in separate lists.
- The lists were then converted into a pandas DataFrame for easier manipulation and analysis.
After obtaining the scraped data in the pandas DataFrame, an unsupervised model was built using the extracted features. The specifics of the unsupervised model are not mentioned in the readme file. Please refer to the code or documentation for more information on the model implementation.
This project demonstrates proficiency in web scraping using BeautifulSoup and Requests libraries. By scraping the 'books.toscrape.com' website, relevant data such as book titles, prices, ratings, and URLs were extracted. The extracted data was transformed into a pandas DataFrame for further analysis. Additionally, an unsupervised model was built using the scraped data.
Please refer to the code and associated documentation for a detailed understanding of the implementation and analysis performed in this project.
Note: Make sure to comply with the terms and conditions of the website when scraping data. Respect the website's policies and ensure that the scraping is performed responsibly and ethically.