Web Scraping and Data Analysis

Project at Universidad Politecnica de Madrid.

DESCRIPTION OF FILES

• Scrapper.py : This python file show a code that uses Selenium and BeautifulSoup to scrape car listings from https://heycar.com/uk/autos/make/audi/page/ .It navigates through multiple pages of listings, extracts car details, and saves them to a CSV file called ' dataset.csv' with columns for car name, type, mileage, year, condition, and price. Finally, it handles any errors and closes the browser after scraping.
• Data_visualization.ipynb : This Jupyter Notebook shows a code that use python libraries as matplotlib.pyplot for plotting, pandas for data manipulation, drive from google.colab to access files from Google Drive, and seaborn for advanced data visualization.
• dataset.csv : This is the dataset scraped by the python file "Scrapper.py".
• Web Scraping and Data visualization: This is the presentation the group made for the video.

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HOW TO EXECUTE THE CODE

To execute the project, it is necessary to upload all files to a Google Drive. There are two sequential methods to proceed:

1. Initially, the "Scrapper.py" file can be executed to retrieve the dataset. Subsequently, the "Data_visualization.ipynb" can be executed.
2. Alternatively, the dataset already uploaded within the drive can be utilized, allowing direct execution of the "Data_visualization.ipynb" file.

This procedure ensures the proper execution of the project, facilitating data access and processing.

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LINK TO THE VIDEO

https://drive.google.com/file/d/1nB3fPJunKRuLR2ccFqG5HT02fkHCb0IN/view?usp=sharing

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Students of Group 11

Gabriel-Cosmin Bolbotina Sajipan Sivatheesan Francesco Della Valle Gaetano Saviano Jan Durinec