The "Redbus Data Scraping and Filtering with Streamlit Application" aims to revolutionize the transportation industry by providing a comprehensive solution for collecting, analyzing, and visualizing bus travel data. By utilizing Selenium for web scraping, this project automates the extraction of detailed information from Redbus, including bus routes, schedules, prices, and seat availability. By streamlining data collection and providing powerful tools for data-driven decision-making, this project can significantly improve operational efficiency and strategic planning in the transportation industry.
- Data Scraping:
- Use Selenium to automate the extraction of Redbus data including routes, schedules, prices, and seat availability.
- Data Storage:
- Store the scraped data in a SQL database.
- Streamlit Application:
- Develop a Streamlit application to display and filter the scraped data.
- Implement various filters such as bustype, route, price range, star rating, availability.
- Data Analysis/Filtering using Streamlit:
- Use SQL queries to retrieve and filter data based on user inputs.
- Use Streamlit to allow users to interact with and filter the data through the application.
pip install selenium pandas streamlit