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.
- Travel Aggregators: Providing real-time bus schedules and seat availability for customers.
- Market Analysis: Analyzing travel patterns and preferences for market research.
- Customer Service: Enhancing user experience by offering customized travel options based on data insights.
- Competitor Analysis: Comparing pricing and service levels with competitors
Web Scraping using Selenium, Python, Streamlit , SQL, Data Analysis, Interactive Application
- Successfully scrape a minimum of 10 Government State Bus Transport data from Redbus website using Selenium. Also include the private bus information for the selected routes.
- Store the data in a structured SQL database.
- Develop an interactive Streamlit application for data filtering.
- Ensure the application is user-friendly and efficient
Clone the project
git clone https://github.com/Vijay6383/Redbus-Webscraping-project.git
Go to the project directory
cd redbus\ webscraping
Install modules
pip install selenium
pip install streamlit
Run all the cells in jupyter notebook file named redbus_scrape.ipynb one by one
After running all cells, Run the streamlit application
streamlit run mainpage.py