Redbus Data Scraping with Selenium & Dynamic Filtering using Streamlit

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.

Business Use Cases

• 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

🛠 Skills

Web Scraping using Selenium, Python, Streamlit , SQL, Data Analysis, Interactive Application

Objectives

• 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

Run Locally

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

Source

• RedBus Website

REFERENCES

• Selenium
• Streamlit

🔗 Links