https://github.com/udhaya2823/red_bus_project

🚌 Red Bus Project Overview The Red Bus Project is a web scraping and visualization tool built with Selenium to extract bus information from the RedBus website. It stores the data in a MySQL database and provides an interactive visualization interface using Streamlit. The goal is to deliver insights into bus schedules, prices, ratings, etc...
https://github.com/udhaya2823/red_bus_project

data-science database-management datascraping pandas python selenium-python sql streamlit-webapp

Last synced: 9 days ago
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🚌 Red Bus Project Overview The Red Bus Project is a web scraping and visualization tool built with Selenium to extract bus information from the RedBus website. It stores the data in a MySQL database and provides an interactive visualization interface using Streamlit. The goal is to deliver insights into bus schedules, prices, ratings, etc...

• Host: GitHub
• URL: https://github.com/udhaya2823/red_bus_project
• Owner: udhaya2823
• License: mit
• Created: 2024-09-25T17:10:19.000Z (4 months ago)
• Default Branch: Projects
• Last Pushed: 2024-10-28T12:37:28.000Z (2 months ago)
• Last Synced: 2024-11-15T16:47:39.742Z (about 2 months ago)
• Topics: data-science, database-management, datascraping, pandas, python, selenium-python, sql, streamlit-webapp
• Language: Jupyter Notebook
• Homepage:
• Size: 16.8 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# 🚌 Red Bus Project

# Overview:

The Red Bus Project is a web scraping and visualization tool built with Selenium to extract bus information from the RedBus website. It stores the data in a MySQL database and provides an interactive visualization interface using Streamlit. The goal is to deliver insights into bus schedules, prices, ratings, and seat availability.

# Features:

Data Scraping: Automates the extraction of key information such as bus routes, departure/arrival times, bus types, ratings, and prices using Selenium.

Data Storage: Scraped data is stored in MySQL, enabling efficient query operations and structured data management.

Visualization: An interactive Streamlit app allows users to explore and analyze the bus data through charts and filters. 

## Insights include: 

      * Bus timings (departure and arrival)

      * Price comparisons across different routes

      * Duration of trips

      * Star ratings and seat availability of buses

      

# Technologies Used:

* Selenium: To automate web scraping from RedBus.

* MySQL: As the database for storing the scraped data.

* Streamlit: For creating a web-based interface for visualizing the data.

* Python: For all backend operations, including scraping, data processing, and visualization.