🏨 Booking.com Hotel Scraper & Analyzer

📌 About the Project

This project is a web scraping + data analysis pipeline built with Python, Selenium, Pandas, and Matplotlib. It allows you to extract hotel data from Booking.com (name, location, price, rating, reviews, link), store it in a CSV file, and then perform statistical analysis & visualization.

🎯 Problem

When planning a trip, it's often difficult to:

• Compare hotel prices across multiple listings.
• Identify which hotels have the best value for money (good rating vs low price).
• Visualize trends (price distribution, top-rated hotels, etc.).

💡 Solution

This project solves the problem by:

1. Scraping hotel data from Booking.com using Selenium.
2. Cleaning and structuring the data with Pandas.
3. Generating visual insights using Matplotlib:
   • Price distribution histogram 📊
   • Rating distribution histogram ⭐
   • Price vs Rating scatter plot 💰➡️⭐
   • Top 10 hotels by rating 🏆

⚙️ How It Works

1. User provides:
   • Booking.com search URL
   • Output CSV file name
2. Script runs Selenium to scrape hotel details.
3. Data is saved in a structured CSV format.
4. Pandas cleans the data.
5. Matplotlib visualizes key insights.

📊 Example Visualizations

🚀 Tech Stack

🏆 Key Insights (Sample Run)

• Average hotel price: $120/night
• Average rating: 8.5/10
• Best Value: Small boutique hotels often score higher than luxury ones for the same price.

📌 Future Improvements

• Integrate Seaborn/Plotly for more interactive dashboards.
• Automate scraping across multiple cities.