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Property Finder Project - Web Scraping & Data Visualization

Project Overview

This project involves web scraping commercial rental property listings from PropertyFinder.ae using Selenium. The extracted data is then cleaned using Jupyter Notebook and visualized in Tableau.

Contents

  1. Web Scraping Code

    • The script is written in Python using Selenium.
    • It extracts property details such as type, rent, location, number of bedrooms, bathrooms, area, verification status, and agent type.
    • The extracted data is saved as a CSV file.
  2. Website Scraped

  3. Data Cleaning

    • Data cleaning was performed using Jupyter Notebook.
    • The cleaning script is located at:
      • CapstoneProjectDataCleaning.ipynb
  4. Tableau Dashboard

    • The cleaned data was visualized using Tableau Public.
    • Tableau Dashboard URL: View Dashboard
    • Dashboard Screenshot:
      Tableau Dashboard
  5. Useful Links

    • The PropertyFinder URL and Tableau Dashboard URL are stored in usefulurl.txt.

How to Run the Web Scraper

Prerequisites

  • Install Python (>=3.7)
  • Install required libraries:
    pip install selenium
  • Download and install ChromeDriver (Ensure compatibility with your Chrome version)

Steps to Run

  1. Update the webdriver_path in the script to match your ChromeDriver location.
  2. Run the script using:
    python your_script.py
  3. The extracted data will be saved as a CSV file with a timestamp.

File Structure

CapstoneProject/
│-- CapstoneProjectDataCleaning.ipynb  # Data cleaning script
│-- usefulurl.txt                       # Contains PropertyFinder & Tableau links
│-- your_script.py                      # Web Scraping script
│-- scraped_data/                        
│   ├── property_data_YYYYMMDD_HHMMSS.csv  # Scraped data

Notes

  • The script includes error handling and session restarts to avoid timeouts.
  • Tableau Dashboard provides interactive visualization of property listings.

Author

  • Nurul Bashar

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