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.
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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.
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Website Scraped
- PropertyFinder URL: https://www.propertyfinder.ae/
- The script scrapes multiple pages of property listings dynamically.
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Data Cleaning
- Data cleaning was performed using Jupyter Notebook.
- The cleaning script is located at:
CapstoneProjectDataCleaning.ipynb
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Tableau Dashboard
- The cleaned data was visualized using Tableau Public.
- Tableau Dashboard URL: View Dashboard
- Dashboard Screenshot:

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Useful Links
- The PropertyFinder URL and Tableau Dashboard URL are stored in
usefulurl.txt.
- The PropertyFinder URL and Tableau Dashboard URL are stored in
- Install Python (>=3.7)
- Install required libraries:
pip install selenium
- Download and install ChromeDriver (Ensure compatibility with your Chrome version)
- Update the
webdriver_pathin the script to match your ChromeDriver location. - Run the script using:
python your_script.py
- The extracted data will be saved as a CSV file with a timestamp.
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
- The script includes error handling and session restarts to avoid timeouts.
- Tableau Dashboard provides interactive visualization of property listings.
- Nurul Bashar