Real Estate Agent Web Scraper

This Python project demonstrates web scraping skills using BeautifulSoup and requests to extract real estate agent information from Zillow's professional directory.

Project Highlights

• Utilizes Python for web scraping tasks.
• Employs the BeautifulSoup library to parse HTML content.
• Makes HTTP requests using the requests library.
• Randomizes user agents for variety and introduces delays to simulate human browsing behavior.
• Extracts agent names, phone numbers, and corresponding states from specified URLs.
• Stores scraped data in a pandas DataFrame.
• Exports the DataFrame to a CSV file for further analysis.

Code Sample

# ... (code to import libraries and define base_urls and user_agents)

for base_url in base_urls:
    # ... (loop to iterate through pages and extract agent data)

df = pd.DataFrame(agent_data)
df.to_csv('agents.csv', index=False)

How to Use

1. Clone the repository.
2. Ensure you have the required dependencies installed (requests, beautifulsoup4, pandas).
3. Customize the base_urls list with the URLs you want to scrape.
4. Run the script to extract agent data and save it to a CSV file.