How to Scrape Data From Zillow?

Zillow.com is a popular online real estate marketplace that provides information about real estate properties in the United States. Zillow was founded in 2006 and it is one of the leading real estate websites, offering a wide range of services related to buying, selling, renting, and financing properties.

Zillow allows users to search for homes and apartments available for sale or rent across various locations. The platform provides detailed property listings with information such as property photos, descriptions, pricing, and amenities. Users can also find data on historical property values, local market trends, and neighborhood information.

One of the notable features of Zillow is its Zestimate, an automated valuation model that provides an estimated property value for millions of homes based on various factors such as recent sales data, location, and property characteristics. However, it's essential to note that Zestimates are estimates and may not always reflect the true market value accurately.

In addition to residential properties, Zillow also includes listings for commercial properties, land, and vacation rentals.

What is web scraping?

Web scraping is the process of extracting data from websites automatically. It involves using software or scripts to access web pages, download the content, and extract specific information from the HTML code of the web pages. Web scraping allows you to collect large amounts of data from websites efficiently and can be used for various purposes, such as data analysis, research, or populating a database.

How to scrape Zillow using Python?

You can use Python with libraries like requests for making HTTP requests and BeautifulSoup or Scrapy for parsing and extracting the relevant information from the web pages.

Here's an example of how to use Python with requests and BeautifulSoup to scrape data from a webpage:

import requests
from bs4 import BeautifulSoup

url = "https://www.zillow.com/new-york-city-ny/"

headers = {
    "User-Agent": "Mozilla/5.0 (X11; Linux x86_64) "
                  "AppleWebKit/537.36 (KHTML, like Gecko) Chrome/51.0.2704.103 "
                  "Safari/537.36"
}

response = requests.get(url, headers=headers)

if response.status_code == 200:
    soup = BeautifulSoup(response.content, "html.parser")
    addresses = soup.find_all("address", {"data-test": "property-card-addr"})
    for address in addresses:
        print(address.getText())
        # Output: list of addresses
else:
    print("Failed to retrieve data. Status code:", response.status_code)

Please remember that it will probably be required to implement some rate-limiting between requests or use a proxy and dynamically change User agents per request.

So if you see an error: "ImportError: No module named requests" while running this script, you probably need to install the requests package or BeautifulSoup, and here you can find information on how you can fix this error.

How to scrape Zillow using Python Selenium?

Here's a simple example of how to use Python Selenium for web scraping:

from selenium import webdriver
from selenium.webdriver.common.by import By

# Replace 'path_to_webdriver' with the path to your web driver executable.
driver = webdriver.Chrome(executable_path='path_to_webdriver')

url = 'https://www.zillow.com/new-york-city-ny/'
driver.get(url)

# Extract data using Selenium methods.
items = driver.find_elements(By.CSS_SELECTOR, 'div#grid-search-results ul li')
for item in items:
    address = item.find_element(By.CSS_SELECTOR, "address")
    print(address)

# Close the web driver after scraping.
driver.quit()

You can find more examples of how to scrape Zillow using Python in this thread as well.