Graph and download economic data for Zillow Home Value Index (ZHVI) for All Homes Including Single-Family Residences, Condos, and CO-OPs in the United States of America (USAUCSFRCONDOSMSAMID) from Jan 2000 to Sep 2025 about 1-unit structures, family, residential, housing, indexes, and USA.

Reference: https://www.zillow.com/research/zhvi-methodology/

Official Background

In setting out to create a new home price index, a major problem Zillow sought to overcome in existing indices was their inability to deal with the changing composition of properties sold in one time period versus another time period. Both a median sale price index and a repeat sales index are vulnerable to such biases (see the analysis here for an example of how influential the bias can be). For example, if expensive homes sell at a disproportionately higher rate than less expensive homes in one time period, a median sale price index will characterize this market as experiencing price appreciation relative to the prior period of time even if the true value of homes is unchanged between the two periods.

The ideal home price index would be based off sale prices for the same set of homes in each time period so there was never an issue of the sales mix being different across periods. This approach of using a constant basket of goods is widely used, common examples being a commodity price index and a consumer price index. Unfortunately, unlike commodities and consumer goods, for which we can observe prices in all time periods, we can’t observe prices on the same set of homes in all time periods because not all homes are sold in every time period.

The innovation that Zillow developed in 2005 was a way of approximating this ideal home price index by leveraging the valuations Zillow creates on all homes (called Zestimates). Instead of actual sale prices on every home, the index is created from estimated sale prices on every home. While there is some estimation error associated with each estimated sale price (which we report here), this error is just as likely to be above the actual sale price of a home as below (in statistical terms, this is referred to as minimal systematic error). Because of this fact, the distribution of actual sale prices for homes sold in a given time period looks very similar to the distribution of estimated sale prices for this same set of homes. But, importantly, Zillow has estimated sale prices not just for the homes that sold, but for all homes even if they didn’t sell in that time period. From this data, a comprehensive and robust benchmark of home value trends can be computed which is immune to the changing mix of properties that sell in different periods of time (see Dorsey et al. (2010) for another recent discussion of this approach).

For an in-depth comparison of the Zillow Home Value Index to the Case Shiller Home Price Index, please refer to the Zillow Home Value Index Comparison to Case-Shiller

Each Zillow Home Value Index (ZHVI) is a time series tracking the monthly median home value in a particular geographical region. In general, each ZHVI time series begins in April 1996. We generate the ZHVI at seven geographic levels: neighborhood, ZIP code, city, congressional district, county, metropolitan area, state and the nation.

Underlying Data

Estimated sale prices (Zestimates) are computed based on proprietary statistical and machine learning models. These models begin the estimation process by subdividing all of the homes in United States into micro-regions, or subsets of homes either near one another or similar in physical attributes to one another. Within each micro-region, the models observe recent sale transactions and learn the relative contribution of various home attributes in predicting the sale price. These home attributes include physical facts about the home and land, prior sale transactions, tax assessment information and geographic location. Based on the patterns learned, these models can then estimate sale prices on homes that have not yet sold.

The sale transactions from which the models learn patterns include all full-value, arms-length sales that are not foreclosure resales. The purpose of the Zestimate is to give consumers an indication of the fair value of a home under the assumption that it is sold as a conventional, non-foreclosure sale. Similarly, the purpose of the Zillow Home Value Index is to give consumers insight into the home value trends for homes that are not being sold out of foreclosure status. Zillow research indicates that homes sold as foreclosures have typical discounts relative to non-foreclosure sales of between 20 and 40 percent, depending on the foreclosure saturation of the market. This is not to say that the Zestimate is not influenced by foreclosure resales. Zestimates are, in fact, influenced by foreclosure sales, but the pathway of this influence is through the downward pressure foreclosure sales put on non-foreclosure sale prices. It is the price signal observed in the latter that we are attempting to measure and, in turn, predict with the Zestimate.

Market Segments Within each region, we calculate the ZHVI for various subsets of homes (or mar...

Gain a complete view of the real estate market with our Zillow datasets. Track price trends, rental/sale status, and price per square foot with the Zillow Price History dataset and explore detailed listings with prices, locations, and features using the Zillow Properties Listing dataset. Over 134M records available Price starts at $250/100K records Data formats are available in JSON, NDJSON, CSV, XLSX and Parquet. 100% ethical and compliant data collection Included datapoints:

Zpid
City
State
Home Status
Street Address
Zipcode
Home Type
Living Area Value
Bedrooms
Bathrooms
Price
Property Type
Date Sold
Annual Homeowners Insurance
Price Per Square Foot
Rent Zestimate
Tax Assessed Value
Zestimate
Home Values
Lot Area
Lot Area Unit
Living Area
Living Area Units
Property Tax Rate
Page View Count
Favorite Count
Time On Zillow
Time Zone
Abbreviated Address
Brokerage Name
And much more

This dataset comes from Zillow and provides a comprehensive look at U.S. housing market trends from 2018 to May 2024. It includes detailed data on median home values, average days outstanding for property sales, and their impact on reducing prices in several cities. This dataset is ideal for analyzing the correlation between home values, time to market, and price adjustments, offering valuable insights for real estate professionals, economists, and data analysts interested in the dynamics of the U.S. housing market.

About the license, taken from the Zillow website:

“For research and academic projects, we provide the following metrics that have more flexible Terms of Use regarding data storage and manipulation – https://www.zillow.com/research/data/”

Graph and download economic data for Zillow Home Value Index (ZHVI) for All Homes Including Single-Family Residences, Condos, and CO-OPs in Michigan (MIUCSFRCONDOSMSAMID) from Jan 2000 to Oct 2025 about 1-unit structures, MI, family, residential, housing, indexes, and USA.

The Zillow Home Value Index (ZHRI) presents the Average Annual Median Home Value by Town.

Zillow reigns supreme in the U.S. real estate website landscape, attracting a staggering ***** million monthly visits in 2024. This figure dwarfs its closest competitor, Realtor.com, which garnered less than half of Zillow's traffic. Online platforms are extremely popular, with the majority of homebuyers using a mobile device during the buying process. The rise of Zillow Founded in 2006, the Seattle-headquartered proptech Zillow has steadily grown over the years, establishing itself as the most popular U.S. real estate website. In 2023, the listing platform recorded about *** million unique monthly users across its mobile applications and website. Despite holding an undisputed position as a market leader, Zillow's revenue has decreased since 2021. A probable cause for the decline is the plummeting of housing transactions and the negative housing sentiment. Performance and trends in the proptech market The proptech market has shown remarkable performance, with companies like Opendoor and Redfin experiencing significant stock price increase in 2023. This growth is particularly notable in the residential brokerage segment. Meanwhile, major players in proptech fundraising, such as Fifth Wall and Hidden Hill Capital, have raised billions in direct investment, further fueling the sector's development. As technology continues to reshape the real estate industry, online platforms like Zillow are likely to play an increasingly crucial role in how people search for and purchase homes. (1477916, 1251604)

Graph and download economic data for Zillow Home Value Index (ZHVI) for All Homes Including Single-Family Residences, Condos, and CO-OPs in Florida (FLUCSFRCONDOSMSAMID) from Jan 2000 to Oct 2025 about 1-unit structures, family, residential, FL, housing, indexes, and USA.

Zillow.com is a popular real estate marketplace that provides a comprehensive platform for buying, selling, renting, and exploring homes. Founded in 2006 by Rich Barton and Lloyd Frink, Zillow has become one of the go-to resources for people navigating the real estate market.

Key Features: Home Listings: Zillow offers an extensive database of homes for sale and rent. Users can search for properties by various criteria including location, price range, number of bedrooms, and more.

Zestimate®: One of Zillow's standout features is its Zestimate, an estimated market value for a home based on public data, user-submitted data, and other relevant information. While it's not a definitive appraisal, it provides a starting point for understanding a home's potential market value.

Market Trends: Zillow provides valuable insights into real estate trends and statistics, such as average home prices, appreciation rates, and market health indicators. This can be particularly useful for buyers and sellers looking to understand market dynamics.

Tools for Buyers and Sellers: The platform offers various tools and calculators to help users with financial planning, including mortgage calculators, affordability calculators, and home value estimators. Sellers can use Zillow to list their homes, connect with potential buyers, and track their property’s performance on the market.

Zillow Offers: For those looking to sell their home quickly, Zillow Offers is a service that allows homeowners to receive a cash offer from Zillow, potentially streamlining the selling process.

This dataset is collected from zillow.com using API. This is the raw version of the data fetched using API which requires data cleaning, feature extraction and feature engineering to get useful information for the house price prediction.

VITAL SIGNS INDICATOR Home Prices (EC7)

FULL MEASURE NAME Home Prices

LAST UPDATED August 2019

DESCRIPTION Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.

DATA SOURCE Zillow Median Sale Price (1997-2018) http://www.zillow.com/research/data/

Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1997-2018; specific to each metro area) http://data.bls.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Median housing price estimates for the region, counties, cities, and zip code come from analysis of individual home sales by Zillow. The median sale price is the price separating the higher half of the sales from the lower half. In other words, 50 percent of home sales are below or above the median value. Zillow defines all homes as single-family residential, condominium, and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that you own in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums where the homeowners own shares in the corporation that owns the building, not the actual units themselves.

For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Home sales prices are not reliably available for Houston, because Texas is a non-disclosure state. For more information on non-disclosure states, see: http://www.zillow.com/blog/chronicles-of-data-collection-ii-non-disclosure-states-3783/

Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.

These datasets contain comprehensive information on current real estate listings in Washington, D.C., obtained from Zillow, and offer a detailed overview of the Washington, D.C. housing market as of 5th June 2024.

The data was extracted from Zillow using a combination of two scraping tools from Apify: Zillow ZIP Code Scraper 🔗 https://apify.com/maxcopell/zillow-zip-search and Zillow Details Scraper 🔗 https://apify.com/maxcopell/zillow-detail-scraper.

The full dataset includes all details for each listing for sale, such as:

• 📍 Complete address, city, state, zip code, latitude/longitude coordinates
• 🏡 Property type (single family, condo, apartment, etc.)
• 💵 Listing price
• 🛏️ Number of bedrooms and bathrooms
• 📐 Square footage
• 🌳 Lot size in acres (if applicable)
• 🏗️ Year of construction
• 🏘️ HOA fees (if applicable)
• 💸 Property tax history
• ✨ Amenities such as rooftop terraces, concierge services, etc.
• 🏫 Nearby schools and their GreatSchools ratings
• 🧑‍💼 Property and listing agents, brokers, and their contact information
• 🕒 Availability for tours and open houses
• 🖼️ Links to listing photos

With over 5,000 current listings, this dataset is perfect for in-depth analysis of the Washington, D.C. housing market and the Washington, D.C. real estate scene. Potential applications include:

• Comparing listing prices and price per square foot across various neighborhoods and property types
• Mapping listings to visualize the spatial distribution of available inventory
• Analyzing the age of available housing stock using year-of-construction data
• Assessing typical HOA fees and property taxes for listings
• Identifying listings with desirable amenities
• Evaluating school quality near listings using GreatSchools ratings
• Contacting listing agents programmatically using the provided agent information

Whether you're a real estate professional, market analyst, data scientist, or simply interested in the Washington, D.C., housing market, this dataset offers a wealth of information to explore. You can begin investigating and discovering insights into Washington, D.C. real estate today.

Hello my fellow data enthusiasts! I'm back!

My journey into the world of real estate data has been nothing short of exciting, and I’m thrilled to share the fruits of that adventure with you all. After spending a few weeks tinkering with APIs, parsing responses, and structuring data into something meaningful, I'm excited to present the CLEANEST Zillow Dataset you've every seen!

Analysts will be able to get actionable insights and a structured view into the fascinating world of property data.

Here’s the story behind the dataset: Zillow’s data provides a treasure trove of information, but raw responses can be messy with nested structures, and scattered details. So, I rolled up my sleeves and built a robust pipeline to extract key data points from each response. From property details to price history, every piece of information was carefully categorized and mapped into logical fields. My goal was to create a dataset that feels as polished and user-friendly as the apps we rely on daily.

What Makes This Dataset Special?

• Structured & Clean Data: Every property in the dataset has been meticulously processed, cleaned, and formatted to make analysis seamless.
• Comprehensive Coverage: Whether you're analyzing trends in property values or studying features that drive price differences, this dataset has you covered.
• Accessible Layout: Tables are structured logically, with relationships that make sense for analysts at every level. This dataset is more than just numbers – it’s a toolkit for anyone looking to dive into real estate analysis, build predictive models, or simply explore trends in the housing market.

If you have any questions, feedback, or just want to geek out about data, don’t hesitate to connect with me on LinkedIn or here on Kaggle. Let’s build something awesome together!

NOTES: I use Google's Cloud Composer to request this data and due to costs, I'm only grabbing data for properties that were recently put up for sale or sold within the day of execution. If you're looking for historical data, please reach out!

Disclaimer: This dataset is intended for non-commercial, academic purposes and does not infringe upon Zillow's intellectual property rights. For full details on Zillow's terms, please visit Zillow's Terms of Use.

Dive in, explore, and let me know what you think. Happy analyzing!

Other Datasets: - Spotify

VITAL SIGNS INDICATOR Home Prices (EC7)

FULL MEASURE NAME Home Prices

LAST UPDATED August 2019

DESCRIPTION Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.

DATA SOURCE Zillow Median Sale Price (1997-2018) http://www.zillow.com/research/data/

Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1997-2018; specific to each metro area) http://data.bls.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Median housing price estimates for the region, counties, cities, and zip code come from analysis of individual home sales by Zillow. The median sale price is the price separating the higher half of the sales from the lower half. In other words, 50 percent of home sales are below or above the median value. Zillow defines all homes as single-family residential, condominium, and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that you own in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums where the homeowners own shares in the corporation that owns the building, not the actual units themselves.

For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Home sales prices are not reliably available for Houston, because Texas is a non-disclosure state. For more information on non-disclosure states, see: http://www.zillow.com/blog/chronicles-of-data-collection-ii-non-disclosure-states-3783/

Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.

Graph and download economic data for Zillow Home Value Index (ZHVI) for All Homes Including Single-Family Residences, Condos, and CO-OPs in Massachusetts (MAUCSFRCONDOSMSAMID) from Jan 2000 to Oct 2025 about MA, 1-unit structures, family, residential, housing, indexes, and USA.

Searchable online database of homes for sale, rent, and not currently on the market, with value estimator, market report, and real-estate trend tool. Users search by location (neighborhood, city, zip code, address) and parameters, such as property specifications, pricing, and keyword. Registration allows for favorite listing saving, customized property e-mail alerts, and other privileges. Users can also access real-estate listing data through an API.

The online residential home sale listings industry is experiencing significant changes in its dynamics because of the increased number of homes for sale. The growth in listings is because of various factors, including a climb in the number of homeowners choosing to sell, the easing of the mortgage rate lock-in effect, and economic concerns driving the sale of investment properties. These conditions and the shift from a seller's market towards a more balanced, or even a buyer's market, translate into increased traffic and engagement on home sale platforms. This presents an opportunity for these online platforms to enhance their user experience, refine search tools and offer data analytics to help buyers navigate the increased options. By the end of 2025, industry revenue has climbed at a CAGR of 3.0% and is expected to total $2.2 billion in 2025. In 2025, revenue is expected to strengthen by an estimated 4.2%. Despite enjoying growth, the industry faces challenges with the elevated mortgage rates reducing demand for home purchases, leading to a market freeze. Despite the gain in home listings, actual transaction volumes have remained subdued, creating a challenging environment for the online residential home sale listing platforms. To stay competitive, these platforms are pivoting to offer enhanced tools for price comparisons, real-time mortgage calculators and in-depth educational content to help buyers understand the increased cost of borrowing and also navigate the high inventory but low turnover market. Industry profit has climbed as revenue has outpaced wage growth through the end of 2025. Through the end of 2030, online platforms must position themselves for demographic shifts and changing consumer preferences. Gen Z and younger millennials, who are entering homebuying age, are demanding a more tech-driven, seamless and mobile-first experience. The industry will also continue to see online platforms transform into comprehensive, one-stop digital destinations offering integrated services for every stage of the housing journey. Embracing changes such as artificial intelligence and data analytics to enhance user experience, streamlining listings uploads and offering real-time communication between buyers, sellers, and agents will be crucial for future success. Platforms that offer user-friendly, one-stop experiences and are equipped to provide advanced, feature-rich mobile experiences are set to capture greater market share. Overall, industry revenue will gain at a CAGR of 3.3% through 2030 to total $2.6 billion.

Time series Zillow Housing price index data and 2023 population and 2023 median household income data for municipalities within Wyoming and surrounding states.

Graph and download economic data for Zillow Home Value Index (ZHVI) for All Homes Including Single-Family Residences, Condos, and CO-OPs in New Jersey (NJUCSFRCONDOSMSAMID) from Jan 2000 to Oct 2025 about 1-unit structures, NJ, family, residential, housing, indexes, and USA.

Discover the booming rental housing market! Explore key trends, drivers, and challenges impacting this multi-trillion dollar industry. Learn about top players like Airbnb and Zillow, regional market share, and future growth projections to 2033. Get insights to inform your investment or business strategy.

This dataset is comprised of seven different configurations of data covering different aspects of the housing market in the United States. All data is provided by Zillow. The seven configurations are: home_values_forecasts, new_construction, for_sale_listings, rentals, sales, home_values, and days_on_market. Each configuration has a different set of features and target variables. The data is provided in JSONL format.