100+ datasets found
  1. c

    Redfin properties dataset

    • crawlfeeds.com
    csv, zip
    Updated Jun 13, 2025
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    Crawl Feeds (2025). Redfin properties dataset [Dataset]. https://crawlfeeds.com/datasets/redfin-properties-dataset
    Explore at:
    zip, csvAvailable download formats
    Dataset updated
    Jun 13, 2025
    Dataset authored and provided by
    Crawl Feeds
    License

    https://crawlfeeds.com/privacy_policyhttps://crawlfeeds.com/privacy_policy

    Description

    Our dataset features comprehensive housing market data, extracted from 250,000 records sourced directly from Redfin USA. Our Crawl Feeds team utilized proprietary in-house tools to meticulously scrape and compile this valuable data.

    Key Benefits of Our Housing Market Data:

    • In-Depth Market Analysis: Gain insights into the real estate market with up-to-date data on recently sold properties.

    • Price Trend Identification: Track and analyze price trends across different cities.

    • Accurate Price Estimation: Estimate property values based on key factors such as area, number of beds and baths, square footage, and more.

    • Detailed Real Estate Statistics: Access detailed statistics segmented by zip code, area, and state.

    Unlock the Power of Redfin Data for Real Estate Professionals

    Leveraging our Redfin properties dataset allows real estate professionals to make data-driven decisions. With detailed insights into property listings, sales history, and pricing trends, agents and investors can identify opportunities in the market more effectively. The data is particularly useful for comparing neighborhood trends, understanding market demand, and making informed investment decisions.

    Enhance Your Real Estate Research with Custom Filters and Analysis

    Our Redfin dataset is not only extensive but also customizable, allowing users to apply filters based on specific criteria such as property type, listing status, and geographic location. This flexibility enables researchers and analysts to drill down into the data, uncovering patterns and insights that can guide strategic planning and market entry decisions. Whether you're tracking the performance of single-family homes or exploring multi-family property trends, this dataset offers the depth and accuracy needed for thorough analysis.

    Looking for deeper insights or a custom data pull from Redfin?
    Send a request with just one click and explore detailed property listings, price trends, and housing data.
    đź”— Request Redfin Real Estate Data

  2. Zillow (Phila. only)

    • s.cnmilf.com
    • catalog.data.gov
    • +1more
    Updated Mar 31, 2025
    + more versions
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    Zillow (2025). Zillow (Phila. only) [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/zillow-phila-only
    Explore at:
    Dataset updated
    Mar 31, 2025
    Dataset provided by
    Zillowhttp://zillow.com/
    Area covered
    Philadelphia
    Description

    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.

  3. d

    Autoscraping | Zillow USA Real Estate Data | 10M Listings with Pricing &...

    • datarade.ai
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    AutoScraping, Autoscraping | Zillow USA Real Estate Data | 10M Listings with Pricing & Market Insights [Dataset]. https://datarade.ai/data-products/autoscraping-s-zillow-usa-real-estate-data-10m-listings-wit-autoscraping
    Explore at:
    .json, .csv, .xls, .sqlAvailable download formats
    Dataset authored and provided by
    AutoScraping
    Area covered
    United States
    Description

    Autoscraping's Zillow USA Real Estate Data is a comprehensive and meticulously curated dataset that covers over 10 million property listings across the United States. This data product is designed to meet the needs of professionals across various sectors, including real estate investment, market analysis, urban planning, and academic research. Our dataset is unique in its depth, accuracy, and timeliness, ensuring that users have access to the most relevant and actionable information available.

    What Makes Our Data Unique? The uniqueness of our data lies in its extensive coverage and the precision of the information provided. Each property listing is enriched with detailed attributes, including but not limited to, full addresses, asking prices, property types, number of bedrooms and bathrooms, lot size, and Zillow’s proprietary value and rent estimates. This level of detail allows users to perform in-depth analyses, make informed decisions, and gain a competitive edge in their respective fields.

    Furthermore, our data is continually updated to reflect the latest market conditions, ensuring that users always have access to current and accurate information. We prioritize data quality, and each entry is carefully validated to maintain a high standard of accuracy, making this dataset one of the most reliable on the market.

    Data Sourcing: The data is sourced directly from Zillow, one of the most trusted names in the real estate industry. By leveraging Zillow’s extensive real estate database, Autoscraping ensures that users receive data that is not only comprehensive but also highly reliable. Our proprietary scraping technology ensures that data is extracted efficiently and without errors, preserving the integrity and accuracy of the original source. Additionally, we implement strict data processing and validation protocols to filter out any inconsistencies or outdated information, further enhancing the quality of the dataset.

    Primary Use-Cases and Vertical Applications: Autoscraping's Zillow USA Real Estate Data is versatile and can be applied across a variety of use cases and industries:

    Real Estate Investment: Investors can use this data to identify lucrative opportunities, analyze market trends, and compare property values across different regions. The detailed pricing and valuation data allow for comprehensive due diligence and risk assessment.

    Market Analysis: Market researchers can leverage this dataset to track real estate trends, evaluate the performance of different property types, and assess the impact of economic factors on property values. The dataset’s nationwide coverage makes it ideal for both local and national market studies.

    Urban Planning and Development: Urban planners and developers can use the data to identify growth areas, plan new developments, and assess the demand for different property types in various regions. The detailed location data is particularly valuable for site selection and zoning analysis.

    Academic Research: Universities and research institutions can utilize this data for studies on housing markets, urbanization, and socioeconomic trends. The comprehensive nature of the dataset allows for a wide range of academic applications.

    Integration with Our Broader Data Offering: Autoscraping's Zillow USA Real Estate Data is part of our broader data portfolio, which includes various datasets focused on real estate, market trends, and consumer behavior. This dataset can be seamlessly integrated with our other offerings to provide a more holistic view of the market. For example, combining this data with our consumer demographic datasets can offer insights into the relationship between property values and demographic trends.

    By choosing Autoscraping's data products, you gain access to a suite of complementary datasets that can be tailored to meet your specific needs. Whether you’re looking to gain a comprehensive understanding of the real estate market, identify new investment opportunities, or conduct advanced research, our data offerings are designed to provide you with the insights you need.

  4. c

    Redfin usa properties dataset

    • crawlfeeds.com
    csv, zip
    Updated Jun 13, 2025
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    Crawl Feeds (2025). Redfin usa properties dataset [Dataset]. https://crawlfeeds.com/datasets/redfin-usa-properties-dataset
    Explore at:
    zip, csvAvailable download formats
    Dataset updated
    Jun 13, 2025
    Dataset authored and provided by
    Crawl Feeds
    License

    https://crawlfeeds.com/privacy_policyhttps://crawlfeeds.com/privacy_policy

    Area covered
    United States
    Description

    Explore the Redfin USA Properties Dataset, available in CSV format. This extensive dataset provides valuable insights into the U.S. real estate market, including detailed property listings, prices, property types, and more across various states and cities. Perfect for those looking to conduct in-depth market analysis, real estate investment research, or financial forecasting.

    Key Features:

    • Comprehensive Property Data: Includes essential details such as listing prices, property types, square footage, and the number of bedrooms and bathrooms.
    • Geographic Coverage: Encompasses a wide range of U.S. states and cities, providing a broad view of the national real estate market.
    • Historical Trends: Analyze past market data to understand price movements, regional differences, and market trends over time.
    • Geo-Location Details: Enables spatial analysis and mapping by including precise geographical coordinates of properties.

    Who Can Benefit From This Dataset:

    • Real Estate Investors: Identify lucrative opportunities by analyzing property values, market trends, and regional price variations.
    • Market Analysts: Gain a deeper understanding of the U.S. housing market dynamics to inform research and reporting.
    • Data Scientists and Researchers: Leverage detailed real estate data for modeling, urban studies, or economic analysis.
    • Financial Analysts: Utilize the dataset for financial modeling, helping to predict market behavior and assess investment risks.

    Download the Redfin USA Properties Dataset to access essential information on the U.S. housing market, ideal for professionals in real estate, finance, and data analytics. Unlock key insights to make informed decisions in a dynamic market environment.

    Looking for deeper insights or a custom data pull from Redfin?
    Send a request with just one click and explore detailed property listings, price trends, and housing data.
    đź”— Request Redfin Real Estate Data

  5. F

    Housing Inventory: Median Days on Market in the United States

    • fred.stlouisfed.org
    json
    Updated Jul 10, 2025
    + more versions
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    (2025). Housing Inventory: Median Days on Market in the United States [Dataset]. https://fred.stlouisfed.org/series/MEDDAYONMARUS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 10, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Area covered
    United States
    Description

    Graph and download economic data for Housing Inventory: Median Days on Market in the United States (MEDDAYONMARUS) from Jul 2016 to Jun 2025 about median and USA.

  6. d

    Property Listings Data | USA Coverage | 74% Right Party Contact Rate |...

    • datarade.ai
    Updated Aug 14, 2024
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    BatchService (2024). Property Listings Data | USA Coverage | 74% Right Party Contact Rate | BatchData [Dataset]. https://datarade.ai/data-products/batchservice-u-s-property-listings-data-real-estate-mark-batchservice
    Explore at:
    .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Aug 14, 2024
    Dataset authored and provided by
    BatchService
    Area covered
    United States
    Description

    BatchData's property listings data provides comprehensive insights with over 140 data points and nationwide listing data inclusive of For Sale By Owner (FSBO) listings across the United States. Updated daily in most markets, the data includes:

    • Listing Details: property listings descriptions, property characteristics, pricing, days on market, and more.
    • Agent Information: agent names, license numbers, contact details, listing counts, and listing histories.
    • Broker Information: Broker names, locations, URLs, emails, phone numbers, and licensing information.
    • Additional Details: Information about schools, neighborhoods, subdivisions, and tax data.

    Common Use Cases: - Recruiting Teams: Enhance talent acquisition by analyzing agents' listing counts, close rates, property types, and client profiles. - Proptech Software & Marketplaces: Integrate current and historical listings to create detailed property profiles, advanced search features, and robust analytics. - Home Service Providers: Target marketing and outreach efforts to homeowners, whether they are preparing to move or have recently relocated. - Real Estate Agents & Investors: Identify undervalued properties, connect with buyers/sellers based on activity, analyze market trends, and develop effective marketing strategies.

    Our property listings data can be delivered in a variety of formats to suit your needs. Choose from API integration for seamless, real-time data access, bulk data delivery for extensive datasets, S3 bucket storage for scalable cloud solutions, and more. This flexibility ensures that you can incorporate our comprehensive property information into your systems efficiently and effectively, whether you're building a new platform, enhancing existing tools, or conducting in-depth analyses.

  7. F

    Median Sales Price of Houses Sold for the United States

    • fred.stlouisfed.org
    json
    Updated Apr 23, 2025
    + more versions
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    (2025). Median Sales Price of Houses Sold for the United States [Dataset]. https://fred.stlouisfed.org/series/MSPUS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Apr 23, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q1 2025 about sales, median, housing, and USA.

  8. CoreLogic Multiple Listing Service

    • redivis.com
    application/jsonl +7
    Updated Sep 11, 2024
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    Stanford University Libraries (2024). CoreLogic Multiple Listing Service [Dataset]. http://doi.org/10.57761/cx2z-qr20
    Explore at:
    parquet, arrow, application/jsonl, sas, spss, stata, csv, avroAvailable download formats
    Dataset updated
    Sep 11, 2024
    Dataset provided by
    Redivis Inc.
    Authors
    Stanford University Libraries
    Description

    Abstract

    A multiple listing service (MLS) is an exchange where real estate brokers share information about properties they are selling. Other real estate brokers review the listings, and are compensated if they can identify a buyer for a property. Multiple listing services promote cooperation and mutual benefit for real estate brokers representing buyers and sellers. The CoreLogic Multiple Listing Service data contains listings from 135 real estate boards utilizing CoreLogic’s multiple listing service software. The data was produced in August 2024.

    Methodology

    The data consists of listings from 135 real estate boards that use CoreLogic listing software. The data DOES NOT cover listings from all real estate boards in the United States. The National Association of Realtors maintains the most complete and up-to-date list of real estate boards; however, this information is only available to members of the National Association of Realtors.

    For more information about how the data was prepared for Redivis, please see CoreLogic 2024 GitLab.

    Usage

    Quick Search (QS) contains the most recent listing data (as of August 2024). In order to see the entire listing history of a property/record, you will need to search the Quick History (QH) table on the SysPropertyID, which is a unique key for a listing across multiple listing boards. You can use the variable FA_PostDate to see when updates occurred. Updates include name changes, price changes, etc.

    During upload to Data Farm, a small number of invalid records were dropped from the Quick History (QH) table. For more information, see CoreLogic 2024 GitLab. To access the complete data (including invalid records), please see Bulk Data Access instructions, below.

    Bulk Data Access

    Data access is required to view this section.

  9. Real Estate Data South Carolina 2025

    • kaggle.com
    Updated Jul 8, 2025
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    Kanchana1990 (2025). Real Estate Data South Carolina 2025 [Dataset]. http://doi.org/10.34740/kaggle/ds/7823602
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 8, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Kanchana1990
    License

    Open Data Commons Attribution License (ODC-By) v1.0https://www.opendatacommons.org/licenses/by/1.0/
    License information was derived automatically

    Area covered
    South Carolina
    Description

    South Carolina Real Estate Dataset 2025

    Dataset Overview

    This comprehensive real estate dataset contains over 5,000 property listings from South Carolina, collected in 2025 from Realtor.com using apify api. The dataset captures diverse property types including single-family homes, condominiums, land parcels, townhomes, and other residential properties. This dataset provides a rich snapshot of South Carolina's real estate market suitable for predictive modeling, market analysis, and investment research.

    Data Science Applications

    • Price Prediction Models: Build regression models (Random Forest, XGBoost, Neural Networks) to predict property values based on size, location, bedrooms, and age
    • Property Type Classification: Develop multi-class classifiers to categorize properties based on physical characteristics
    • Market Segmentation: Apply clustering algorithms (K-means, DBSCAN) to identify distinct property segments and price brackets
    • Time Series Analysis: Analyze construction trends and property age distributions to forecast future development patterns
    • Investment Opportunity Detection: Create anomaly detection models to identify undervalued properties or outliers
    • Feature Engineering: Generate derived features like price per square foot, bathroom-to-bedroom ratios for enhanced model performance

    Column Descriptors

    • type: Primary property category (single_family, condos, land, townhomes, multi_family, farm)
    • sub_type: Detailed property classification (condo, townhouse, co_op)
    • sqft: Property size in square feet
    • baths: Number of bathrooms (decimal values indicate half baths)
    • beds: Number of bedrooms
    • stories: Number of floors/stories in the property
    • year_built: Construction year of the property
    • listPrice: Property listing price in USD

    Ethically Obtained Data

    This dataset was ethically scraped from publicly available listings on Realtor.com and is provided strictly for educational and learning purposes only. The data collection complied with ethical web scraping practices and contains only publicly accessible information. Users should utilize this dataset exclusively for academic research, educational projects, and learning data science techniques. Any commercial use is strictly prohibited.

  10. d

    Live Rental Listing Data | US Rental | National Coverage | Bulk | 970k...

    • datarade.ai
    .json, .csv, .xls
    Updated Mar 11, 2025
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    CompCurve (2025). Live Rental Listing Data | US Rental | National Coverage | Bulk | 970k Properties Daily | Rental Data Real Estate Data [Dataset]. https://datarade.ai/data-products/live-rental-listing-data-us-rental-national-coverage-bu-compcurve
    Explore at:
    .json, .csv, .xlsAvailable download formats
    Dataset updated
    Mar 11, 2025
    Dataset authored and provided by
    CompCurve
    Area covered
    United States of America
    Description

    Our extensive database contains approximately 800,000 active rental property listings from across the United States. Updated daily, this comprehensive collection provides real estate professionals, investors, and property managers with valuable market intelligence and business opportunities. Database Contents

    Property Addresses: Complete location data including street address, city, state, ZIP code Listing Dates: Original listing date and most recent update date Availability Status: Currently available, pending, or recently rented properties Geographic Coverage: Properties spanning all 50 states and major metropolitan areas

    Applications & Uses

    Market Analysis: Track rental pricing trends across different regions and property types Investment Research: Identify high-opportunity markets with favorable rental conditions Lead Generation: Connect with property owners potentially needing management services Competitive Intelligence: Monitor listing volumes, vacancy rates, and market saturation Business Development: Target specific neighborhoods or property categories for expansion

    File Format & Delivery

    Organized in easy-to-use CSV format for seamless integration with data analysis tools Accessible through secure download portal or API connection Daily updates ensure you're working with the most current market information Custom filtering options available to narrow results by location, date range, or other criteria

    Data Quality

    Rigorous validation processes to ensure address accuracy Duplicate listing detection and removal Regular verification of active status Standardized format for consistent analysis

    Subscription Benefits

    Access to historical listing archives for trend analysis Advanced search capabilities to target specific property characteristics Regular market reports summarizing key trends and opportunities Custom data exports tailored to your specific business needs

    AK ~ 1,342 listings AL ~ 6,636 listings AR ~ 4,024 listings AZ ~ 25,782 listings CA ~ 102,833 listings CO ~ 14,333 listings CT ~ 10,515 listings DC ~ 1,988 listings DE ~ 1,528 listings FL ~ 152,258 listings GA ~ 28,248 listings HI ~ 3,447 listings IA ~ 4,557 listings ID ~ 3,426 listings IL ~ 42,642 listings IN ~ 8,634 listings KS ~ 3,263 listings KY ~ 5,166 listings LA ~ 11,522 listings MA ~ 53,624 listings MD ~ 12,124 listings ME ~ 1,754 listings MI ~ 12,040 listings MN ~ 7,242 listings MO ~ 10,766 listings MS ~ 2,633 listings MT ~ 1,953 listings NC ~ 22,708 listings ND ~ 1,268 listings NE ~ 1,847 listings NH ~ 2,672 listings NJ ~ 31,286 listings NM ~ 2,084 listings NV ~ 13,111 listings NY ~ 94,790 listings OH ~ 15,843 listings OK ~ 5,676 listings OR ~ 8,086 listings PA ~ 37,701 listings RI ~ 4,345 listings SC ~ 8,018 listings SD ~ 1,018 listings TN ~ 15,983 listings TX ~ 132,620 listings UT ~ 3,798 listings VA ~ 14,087 listings VT ~ 946 listings WA ~ 15,039 listings WI ~ 7,393 listings WV ~ 1,681 listings WY ~ 730 listings

    Grand Total ~ 977,010 listings

  11. d

    Realtor Property Data, Realtor Data, Realtor API, Property Owner Data,...

    • datarade.ai
    Updated Jan 13, 2024
    + more versions
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    APISCRAPY (2024). Realtor Property Data, Realtor Data, Realtor API, Property Owner Data, Scrape All Publicly Available Property Listings & Data - Easy to Integrate. [Dataset]. https://datarade.ai/data-products/realtor-property-data-realtor-data-realtor-api-zillow-prop-apiscrapy
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Jan 13, 2024
    Dataset authored and provided by
    APISCRAPY
    Area covered
    Croatia, Romania, Sweden, Monaco, Japan, Guernsey, China, Lithuania, United Kingdom, Norway
    Description

    Note:- Only publicly available real estate data can be worked upon.

    Discover the world of property insights with APISCRAPY's user-friendly services – Realtor Property Data, Realtor Data, and Realtor API. Designed for ease of use, our platform allows anyone, from real estate professionals to researchers and businesses, to effortlessly access publicly available property listings and Property owner Data.

    Our Realtor Property Data service provides comprehensive details on property listings, while Realtor API ensures easy integration for streamlined access. Additionally, we offer Zillow Property Data, enriching your property insights with information from one of the leading property platforms.

    Key Features:

    Realtor Property Data: Dive into detailed property listings effortlessly with our user-friendly platform.

    Realtor API Integration: Seamlessly integrate our Realtor API into your systems for easy access to property data.

    Zillow Property Data: Enrich your property insights with data from Zillow, one of the leading property platforms.

    Publicly Available Property Listings: APISCRAPY ensures access to publicly available property listings, making property data easily accessible.

    Easy Integration: Our platform is designed for simplicity, allowing for easy integration into your existing systems.

    Whether you're a real estate professional, researcher, or business looking for straightforward access to property information, APISCRAPY's services cater to your needs. Choose us for simple and efficient property data services, where ease of use and accessibility come together for your convenience.

  12. T

    United States Existing Home Sales

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +12more
    csv, excel, json, xml
    Updated May 22, 2025
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    TRADING ECONOMICS (2025). United States Existing Home Sales [Dataset]. https://tradingeconomics.com/united-states/existing-home-sales
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset updated
    May 22, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1968 - May 31, 2025
    Area covered
    United States
    Description

    Existing Home Sales in the United States increased to 4030 Thousand in May from 4000 Thousand in April of 2025. This dataset provides the latest reported value for - United States Existing Home Sales - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  13. F

    Housing Inventory: Active Listing Count in the United States

    • fred.stlouisfed.org
    json
    Updated Jul 10, 2025
    + more versions
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    Housing Inventory: Active Listing Count in the United States [Dataset]. https://fred.stlouisfed.org/series/ACTLISCOUUS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 10, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Area covered
    United States
    Description

    Graph and download economic data for Housing Inventory: Active Listing Count in the United States (ACTLISCOUUS) from Jul 2016 to Jun 2025 about active listing, listing, and USA.

  14. Donuka: USA Nationwide Property Data (155M+ Properties)

    • datarade.ai
    Updated Dec 13, 2006
    + more versions
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    Donuka (2006). Donuka: USA Nationwide Property Data (155M+ Properties) [Dataset]. https://datarade.ai/data-products/donuka-usa-nationwide-property-data-155m-properties-donuka
    Explore at:
    .json, .xml, .csv, .xls, .txtAvailable download formats
    Dataset updated
    Dec 13, 2006
    Dataset authored and provided by
    Donuka
    Area covered
    United States
    Description

    Donuka offers a simple, reliable property data solution to power innovation and create seamless business solutions for companies of all sizes. Our data covers more than 155+ million properties spread out across the U.S. that can be accessed in bulk-file format or through our APIs.

    We offer access to data ONLY in selected states and counties

    DATA SOURCES:

    1. ONLY state sources (city/county/state administration, federal agencies, ministries, etc.). We DO NOT use unverified databases
    2. Over 2300 sources. We use even the smallest sources, because they contain valuable data. This allows us to provide our users with the most complete data

    DATA RELEVANCE:

    1. Our data is updated daily, weekly, monthly depending on the sources
    2. We collect, process and store all data, regardless of their relevance. Historical data is also valuable

    DATA TYPES:

    1. Specifications
    2. Owners
    3. Permits
    4. Sales
    5. Inspections
    6. Violations
    7. Assessed values
    8. Taxes
    9. Risks
    10. Foreclosures
    11. Property Tax Liens
    12. Deed Restrictions

    NUMBERS:

    1. 2300+ data sources in total
    2. 4 billion records (listed in the "data types" block above) in total
    3. 2 million new records every day

    DATA USAGE:

    1. Property check, investigation (even the smallest events are stored in our database)
    2. Prospecting (more than 100 parameters to find the required records)
    3. Tracking (our data allows us to track any changes)
  15. Zingat Property Listing Data

    • kaggle.com
    Updated Mar 7, 2019
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    Zingat (2019). Zingat Property Listing Data [Dataset]. https://www.kaggle.com/zingatbi/zingat-real-estate/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 7, 2019
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Zingat
    Description

    Motivation

    Zingat operates as an intermediary between potential buyers and sellers in the real estate market. In this regard, to help both parties we routinely value and monitor real estate market. For this purpose, we regularly build new and better models using new technologies in the field of data science. Not only with automated valuation models that predict house prices, we also employ time series models to understand market trends. These models include both the statistical excellence and the domain know-how. As strong believers of sharing and data, we would like to contribute to community by sharing our data. This is just a first step of our public data policy. More data will be opened when we have availability.

    Goal

    We would like you use this sample listing data. You may always crawl our site within ethical and legal boundaries. However if you dont prefer it, here is sample dataset for you to use it in your research. Should you need more and broader data, feel free to contact us. Give it a go, play around with data. We are curious about hearing your findings. In near future, we will also organize datathons with similar datasets. So this should give you some playground beforehand.

  16. M

    Vital Signs: List Rents – by city

    • open-data-demo.mtc.ca.gov
    • data.bayareametro.gov
    application/rdfxml +5
    Updated Jan 19, 2017
    + more versions
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    real Answers (2017). Vital Signs: List Rents – by city [Dataset]. https://open-data-demo.mtc.ca.gov/dataset/Vital-Signs-List-Rents-by-city/vpmm-yh3p/about
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    tsv, csv, json, xml, application/rdfxml, application/rssxmlAvailable download formats
    Dataset updated
    Jan 19, 2017
    Dataset authored and provided by
    real Answers
    Description

    VITAL SIGNS INDICATOR List Rents (EC9)

    FULL MEASURE NAME List Rents

    LAST UPDATED October 2016

    DESCRIPTION List rent refers to the advertised rents for available rental housing and serves as a measure of housing costs for new households moving into a neighborhood, city, county or region.

    DATA SOURCE real Answers (1994 – 2015) no link

    Zillow Metro Median Listing Price All Homes (2010-2016) http://www.zillow.com/research/data/

    CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

    METHODOLOGY NOTES (across all datasets for this indicator) List rents data reflects median rent prices advertised for available apartments rather than median rent payments; more information is available in the indicator definition above. Regional and local geographies rely on data collected by real Answers, a research organization and database publisher specializing in the multifamily housing market. real Answers focuses on collecting longitudinal data for individual rental properties through quarterly surveys. For the Bay Area, their database is comprised of properties with 40 to 3,000+ housing units. Median list prices most likely have an upward bias due to the exclusion of smaller properties. The bias may be most extreme in geographies where large rental properties represent a small portion of the overall rental market. A map of the individual properties surveyed is included in the Local Focus section.

    Individual properties surveyed provided lower- and upper-bound ranges for the various types of housing available (studio, 1 bedroom, 2 bedroom, etc.). Median lower- and upper-bound prices are determined across all housing types for the regional and county geographies. The median list price represented in Vital Signs is the average of the median lower- and upper-bound prices for the region and counties. Median upper-bound prices are determined across all housing types for the city geographies. The median list price represented in Vital Signs is the median upper-bound price for cities. For simplicity, only the mean list rent is displayed for the individual properties. The metro areas geography rely upon Zillow data, which is the median price for rentals listed through www.zillow.com during the month. Like the real Answers data, Zillow's median list prices most likely have an upward bias since small properties are underrepresented in Zillow's listings. The metro area data for the Bay Area cannot be compared to the regional Bay Area data. Due to afore mentioned data limitations, this data is suitable for analyzing the change in list rents over time but not necessarily comparisons of absolute list rents. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries.

    Due to the limited number of rental properties surveyed, city-level data is unavailable for Atherton, Belvedere, Brisbane, Calistoga, Clayton, Cloverdale, Cotati, Fairfax, Half Moon Bay, Healdsburg, Hillsborough, Los Altos Hills, Monte Sereno, Moranga, Oakley, Orinda, Portola Valley, Rio Vista, Ross, San Anselmo, San Carlos, Saratoga, Sebastopol, Windsor, Woodside, and Yountville.

    Inflation-adjusted data are presented to illustrate how rents 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. Percent change in inflation-adjusted median is calculated with respect to the median price from the fourth quarter or December of the base year.

  17. C

    Allegheny County Property Sale Transactions

    • data.wprdc.org
    • datadiscoverystudio.org
    • +3more
    csv, html
    Updated Jul 12, 2025
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    Allegheny County (2025). Allegheny County Property Sale Transactions [Dataset]. https://data.wprdc.org/dataset/real-estate-sales
    Explore at:
    csv, htmlAvailable download formats
    Dataset updated
    Jul 12, 2025
    Dataset provided by
    Allegheny County
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Allegheny County
    Description

    This dataset contains data on all Real Property parcels that have sold since 2013 in Allegheny County, PA.

    Before doing any market analysis on property sales, check the sales validation codes. Many property "sales" are not considered a valid representation of the true market value of the property. For example, when multiple lots are together on one deed with one price they are generally coded as invalid ("H") because the sale price for each parcel ID number indicates the total price paid for a group of parcels, not just for one parcel. See the Sales Validation Codes Dictionary for a complete explanation of valid and invalid sale codes.

    Sales Transactions Disclaimer: Sales information is provided from the Allegheny County Department of Administrative Services, Real Estate Division. Content and validation codes are subject to change. Please review the Data Dictionary for details on included fields before each use. Property owners are not required by law to record a deed at the time of sale. Consequently the assessment system may not contain a complete sales history for every property and every sale. You may do a deed search at http://www.alleghenycounty.us/re/index.aspx directly for the most updated information. Note: Ordinance 3478-07 prohibits public access to search assessment records by owner name. It was signed by the Chief Executive in 2007.

  18. F

    Average Sales Price of Houses Sold for the United States

    • fred.stlouisfed.org
    json
    Updated Apr 23, 2025
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    (2025). Average Sales Price of Houses Sold for the United States [Dataset]. https://fred.stlouisfed.org/series/ASPUS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Apr 23, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Average Sales Price of Houses Sold for the United States (ASPUS) from Q1 1963 to Q1 2025 about sales, housing, and USA.

  19. AI-Generated Real Estate Listing Market Research Report 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jun 28, 2025
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    Dataintelo (2025). AI-Generated Real Estate Listing Market Research Report 2033 [Dataset]. https://dataintelo.com/report/ai-generated-real-estate-listing-market
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Jun 28, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    AI-Generated Real Estate Listing Market Outlook



    According to our latest research, the AI-generated real estate listing market size reached USD 1.57 billion globally in 2024, reflecting a robust surge in adoption across multiple verticals. The market is projected to grow at a CAGR of 18.9% from 2025 to 2033, with the total market size expected to reach USD 7.28 billion by the end of the forecast period. This growth trajectory is primarily fueled by the increasing demand for automation, enhanced property marketing, and the need for data-driven insights to optimize real estate transactions. As per the latest research, the integration of AI technologies in property listing platforms is transforming how properties are marketed, discovered, and managed, providing unprecedented value to real estate stakeholders globally.




    The rapid expansion of the AI-generated real estate listing market is underpinned by several compelling growth factors. Chief among these is the rising need for efficiency and accuracy in property listing creation and management. Traditional real estate listing processes are time-consuming and prone to human error, often resulting in incomplete or inconsistent property data. AI-powered solutions automate the generation of property descriptions, image enhancements, and even virtual staging, enabling real estate professionals to deliver high-quality listings at scale. This automation not only reduces operational costs but also accelerates the time-to-market for new listings, allowing agencies and agents to respond swiftly to changing market dynamics and consumer preferences.




    Another major driver for the AI-generated real estate listing market is the increasing consumer expectation for personalized and engaging property search experiences. Modern buyers and renters demand comprehensive, visually appealing, and accurate property information that AI can deliver through advanced natural language processing (NLP) and computer vision technologies. AI-generated listings can tailor content based on user behavior, search history, and demographic data, resulting in higher engagement rates and improved conversion metrics. Furthermore, the integration of AI with virtual tours, chatbots, and predictive analytics enhances the overall customer journey, making property discovery more intuitive and satisfying for end-users.




    The proliferation of digital platforms and the shift towards online property transactions have further accelerated the adoption of AI-generated real estate listing solutions. As the real estate industry becomes increasingly digitalized, stakeholders are leveraging AI to gain a competitive edge by offering differentiated services and richer content. The ability of AI to analyze vast datasets, identify emerging trends, and generate actionable insights is particularly valuable in highly competitive markets. Additionally, regulatory changes and the growing emphasis on transparency and compliance are prompting agencies to adopt AI tools that ensure listings are accurate, up-to-date, and legally compliant. These factors collectively create a fertile environment for sustained growth in the AI-generated real estate listing market.




    From a regional perspective, North America currently leads the global AI-generated real estate listing market, accounting for the largest share in 2024. The region’s dominance is attributed to the high rate of technology adoption, significant investments in AI research, and a mature real estate ecosystem. Europe and Asia Pacific are also witnessing rapid growth, with countries like the United Kingdom, Germany, China, and India emerging as key markets. The Asia Pacific region, in particular, is expected to register the highest CAGR during the forecast period, driven by urbanization, a booming property sector, and increasing digital transformation initiatives. Latin America and the Middle East & Africa, while still nascent, are poised for substantial growth as internet penetration and real estate investments continue to rise.



    Component Analysis



    The AI-generated real estate listing market can be segmented by component into software and services, each playing a critical role in the ecosystem. The software segment comprises AI-powered platforms, listing engines, and data analytics tools that automate the creation and optimization of property listings. These solutions leverage advanced algorithms for natural language generation, image recognition, and content personalization, enabling real estat

  20. d

    Real Estate Transaction Data | USA Coverage | 74% Right Party Contact Rate |...

    • datarade.ai
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    BatchService, Real Estate Transaction Data | USA Coverage | 74% Right Party Contact Rate | BatchData [Dataset]. https://datarade.ai/data-products/batchservice-s-deed-history-real-estate-transaction-data-batchservice
    Explore at:
    .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset authored and provided by
    BatchService
    Area covered
    United States of America
    Description

    BatchData's Deed Dataset - Real Estate Transaction Data + Property Transaction Data

    Unlock a wealth of historical real estate insights with BatchData's Deed Dataset. This premium offering provides detailed real estate transaction data, including comprehensive property transaction records with over 15 critical data points. Whether you're analyzing market trends, assessing investment opportunities, or conducting in-depth property research, this dataset delivers the granular information you need.

    Why Choose BatchData?

    At BatchData, we are committed to delivering the most accurate and comprehensive datasets in the industry. Our Deed Dataset exemplifies our dedication to quality and precision:

    • Comprehensive Datasets: As a single-vendor provider, we offer an extensive array of data including property, homeowner, mortgage, listing, valuation, permit, demographic, foreclosure, and contact information. All this is available from one reliable source, streamlining your data acquisition process.

    • Technical Excellence: Our dataset comes with clear documentation, purpose-built APIs, and extensive developer resources. Our technical teams are supported by robust engineering resources to ensure seamless integration and utilization.

    • Tailor-Fit Pricing and Packaging: We understand that different businesses have different needs. That’s why we offer flexible pricing models and practical API metering. You only pay for the data you need, making our solutions scalable and aligned with your business objectives.

    • Unmatched Contact Information Accuracy: We lead the industry with superior right-party contact rates, ensuring you get multiple accurate contact points, including highly reliable phone numbers.

    Choose BatchData for your real estate data needs and experience unparalleled accuracy and flexibility in data solutions.

Share
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Crawl Feeds (2025). Redfin properties dataset [Dataset]. https://crawlfeeds.com/datasets/redfin-properties-dataset

Redfin properties dataset

Redfin properties dataset from redfin.com

Explore at:
zip, csvAvailable download formats
Dataset updated
Jun 13, 2025
Dataset authored and provided by
Crawl Feeds
License

https://crawlfeeds.com/privacy_policyhttps://crawlfeeds.com/privacy_policy

Description

Our dataset features comprehensive housing market data, extracted from 250,000 records sourced directly from Redfin USA. Our Crawl Feeds team utilized proprietary in-house tools to meticulously scrape and compile this valuable data.

Key Benefits of Our Housing Market Data:

  • In-Depth Market Analysis: Gain insights into the real estate market with up-to-date data on recently sold properties.

  • Price Trend Identification: Track and analyze price trends across different cities.

  • Accurate Price Estimation: Estimate property values based on key factors such as area, number of beds and baths, square footage, and more.

  • Detailed Real Estate Statistics: Access detailed statistics segmented by zip code, area, and state.

Unlock the Power of Redfin Data for Real Estate Professionals

Leveraging our Redfin properties dataset allows real estate professionals to make data-driven decisions. With detailed insights into property listings, sales history, and pricing trends, agents and investors can identify opportunities in the market more effectively. The data is particularly useful for comparing neighborhood trends, understanding market demand, and making informed investment decisions.

Enhance Your Real Estate Research with Custom Filters and Analysis

Our Redfin dataset is not only extensive but also customizable, allowing users to apply filters based on specific criteria such as property type, listing status, and geographic location. This flexibility enables researchers and analysts to drill down into the data, uncovering patterns and insights that can guide strategic planning and market entry decisions. Whether you're tracking the performance of single-family homes or exploring multi-family property trends, this dataset offers the depth and accuracy needed for thorough analysis.

Looking for deeper insights or a custom data pull from Redfin?
Send a request with just one click and explore detailed property listings, price trends, and housing data.
đź”— Request Redfin Real Estate Data

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