100+ datasets found
  1. d

    Real Estate Sales 2001-2023 GL

    • catalog.data.gov
    • data.ct.gov
    Updated Aug 23, 2025
    + more versions
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    data.ct.gov (2025). Real Estate Sales 2001-2023 GL [Dataset]. https://catalog.data.gov/dataset/real-estate-sales-2001-2018
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    Dataset updated
    Aug 23, 2025
    Dataset provided by
    data.ct.gov
    Description

    The Office of Policy and Management maintains a listing of all real estate sales with a sales price of $2,000 or greater that occur between October 1 and September 30 of each year. For each sale record, the file includes: town, property address, date of sale, property type (residential, apartment, commercial, industrial or vacant land), sales price, and property assessment. Data are collected in accordance with Connecticut General Statutes, section 10-261a and 10-261b: https://www.cga.ct.gov/current/pub/chap_172.htm#sec_10-261a and https://www.cga.ct.gov/current/pub/chap_172.htm#sec_10-261b. Annual real estate sales are reported by grand list year (October 1 through September 30 each year). For instance, sales from 2018 GL are from 10/01/2018 through 9/30/2019. Some municipalities may not report data for certain years because when a municipality implements a revaluation, they are not required to submit sales data for the twelve months following implementation.

  2. F

    Median Sales Price of Houses Sold for the United States

    • fred.stlouisfed.org
    json
    Updated Jul 24, 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
    Jul 24, 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 Q2 2025 about sales, median, housing, and USA.

  3. C

    Allegheny County Property Sale Transactions

    • data.wprdc.org
    • datadiscoverystudio.org
    • +3more
    csv, html
    Updated Sep 8, 2025
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    Allegheny County (2025). Allegheny County Property Sale Transactions [Dataset]. https://data.wprdc.org/dataset/real-estate-sales
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    csv, htmlAvailable download formats
    Dataset updated
    Sep 8, 2025
    Dataset authored and 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.

  4. T

    United States Existing Home Sales

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +12more
    csv, excel, json, xml
    Updated Aug 21, 2025
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    TRADING ECONOMICS (2025). United States Existing Home Sales [Dataset]. https://tradingeconomics.com/united-states/existing-home-sales
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    csv, json, xml, excelAvailable download formats
    Dataset updated
    Aug 21, 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 - Jul 31, 2025
    Area covered
    United States
    Description

    Existing Home Sales in the United States increased to 4010 Thousand in July from 3930 Thousand in June 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.

  5. F

    Average Sales Price of Houses Sold for the United States

    • fred.stlouisfed.org
    json
    Updated Jul 24, 2025
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    (2025). Average Sales Price of Houses Sold for the United States [Dataset]. https://fred.stlouisfed.org/series/ASPUS
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    jsonAvailable download formats
    Dataset updated
    Jul 24, 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 Q2 2025 about sales, housing, and USA.

  6. d

    Tax Administration's Real Estate - Sales Data

    • catalog.data.gov
    • data.virginia.gov
    • +3more
    Updated Apr 22, 2023
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    County of Fairfax (2023). Tax Administration's Real Estate - Sales Data [Dataset]. https://catalog.data.gov/dataset/tax-administrations-real-estate-sales-data-d73c9
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    Dataset updated
    Apr 22, 2023
    Dataset provided by
    County of Fairfax
    Description

    This table contains property sales information including sale date, price, and amounts for properties within Fairfax County. There is a one to many relationship to the parcel data. Refer to this document for descriptions of the data in the table.

  7. F

    Data from: Existing Home Sales

    • fred.stlouisfed.org
    json
    Updated Aug 21, 2025
    + more versions
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    (2025). Existing Home Sales [Dataset]. https://fred.stlouisfed.org/series/EXHOSLUSM495S
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Aug 21, 2025
    License

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

    Description

    Graph and download economic data for Existing Home Sales (EXHOSLUSM495S) from Jul 2024 to Jul 2025 about headline figure, sales, housing, and USA.

  8. 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
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    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.
    🔗 Request Redfin Real Estate Data

  9. d

    Zillow Real Estate Data Extraction | Real-time Real Estate Market Data | No...

    • datarade.ai
    Updated Nov 7, 2023
    + more versions
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    APISCRAPY (2023). Zillow Real Estate Data Extraction | Real-time Real Estate Market Data | No Infra Cost | Pre-built AI & Automation | 50% Cost Saving | Free Sample [Dataset]. https://datarade.ai/data-products/zillow-real-estate-data-extraction-real-time-real-estate-ma-apiscrapy
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Nov 7, 2023
    Dataset authored and provided by
    APISCRAPY
    Area covered
    Isle of Man, Spain, Liechtenstein, Albania, Iceland, Croatia, Portugal, Bulgaria, Belgium, Canada
    Description

    Note:- Only publicly available data can be worked upon

    APISCRAPY collects and organizes data from Zillow's massive database, whether it's property characteristics, market trends, pricing histories, or more. Because of APISCRAPY's first-rate data extraction services, tracking property values, examining neighborhood trends, and monitoring housing market variations become a straightforward and efficient process.

    APISCRAPY's Zillow real estate data scraping service offers numerous advantages for individuals and businesses seeking valuable insights into the real estate market. Here are key benefits associated with their advanced data extraction technology:

    1. Real-time Zillow Real Estate Data: Users can access real-time data from Zillow, providing timely updates on property listings, market dynamics, and other critical factors. This real-time information is invaluable for making informed decisions in a fast-paced real estate environment.

    2. Data Customization: APISCRAPY allows users to customize the data extraction process, tailoring it to their specific needs. This flexibility ensures that the extracted Zillow real estate data aligns precisely with the user's requirements.

    3. Precision and Accuracy: The advanced algorithms utilized by APISCRAPY enhance the precision and accuracy of the extracted Zillow real estate data. This reliability is crucial for making well-informed decisions related to property investments and market trends.

    4. Efficient Data Extraction: APISCRAPY's technology streamlines the data extraction process, saving users time and effort. The efficiency of the extraction workflow ensures that users can access the desired Zillow real estate data without unnecessary delays.

    5. User-friendly Interface: APISCRAPY provides a user-friendly interface, making it accessible for individuals and businesses to navigate and utilize the Zillow real estate data scraping service with ease.

    APISCRAPY provides real-time real estate market data drawn from Zillow, ensuring that consumers have access to the most up-to-date and comprehensive real estate insights available. Our real-time real estate market data services aren't simply a game changer in today's dynamic real estate landscape; they're an absolute requirement.

    Our dedication to offering high-quality real estate data extraction services is based on the utilization of Zillow Real Estate Data. APISCRAPY's integration of Zillow Real Estate Data sets it different from the competition, whether you're a seasoned real estate professional or a homeowner wanting to sell, buy, or invest.

    APISCRAPY's data extraction is a key element, and it is an automated and smooth procedure that is at the heart of the platform's operation. Our platform gathers Zillow real estate data quickly and offers it in an easily consumable format with the click of a button.

    [Tags;- Zillow real estate scraper, Zillow data, Zillow API, Zillow scraper, Zillow web scraping tool, Zillow data extraction, Zillow Real estate data, Zillow scraper, Zillow scraping API, Zillow real estate da extraction, Extract Real estate Data, Property Listing Data, Real estate Data, Real estate Data sets, Real estate market data, Real estate data extraction, real estate web scraping, real estate api, real estate data api, real estate web scraping, web scraping real estate data, scraping real estate data, real estate scraper, best real, estate api, web scraping real estate, api real estate, Zillow scraping software ]

  10. F

    Housing Inventory: Median Days on Market in the United States

    • fred.stlouisfed.org
    json
    Updated Jul 31, 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 31, 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 Jul 2025 about median and USA.

  11. US Real Estate

    • zenrows.com
    csv
    Updated Jun 27, 2021
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    ZenRows (2021). US Real Estate [Dataset]. https://www.zenrows.com/datasets/us-real-estate
    Explore at:
    csv(5,8MB)Available download formats
    Dataset updated
    Jun 27, 2021
    Dataset provided by
    ZenRows S.L.
    Authors
    ZenRows
    License

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

    Area covered
    United States
    Description

    High-quality, free real estate dataset from all around the United States, in CSV format. Over 10.000 records relevant to Real Estate investors, agents, and data scientists. We are working on complete datasets from a wide variety of countries. Don't hesitate to contact us for more information.

  12. d

    Property Owner Data | USA Coverage

    • datarade.ai
    .csv
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    BIGDBM, Property Owner Data | USA Coverage [Dataset]. https://datarade.ai/data-products/bigdbm-us-commercial-property-real-estate-data-bigdbm
    Explore at:
    .csvAvailable download formats
    Dataset authored and provided by
    BIGDBM
    Area covered
    United States
    Description

    The US Consumer Commercial Property/Real Estate file has 30 million+ non-residential properties which include property characteristics, site details, purchase details, tax details, and ownership information.

    We have developed this file to be tied to our Consumer and B2B Database so additional data fields can be applied to the owners. Each record is ranked by confidence and only the highest quality data is used.

    Note - all Consumer packages can include necessary PII (address, email, phone, DOB, etc.) for merging, linking, and activation of the data.

    BIGDBM Privacy Policy: https://bigdbm.com/privacy.html

  13. Number of existing homes sold in the U.S. 1995-2024, with a forecast until...

    • statista.com
    Updated Apr 28, 2025
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    Statista (2025). Number of existing homes sold in the U.S. 1995-2024, with a forecast until 2026 [Dataset]. https://www.statista.com/statistics/226144/us-existing-home-sales/
    Explore at:
    Dataset updated
    Apr 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The number of U.S. home sales in the United States declined in 2024, after soaring in 2021. A total of four million transactions of existing homes, including single-family, condo, and co-ops, were completed in 2024, down from 6.12 million in 2021. According to the forecast, the housing market is forecast to head for recovery in 2025, despite transaction volumes expected to remain below the long-term average. Why have home sales declined? The housing boom during the coronavirus pandemic has demonstrated that being a homeowner is still an integral part of the American dream. Nevertheless, sentiment declined in the second half of 2022 and Americans across all generations agreed that the time was not right to buy a home. A combination of factors has led to house prices rocketing and making homeownership unaffordable for the average buyer. A survey among owners and renters found that the high home prices and unfavorable economic conditions were the two main barriers to making a home purchase. People who would like to purchase their own home need to save up a deposit, have a good credit score, and a steady and sufficient income to be approved for a mortgage. In 2022, mortgage rates experienced the most aggressive increase in history, making the total cost of homeownership substantially higher. Are U.S. home prices expected to fall? The median sales price of existing homes stood at 413,000 U.S. dollars in 2024 and was forecast to increase slightly until 2026. The development of the S&P/Case Shiller U.S. National Home Price Index shows that home prices experienced seven consecutive months of decline between June 2022 and January 2023, but this trend reversed in the following months. Despite mild fluctuations throughout the year, home prices in many metros are forecast to continue to grow, albeit at a much slower rate.

  14. Commercial Real Estate Data | Global Real Estate Professionals | Work...

    • datarade.ai
    Updated Oct 27, 2021
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    Success.ai (2021). Commercial Real Estate Data | Global Real Estate Professionals | Work Emails, Phone Numbers & Verified Profiles | Best Price Guaranteed [Dataset]. https://datarade.ai/data-products/commercial-real-estate-data-global-real-estate-professional-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Oct 27, 2021
    Dataset provided by
    Area covered
    Comoros, Hong Kong, El Salvador, Bolivia (Plurinational State of), Burkina Faso, Guatemala, Netherlands, Marshall Islands, Sierra Leone, Korea (Republic of)
    Description

    Success.ai’s Commercial Real Estate Data and B2B Contact Data for Global Real Estate Professionals is a comprehensive dataset designed to connect businesses with industry leaders in real estate worldwide. With over 170M verified profiles, including work emails and direct phone numbers, this solution ensures precise outreach to agents, brokers, property developers, and key decision-makers in the real estate sector.

    Utilizing advanced AI-driven validation, our data is continuously updated to maintain 99% accuracy, offering actionable insights that empower targeted marketing, streamlined sales strategies, and efficient recruitment efforts. Whether you’re engaging with top real estate executives or sourcing local property experts, Success.ai provides reliable and compliant data tailored to your needs.

    Key Features of Success.ai’s Real Estate Professional Contact Data

    • Comprehensive Industry Coverage Gain direct access to verified profiles of real estate professionals across the globe, including:
    1. Real Estate Agents: Professionals facilitating property sales and purchases.
    2. Brokers: Key intermediaries managing transactions between buyers and sellers.
    3. Property Developers: Decision-makers shaping residential, commercial, and industrial projects.
    4. Real Estate Executives: Leaders overseeing multi-regional operations and business strategies.
    5. Architects & Consultants: Experts driving design and project feasibility.
    • Verified and Continuously Updated Data

    AI-Powered Validation: All profiles are verified using cutting-edge AI to ensure up-to-date accuracy. Real-Time Updates: Our database is refreshed continuously to reflect the most current information. Global Compliance: Fully aligned with GDPR, CCPA, and other regional regulations for ethical data use.

    • Customizable Data Delivery Tailor your data access to align with your operational goals:

    API Integration: Directly integrate data into your CRM or project management systems for seamless workflows. Custom Flat Files: Receive detailed datasets customized to your specifications, ready for immediate application.

    Why Choose Success.ai for Real Estate Contact Data?

    • Best Price Guarantee Enjoy competitive pricing that delivers exceptional value for verified, comprehensive contact data.

    • Precision Targeting for Real Estate Professionals Our dataset equips you to connect directly with real estate decision-makers, minimizing misdirected efforts and improving ROI.

    • Strategic Use Cases

      Lead Generation: Target qualified real estate agents and brokers to expand your network. Sales Outreach: Engage with property developers and executives to close high-value deals. Marketing Campaigns: Drive targeted campaigns tailored to real estate markets and demographics. Recruitment: Identify and attract top talent in real estate for your growing team. Market Research: Access firmographic and demographic data for in-depth industry analysis.

    • Data Highlights 170M+ Verified Professional Profiles 50M Work Emails 30M Company Profiles 700M Global Professional Profiles

    • Powerful APIs for Enhanced Functionality

      Enrichment API Ensure your contact database remains relevant and up-to-date with real-time enrichment. Ideal for businesses seeking to maintain competitive agility in dynamic markets.

    Lead Generation API Boost your lead generation with verified contact details for real estate professionals, supporting up to 860,000 API calls per day for robust scalability.

    • Use Cases for Real Estate Contact Data
    1. Targeted Outreach for New Projects Connect with property developers and brokers to pitch your services or collaborate on upcoming projects.

    2. Real Estate Marketing Campaigns Execute personalized marketing campaigns targeting agents and clients in residential, commercial, or industrial sectors.

    3. Enhanced Sales Strategies Shorten sales cycles by directly engaging with decision-makers and key stakeholders.

    4. Recruitment and Talent Acquisition Access profiles of highly skilled professionals to strengthen your real estate team.

    5. Market Analysis and Intelligence Leverage firmographic and demographic insights to identify trends and optimize business strategies.

    • What Makes Us Stand Out? >> Unmatched Data Accuracy: Our AI-driven validation ensures 99% accuracy for all contact details. >> Comprehensive Global Reach: Covering professionals across diverse real estate markets worldwide. >> Flexible Delivery Options: Access data in formats that seamlessly fit your existing systems. >> Ethical and Compliant Data Practices: Adherence to global standards for secure and responsible data use.

    Success.ai’s B2B Contact Data for Global Real Estate Professionals delivers the tools you need to connect with the right people at the right time, driving efficiency and success in your business operations. From agents and brokers to property developers and executiv...

  15. a

    Home Sales Trends in the United States

    • attomdata.com
    attom api +4
    Updated Oct 3, 2018
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    ATTOM Data Solutions (2018). Home Sales Trends in the United States [Dataset]. https://www.attomdata.com/data/real-estate-market-analytics/sales-trend/
    Explore at:
    attom api, neighborhood navigator, excel, attom cloud, csvAvailable download formats
    Dataset updated
    Oct 3, 2018
    Dataset authored and provided by
    ATTOM Data Solutions
    Description

    Home sales data aggregated by boundaries (neighborhood, zip code, city, etc) in increments of month, quarter, or year

  16. F

    Housing Inventory: Active Listing Count in the United States

    • fred.stlouisfed.org
    json
    Updated Jul 31, 2025
    + more versions
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    (2025). Housing Inventory: Active Listing Count in the United States [Dataset]. https://fred.stlouisfed.org/series/ACTLISCOUUS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 31, 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 Jul 2025 about active listing, listing, and USA.

  17. C

    Property Sales Data

    • data.milwaukee.gov
    csv
    Updated Apr 21, 2025
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    Assessor's Office (2025). Property Sales Data [Dataset]. https://data.milwaukee.gov/dataset/property-sales-data
    Explore at:
    csv(949709), csv(34325), csv(42822), csv(892761), csv(201294), csv(50434), csv(26978), csv(3975005), csv(340253), csv(315750), csv(507943), csv(635017), csv(19324), csv(425413), csv(20614), csv(338764), csv(34804), csv(816529), csv(868351), csv(557038), csv(219127), csv(229224), csv(730644), csv(775983)Available download formats
    Dataset updated
    Apr 21, 2025
    Dataset authored and provided by
    Assessor's Office
    License

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

    Description

    Update Frequency: Yearly

    Access to Residential, Condominium, Commercial, Apartment properties and vacant land sales history data.

    To download XML and JSON files, click the CSV option below and click the down arrow next to the Download button in the upper right on its page.

  18. c

    Real Estate (Sales)

    • opendata.charlottesville.org
    • data-charlottesville.opendata.arcgis.com
    • +2more
    Updated May 25, 2017
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    City of Charlottesville (2017). Real Estate (Sales) [Dataset]. https://opendata.charlottesville.org/datasets/real-estate-sales
    Explore at:
    Dataset updated
    May 25, 2017
    Dataset authored and provided by
    City of Charlottesville
    License

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

    Area covered
    Description

    This data set includes information pertaining to the transfer (sales) history for parcels. The "ParcelNumber" field can be joined to the "ParcelNumber" field in the "Parcel Area Details" data set for mapping purposes (current parcels only).This dataset is updated on a daily basis and reflects the Real Estate system as of the previous business day.

    The assessment values are done yearly and reassessment notices go out at the end of January.

    The new assessment values will be reflected on the GIS viewer after reassessment notices are mailed.

  19. Real Estate Data for Flat prices

    • kaggle.com
    zip
    Updated Sep 24, 2020
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    Poonam Vermaa (2020). Real Estate Data for Flat prices [Dataset]. https://www.kaggle.com/poonamvermaa/real-estate-data-for-flat-prices
    Explore at:
    zip(7567 bytes)Available download formats
    Dataset updated
    Sep 24, 2020
    Authors
    Poonam Vermaa
    Description

    Context This dataset is a record of every building or building unit (apartment, etc.) sold in the California property market along with the customer data.

    Content Real estate is property consisting of land and the buildings on it, along with its natural resources such as crops, minerals or water; immovable property of this nature; an interest vested in this (also) an item of real property, (more generally) buildings or housing in general.

    Inspiration

    What can you discover about California real estate by looking at a year's worth of raw transaction records? Can you spot trends in the market, or build a model that predicts sale value in the future?

  20. V

    Property Sales

    • data.virginia.gov
    • gis.data.vbgov.com
    • +1more
    Updated Sep 1, 2025
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    Virginia Beach (2025). Property Sales [Dataset]. https://data.virginia.gov/dataset/property-sales
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    html, gpkg, gdb, arcgis geoservices rest api, zip, geojson, kml, xlsx, csv, txtAvailable download formats
    Dataset updated
    Sep 1, 2025
    Dataset provided by
    VBCGIS_OrgAcct1
    Authors
    Virginia Beach
    Description

    This dataset has been published by the Office of the Real Estate Assessor of the City of Virginia Beach and data.virginiabeach.gov. The mission of data.virginiabeach.gov is to provide timely and accurate City information to increase government transparency and access to useful and well organized data by the general public, non-governmental organizations, and City of Virginia Beach employees.

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data.ct.gov (2025). Real Estate Sales 2001-2023 GL [Dataset]. https://catalog.data.gov/dataset/real-estate-sales-2001-2018

Real Estate Sales 2001-2023 GL

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3 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Aug 23, 2025
Dataset provided by
data.ct.gov
Description

The Office of Policy and Management maintains a listing of all real estate sales with a sales price of $2,000 or greater that occur between October 1 and September 30 of each year. For each sale record, the file includes: town, property address, date of sale, property type (residential, apartment, commercial, industrial or vacant land), sales price, and property assessment. Data are collected in accordance with Connecticut General Statutes, section 10-261a and 10-261b: https://www.cga.ct.gov/current/pub/chap_172.htm#sec_10-261a and https://www.cga.ct.gov/current/pub/chap_172.htm#sec_10-261b. Annual real estate sales are reported by grand list year (October 1 through September 30 each year). For instance, sales from 2018 GL are from 10/01/2018 through 9/30/2019. Some municipalities may not report data for certain years because when a municipality implements a revaluation, they are not required to submit sales data for the twelve months following implementation.

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