100+ datasets found
  1. New York Housing Market

    • kaggle.com
    Updated Jan 6, 2024
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    Nidula Elgiriyewithana ⚡ (2024). New York Housing Market [Dataset]. http://doi.org/10.34740/kaggle/dsv/7351086
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 6, 2024
    Dataset provided by
    Kaggle
    Authors
    Nidula Elgiriyewithana ⚡
    Area covered
    New York
    Description

    Description:

    This dataset contains prices of New York houses, providing valuable insights into the real estate market in the region. It includes information such as broker titles, house types, prices, number of bedrooms and bathrooms, property square footage, addresses, state, administrative and local areas, street names, and geographical coordinates.

    DOI

    Key Features:

    • BROKERTITLE: Title of the broker
    • TYPE: Type of the house
    • PRICE: Price of the house
    • BEDS: Number of bedrooms
    • BATH: Number of bathrooms
    • PROPERTYSQFT: Square footage of the property
    • ADDRESS: Full address of the house
    • STATE: State of the house
    • MAIN_ADDRESS: Main address information
    • ADMINISTRATIVE_AREA_LEVEL_2: Administrative area level 2 information
    • LOCALITY: Locality information
    • SUBLOCALITY: Sublocality information
    • STREET_NAME: Street name
    • LONG_NAME: Long name
    • FORMATTED_ADDRESS: Formatted address
    • LATITUDE: Latitude coordinate of the house
    • LONGITUDE: Longitude coordinate of the house

    Potential Use Cases:

    • Price analysis: Analyze the distribution of house prices to understand market trends and identify potential investment opportunities.
    • Property size analysis: Explore the relationship between property square footage and prices to assess the value of different-sized houses.
    • Location-based analysis: Investigate geographical patterns to identify areas with higher or lower property prices.
    • Bedroom and bathroom trends: Analyze the impact of the number of bedrooms and bathrooms on house prices.
    • Broker performance analysis: Evaluate the influence of different brokers on the pricing of houses.

    If you find this dataset useful, your support through an upvote would be greatly appreciated ❤️🙂 Thank you

  2. C

    Housing Market Value Analysis 2021

    • data.wprdc.org
    • gimi9.com
    • +1more
    geojson, html, pdf +2
    Updated Jul 8, 2025
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    Allegheny County (2025). Housing Market Value Analysis 2021 [Dataset]. https://data.wprdc.org/dataset/market-value-analysis-2021
    Explore at:
    html, geojson(10301172), zip(2039140), pdf(881980), xlsx(22669), pdf(28782887), zip(1996574)Available download formats
    Dataset updated
    Jul 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

    Description

    In 2021, Allegheny County Economic Development (ACED), in partnership with Urban Redevelopment Authority of Pittsburgh(URA), completed the a Market Value Analysis (MVA) for Allegheny County. This analysis services as both an update to previous MVA’s commissioned separately by ACED and the URA and combines the MVA for the whole of Allegheny County (inclusive of the City of Pittsburgh). The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional community boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies.

    This MVA utilized data that helps to define the local real estate market. The data used covers the 2017-2019 period, and data used in the analysis includes:

    • Residential Real Estate Sales
    • Mortgage Foreclosures
    • Residential Vacancy
    • Parcel Year Built
    • Parcel Condition
    • Building Violations
    • Owner Occupancy
    • Subsidized Housing Units

    The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources.

    Please refer to the presentation and executive summary for more information about the data, methodology, and findings.

  3. Residential Real Estate Market Analysis, Size, and Forecast 2025-2029: North...

    • technavio.com
    pdf
    Updated Jun 14, 2025
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    Technavio (2025). Residential Real Estate Market Analysis, Size, and Forecast 2025-2029: North America (US, Canada, and Mexico), Europe (France, Germany, and UK), APAC (Australia, Japan, and South Korea), South America (Brazil), and Rest of World (ROW) [Dataset]. https://www.technavio.com/report/residential-real-estate-market-analysis
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Jun 14, 2025
    Dataset provided by
    TechNavio
    Authors
    Technavio
    License

    https://www.technavio.com/content/privacy-noticehttps://www.technavio.com/content/privacy-notice

    Time period covered
    2025 - 2029
    Area covered
    Brazil, Japan, Mexico, Europe, Germany, Canada, United States, United Kingdom
    Description

    Snapshot img

    Residential Real Estate Market Size 2025-2029

    The residential real estate market size is valued to increase USD 485.2 billion, at a CAGR of 4.5% from 2024 to 2029. Growing residential sector globally will drive the residential real estate market.

    Major Market Trends & Insights

    APAC dominated the market and accounted for a 55% growth during the forecast period.
    By Mode Of Booking - Sales segment was valued at USD 926.50 billion in 2023
    By Type - Apartments and condominiums segment accounted for the largest market revenue share in 2023
    

    Market Size & Forecast

    Market Opportunities: USD 41.01 billion
    Market Future Opportunities: USD 485.20 billion
    CAGR : 4.5%
    APAC: Largest market in 2023
    

    Market Summary

    The market is a dynamic and ever-evolving sector that continues to shape the global economy. With increasing marketing initiatives and the growing residential sector globally, the market presents significant opportunities for growth. However, regulatory uncertainty looms large, posing challenges for stakeholders. According to recent reports, technology adoption in residential real estate has surged, with virtual tours and digital listings becoming increasingly popular. In fact, over 40% of homebuyers in the US prefer virtual property viewings. Core technologies such as artificial intelligence and blockchain are revolutionizing the industry, offering enhanced customer experiences and streamlined processes.
    Despite these advancements, regulatory compliance remains a major concern, with varying regulations across regions adding complexity to market operations. The market is a complex and intriguing space, with ongoing activities and evolving patterns shaping its future trajectory.
    

    What will be the Size of the Residential Real Estate Market during the forecast period?

    Get Key Insights on Market Forecast (PDF) Request Free Sample

    How is the Residential Real Estate Market Segmented and what are the key trends of market segmentation?

    The residential real estate industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

    Mode Of Booking
    
      Sales
      Rental or lease
    
    
    Type
    
      Apartments and condominiums
      Landed houses and villas
    
    
    Location
    
      Urban
      Suburban
      Rural
    
    
    End-user
    
      Mid-range housing
      Affordable housing
      Luxury housing
    
    
    Geography
    
      North America
    
        US
        Canada
        Mexico
    
    
      Europe
    
        France
        Germany
        UK
    
    
      APAC
    
        Australia
        Japan
        South Korea
    
    
      South America
    
        Brazil
    
    
      Rest of World (ROW)
    

    By Mode Of Booking Insights

    The sales segment is estimated to witness significant growth during the forecast period.

    Request Free Sample

    The Sales segment was valued at USD 926.50 billion in 2019 and showed a gradual increase during the forecast period.

    Request Free Sample

    Regional Analysis

    APAC is estimated to contribute 55% to the growth of the global market during the forecast period.Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

    See How Residential Real Estate Market Demand is Rising in APAC Request Free Sample

    The market in the Asia Pacific (APAC) region holds a significant share and is projected to lead the global market growth. Factors fueling this expansion include the region's rapid urbanization and increasing consumer spending power. Notably, residential and commercial projects in countries like India and China are experiencing robust development. The residential real estate sector in China plays a pivotal role in the economy and serves as a major growth driver for the market.

    With these trends continuing, the APAC the market is poised for continued expansion during the forecast period.

    Market Dynamics

    Our researchers analyzed the data with 2024 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.

    In the Residential Real Estate Market, understanding the impact property tax rates home values and effect interest rates mortgage affordability is essential for buyers and investors. Key factors affecting home price appreciation and factors influencing housing affordability shape market trends, while the importance property due diligence process and requirements environmental site assessment ensure informed decisions. Investors benefit from methods calculating rental property roi, process home equity loan application, and benefits real estate portfolio diversification. Tools like property management software efficiency and techniques effective property marketing help tackle challenges managing rental properties. Additionally, strategies successf

  4. Redfin usa properties dataset

    • crawlfeeds.com
    csv, zip
    Updated Jun 13, 2025
    + more versions
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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

    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.
    🔗 Request Redfin Real Estate Data

  5. C

    Housing Market Value Analysis - Allegheny County Economic Development

    • data.wprdc.org
    • catalog.data.gov
    csv, html, lyr, pdf +2
    Updated May 26, 2023
    + more versions
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    Allegheny County (2023). Housing Market Value Analysis - Allegheny County Economic Development [Dataset]. https://data.wprdc.org/dataset/market-value-analysis-allegheny-county-economic-development
    Explore at:
    pdf(11534), zip, png, html, pdf(9358422), lyr, csvAvailable download formats
    Dataset updated
    May 26, 2023
    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

    In 2017, the County Department of Economic Development, in conjunction with Reinvestment Fund, completed the 2016 Market Value Analysis (MVA) for Allegheny County. A similar MVA was completed with the Pittsburgh Urban Redevelopment Authority in 2016. The Market Value Analysis (MVA) offers an approach for community revitalization; it recommends applying interventions not only to where there is a need for development but also in places where public investment can stimulate private market activity and capitalize on larger public investment activities. The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional community boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies.

    The 2016 Allegheny County MVA does not include the City of Pittsburgh, which was characterized at the same time in the fourth update of the City of Pittsburgh’s MVA. All calculations herein therefore do not include the City of Pittsburgh. While the methodology between the City and County MVA's are very similar, the classification of communities will differ, and so the data between the two should not be used interchangeably.

    Allegheny County's MVA utilized data that helps to define the local real estate market. Most data used covers the 2013-2016 period, and data used in the analysis includes:

    •Residential Real Estate Sales; • Mortgage Foreclosures; • Residential Vacancy; • Parcel Year Built; • Parcel Condition; • Owner Occupancy; and • Subsidized Housing Units.

    The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources.

    During the research process, staff from the County and Reinvestment Fund spent an extensive amount of effort ensuring the data and analysis was accurate. In addition to testing the data, staff physically examined different areas to verify the data sets being used were appropriate indicators and the resulting MVA categories accurately reflect the market.

    Please refer to the report (included here as a pdf) for more information about the data, methodology, and findings.

  6. 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.

  7. US Residential Real Estate Market Analysis | Trends, Forecast, Size &...

    • mordorintelligence.com
    pdf,excel,csv,ppt
    Updated Jul 10, 2025
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    Mordor Intelligence (2025). US Residential Real Estate Market Analysis | Trends, Forecast, Size & Industry Growth Report 2030 [Dataset]. https://www.mordorintelligence.com/industry-reports/residential-real-estate-market-in-usa
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Jul 10, 2025
    Dataset provided by
    Authors
    Mordor Intelligence
    License

    https://www.mordorintelligence.com/privacy-policyhttps://www.mordorintelligence.com/privacy-policy

    Time period covered
    2019 - 2030
    Area covered
    United States
    Description

    The United States Residential Real Estate Market is Segmented by Property Type (Apartments and Condominiums, and Villas and Landed Houses), by Price Band (Affordable, Mid-Market and Luxury), by Business Model (Sales and Rental), by Mode of Sale (Primary and Secondary), and by Region (Northeast, Midwest, Southeast, West and Southwest). The Market Forecasts are Provided in Terms of Value (USD)

  8. Housing Market Value Analysis - Urban Redevelopment Authority

    • catalog.data.gov
    • data.wprdc.org
    • +2more
    Updated Jan 24, 2023
    + more versions
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    Urban Redevelopment Authority of Pittsburgh (2023). Housing Market Value Analysis - Urban Redevelopment Authority [Dataset]. https://catalog.data.gov/dataset/housing-market-value-analysis-urban-redevelopment-authority
    Explore at:
    Dataset updated
    Jan 24, 2023
    Dataset provided by
    Urban Redevelopment Authority of Pittsburghhttp://www.ura.org/
    Description

    In late 2016, the URA, in conjunction with Reinvestment Fund, completed the 2016 Market Value Analysis (MVA) for the City of Pittsburgh. The Market Value Analysis (MVA) offers an approach for community revitalization; it recommends applying interventions not only to where there is a need for development but also in places where public investment can stimulate private market activity and capitalize on larger public investment activities. The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional neighborhood boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies. Pittsburgh’s 2016 MVA utilized data that helps to define the local real estate market between July, 2013 and June, 2016: • Median Sales Price • Variance of Sales Price • Percent Households Owner Occupied • Density of Residential Housing Units • Percent Rental with Subsidy • Foreclosures as a Percent of Sales • Permits as a Percent of Housing Units • Percent of Housing Units Built Before 1940 • Percent of Properties with Assessed Condition “Poor” or worse • Vacant Housing Units as a Percentage of Habitable Units The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources. During the research process, staff from the URA and Reinvestment Fund spent an extensive amount of effort ensuring the data and analysis was accurate. In addition to testing the data, staff physically examined different areas to verify the data sets being used were appropriate indicators and the resulting MVA categories accurately reflect the market.

  9. T

    United States FHFA House Price Index

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States FHFA House Price Index [Dataset]. https://tradingeconomics.com/united-states/housing-index
    Explore at:
    xml, excel, json, csvAvailable download formats
    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, 1991 - Jul 31, 2025
    Area covered
    United States
    Description

    Housing Index in the United States decreased to 433.40 points in July from 433.90 points in June of 2025. This dataset provides the latest reported value for - United States House Price Index MoM Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  10. Housing Price Indexes

    • kaggle.com
    Updated Nov 29, 2024
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    Noey Ignacio (2024). Housing Price Indexes [Dataset]. https://www.kaggle.com/datasets/noeyislearning/housing-price-indexes
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 29, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Noey Ignacio
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    This dataset provides a comprehensive overview of new housing price indexes in Canada. The data is sourced from a reliable statistical survey, offering a detailed breakdown of housing prices across different components such as total house and land, house only, and land only. The dataset is structured to include key metrics such as geographical location, price index classification, and specific price values, providing a robust foundation for analyzing housing price dynamics within the country.

    Key Features

    • Price Index Metrics: The dataset includes price indexes for total house and land, house only, and land only, providing a complete picture of housing price dynamics across different components.
    • Geographical Focus: Data is specific to Canada, providing insights into national housing price trends and patterns.
    • Unit of Measurement: Information is presented in index units (201612=100), allowing for straightforward analysis and comparison.
    • Temporal Precision: The data is time-stamped for January 1981, ensuring relevance and accuracy for temporal analysis.

    Potential Uses

    • Real Estate Market Analysis: Assist in understanding the housing price dynamics in Canada, which is crucial for real estate market forecasting and planning.
    • Investment Decisions: Provide insights into optimal investment strategies for real estate in various regions.
    • Economic Policy: Support policymakers in monitoring and ensuring compliance with housing market trends and economic standards.
    • Market-Specific Insights: Evaluate the impact of housing price trends on specific regions and potential growth or decline areas.
    • Strategic Planning: Inform strategic planning for real estate developers and policymakers by providing a clear snapshot of current housing price levels and trends.
  11. Houston housing market 2024

    • kaggle.com
    Updated Jun 5, 2024
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    Natasha Lekh (2024). Houston housing market 2024 [Dataset]. https://www.kaggle.com/datasets/datadetective08/houston-housing-market-2024
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 5, 2024
    Dataset provided by
    Kaggle
    Authors
    Natasha Lekh
    License

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

    Area covered
    Houston
    Description

    This dataset contains detailed information on current real estate listings in Houston, Texas, sourced from Zillow, and provides a comprehensive snapshot of the Houston 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 data includes key 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 25,900 current listings, this dataset is ideal for in-depth analysis of the Houston housing market and the Houston real estate market. Potential use cases include:

    • Comparing listing prices, price per square foot across different neighborhoods, property types
    • Mapping listings to visualize the spatial distribution of for-sale inventory
    • Analyzing the age of for-sale housing stock from year-built data
    • Evaluating typical HOA fees, and property taxes for listings
    • Identifying listings with sought-after amenities
    • Assessing school quality near listings from GreatSchools ratings
    • Contacting listing agents programmatically using the included agent info

    Whether you're a real estate professional, market researcher, data scientist, or just curious about the Houston housing market, this dataset provides a wealth of information to explore. You can start investigating Houston real estate today.

  12. F

    All-Transactions House Price Index for Michigan

    • fred.stlouisfed.org
    json
    Updated Aug 26, 2025
    + more versions
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    (2025). All-Transactions House Price Index for Michigan [Dataset]. https://fred.stlouisfed.org/series/MISTHPI
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Aug 26, 2025
    License

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

    Area covered
    Michigan
    Description

    Graph and download economic data for All-Transactions House Price Index for Michigan (MISTHPI) from Q1 1975 to Q2 2025 about MI, appraisers, HPI, housing, price index, indexes, price, and USA.

  13. U

    United States House Prices Growth

    • ceicdata.com
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    CEICdata.com, United States House Prices Growth [Dataset]. https://www.ceicdata.com/en/indicator/united-states/house-prices-growth
    Explore at:
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Mar 1, 2022 - Dec 1, 2024
    Area covered
    United States
    Description

    Key information about House Prices Growth

    • US house prices grew 5.2% YoY in Dec 2024, following an increase of 5.4% YoY in the previous quarter.
    • YoY growth data is updated quarterly, available from Mar 1992 to Dec 2024, with an average growth rate of 5.4%.
    • House price data reached an all-time high of 17.7% in Sep 2021 and a record low of -12.4% in Dec 2008.

    CEIC calculates House Prices Growth from quarterly House Price Index. Federal Housing Finance Agency provides House Price Index with base January 1991=100.

  14. Residential Real Estate Market Size, Share, Growth & Industry Trends Report,...

    • mordorintelligence.com
    pdf,excel,csv,ppt
    Updated Jun 26, 2025
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    Mordor Intelligence (2025). Residential Real Estate Market Size, Share, Growth & Industry Trends Report, 2030 [Dataset]. https://www.mordorintelligence.com/industry-reports/residential-real-estate-market
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Jun 26, 2025
    Dataset provided by
    Authors
    Mordor Intelligence
    License

    https://www.mordorintelligence.com/privacy-policyhttps://www.mordorintelligence.com/privacy-policy

    Time period covered
    2019 - 2030
    Area covered
    Global
    Description

    Residential Real Estate Market is Segmented by Property Type (Apartments & Condominiums, and Landed Houses & Villas), by Price Band (Affordable, Mid-Market, and Luxury/Super-prime), by Business Model (Sales and Rental), by Mode of Sale (Primary and Secondary), and by Region (North America, South America, Europe, Asia-Pacific, and Middle East & Africa). The Market Forecasts are Provided in Terms of Value (USD).

  15. 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

  16. House price index in emerging and advanced economies worldwide 2008-2024, by...

    • statista.com
    Updated May 28, 2025
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    Statista (2025). House price index in emerging and advanced economies worldwide 2008-2024, by quarter [Dataset]. https://www.statista.com/statistics/1427342/house-price-index-emerging-and-advanced-economies-worldwide/
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    Dataset updated
    May 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Global house prices experienced a significant shift in 2022, with advanced economies seeing a notable decline after a prolonged period of growth. The real house price index (adjusted for inflation) for advanced economies peaked at nearly *** index points in early 2022 before falling to around ****** points by the fourth quarter of 2024. This represents a reversal of the upward trend that had characterized the housing market for roughly a decade. Conversely, real house prices in emerging economies resumed growing, after a brief correction in the second half of 2022. What is behind the slowdown? Inflation and slow economic growth have been the primary drivers for the cooling of the housing market. Secondly, the growing gap between incomes and house prices since 2012 has decreased the affordability of homeownership. Last but not least, homebuyers in 2024 faced dramatically higher mortgage interest rates, further contributing to worsening sentiment and declining transactions. Some markets continue to grow While many countries witnessed a deceleration in house price growth in 2022, some markets continued to see substantial increases. Turkey, in particular, stood out with a nominal increase in house prices of over ** percent in the first quarter of 2024. Other countries that recorded a two-digit growth include Russia and the United Arab Emirates. When accounting for inflation, the three countries with the fastest growing residential prices in early 2024 were the United Arab Emirates, Poland, and Bulgaria.

  17. US Real Estate Market Report and Forecast 2026-2032

    • thereportcubes.com
    pdf
    Updated Apr 22, 2025
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    The Report Cube (2025). US Real Estate Market Report and Forecast 2026-2032 [Dataset]. https://www.thereportcubes.com/report-store/us-real-estate-market
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Apr 22, 2025
    Dataset provided by
    Authors
    The Report Cube
    License

    https://www.thereportcubes.com/privacy-policyhttps://www.thereportcubes.com/privacy-policy

    Area covered
    Country Level
    Description

    US Real Estate Market Size & Growth 2025-2032: Valued at USD 3T in 2025, the market is projected to reach nearly USD 3.9T by 2032, growing at a CAGR of 4.12%. Get the latest industry forecast and analysis.

  18. North America Prefabricated Housing Market Size & Share Analysis - Industry...

    • mordorintelligence.com
    pdf,excel,csv,ppt
    Updated Aug 22, 2025
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    Mordor Intelligence (2025). North America Prefabricated Housing Market Size & Share Analysis - Industry Research Report - Growth Trends [Dataset]. https://www.mordorintelligence.com/industry-reports/north-america-prefabricated-housing-market
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Aug 22, 2025
    Dataset provided by
    Authors
    Mordor Intelligence
    License

    https://www.mordorintelligence.com/privacy-policyhttps://www.mordorintelligence.com/privacy-policy

    Time period covered
    2019 - 2030
    Area covered
    North America
    Description

    The North America Prefabricated Housing Market Report is Segmented by Material Type (Concrete, Glass, Metal, Timber, Other Materials), by Type (Single Family, Multi Family), by Product Type (Modular Homes, Panelized & Componentized Systems, Manufactured Homes, Other Prefab Types), and by Country (United States, Canada, Mexico). The Market Forecasts are Provided in Terms of Value (USD).

  19. House price index in the UK 2015-2025, by month

    • statista.com
    Updated Jul 16, 2025
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    Statista (2025). House price index in the UK 2015-2025, by month [Dataset]. https://www.statista.com/statistics/285705/monthly-house-price-index-in-the-united-kingdom-uk/
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    Dataset updated
    Jul 16, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2015 - Apr 2025
    Area covered
    United Kingdom
    Description

    The house price index (HPI) shows changes in the value of residential properties in England, Scotland, Wales, and Northern Ireland. With the HPI set at a base of 100 in January 2023, a value of over 100 would mark an increase in the average dwelling price. A value of under 100 points, on the other hand, would indicate that the average price has dropped. In April 2025, the index measured 101.7 index points, showing an increase of 1.7 percent since January 2023. UK house prices grew rapidly during the COVID-19 pandemic House prices in the UK grew steadily between 2015 and 2020, fueled by stable economic growth and low borrowing costs. In the following two years, a combination of factors exacerbated this trend. These factors included a stamp duty holiday, low interest rates, a shortage of new homes supplied, and a high housing demand. As a result, house price growth soared, hitting a record 13.6 percent in July 2022. This trend in the index, and therefore the value of UK residential properties, has also been observed by the Halifax house price index. What is the average house price in the UK? Average house prices are affected by several factors. Economic growth, unemployment, interest rates and mortgage availability can all drive them up or down. A shortage of supply means that the need for housing and the competitive market created will push house prices up. An excess of housing, on the other hand, means prices fall to stimulate buyers.

  20. T

    United States House Price Index YoY

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Mar 15, 2025
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    TRADING ECONOMICS (2025). United States House Price Index YoY [Dataset]. https://tradingeconomics.com/united-states/house-price-index-yoy
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset updated
    Mar 15, 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, 1992 - Jul 31, 2025
    Area covered
    United States
    Description

    House Price Index YoY in the United States decreased to 2.30 percent in July from 2.70 percent in June of 2025. This dataset includes a chart with historical data for the United States FHFA House Price Index YoY.

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Nidula Elgiriyewithana ⚡ (2024). New York Housing Market [Dataset]. http://doi.org/10.34740/kaggle/dsv/7351086
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New York Housing Market

Unlock the Door to New York Real Estate Excellence

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Jan 6, 2024
Dataset provided by
Kaggle
Authors
Nidula Elgiriyewithana ⚡
Area covered
New York
Description

Description:

This dataset contains prices of New York houses, providing valuable insights into the real estate market in the region. It includes information such as broker titles, house types, prices, number of bedrooms and bathrooms, property square footage, addresses, state, administrative and local areas, street names, and geographical coordinates.

DOI

Key Features:

  • BROKERTITLE: Title of the broker
  • TYPE: Type of the house
  • PRICE: Price of the house
  • BEDS: Number of bedrooms
  • BATH: Number of bathrooms
  • PROPERTYSQFT: Square footage of the property
  • ADDRESS: Full address of the house
  • STATE: State of the house
  • MAIN_ADDRESS: Main address information
  • ADMINISTRATIVE_AREA_LEVEL_2: Administrative area level 2 information
  • LOCALITY: Locality information
  • SUBLOCALITY: Sublocality information
  • STREET_NAME: Street name
  • LONG_NAME: Long name
  • FORMATTED_ADDRESS: Formatted address
  • LATITUDE: Latitude coordinate of the house
  • LONGITUDE: Longitude coordinate of the house

Potential Use Cases:

  • Price analysis: Analyze the distribution of house prices to understand market trends and identify potential investment opportunities.
  • Property size analysis: Explore the relationship between property square footage and prices to assess the value of different-sized houses.
  • Location-based analysis: Investigate geographical patterns to identify areas with higher or lower property prices.
  • Bedroom and bathroom trends: Analyze the impact of the number of bedrooms and bathrooms on house prices.
  • Broker performance analysis: Evaluate the influence of different brokers on the pricing of houses.

If you find this dataset useful, your support through an upvote would be greatly appreciated ❤️🙂 Thank you

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