100+ datasets found
  1. Housing Price Data

    • kaggle.com
    zip
    Updated Mar 13, 2024
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    Saurabh Badole (2024). Housing Price Data [Dataset]. https://www.kaggle.com/datasets/saurabhbadole/housing-price-data
    Explore at:
    zip(4762 bytes)Available download formats
    Dataset updated
    Mar 13, 2024
    Authors
    Saurabh Badole
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Description

    Description:

    This dataset contains various features of residential properties along with their corresponding prices. It is suitable for exploring and analyzing factors influencing housing prices and for building predictive models to estimate the price of a property based on its attributes.

    FeatureDescription
    priceThe price of the property.
    areaThe total area of the property in square feet.
    bedroomsThe number of bedrooms in the property.
    bathroomsThe number of bathrooms in the property.
    storiesThe number of stories (floors) in the property.
    mainroadIndicates whether the property is located on a main road (binary: yes/no).
    guestroomIndicates whether the property has a guest room (binary: yes/no).
    basementIndicates whether the property has a basement (binary: yes/no).
    hotwaterheatingIndicates whether the property has hot water heating (binary: yes/no).
    airconditioningIndicates whether the property has air conditioning (binary: yes/no).
    parkingThe number of parking spaces available with the property.
    prefareaIndicates whether the property is in a preferred area (binary: yes/no).
    furnishingstatusThe furnishing status of the property (e.g., furnished, semi-furnished, unfurnished).

    Usage:

    • This dataset can be used for exploratory data analysis to understand the relationships between different housing features and prices.
    • It can also be used to build machine learning models for predicting housing prices based on the given features.

    License: This dataset is made available under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

  2. Fastest growing housing markets worldwide 2025

    • statista.com
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    Statista, Fastest growing housing markets worldwide 2025 [Dataset]. https://www.statista.com/statistics/1041586/price-growth-fastest-growing-home-markets-worldwide/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Turkey experienced the highest annual change in house prices in 2025, followed by North Macedonia and Portugal. In the second quarter of the year, the nominal house price in Turkey grew by **** percent, while in North Macedonia and Portugal, the increase was **** and **** percent, respectively. Meanwhile, some countries saw prices fall throughout the year. That has to do with an overall cooling of the global housing market that started in 2022. When accounting for inflation, house price growth was slower, and even more countries saw the market shrink.

  3. T

    United States Existing Home Sales Prices

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Oct 16, 2025
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    TRADING ECONOMICS (2025). United States Existing Home Sales Prices [Dataset]. https://tradingeconomics.com/united-states/single-family-home-prices
    Explore at:
    xml, excel, json, csvAvailable download formats
    Dataset updated
    Oct 16, 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 - Oct 31, 2025
    Area covered
    United States
    Description

    Single Family Home Prices in the United States increased to 415200 USD in October from 412300 USD in September of 2025. This dataset provides - United States Existing Single Family Home Prices- actual values, historical data, forecast, chart, statistics, economic calendar and news.

  4. T

    Hong Kong House Price Index

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Hong Kong House Price Index [Dataset]. https://tradingeconomics.com/hong-kong/housing-index
    Explore at:
    excel, xml, csv, jsonAvailable 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 2, 1994 - Nov 23, 2025
    Area covered
    Hong Kong
    Description

    Housing Index in Hong Kong increased to 143.46 points in November 23 from 142.49 points in the previous week. This dataset provides - Hong Kong House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  5. F

    All-Transactions House Price Index for Newport News city, VA

    • fred.stlouisfed.org
    json
    Updated Mar 25, 2025
    + more versions
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    (2025). All-Transactions House Price Index for Newport News city, VA [Dataset]. https://fred.stlouisfed.org/series/ATNHPIUS51700A
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Mar 25, 2025
    License

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

    Area covered
    Virginia, Newport News
    Description

    Graph and download economic data for All-Transactions House Price Index for Newport News city, VA (ATNHPIUS51700A) from 1975 to 2024 about Newport News City, VA; Virginia Beach; VA; HPI; housing; price index; indexes; price; and USA.

  6. House-price-to-income ratio in selected countries worldwide 2024

    • statista.com
    Updated Nov 29, 2025
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    Statista (2025). House-price-to-income ratio in selected countries worldwide 2024 [Dataset]. https://www.statista.com/statistics/237529/price-to-income-ratio-of-housing-worldwide/
    Explore at:
    Dataset updated
    Nov 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    Worldwide
    Description

    Portugal, Canada, and the United States were the countries with the highest house price to income ratio in 2024. In all three countries, the index exceeded 130 index points, while the average for all OECD countries stood at 116.2 index points. The index measures the development of housing affordability and is calculated by dividing nominal house price by nominal disposable income per head, with 2015 set as a base year when the index amounted to 100. An index value of 120, for example, would mean that house price growth has outpaced income growth by 20 percent since 2015. How have house prices worldwide changed since the COVID-19 pandemic? House prices started to rise gradually after the global financial crisis (2007–2008), but this trend accelerated with the pandemic. The countries with advanced economies, which usually have mature housing markets, experienced stronger growth than countries with emerging economies. Real house price growth (accounting for inflation) peaked in 2022 and has since lost some of the gain. Although, many countries experienced a decline in house prices, the global house price index shows that property prices in 2023 were still substantially higher than before COVID-19. Renting vs. buying In the past, house prices have grown faster than rents. However, the home affordability has been declining notably, with a direct impact on rental prices. As people struggle to buy a property of their own, they often turn to rental accommodation. This has resulted in a growing demand for rental apartments and soaring rental prices.

  7. F

    Real Residential Property Prices for Emerging Markets (aggregate)

    • fred.stlouisfed.org
    json
    Updated Nov 27, 2025
    + more versions
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    (2025). Real Residential Property Prices for Emerging Markets (aggregate) [Dataset]. https://fred.stlouisfed.org/series/Q4TR771BIS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Nov 27, 2025
    License

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

    Description

    Graph and download economic data for Real Residential Property Prices for Emerging Markets (aggregate) (Q4TR771BIS) from Q4 2008 to Q2 2025 about emerging markets, residential, HPI, housing, real, price index, indexes, and price.

  8. T

    China Newly Built House Prices YoY Change

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Nov 14, 2025
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    TRADING ECONOMICS (2025). China Newly Built House Prices YoY Change [Dataset]. https://tradingeconomics.com/china/housing-index
    Explore at:
    xml, excel, csv, jsonAvailable download formats
    Dataset updated
    Nov 14, 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, 2011 - Oct 31, 2025
    Area covered
    China
    Description

    Housing Index in China remained unchanged at -2.20 percent in October. This dataset provides the latest reported value for - China Newly Built House Prices YoY Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  9. Nominal house price index in select countries in APAC region 2010-2025, by...

    • statista.com
    Updated Feb 3, 2025
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    Statista Research Department (2025). Nominal house price index in select countries in APAC region 2010-2025, by quarter [Dataset]. https://www.statista.com/topics/5466/global-housing-market/
    Explore at:
    Dataset updated
    Feb 3, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    In 2025, India was the country with the highest increase in house prices since 2010 among the Asia-Pacific (APAC) countries under observation. In the second quarter of the year, the nominal house price index in India reached over 359 index points. This suggests an increase of 259 percent since 2010, the baseline year when the index value was set to 100. It is important to note that the nominal index does not account for the effects of inflation, meaning when adjusted for inflation, price growth in real terms was slower.

  10. d

    Housing Market Value Analysis 2021

    • catalog.data.gov
    • data.wprdc.org
    • +1more
    Updated Jan 24, 2023
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    Allegheny County (2023). Housing Market Value Analysis 2021 [Dataset]. https://catalog.data.gov/dataset/housing-market-value-analysis-2021
    Explore at:
    Dataset updated
    Jan 24, 2023
    Dataset provided by
    Allegheny County
    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.

  11. Annual home price appreciation in the U.S. 2025, by state

    • statista.com
    Updated Nov 29, 2025
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    Statista (2025). Annual home price appreciation in the U.S. 2025, by state [Dataset]. https://www.statista.com/statistics/1240802/annual-home-price-appreciation-by-state-usa/
    Explore at:
    Dataset updated
    Nov 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    House prices grew year-on-year in most states in the U.S. in the first quarter of 2025. Hawaii was the only exception, with a decline of **** percent. The annual appreciation for single-family housing in the U.S. was **** percent, while in Rhode Island—the state where homes appreciated the most—the increase was ******percent. How have home prices developed in recent years? House price growth in the U.S. has been going strong for years. In 2025, the median sales price of a single-family home exceeded ******* U.S. dollars, up from ******* U.S. dollars five years ago. One of the factors driving house prices was the cost of credit. The record-low federal funds effective rate allowed mortgage lenders to set mortgage interest rates as low as *** percent. With interest rates on the rise, home buying has also slowed, causing fluctuations in house prices. Why are house prices growing? Many markets in the U.S. are overheated because supply has not been able to keep up with demand. How many homes enter the housing market depends on the construction output, whereas the availability of existing homes for purchase depends on many other factors, such as the willingness of owners to sell. Furthermore, growing investor appetite in the housing sector means that prospective homebuyers have some extra competition to worry about. In certain metros, for example, the share of homes bought by investors exceeded ** percent in 2025.

  12. Most expensive housing markets worldwide 2020

    • statista.com
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    Statista, Most expensive housing markets worldwide 2020 [Dataset]. https://www.statista.com/statistics/1040698/most-expensive-property-markets-worldwide/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2020
    Area covered
    Worldwide
    Description

    In 2020, Hong Kong had the most expensive residential property market worldwide, with an average property price of 1.25 million U.S. dollars. The government of Hong Kong provide public housing for lower-income residents and almost 45 percent of the Hong Kong population lived in public permanent housing in 2018.

  13. w

    UK House Price Index: data downloads July 2023

    • gov.uk
    Updated Sep 20, 2023
    + more versions
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    HM Land Registry (2023). UK House Price Index: data downloads July 2023 [Dataset]. https://www.gov.uk/government/statistical-data-sets/uk-house-price-index-data-downloads-july-2023
    Explore at:
    Dataset updated
    Sep 20, 2023
    Dataset provided by
    GOV.UK
    Authors
    HM Land Registry
    Area covered
    United Kingdom
    Description

    The UK House Price Index is a National Statistic.

    Create your report

    Download the full UK House Price Index data below, or use our tool to https://landregistry.data.gov.uk/app/ukhpi?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=tool&utm_term=9.30_20_09_23" class="govuk-link">create your own bespoke reports.

    Download the data

    Datasets are available as CSV files. Find out about republishing and making use of the data.

    Google Chrome is blocking downloads of our UK HPI data files (Chrome 88 onwards). Please use another internet browser while we resolve this issue. We apologise for any inconvenience caused.

    Full file

    This file includes a derived back series for the new UK HPI. Under the UK HPI, data is available from 1995 for England and Wales, 2004 for Scotland and 2005 for Northern Ireland. A longer back series has been derived by using the historic path of the Office for National Statistics HPI to construct a series back to 1968.

    Download the full UK HPI background file:

    Individual attributes files

    If you are interested in a specific attribute, we have separated them into these CSV files:

  14. c

    Data from: What’s Really Happening in Housing Markets?

    • clevelandfed.org
    Updated Jul 1, 2007
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    Federal Reserve Bank of Cleveland (2007). What’s Really Happening in Housing Markets? [Dataset]. https://www.clevelandfed.org/publications/economic-commentary/2007/ec-20070701-whats-really-going-on-in-housing-markets
    Explore at:
    Dataset updated
    Jul 1, 2007
    Dataset authored and provided by
    Federal Reserve Bank of Cleveland
    Description

    Most of the public concern about housing markets is based on claims that house prices have increased at historically anomalous rates and that house prices have outpaced incomes. The first claim is based on inaccurate historical data. The second is linked to relaxed credit constraints. House prices are likely to fall further, but not for the reasons usually proposed.

  15. M

    HPI y/y - economic news from the United States

    • mql5.com
    csv
    Updated Nov 28, 2025
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    MQL5 Community (2025). HPI y/y - economic news from the United States [Dataset]. https://www.mql5.com/en/economic-calendar/united-states/house-price-index-yy
    Explore at:
    csvAvailable download formats
    Dataset updated
    Nov 28, 2025
    Dataset authored and provided by
    MQL5 Community
    Time period covered
    Dec 26, 2023 - Nov 25, 2025
    Area covered
    United States
    Description

    Overview with Chart & Report: House Price Index y/y measures average changes in the value of single-family homes in the US in the given month compared to the same period of the previous year. Higher housing prices can strengthen

  16. T

    United Kingdom House Price Index

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Oct 15, 2025
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    TRADING ECONOMICS (2025). United Kingdom House Price Index [Dataset]. https://tradingeconomics.com/united-kingdom/housing-index
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset updated
    Oct 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, 1983 - Oct 31, 2025
    Area covered
    United Kingdom
    Description

    Housing Index in the United Kingdom increased to 517.10 points in October from 514.20 points in September of 2025. This dataset provides - United Kingdom House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  17. F

    All-Transactions House Price Index for Virginia Beach-Norfolk-Newport News,...

    • fred.stlouisfed.org
    json
    Updated Nov 25, 2025
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    (2025). All-Transactions House Price Index for Virginia Beach-Norfolk-Newport News, VA-NC (MSA) [Dataset]. https://fred.stlouisfed.org/series/ATNHPIUS47260Q
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Nov 25, 2025
    License

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

    Area covered
    Hampton Roads, North Carolina, Virginia, Newport News
    Description

    Graph and download economic data for All-Transactions House Price Index for Virginia Beach-Norfolk-Newport News, VA-NC (MSA) (ATNHPIUS47260Q) from Q3 1976 to Q3 2025 about Virginia Beach, VA, NC, appraisers, HPI, housing, price index, indexes, price, and USA.

  18. USA House Prices

    • kaggle.com
    zip
    Updated Jul 21, 2024
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    Fırat Özcan (2024). USA House Prices [Dataset]. https://www.kaggle.com/datasets/fratzcan/usa-house-prices/code
    Explore at:
    zip(121422 bytes)Available download formats
    Dataset updated
    Jul 21, 2024
    Authors
    Fırat Özcan
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Area covered
    United States
    Description

    Real estate markets are of great importance for both local and international investors. Sydney and Melbourne are two dynamic markets where economic and social factors have significant impacts on property prices. Below is a detailed description of each feature:

    1. Date: The date when the property was sold. This feature helps in understanding the temporal trends in property prices.
    2. Price:The sale price of the property in USD. This is the target variable we aim to predict.
    3. Bedrooms:The number of bedrooms in the property. Generally, properties with more bedrooms tend to have higher prices.
    4. Bathrooms: The number of bathrooms in the property. Similar to bedrooms, more bathrooms can increase a property’s value.
    5. Sqft Living: The size of the living area in square feet. Larger living areas are typically associated with higher property values.
    6. Sqft Lot:The size of the lot in square feet. Larger lots may increase a property’s desirability and value.
    7. Floors: The number of floors in the property. Properties with multiple floors may offer more living space and appeal.
    8. Waterfront: A binary indicator (1 if the property has a waterfront view, 0 other- wise). Properties with waterfront views are often valued higher.
    9. View: An index from 0 to 4 indicating the quality of the property’s view. Better views are likely to enhance a property’s value.
    10. Condition: An index from 1 to 5 rating the condition of the property. Properties in better condition are typically worth more.
    11. Sqft Above: The square footage of the property above the basement. This can help isolate the value contribution of above-ground space.
    12. Sqft Basement: The square footage of the basement. Basements may add value depending on their usability.
    13. Yr Built: The year the property was built. Older properties may have historical value, while newer ones may offer modern amenities.
    14. Yr Renovated: The year the property was last renovated. Recent renovations can increase a property’s appeal and value.
    15. Street: The street address of the property. This feature can be used to analyze location-specific price trends.
    16. City: The city where the property is located. Different cities have distinct market dynamics.
    17. Statezip: The state and zip code of the property. This feature provides regional context for the property.
    18. Country: The country where the property is located. While this dataset focuses on properties in Australia, this feature is included for completeness.

    If you like this dataset, please contribute by upvoting

  19. T

    United States FHFA House Price Index

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Sep 15, 2025
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    TRADING ECONOMICS (2025). United States FHFA House Price Index [Dataset]. https://tradingeconomics.com/united-states/housing-index
    Explore at:
    xml, excel, json, csvAvailable download formats
    Dataset updated
    Sep 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, 1991 - Sep 30, 2025
    Area covered
    United States
    Description

    Housing Index in the United States decreased to 435.40 points in September from 435.60 points in August 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.

  20. T

    Slovakia House Price Index

    • tradingeconomics.com
    • es.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Slovakia House Price Index [Dataset]. https://tradingeconomics.com/slovakia/housing-index
    Explore at:
    excel, json, xml, 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
    Mar 31, 2006 - Jun 30, 2025
    Area covered
    Slovakia
    Description

    Housing Index in Slovakia increased to 198.85 points in the second quarter of 2025 from 194.60 points in the first quarter of 2025. This dataset provides - Slovakia House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Saurabh Badole (2024). Housing Price Data [Dataset]. https://www.kaggle.com/datasets/saurabhbadole/housing-price-data
Organization logo

Housing Price Data

Explore Real Estate Markets and Property Valuations

Explore at:
zip(4762 bytes)Available download formats
Dataset updated
Mar 13, 2024
Authors
Saurabh Badole
License

Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
License information was derived automatically

Description

Description:

This dataset contains various features of residential properties along with their corresponding prices. It is suitable for exploring and analyzing factors influencing housing prices and for building predictive models to estimate the price of a property based on its attributes.

FeatureDescription
priceThe price of the property.
areaThe total area of the property in square feet.
bedroomsThe number of bedrooms in the property.
bathroomsThe number of bathrooms in the property.
storiesThe number of stories (floors) in the property.
mainroadIndicates whether the property is located on a main road (binary: yes/no).
guestroomIndicates whether the property has a guest room (binary: yes/no).
basementIndicates whether the property has a basement (binary: yes/no).
hotwaterheatingIndicates whether the property has hot water heating (binary: yes/no).
airconditioningIndicates whether the property has air conditioning (binary: yes/no).
parkingThe number of parking spaces available with the property.
prefareaIndicates whether the property is in a preferred area (binary: yes/no).
furnishingstatusThe furnishing status of the property (e.g., furnished, semi-furnished, unfurnished).

Usage:

  • This dataset can be used for exploratory data analysis to understand the relationships between different housing features and prices.
  • It can also be used to build machine learning models for predicting housing prices based on the given features.

License: This dataset is made available under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

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