100+ datasets found
  1. Housing Prices Dataset

    • kaggle.com
    zip
    Updated Jan 12, 2022
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    M Yasser H (2022). Housing Prices Dataset [Dataset]. https://www.kaggle.com/datasets/yasserh/housing-prices-dataset
    Explore at:
    zip(4740 bytes)Available download formats
    Dataset updated
    Jan 12, 2022
    Authors
    M Yasser H
    License

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

    Description

    https://raw.githubusercontent.com/Masterx-AI/Project_Housing_Price_Prediction_/main/hs.jpg" alt="">

    Description:

    A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to mainroad, etc. The dataset is small yet, it's complexity arises due to the fact that it has strong multicollinearity. Can you overcome these obstacles & build a decent predictive model?

    Acknowledgement:

    Harrison, D. and Rubinfeld, D.L. (1978) Hedonic prices and the demand for clean air. J. Environ. Economics and Management 5, 81–102. Belsley D.A., Kuh, E. and Welsch, R.E. (1980) Regression Diagnostics. Identifying Influential Data and Sources of Collinearity. New York: Wiley.

    Objective:

    • Understand the Dataset & cleanup (if required).
    • Build Regression models to predict the sales w.r.t a single & multiple feature.
    • Also evaluate the models & compare thier respective scores like R2, RMSE, etc.
  2. 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
    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 Average Sales Price of Houses Sold for the United States (ASPUS) from Q1 1963 to Q2 2025 about sales, housing, and USA.

  3. Average sales price of new homes sold in the U.S. 1965-2024

    • statista.com
    Updated Nov 19, 2025
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    Statista (2025). Average sales price of new homes sold in the U.S. 1965-2024 [Dataset]. https://www.statista.com/statistics/240991/average-sales-prices-of-new-homes-sold-in-the-us/
    Explore at:
    Dataset updated
    Nov 19, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The average sales price of new homes in the United States experienced a slight decrease in 2024, dropping to 512,2000 U.S. dollars from the peak of 521,500 U.S. dollars in 2022. This decline came after years of substantial price increases, with the average price surpassing 400,000 U.S. dollars for the first time in 2021. The recent cooling in the housing market reflects broader economic trends and changing consumer sentiment towards homeownership. Factors influencing home prices and affordability The rapid rise in home prices over the past few years has been driven by several factors, including historically low mortgage rates and increased demand during the COVID-19 pandemic. However, the market has since slowed down, with the number of home sales declining by over two million between 2021 and 2023. This decline can be attributed to rising mortgage rates and decreased affordability. The Housing Affordability Index hit a record low of 98.1 in 2023, indicating that the median-income family could no longer afford a median-priced home. Future outlook for the housing market Despite the recent cooling, experts forecast a potential recovery in the coming years. The Freddie Mac House Price Index showed a growth of 6.5 percent in 2023, which is still above the long-term average of 4.4 percent since 1990. However, homebuyer sentiment remains low across all age groups, with people aged 45 to 64 expressing the most pessimistic outlook. The median sales price of existing homes is expected to increase slightly until 2025, suggesting that affordability challenges may persist in the near future.

  4. 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.

  5. US Cities Housing Market Data - Live Dataset

    • kaggle.com
    zip
    Updated Oct 12, 2025
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    Vincent Vaseghi (2025). US Cities Housing Market Data - Live Dataset [Dataset]. https://www.kaggle.com/datasets/vincentvaseghi/us-cities-housing-market-data
    Explore at:
    zip(984945960 bytes)Available download formats
    Dataset updated
    Oct 12, 2025
    Authors
    Vincent Vaseghi
    Area covered
    United States
    Description

    Redfin is a real estate brokerage and publishes the US housing market data on a regular basis. Using this dataset, you can analyze and visualize housing market data for US cities. Timeline: Starting from February 2012 until the present time (Data is refreshed and updated on a monthly basis)

    The dataset has the following columns: - period_begin - period_end - period_duration
    - region_type
    - region_type_id - table_id - is_seasonally_adjusted. (indicates if prices are seasonally adjusted; f represents False) - region - city - state - state_code - property_type - property_type_id - median_sale_price
    - median_sale_price_mom (median sale price changes month over month) - median_sale_price_yoy (median sale price changes year over year) - median_list_price
    - median_list_price_mom (median list price changes month over month) - median_list_price_yoy (median list price changes year over year) - median_ppsf (median sale price per square foot) - median_ppsf_mom (median sale price per square foot changes month over month) - median_ppsf_yoy (median sale price per square foot changes year over year) - median_list_ppsf (median list price per square foot) - median_list_ppsf_mom (median list price per square foot changes month over month) - median_list_ppsf_yoy. (median list price per square foot changes year over year) - homes_sold (number of homes sold) - homes_sold_mom (number of homes sold month over month) - homes_sold_yoy (number of homes sold year over year) - pending_sales
    - pending_sales_mom
    - pending_sales_yoy
    - new_listings - new_listings_mom
    - new_listings_yoy
    - inventory - inventory_mom
    - inventory_yoy
    - months_of_supply
    - months_of_supply_mom - months_of_supply_yoy
    - median_dom (median days on market until property is sold) - median_dom_mom (median days on market changes month over month) - median_dom_yoy (median days on market changes year over year) - avg_sale_to_list (average sale price to list price ratio) - avg_sale_to_list_mom (average sale price to list price ratio changes month over month) - avg_sale_to_list_yoy (average sale price to list price ratio changes year over year) - sold_above_list
    - sold_above_list_mom - sold_above_list_yoy - price_drops - price_drops_mom - price_drops_yoy - off_market_in_two_weeks (number of properties that will be taken off the market within 2 weeks) - off_market_in_two_weeks_mom (changes in number of properties that will be taken off the market within 2 weeks, month over month) - off_market_in_two_weeks_yoy (changes in number of properties that will be taken off the market within 2 weeks, year over year) - parent_metro_region - parent_metro_region_metro_code - last_updated

    Filetype: gzip (gz) Support for gzip files in Python: https://docs.python.org/3/library/gzip.html

    Data Source & Credit: Redfin.com

  6. T

    United States New Home Average Sales Price

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Oct 16, 2025
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    TRADING ECONOMICS (2025). United States New Home Average Sales Price [Dataset]. https://tradingeconomics.com/united-states/average-house-prices
    Explore at:
    excel, csv, xml, jsonAvailable 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, 1975 - Aug 31, 2025
    Area covered
    United States
    Description

    Average House Prices in the United States increased to 534100 USD in August from 478200 USD in July of 2025. This dataset includes a chart with historical data for the United States New Home Average Sales Price.

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

    • statista.com
    Updated Nov 19, 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
    Nov 19, 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.

  8. y

    US Existing Home Median Sales Price

    • ycharts.com
    html
    Updated Oct 23, 2025
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    National Association of Realtors (2025). US Existing Home Median Sales Price [Dataset]. https://ycharts.com/indicators/us_existing_home_median_sales_price
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Oct 23, 2025
    Dataset provided by
    YCharts
    Authors
    National Association of Realtors
    License

    https://www.ycharts.com/termshttps://www.ycharts.com/terms

    Time period covered
    Jan 31, 1999 - Sep 30, 2025
    Area covered
    United States
    Variables measured
    US Existing Home Median Sales Price
    Description

    View monthly updates and historical trends for US Existing Home Median Sales Price. from United States. Source: National Association of Realtors. Track ec…

  9. House Price Prediction Treated Dataset

    • kaggle.com
    zip
    Updated Oct 22, 2024
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    Vinicius Araujo (2024). House Price Prediction Treated Dataset [Dataset]. https://www.kaggle.com/datasets/aravinii/house-price-prediction-treated-dataset
    Explore at:
    zip(286105 bytes)Available download formats
    Dataset updated
    Oct 22, 2024
    Authors
    Vinicius Araujo
    License

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

    Description

    PLEASE UPVOTE IF YOU LIKE THIS CONTENT! 😍

    Same dataset as "House Sales in King County, USA", but with treated content and with a split version (train-test) allowing direct use in machine learning models.

    We have 14 columns in the dataset, as it follows:

    • date: Date of the home sale
    • price: Price of each home sold
    • bedrooms: Number of bedrooms
    • bathrooms: Number of bathrooms
    • living_in_m2: Square meters of the apartments interior living space
    • nice_view: A flag that indicates the view's quality of a property
    • perfect_condition: A flag that indicates the maximum index of the apartment condition
    • grade: An index from 1 to 5, where 1 falls short of quality level and 5 have a high quality level of construction and design
    • has_basement: A flag indicating whether or not a property has a basement
    • renovated: A flag if the property was renovated
    • has_lavatory: Check for the presence of these incomplete/secondary bathrooms (bathtub, sink, toilet)
    • single_floor: A flag indicating whether the property had only one floor
    • month: The month of the home sale
    • quartile_zone: A quartile distribution index of the most expensive zip codes, where 1 means less expansive and 4 most expansive.
  10. T

    Median Sales Price of Houses Sold for the United States

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 12, 2018
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    TRADING ECONOMICS (2018). Median Sales Price of Houses Sold for the United States [Dataset]. https://tradingeconomics.com/united-states/median-sales-price-of-houses-sold-for-the-united-states-fed-data.html
    Explore at:
    excel, csv, xml, jsonAvailable download formats
    Dataset updated
    Mar 12, 2018
    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 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    Median Sales Price of Houses Sold for the United States was 410800.00000 $ in April of 2025, according to the United States Federal Reserve. Historically, Median Sales Price of Houses Sold for the United States reached a record high of 442600.00000 in October of 2022 and a record low of 17800.00000 in January of 1963. Trading Economics provides the current actual value, an historical data chart and related indicators for Median Sales Price of Houses Sold for the United States - last updated from the United States Federal Reserve on December of 2025.

  11. Price Paid Data

    • gov.uk
    Updated Dec 1, 2025
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    HM Land Registry (2025). Price Paid Data [Dataset]. https://www.gov.uk/government/statistical-data-sets/price-paid-data-downloads
    Explore at:
    Dataset updated
    Dec 1, 2025
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    HM Land Registry
    Description

    Our Price Paid Data includes information on all property sales in England and Wales that are sold for value and are lodged with us for registration.

    Get up to date with the permitted use of our Price Paid Data:
    check what to consider when using or publishing our Price Paid Data

    Using or publishing our Price Paid Data

    If you use or publish our Price Paid Data, you must add the following attribution statement:

    Contains HM Land Registry data © Crown copyright and database right 2021. This data is licensed under the Open Government Licence v3.0.

    Price Paid Data is released under the http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/">Open Government Licence (OGL). You need to make sure you understand the terms of the OGL before using the data.

    Under the OGL, HM Land Registry permits you to use the Price Paid Data for commercial or non-commercial purposes. However, OGL does not cover the use of third party rights, which we are not authorised to license.

    Price Paid Data contains address data processed against Ordnance Survey’s AddressBase Premium product, which incorporates Royal Mail’s PAF® database (Address Data). Royal Mail and Ordnance Survey permit your use of Address Data in the Price Paid Data:

    • for personal and/or non-commercial use
    • to display for the purpose of providing residential property price information services

    If you want to use the Address Data in any other way, you must contact Royal Mail. Email address.management@royalmail.com.

    Address data

    The following fields comprise the address data included in Price Paid Data:

    • Postcode
    • PAON Primary Addressable Object Name (typically the house number or name)
    • SAON Secondary Addressable Object Name – if there is a sub-building, for example, the building is divided into flats, there will be a SAON
    • Street
    • Locality
    • Town/City
    • District
    • County

    October 2025 data (current month)

    The October 2025 release includes:

    • the first release of data for October 2025 (transactions received from the first to the last day of the month)
    • updates to earlier data releases
    • Standard Price Paid Data (SPPD) and Additional Price Paid Data (APPD) transactions

    As we will be adding to the October data in future releases, we would not recommend using it in isolation as an indication of market or HM Land Registry activity. When the full dataset is viewed alongside the data we’ve previously published, it adds to the overall picture of market activity.

    Your use of Price Paid Data is governed by conditions and by downloading the data you are agreeing to those conditions.

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

    We update the data on the 20th working day of each month. You can download the:

    Single file

    These include standard and additional price paid data transactions received at HM Land Registry from 1 January 1995 to the most current monthly data.

    Your use of Price Paid Data is governed by conditions and by downloading the data you are agreeing to those conditions.

    The data is updated monthly and the average size of this file is 3.7 GB, you can download:

  12. Existing own homes; average purchase prices, region

    • data.overheid.nl
    • cbs.nl
    • +1more
    atom, json
    Updated Feb 17, 2025
    + more versions
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    Centraal Bureau voor de Statistiek (Rijk) (2025). Existing own homes; average purchase prices, region [Dataset]. https://data.overheid.nl/dataset/4146-existing-own-homes--average-purchase-prices--region
    Explore at:
    json(KB), atom(KB)Available download formats
    Dataset updated
    Feb 17, 2025
    Dataset provided by
    Statistics Netherlands
    License

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

    Description

    This table shows the average purchase price that has been paid in the reporting period for existing own homes purchased by a private individual. The average purchase price of existing own homes may differ from the price index of existing own homes. The average purchase price is no indicator for price developments of owner-occupied residential property. The average purchase price reflects the average price of dwellings sold in a particular period. The fact that de dwellings sold differs from one period to another is not taken into account. The following instance explains which problems are entailed by the continually changing of the quality of the dwellings sold. Suppose in February of a particular year mainly big houses with extensive gardens beautifully situated alongside canals are sold, whereas in March many small terraced houses are sold. In that case the average purchase price in February will be higher than in March but this does not mean that house prices are increased. See note 3 for a link to the article 'Why the average purchase price is not an indicator'.

    Data available from: 1995

    Status of the figures: The figures in this table are immediately definitive. The calculation of these figures is based on the number of notary transactions that are registered every month by the Dutch Land Registry Office (Kadaster). A revision of the figures is exceptional and occurs specifically if an error significantly exceeds the acceptable statistical margins. The average purchasing prices of existing owner-occupied sold homes can be calculated by Kadaster at a later date. These figures are usually the same as the publication on Statline, but in some periods they differ. Kadaster calculates the average purchasing prices based on the most recent data. These may have changed since the first publication. Statistics Netherlands uses figures from the first publication in accordance with the revision policy described above.

    Changes as of 17 February 2025: Added average purchase prices of the municipalities for the year 2024.

    When will new figures be published? New figures are published approximately one to three months after the period under review.

  13. b

    Median house price (affordability ratios) - WMCA

    • cityobservatory.birmingham.gov.uk
    csv, excel, geojson +1
    Updated Dec 3, 2025
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    (2025). Median house price (affordability ratios) - WMCA [Dataset]. https://cityobservatory.birmingham.gov.uk/explore/dataset/median-house-price-affordability-ratios-wmca/
    Explore at:
    excel, geojson, json, csvAvailable download formats
    Dataset updated
    Dec 3, 2025
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    This is the unadjusted median house priced for residential property sales (transactions) in the area for a 12 month period with April in the middle (year-ending September). These figures have been produced by the ONS (Office for National Statistics) using the Land Registry (LR) Price Paid data on residential dwelling transactions.

    The LR Price Paid data are comprehensive in that they capture changes of ownership for individual residential properties which have sold for full market value and covers both cash sales and those involving a mortgage.

    The median is the value determined by putting all the house sales for a given year, area and type in order of price and then selecting the price of the house sale which falls in the middle. The median is less susceptible to distortion by the presence of extreme values than is the mean. It is the most appropriate average to use because it best takes account of the skewed distribution of house prices.

    Note that a transaction occurs when a change of freeholder or leaseholder takes place regardless of the amount of money involved and a property can transact more than once in the time period.

    The LR records the actual price for which the property changed hands. This will usually be an accurate reflection of the market value for the individual property, but it is not always the case. In order to generate statistics that more accurately reflect market values, the LR has excluded records of houses that were not sold at market value from the dataset. The remaining data are considered a good reflection of market values at the time of the transaction. For full details of exclusions and more information on the methodology used to produce these statistics please see http://www.ons.gov.uk/peoplepopulationandcommunity/housing/qmis/housepricestatisticsforsmallareasqmi

    The LR Price Paid data are not adjusted to reflect the mix of houses in a given area. Fluctuations in the types of house that are sold in that area can cause differences between the median transactional value of houses and the overall market value of houses. Therefore these statistics differ to the new UK House Price Index (HPI) which reports mix-adjusted average house prices and house price indices.

    If, for a given year, for house type and area there were fewer than 5 sales records in the LR Price Paid data, the house price statistics are not reported. Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

  14. T

    Canada Average House Prices

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +12more
    csv, excel, json, xml
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    TRADING ECONOMICS, Canada Average House Prices [Dataset]. https://tradingeconomics.com/canada/average-house-prices
    Explore at:
    json, csv, xml, excelAvailable 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, 2005 - Oct 31, 2025
    Area covered
    Canada
    Description

    Average House Prices in Canada increased to 688800 CAD in October from 687600 CAD in September of 2025. This dataset includes a chart with historical data for Canada Average House Prices.

  15. Median sales price of new homes sold in the U.S. 1965-2024

    • statista.com
    Updated Aug 11, 2025
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    Statista (2025). Median sales price of new homes sold in the U.S. 1965-2024 [Dataset]. https://www.statista.com/statistics/199895/median-sales-prices-of-new-homes-sold-in-the-us-since-1965/
    Explore at:
    Dataset updated
    Aug 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The median sales price of new homes sold in the United States increased steadily from 1965 to 2022, followed by two years of decline. In 2024, a newly built home cost approximately ******* U.S. dollars. That was a decline from the peak price of 434,500 U.S. dollars in 2022. Prices varied greatly across different regions in the country, with the most expensive housing found in the Northeast region.

  16. d

    NORA Sold Properties

    • catalog.data.gov
    • data.nola.gov
    • +1more
    Updated Nov 8, 2025
    + more versions
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    data.nola.gov (2025). NORA Sold Properties [Dataset]. https://catalog.data.gov/dataset/nora-sold-properties
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    Dataset updated
    Nov 8, 2025
    Dataset provided by
    data.nola.gov
    Description

    This data set is a listing of all property sales by NORA through the following disposition channels. - Auction: Properties put up for auction and sold to the highest bidder. - Development: Properties offered to development partners at a discounted rate to support the development of affordable housing. - Lot Next Door: Properties sold to adjacent parcel owners, with discount opportunities for eligible participants. - Alternative Land Use: Properties sold for development of green space and community gardens. Note: this dataset contains duplicate addresses, which likely represent reversions or quitclaims that NORA sold again.

  17. Egypt Housing Prices

    • kaggle.com
    zip
    Updated Nov 14, 2022
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    Abdelwahab Kamal (2022). Egypt Housing Prices [Dataset]. https://www.kaggle.com/datasets/abdelwahabkamal/egypt-housing-prices
    Explore at:
    zip(674289 bytes)Available download formats
    Dataset updated
    Nov 14, 2022
    Authors
    Abdelwahab Kamal
    License

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

    Area covered
    Egypt
    Description

    this dataset was scraped from OLX posted every week . I cleaned it Partially, and now it's up to you to make data analysis magic. The dataset includes region, Type of Real estate, Suburb, Method of Selling, Rooms, Price, City, Area ,Furnished or not and contain rent properties

  18. Existing own homes; purchase price indices by region 2015=100 1995-2023

    • cbs.nl
    • data.overheid.nl
    xml
    Updated Jun 6, 2024
    + more versions
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    Centraal Bureau voor de Statistiek (2024). Existing own homes; purchase price indices by region 2015=100 1995-2023 [Dataset]. https://www.cbs.nl/en-gb/figures/detail/83913ENG
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    xmlAvailable download formats
    Dataset updated
    Jun 6, 2024
    Dataset authored and provided by
    Centraal Bureau voor de Statistiek
    License

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

    Area covered
    Netherlands
    Description

    The figures of existing own homes are related to the stock of existing own homes. Besides the price indices, figures are also published about the numbers sold, the average purchase price, and the total sum of the purchase prices of the sold dwellings. The House Price Index of existing own homes is based on a complete registration of sales of dwellings by the Dutch Land Registry Office (Kadaster) and the (WOZ) value of all dwellings in the Netherlands. Indices may fluctuate, for example if a small number of dwellings are sold in a certain region. In such cases we recommended using the long-term figures. The average purchase price of existing own homes may differ from the price index of existing own homes. The change in the average purchase price, however, is not an indicator for price developments of existing own homes.

    Data available from: 1st quarter 1995 to 4th quarter 2023

    Status of the figures: The figures in this table are immediately definitive. The calculation of these figures is based on the number of notary transactions that are registered every month by the Dutch Land Registry Office (Kadaster). A revision of the figures is exceptional and occurs specifically if an error significantly exceeds the acceptable statistical margins. The numbers of existing owner-occupied sold homes can be recalculated by Kadaster at a later date. These figures are usually the same as the publication on Statline, but in some periods they differ. Kadaster calculates the average purchasing prices based on the most recent data. These may have changed since the first publication. Statistics Netherlands uses figures from the first publication in accordance with the revision policy described above.

    Changes as of 6 June 2024: This table has been discontinued. This table is followed by Existing own homes; purchase prices, price index 2020=100, region. See paragraph 3.

    From reporting period 2024 quarter 1, the base year of the House Price Index for Existing Dwellings (PBK) will be adjusted from 2015 to 2020. In April 2024, the first figures of this new series will be released. These figures will be available in a new StatLine table. The old series (base year = 2015) can still be consulted via StatLine, but will no longer be updated.

  19. Real Estate Sales 2001-2020

    • kaggle.com
    Updated Dec 7, 2023
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    Derrek Devon (2023). Real Estate Sales 2001-2020 [Dataset]. https://www.kaggle.com/datasets/derrekdevon/real-estate-sales-2001-2020
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 7, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Derrek Devon
    License

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

    Description

    Here's a short description of the dataset:

    Serial Number: Is just a unique set of digits to identify each transaction

    List year: This is the year that the particular property was put up for sale.

    Date Recorded: Is the date that the transaction was completed. That is, the year the property was bought.

    Town: The town where this property is located.

    Address: The property's address.

    Assessed Value: How much the property is generally considered to be worth.

    Sale Amount: How much the property was actually sold for.

    Sales Ratio: The ratio measures how close the selling price of the property is to it's assessed value.

    Property Type: What kind of property it is.

    Residential Type: If it is a residential property, what type is it.

    Years until sold: Number of years before the property was finally sold

    This dataset can be used for analysis and even machine learning projects. For those doing analysis, I invite you to try and answer these questions: * Average assessed value of properties from year to year? * Average sale amount of properties from year to year? * Average sales ratio of properties from year to year? * How long, on average, did it take for the different property types to get sold? * How long, on average, did it take for the different residential types to get sold? * Which towns saw the most property sales in 2021?

    For those more interested in using this dataset in machine learning projects to forecast future property prices, I invite you also. Let's learn from your work.

  20. Real Estate Price Insights

    • kaggle.com
    zip
    Updated Oct 14, 2025
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    Warda Bilal (2025). Real Estate Price Insights [Dataset]. https://www.kaggle.com/datasets/wardabilal/real-estate-price-insights
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    zip(4762 bytes)Available download formats
    Dataset updated
    Oct 14, 2025
    Authors
    Warda Bilal
    License

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

    Description

    Introduction

    This dataset provide information the property of different houses and their selling prices.Through this dataset, we can understand how factors like bedrooms, bathrooms, area, and furnishing affect the price of a house.This dataset is beneficial for those student who learn prediction of price through data analysis or machine learning.

    Context

    One of the most frequent problems in the real estate sector is figuring out what influences property values. This dataset is used to construct prediction models that forecast property prices based on particular qualities and provides important insights into the housing market.

    Content

    • price:Selling price of the house
    • area:Total area (in square feet)
    • bedrooms:Number of bedrooms
    • bathrooms:Number of bathrooms
    • stories:Total floors in the house
    • mainroad:Whether the house is connected to the main road (yes/no)
    • guestroom:Availability of a guest room
    • basement:Availability of a basement
    • hotwaterheating:Whether hot water heating is available
    • airconditioning:Whether air conditioning is available
    • parking:Number of parking spaces
    • prefarea:If the house is in a preferred area
    • furnishingstatus:Furnishing condition (furnished, semi-furnished, unfurnished)
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M Yasser H (2022). Housing Prices Dataset [Dataset]. https://www.kaggle.com/datasets/yasserh/housing-prices-dataset
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Housing Prices Dataset

Housing Prices Prediction - Regression Problem

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13 scholarly articles cite this dataset (View in Google Scholar)
zip(4740 bytes)Available download formats
Dataset updated
Jan 12, 2022
Authors
M Yasser H
License

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

Description

https://raw.githubusercontent.com/Masterx-AI/Project_Housing_Price_Prediction_/main/hs.jpg" alt="">

Description:

A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to mainroad, etc. The dataset is small yet, it's complexity arises due to the fact that it has strong multicollinearity. Can you overcome these obstacles & build a decent predictive model?

Acknowledgement:

Harrison, D. and Rubinfeld, D.L. (1978) Hedonic prices and the demand for clean air. J. Environ. Economics and Management 5, 81–102. Belsley D.A., Kuh, E. and Welsch, R.E. (1980) Regression Diagnostics. Identifying Influential Data and Sources of Collinearity. New York: Wiley.

Objective:

  • Understand the Dataset & cleanup (if required).
  • Build Regression models to predict the sales w.r.t a single & multiple feature.
  • Also evaluate the models & compare thier respective scores like R2, RMSE, etc.
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