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Annual house price data based on a sub-sample of the Regulated Mortgage Survey.
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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?
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.
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Summary of UK House Price Index (HPI) price statistics covering England, Scotland, Wales and Northern Ireland. Full UK HPI data are available on GOV.UK.
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TwitterOur 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.
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check what to consider when 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:
If you want to use the Address Data in any other way, you must contact Royal Mail. Email address.management@royalmail.com.
The following fields comprise the address data included in Price Paid Data:
The October 2025 release includes:
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:
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:
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Median price paid for residential property in England and Wales, by property type and administrative geographies. Annual data.
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The dataset contains 2000 rows of house-related data, representing various features that could influence house prices. Below, we discuss key aspects of the dataset, which include its structure, the choice of features, and potential use cases for analysis.
The dataset is designed to capture essential attributes for predicting house prices, including:
Area: Square footage of the house, which is generally one of the most important predictors of price. Bedrooms & Bathrooms: The number of rooms in a house significantly affects its value. Homes with more rooms tend to be priced higher. Floors: The number of floors in a house could indicate a larger, more luxurious home, potentially raising its price. Year Built: The age of the house can affect its condition and value. Newly built houses are generally more expensive than older ones. Location: Houses in desirable locations such as downtown or urban areas tend to be priced higher than those in suburban or rural areas. Condition: The current condition of the house is critical, as well-maintained houses (in 'Excellent' or 'Good' condition) will attract higher prices compared to houses in 'Fair' or 'Poor' condition. Garage: Availability of a garage can increase the price due to added convenience and space. Price: The target variable, representing the sale price of the house, used to train machine learning models to predict house prices based on the other features.
Area Distribution: The area of the houses in the dataset ranges from 500 to 5000 square feet, which allows analysis across different types of homes, from smaller apartments to larger luxury houses. Bedrooms and Bathrooms: The number of bedrooms varies from 1 to 5, and bathrooms from 1 to 4. This variance enables analysis of homes with different sizes and layouts. Floors: Houses in the dataset have between 1 and 3 floors. This feature could be useful for identifying the influence of multi-level homes on house prices. Year Built: The dataset contains houses built from 1900 to 2023, giving a wide range of house ages to analyze the effects of new vs. older construction. Location: There is a mix of urban, suburban, downtown, and rural locations. Urban and downtown homes may command higher prices due to proximity to amenities. Condition: Houses are labeled as 'Excellent', 'Good', 'Fair', or 'Poor'. This feature helps model the price differences based on the current state of the house. Price Distribution: Prices range between $50,000 and $1,000,000, offering a broad spectrum of property values. This range makes the dataset appropriate for predicting a wide variety of housing prices, from affordable homes to luxury properties.
3. Correlation Between Features
A key area of interest is the relationship between various features and house price: Area and Price: Typically, a strong positive correlation is expected between the size of the house (Area) and its price. Larger homes are likely to be more expensive. Location and Price: Location is another major factor. Houses in urban or downtown areas may show a higher price on average compared to suburban and rural locations. Condition and Price: The condition of the house should show a positive correlation with price. Houses in better condition should be priced higher, as they require less maintenance and repair. Year Built and Price: Newer houses might command a higher price due to better construction standards, modern amenities, and less wear-and-tear, but some older homes in good condition may retain historical value. Garage and Price: A house with a garage may be more expensive than one without, as it provides extra storage or parking space.
The dataset is well-suited for various machine learning and data analysis applications, including:
House Price Prediction: Using regression techniques, this dataset can be used to build a model to predict house prices based on the available features. Feature Importance Analysis: By using techniques such as feature importance ranking, data scientists can determine which features (e.g., location, area, or condition) have the greatest impact on house prices. Clustering: Clustering techniques like k-means could help identify patterns in the data, such as grouping houses into segments based on their characteristics (e.g., luxury homes, affordable homes). Market Segmentation: The dataset can be used to perform segmentation by location, price range, or house type to analyze trends in specific sub-markets, like luxury vs. affordable housing. Time-Based Analysis: By studying how house prices vary with the year built or the age of the house, analysts can derive insights into the trends of older vs. newer homes.
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TwitterHouse prices in the UK rose dramatically during the coronavirus pandemic, with growth slowing down in 2022 and turning negative in 2023. The year-on-year annual house price change peaked at 14 percent in July 2022. In April 2025, house prices increased by 3.5 percent. As of late 2024, the average house price was close to 290,000 British pounds. Correction in housing prices: a European phenomenon The trend of a growing residential real estate market was not exclusive to the UK during the pandemic. Likewise, many European countries experienced falling prices in 2023. When comparing residential property RHPI (price index in real terms, e.g. corrected for inflation), countries such as Germany, France, Italy, and Spain also saw prices decline. Sweden, one of the countries with the fastest growing residential markets, saw one of the largest declines in prices. How has demand for UK housing changed since the outbreak of the coronavirus? The easing of the lockdown was followed by a dramatic increase in home sales. In November 2020, the number of mortgage approvals reached an all-time high of over 107,000. One of the reasons for the housing boom were the low mortgage rates, allowing home buyers to take out a loan with an interest rate as low as 2.5 percent. That changed as the Bank of England started to raise the base lending rate, resulting in higher borrowing costs and a decline in homebuyer sentiment.
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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_16_07_25" class="govuk-link">create your own bespoke reports.
Datasets are available as CSV files. Find out about republishing and making use of the data.
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:
If you are interested in a specific attribute, we have separated them into these CSV files:
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Average-prices-2025-05.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=average_price&utm_term=9.30_16_07_25" class="govuk-link">Average price (CSV, 7.1MB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Average-prices-Property-Type-2025-05.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=average_price_property_price&utm_term=9.30_16_07_25" class="govuk-link">Average price by property type (CSV, 15.4KB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Sales-2025-05.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=sales&utm_term=9.30_16_07_25" class="govuk-link">Sales (CSV, 5.2KB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Cash-mortgage-sales-2025-05.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=cash_mortgage-sales&utm_term=9.30_16_07_25" class="govuk-link">Cash mortgage sales (CSV, 4.9KB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/First-Time-Buyer-Former-Owner-Occupied-2025-05.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=FTNFOO&utm_term=9.30_16_07_25" class="govuk-link">First time buyer and former owner occupier (CSV, 4.5KB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/New-and-Old-2025-05.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=new_build&utm_term=9.30_16_07_25" class="govuk-link">New build and existing resold property (CSV, 11KB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Indices-2025-05.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=index&utm_term=9.30_16_07_25" class="govuk-link">Index (CSV, 5.5KB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Indices-seasonally-adjusted-2025-05.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=index_season_adjusted&utm_term=9.30_16_07_25" class="govuk-link">Index seasonally adjusted (CSV, 196KB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Average-price-seasonally-adjusted-2025-05.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=average-price_season_adjusted&utm_term=9.30_16_07_25" class="govuk-link">Average price seasonally adjusted (CSV, 206KB)
<a rel="external" href="https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Repossession-2025-05.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=repossession&utm_term=9.30_16_07
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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.
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Median price paid for residential property in England and Wales, for all property types by lower layer super output area. Annual data..
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TwitterIn 2022, house price growth in the UK slowed, after a period of decade-long increase. Nevertheless, in June 2025, prices reached a new peak, with the average home costing ******* British pounds. This figure refers to all property types, including detached, semi-detached, terraced houses, and flats and maisonettes. Compared to other European countries, the UK had some of the highest house prices. How have UK house prices increased over the last 10 years? Property prices have risen dramatically over the past decade. According to the UK house price index, the average house price has grown by over ** percent since 2015. This price development has led to the gap between the cost of buying and renting a property to close. In 2023, buying a three-bedroom house in the UK was no longer more affordable than renting one. Consequently, Brits have become more likely to rent longer and push off making a house purchase until they have saved up enough for a down payment and achieved the financial stability required to make the step. What caused the recent fluctuations in house prices? House prices are affected by multiple factors, such as mortgage rates, supply, and demand on the market. For nearly a decade, the UK experienced uninterrupted house price growth as a result of strong demand and a chronic undersupply. Homebuyers who purchased a property at the peak of the housing boom in July 2022 paid ** percent more compared to what they would have paid a year before. Additionally, 2022 saw the most dramatic increase in mortgage rates in recent history. Between December 2021 and December 2022, the **-year fixed mortgage rate doubled, adding further strain to prospective homebuyers. As a result, the market cooled, leading to a correction in pricing.
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TwitterThe 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.
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TwitterIn December 2024, the average house price in England was pricier than in any other country. This considerable disparity in average house prices is in no small part down to the country's capital city, where the average asking price was more than double that of the UK’s average. Even in London, for those who can afford a mortgage, the savings made through buying over renting can be beneficial. What drives house prices? Average house prices are affected by several factors, including economic growth, unemployment, and interest rates. Housing supply also plays a considerable role, with a shortage of supply leading to increased competition and an upward push in prices. Conversely, an excess of housing means prices fall to stimulate buyers. House prices still set to grow The housing market in the UK is expected to continue to grow in the next years. By 2029,.the annual number of housing transactions is set to reach *** million. With transactions on the rise, the average house price is also set to rise.
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TwitterAfter a period of rapid increase, house price growth in the UK has moderated. In 2025, house prices are forecast to increase by ****percent. Between 2025 and 2029, the average house price growth is projected at *** percent. According to the source, home building is expected to increase slightly in this period, fueling home buying. On the other hand, higher borrowing costs despite recent easing of mortgage rates and affordability challenges may continue to suppress transaction activity. Historical house price growth in the UK House prices rose steadily between 2015 and 2020, despite minor fluctuations. In the following two years, prices soared, leading to the house price index jumping by about 20 percent. As the market stood in April 2025, the average price for a home stood at approximately ******* British pounds. Rents are expected to continue to grow According to another forecast, the prime residential market is also expected to see rental prices grow in the next five years. Growth is forecast to be stronger in 2025 and slow slightly until 2029. The rental market in London is expected to follow a similar trend, with Outer London slightly outperforming Central London.
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This is the unadjusted lower quartile 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 lower quartile 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 three quarters of the way down the list, such that 75Percentage of transactions lie above and 25Percentage lie below that value. These are particularly useful for assessing housing affordability when viewed alongside average and lower quartile income for given areas.
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 lower quartile transactional value of houses and the overall market value of houses.
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.
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Key information about House Prices Growth
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TwitterThe year-end value of the S&P Case Shiller National Home Price Index amounted to 321.45 in 2024. The index value was equal to 100 as of January 2000, so if the index value is equal to 130 in a given year, for example, it means that the house prices increased by 30 percent since 2000. S&P/Case Shiller U.S. home indices – additional informationThe S&P Case Shiller National Home Price Index is calculated on a monthly basis and is based on the prices of single-family homes in nine U.S. Census divisions: New England, Middle Atlantic, East North Central, West North Central, South Atlantic, East South Central, West South Central, Mountain and Pacific. The index is the leading indicator of the American housing market and one of the indicators of the state of the broader economy. The index illustrates the trend of home prices and can be helpful during house purchase decisions. When house prices are rising, a house buyer might want to speed up the house purchase decision as the transaction costs can be much higher in the future. The S&P Case Shiller National Home Price Index has been on the rise since 2011.The S&P Case Shiller National Home Price Index is one of the indices included in the S&P/Case-Shiller Home Price Index Series. Other indices are the S&P/Case Shiller 20-City Composite Home Price Index, the S&P/Case Shiller 10-City Composite Home Price Index and twenty city composite indices.
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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.
| Feature | Description |
|---|---|
| price | The price of the property. |
| area | The total area of the property in square feet. |
| bedrooms | The number of bedrooms in the property. |
| bathrooms | The number of bathrooms in the property. |
| stories | The number of stories (floors) in the property. |
| mainroad | Indicates whether the property is located on a main road (binary: yes/no). |
| guestroom | Indicates whether the property has a guest room (binary: yes/no). |
| basement | Indicates whether the property has a basement (binary: yes/no). |
| hotwaterheating | Indicates whether the property has hot water heating (binary: yes/no). |
| airconditioning | Indicates whether the property has air conditioning (binary: yes/no). |
| parking | The number of parking spaces available with the property. |
| prefarea | Indicates whether the property is in a preferred area (binary: yes/no). |
| furnishingstatus | The furnishing status of the property (e.g., furnished, semi-furnished, unfurnished). |
License: This dataset is made available under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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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.
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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.
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Annual house price data based on a sub-sample of the Regulated Mortgage Survey.