A comprehensive UK building age dataset containing 32.8 million records across the UK, including age bands, full addresses, postcodes, and source methodology.

Most of England's housing stock is owner occupied and built before 1919. Among the homes built after 2002, about 2.1 million homes were owner occupied, about 654,000 were privately rented and approximately 459,000 were social housing. The largest share of social housing was found in buildings built between 1945 and 1980. In 2024, there were around 15.8 million owner occupied households in England.

This dataset provides detailed property-level information for over 3,800 UK households with corresponding Heat Transfer Coefficient (HTC) data, enabling in-depth analysis of how physical building characteristics influence energy efficiency and heat retention.

Each record includes the following attributes: 1. Postcode: Area-level geographic identifier for spatial and regional analysis. 2. Total Floor Area (m²): Size of the property, providing essential context for normalising heat performance and consumption. 3. Current Energy Rating: The property’s Energy Performance Certificate (EPC) band (A–G), indicating overall efficiency. 4. Construction Age Band: The building’s construction period (e.g., 1930–1949, 2007 onwards), offering insight into design standards and insulation quality.

By linking these characteristics with HTC values, this dataset enables powerful applications in: - Energy Efficiency Modelling: Correlate EPC ratings and HTC scores to assess how building design affects real-world performance. - Retrofit Planning & Policy Analysis: Identify and prioritise homes most in need of energy upgrades or thermal improvements. - Academic & Commercial Research: Support studies into the relationship between construction age, building size, and thermal performance. - Sustainability & Net-Zero Strategy: Provide evidence-based insights for government, energy agencies, and developers to reduce housing stock emissions.

The dataset is fully anonymised and GDPR-compliant, ensuring privacy while maintaining analytical value. It is part of Chameleon Technology’s broader energy data offering and complements the HTC dataset, allowing seamless cross-analysis between property traits and thermal efficiency.

The number of households included continues to grow, expanding coverage and analytical potential across diverse UK housing types.

The Building Class data provides detailed information about residential housing types including the house age and structural type. This information can be used for urban regeneration studies, crime monitoring, urban flooding and urban gardens. These data were collected by The GeoInformation Group (TGG), primarily through interpretation of high-resolution aerial photography, as part of the Cities Revealed project. The data were subsequently acquired by the Landmap project.

The Joint Information Systems Committee (JISC) funded Landmap service which ran from 2001 to July 2014 collected and hosted a large amount of earth observation data for the majority of the UK, part of which was buildings data. After removal of JISC funding in 2013, the Landmap service is no longer operational, with the data now held at the NEODC.

When using these data please also add the following copyright statement: Cities Revealed © The GeoInformation Group yyyy

Starts and completions of new build dwellings in the UK, on a quarterly and annual basis, time series data

The Lower Super Output Area (LSOA) boundaries have been generalised by 50 meters (point removed) for web display. This data has mainly been curated for education and teaching purposes. The data is generally rounded (at source) to the nearest 10. However, where there are more than 0 but less than 5 properties, then the value "1" is assigned. Because of the rounding, then the total population may not be equal to the sum of the constitent populations, for some areas.The "Mode 1" columns relate to the modal age grouping, i.e. the grouping with the most number of properties in it. "Mode 2" is the runner-up age grouping, i.e. the grouping with the second-most number of properties in it. It may be that there are two or more groupings with the same maximum population, in which case Mode 1 is assigned to the most recent one, Mode 2 to the second-most recent etc.Classifications are an average across the local area, rather than for individual houses, therefore the colour coding on a building is not necessarily indicative of that building. For more information about this data please visit: https://www.gov.uk/government/statistics/council-tax-stock-of-properties-2015

The Property Characteristics dataset provides detailed information on residential properties, enabling in-depth analysis of energy performance, building attributes, and their relationship with household energy use. Each record corresponds to a single household and includes a unique anonymised identifier (user_id), allowing seamless integration with half-hourly consumption dataset for comprehensive energy analysis.

Key attributes include:

1. Region: Geographical location of the property (e.g., London, Wales, North East).
2. Postcode: Area-level location for spatial analysis.
3. Total floor area: Floor area of the property in square metres, providing a measure of building size.
4. Current energy rating: Energy Performance Certificate (EPC) rating, ranging from A (most efficient) to G (least efficient).
5. Construction age band: Age band of the building (e.g., 1930–1949, 2007 onwards), reflecting building design standards and potential efficiency characteristics.

This dataset is ideal for: - Energy efficiency analysis: Understanding building performance and potential for energy savings. - Property research: Analysing correlations between building characteristics, size, and energy performance. - Demand modelling: Linking property attributes with household consumption data to improve energy demand forecasting. - Policy evaluation: Assessing the impact of building age and EPC rating on energy efficiency programs and retrofits.

With anonymised identifiers and rich property attributes, this dataset provides a robust foundation for both commercial and research applications. It supports longitudinal studies, energy modelling, and the creation of value-added products, while maintaining household privacy and confidentiality.

This statistic shows the distribution of buyers purchasing prime country houses in the United Kingdom (UK) in the first half of 2014 (between January and May). The prime country house market is made up of properties of value equal to or more than *** thousand British pounds. The most numerous group consisted of buyers in their forties, making up almost half of the whole sample.

FI-London contains a total of 131 high-resolution building facade images. These images contain individual building facades of varying building types such as residential apartment blocks, terraced houses, commercial properties, etc. FI-London covers 15 different architectural age epochs, derived from the Colourring Cities Research Programme. Due to the unbalanced sample distribution and small sample size, FI-London can currently only be used for testing.

The number of dwellings in the UK, and dwelling stock data by tenure for the UK’s constituent countries, where available.

The number of dwellings by dwelling occupancy, shared dwellings, accommodation type, tenure, central heating type and number of bedrooms. Data are available at country, region, local authority, Middle layer Super Output Area and Lower layer Super Output Area in England and Wales, where possible.

The "UK Real Estate" dataset, meticulously constructed with 5000 entries and 10 comprehensive columns, presents a synthesized representation of housing attributes across the United Kingdom. This dataset is a simulated model created for academic or analytical purposes and is not sourced from empirical real estate databases.

The "Price" column encapsulates property valuations, varying between £50,000 and £1,000,000, offering a spectrum of market values. Bedroom and bathroom counts, illustrated in the "Bedrooms" and "Bathrooms" columns respectively, range from 1 to 5 bedrooms and 1 to 3 bathrooms per property. The "SqFt" column denotes the square footage of each property, spanning 500 to 3000 square feet, reflecting a diverse range of property sizes.

Geographical diversity is represented through major UK cities such as London, Manchester, Birmingham, Glasgow, and Edinburgh, listed in the "City" column. Corresponding postcodes for these cities are outlined in the "Postcode" column, encompassing areas like SW, M, B, G, and EH, demonstrating varied regional distributions within the dataset.

The dataset includes the year of construction for each property in the "Year_Built" column, spanning from 1800 to 2022, providing insights into the historical context and age distribution of the properties. Diverse property types, including flats, houses, and bungalows, are outlined in the "Type" column, reflecting the diversity in housing styles within the UK.

The presence of a garage on the property is indicated by the binary "Garage" column, where 1 represents the presence of a garage and 0 indicates its absence. Additionally, the "Lot_Area" column signifies the land area of the property, ranging from 500 to 5000 square feet, showcasing variations in property sizes and space availability.

This dataset serves as a foundational resource for academic research, analytical endeavors, or predictive modeling within the domain of UK real estate. Analysts and researchers may leverage this dataset to explore trends in property valuation, regional housing preferences, the impact of historical construction periods on property values, or the prevalence of specific housing types across different cities and postal regions in the United Kingdom. Such analyses could contribute valuable insights into the dynamics of the UK housing market and inform strategic decision-making processes within the real estate sector.

This dataset contains detailed property information for more than 4,000 UK households, offering a specialised view of building characteristics and energy performance. Key fields include:

1. Total floor area - Property size in square metres
2. Current energy rating (EPC) - A-G efficiency rating
3. Construction age band - e.g., 1930–1949, 2007 onwards

It is a specialised subset of our household data, complementing electricity and gas consumption datasets, home profile attributes, and disaggregation data. This dataset is ideal for building energy modelling, efficiency analysis, and research into household energy behaviour.

This CSV table shows a breakdown of the dwelling stock down to a lower geographic level Lower layer Super Output Area or LSOA, categorised by the property build period and property type. Counts in the tables are rounded to the nearest 10 with those below 5 recorded as negligible and appearing as -. Data on build period, or age of property, has been used to create 12 property build period categories: Pre-1900, 1900-1918, 1919-1929, 1930-1939, 1945-1954, 1955-1964, 1965-1972, 1973-1982, 1983-1992, 1993-1999, 2000-2009, and 2010-2015. Data on property type includes breakdown by bungalow, terraced, flat/maisonette, semi-detached and detached, and by the number of bedrooms. The counts are calculated from domestic property data for England and Wales extracted from the Valuation Office Agencys administrative database on 31 March 2015, and on 1 August 2012 and 31 March 2014. The VOA have published data that shows homes by period built, or type, and council tax band down to MSOA and LSOA level. Rounding: Small differences between the rounding conventions are applied to the 2014 and 2015 statistics. For 2014 The rounding convention applied to the tables: Counts are rounded to the nearest 10 dwellings and counts less than 5 are reported as negligible (-). For 2015 The rounding convention applied to the tables: Counts are rounded to the nearest 10 with counts of zero being reported as "0" and counts fewer than 5 reported as negligible and denoted by "-". National Statistics Postcode Lookup file (NSPL): Different NSPL files have been used for 2014 and 2015 statistics (February 2014 NSLP used February 2015 NSLP used). As a results, postcodes can be moved in different OAs. Further information on NSPL can be found at ONS Property attributes: As part of the day to day VOA work, attributes information can be added (where no information is recorded) and/or changed (existing information is updated). This would result in counts in categories changing. New entries and deletions: New entries into the CT List together with deletions from the CT List will result in changes to counts. New entries could be as a result from splits, mergers, new build but also entries which were not previously in the CT List i.e. a shop is converted in a domestic property. Similarly, deletions could be as a result from splits, mergers, demolitions but also entries no longer domestic properties i.e. a house is converted into a shop (non-domestic property). The map below was created to show the average age of properties at MSOA level.

This statistic displays the share of adults in the United Kingdom (UK) that have home contents and building cover, broken down into age groups in 2017. It can be see that most adults in the United Kingdom (UK) that had home contents and building cover in 2017 were aged between 45 and 54 with ** percent. Only * percent of car insurance owners were aged between 18 and 24 years old in 2017.

Data on the energy efficiency of dwellings, environmental impact score and estimated CO2 emissions in England and Wales at the local authority district level. These are broken down by property type, tenure, age of property and whether a dwelling is new or existing.

These National Statistics provide monthly estimates of the number of residential and non-residential property transactions in the UK and its constituent countries. National Statistics are accredited official statistics.

England and Northern Ireland statistics are based on information submitted to the HM Revenue and Customs (HMRC) Stamp Duty Land Tax (SDLT) database by taxpayers on SDLT returns.

Land and Buildings Transaction Tax (LBTT) replaced SDLT in Scotland from 1 April 2015 and this data is provided to HMRC by https://www.revenue.scot/">Revenue Scotland to continue the time series.

Land Transaction Tax (LTT) replaced SDLT in Wales from 1 April 2018. To continue the time series, the https://gov.wales/welsh-revenue-authority">Welsh Revenue Authority (WRA) have provided HMRC with a monthly data feed of LTT transactions since July 2021.

LTT figures for the latest month are estimated using a grossing factor based on data for the most recent and complete financial year. Until June 2021, LTT transactions for the latest month were estimated by HMRC based upon year on year growth in line with other UK nations.

LTT transactions up to the penultimate month are aligned with LTT statistics.

Go to Stamp Duty Land Tax guidance for the latest rates and information.

Go to Stamp Duty Land Tax rates from 1 December 2003 to 22 September 2022 and Stamp Duty: rates on land transfers before December 2003 for historic rates.

The latest release was published 09:30 28 November 2025 and was updated with provisional data from completed transactions during October 2025.

The next release will be published 09:30 09 January 2026 and will be updated with provisional data from completed transactions during November 2025.

https://webarchive.nationalarchives.gov.uk/ukgwa/20240320184933/https://www.gov.uk/government/statistics/monthly-property-transactions-completed-in-the-uk-with-value-40000-or-above">Archive versions of the Monthly property transactions completed in the UK with value of £40,000 or above are available via the UK Government Web Archive, from the National Archives.