Last updated on 22 Feb 2025

Introduction

This dataset provides comprehensive information on property sales in England and Wales, sourced from the UK government's HM Land Registry. Although the government site claims to update on the same day each month, actual updates can vary. To bridge this update variation gap, our fully automated ETL pipeline retrieves the official government data on a daily basis. This ensures that the dataset always reflects the most current transaction data available.

ETL Process

Our ETL (Extract, Transform, Load) process is designed to automate the data update and publishing workflow: 1. Extract:
The pipeline uses web scraping to retrieve the latest data from the official government website. This step is necessary as the site does not offer an API. 2. Transform:
Before loading the data, the ETL pipeline processes the dataset to ensure consistency and usability. As part of the transformation stage, the first column (Transaction_unique_identifier) is removed. This column is dropped during staging to focus on the most relevant transactional information. The column removal successfully reduces the data file size from almost 6GB to 3.1GB, and therefore will greatly increase the data analysis efficiency, and reduces the chance of kernal error/restart. 3. Load:
Finally, the transformed data is loaded into the dataset.

The transformed data is loaded into the dataset in two parts: - Complete Data (pp-complete.csv): This file encompasses all records from January 1995 to the present. The complete data file is replaced during each update to reflect any corrections or additional historical data. The first column is price. - Monthly Data: A separate monthly file is amended each month. This monthly archive ensures a complete record of updates over time, allowing users to track changes and trends more granularly.

Summary of Results

The dataset (pp-complete.csv) contains records of property sales dating back to January 1995, up to the most recent monthly data. It covers various types of transactions—from residential to commercial properties—providing a holistic view of the real estate market in England and Wales.

Column Descriptions

The original data includes the following columns: - Transaction_unique_identifier
- price
- Date_of_Transfer
- postcode
- Property_Type
- Old/New
- Duration
- PAON
- SAON
- Street
- Locality
- Town/City
- District
- County
- PPDCategory_Type
- Record_Status - monthly_file_only

Note: As part of the transformation process, the Transaction_unique_identifier column is removed from the final published pp-complete.csv data file. Therefore the first column of the pp-complete.csv file is price.

Address data Explanation - Postcode: The postal code where the property is located. - PAON (Primary Addressable Object Name): Typically the house number or name. - SAON (Secondary Addressable Object Name): Additional information if the building is divided into flats or sub-buildings. - Street: The street name where the property is located. - Locality: Additional locality information. - Town/City: The town or city where the property is located. - District: The district in which the property resides. - County: The county where the property is located. - Price Paid: The price for which the property was sold.

Legal and Ethical Considerations

Ownership and Attribution This dataset is the property of HM Land Registry and is released under the Open Government Licence (OGL). If you use or publish this dataset, you are required to include 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."

Usage Guidelines

The data can be used for both commercial and non-commercial purposes.

The OGL does not cover third-party rights, which HM Land Registry is not authorized to license. For any other use of the Address Data, you must contact Royal Mail.

Suggested Usages

Market Trend Analysis: Understand the ups and downs of the property market over time. Investment Research: Identify potential areas for property investment. Academic Studies: Use the data for economic research and studies related to the housing market. Policy Making: Assist government agencies in making informed decisions regarding housing policies. Real Estate Apps: Integrate the data into apps that provide property price information services.

By using this dataset, you agree to abide by the terms and conditions as specified by HM Land Registry. Failure to do so may result in legal consequences.

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.

Affordability ratios calculated by dividing house prices for existing dwellings, by gross annual residence-based earnings. Based on the median and lower quartiles of both house prices and earnings in England and Wales.

Table 3 - Exploring the association between health, local area characteristics and climate action plans in the UK: Cross-sectional analysis using administrative data from 2018 and a citizen science ranking of climate action plans from 2021

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.

Open source modeling code, with which all data were generated: https://github.com/kuangdai/AxiSEM-3D This code was primarily developed within the NERC-funded project, and used for a at least 10 publications over the past two years: [1] Wolf, Long, Leng, Nissen-Meyer. Sensitivity of SK(K)S and ScS phases to heterogeneous anisotropy in the lowermost mantle from global wavefield simulations, 2021. GJI, 228, 366–386, https://doi.org/10.1093/gji/ggab347 [2] Krier, Thorne, Leng, Nissen-Meyer: A compositional component to the Samoa ultralow-velocity zone revealed through 2- and 3-D waveform modeling of SKS and SKKS differential travel-times and amplitudes, Journal of Geophysical Research. doi:10.1029/2021JB021897 [3] Thorne, M. S., Leng, K., Pachhai, S., Rost, S., Wicks, J., & Nissen-Meyer, T. (2021). The most parsimonious ultralow-velocity zone distribution from highly anomalous SPdKS waveforms. Geochemistry, Geophysics, Geosystems, 22, e2020GC009467. https://doi.org/10.1029/2020GC009467 [4] Haindl, Leng, Nissen-Meyer, 2021. A 3D Complexity-Adaptive Approach to Explore Sparsity in Visco-Elastic Wave Propagation, Geophysics, doi.org/10.1190/geo2020-0490.1 [5] Tesoniero, Leng, Long, Nissen-Meyer. Full wave sensitivity of SK(K)S phases to arbitrary anisotropy in the upper and lower mantle, Geophysical Journal International, 222, 412–435, https://doi.org/10.1093/gji/ggaa171 [6] Thorne, M.S.; Pachhai, S.; Leng, K.; Wicks, J.K.; Nissen-Meyer, T, 2020. New Candidate Ultralow-Velocity Zone Locations from Highly Anomalous SPdKS Waveforms. Minerals 2020, 10, 211. [7] Fernando, Leng, Nissen-Meyer, 2020. Oceanic high-frequency global seismic wave propagation with realistic bathymetry, Geophysical Journal International, 222, 1178–1194, https://doi.org/10.1093/gji/ggaa248 [8] Leng, Korenaga, Nissen-Meyer, 2020. Three-dimensional scattering of elastic waves by small-scale heterogeneities in the Earth’s mantle, Geophysical Journal International, 223, 1, 502–525, https://doi.org/10.1093/gji/ggaa331 [9] Szenicer, Leng, Nissen-Meyer, 2020. A complexity-driven framework for waveform tomography with discrete adjoints, Geophysical Journal International, https://doi.org/10.1093/gji/ggaa349 [10] Leng, Nissen-Meyer, van Driel, Hosseini, Al-Attar, 2019. AxiSEM3D: broad-band seismic wavefields in 3-D global earth models with undulating discontinuities, Geophysical J Int., 217, 2125–2146 Each of publications is based on the code mentioned above, and metadata for running the simulations of the papers are given therein, in a reproducible manner.