This dataset contains detailed information about rental properties across various locations in the UK. The data was collected by scraping Rightmove, a popular real estate platform. Each entry in the dataset includes the property's address, subdistrict code, rental price, deposit amount, letting type, furnish type, council tax details, property type, number of bedrooms and bathrooms, size in square feet, average distance to the nearest train station, and the count of nearest stations.

Researchers and analysts interested in the UK rental market can utilize this dataset to explore rental trends, pricing variations based on location and property type, amenities preferences, and more. The dataset provides a valuable resource for machine learning models, statistical analysis, and market research in the real estate sector.

Metadata: Source: The data was collected by scraping the Rightmove real estate platform, a leading source for property listings in the UK. Date Range: The dataset covers rental property listings available during the scraping period. Geographical Coverage: Primarily focused on various locations across the UK, providing insights into regional rental markets. Data Fields: Address: The location of the rental property. Subdistrict Code: A code representing the subdistrict or area of the property. Rent: The monthly rental price in GBP (£) for the property. Deposit: The deposit amount required for renting the property. Let Type: Indicates whether the property is available for short-term or long-term rental. Furnish Type: Describes the furnishing status of the property (e.g., furnished, unfurnished, or flexible options). Council Tax: Information about the council tax associated with the property. Property Type: Specifies the type of property, such as apartment, flat, maisonette, etc. Bedrooms: The number of bedrooms in the property. Bathrooms: The number of bathrooms in the property. Size: The size of the property in square feet (sq ft). Average Distance to Nearest Station: The average distance (in miles) to the nearest train station from the property. Nearest Station Count: The count of nearest train stations within a certain distance from the property. Data Quality: The data may contain missing values or "Ask agent" placeholders, which require direct inquiry with agents or landlords for specific information. Potential Uses: The dataset can be used for market analysis, rental price prediction models, understanding property preferences, and exploring the impact of location and amenities on rental properties in the UK.

In the five-year period between 2025 and 2029, the prime residential rent for existing properties in Greater London is expected to increase by 17.1 percent. The highest percentage change is expected to occur in 2025 and 2029, when rents are to rise by 3.5 percent. In the UK, rental growth has accelerated notably since 2021, with March 2024 experiencing a decade-high annual percentage growth. The trend reflects the complex interplay between housing affordability, mortgage rates, and supply of rental homes as the UK housing market navigates a period of transition.

London Property Listings Dataset

Description

This dataset expands upon the original London Property Listings by including additional attributes to facilitate deeper analysis of rental properties in London. It is ideal for research and projects related to real estate trends, price categorization, and area-wise analysis in one of the world's busiest markets.

Dataset Features

• Price: Monthly rental price in GBP.
• Property Type: Classification of the property (e.g., Apartment, Flat).
• Bedrooms: Number of bedrooms in the property.
• Bathrooms: Number of bathrooms.
• Size: Property size in square feet (where available).
• Postcode: Postal code of the property location.
• Area: General area or neighborhood information.
• Price_Category: Categorization of prices into predefined ranges (e.g., Low, Medium, High).
• Area_Avg_Price: Average price of properties within the same area.

Potential Use Cases

• Price Analysis: Study how property attributes impact rental prices.
• Price Prediction Models: Utilize the dataset for machine learning tasks like regression and classification.
• Regional Insights: Compare rental trends across different neighborhoods.
• Categorical Analysis: Investigate trends within predefined price categories.

Data Summary

• Total Records: 29,537
• Total Attributes: 9
• Data Completeness: No missing values. All columns are fully populated.

Attribution

This dataset was prepared and uploaded by Mehmet Emre Sezer. It is intended for educational and non-commercial use.

Median monthly rental prices for the private rental market in England by bedroom category, region and administrative area, calculated using data from the Valuation Office Agency and Office for National Statistics.

The prime property rental real estate market in Outer London is expected to see an overall increase in rental rates during the ********* period between 2025 and 2029. Over the ********* period, the cumulative prime rental growth is forecast at **** percent. Nationwide, residential rents have soared since 2021, with the annual rental growth peaking at over **** percent in **********.

The prime property rental real estate market in Central London is expected to see an overall increase in rental rates during the five-year period between 2025 and 2029, according to the latest forecast. Over the five-year period, the cumulative prime rental growth is forecast at **** percent. Rent increase in Outer London is expected to follow the same trend.

Historical market performance data including occupancy rates, average daily rates, and revenue trends

London is the most expensive city for office real estate in Europe. In 2023, the per square foot cost of office space in London was higher than in any other European city. In West End, a Grade A office cost about 90 British pounds per square foot in 2023. Prime offices were even more expensive, at 135 British pounds per square meter. Office yields Prime yields in Central London fluctuate depending on the district, but West End areas tend to have lower yields compared to other areas, such as Stratford or Canary Wharf. The prime office yield in Mayfair/St. James' in 2023 was the lowest among the major London office submarkets. In real estate, yields measure the potential return of a rental property and are calculated as the ratio of the property's rental income to the investment cost. Typically, prime office yields in London are lower than the rest of the UK, which is mostly due to the highly competitive market and high investment costs. Vacancy rates Despite the high office rental costs in England’s capital city, vacancy rates in many of London's main office markets were below seven percent in 2023. This is good news for the office sector, as during the coronavirus (COVID-19) pandemic, the share of vacant office space across all Central London districts spiked dramatically. Compared to other European cities, London was in the middle of the ranking, alongside Frankfurt and Lisbon.

Comprehensive Airbnb dataset for Greater London, United Kingdom providing detailed vacation rental analytics including property listings, pricing trends, host information, review sentiment analysis, and occupancy rates for short-term rental market intelligence and investment research.

Discover the latest insights on the booming UK real estate services market. This comprehensive analysis reveals a £32.45 billion industry projected to grow at a CAGR of 3% until 2033, driven by urbanization, proptech, and strong demand. Explore market segments, key players, and regional trends impacting property management, valuation, and more. Recent developments include: January 2023: United Kingdom Sotheby's Property Business Acquired by the Dubai Branch of Sotheby's. UK Sotheby International Realty was previously owned by Robin Paterson, who sold the business to his business partner and affiliate, George Azar. George Azar currently holds and operates Sotheby's Dubai and the MENA region., November 2022: JLL identified a shortage of quality rental homes as a long-term problem for the UK, which the recent boom in rentals has accentuated. This unmet need for quality rental homes has led to continued investor interest in purpose-built rental properties in UK city centers. JLL reported that annual investment in UK living real estate reached £10bn (USD 12.73 bn) in Q3 2022, setting living on track for another record year.. Key drivers for this market are: Improvements in Infrastructure and New Development, Population Growth and Demographic Changes. Potential restraints include: Housing Shortages, Increasing Awareness towards Environmental Issues. Notable trends are: Increasing in the United Kingdom House Prices.

Through reading this publication you will: • gain an understanding of how house prices are set in economics terms, how they are measured, and why the cost of housing matters for London’s economy and its residents • see whether incomes and earnings in London have kept pace with the costs of home ownership in London, and see how affordability may be affected by future changes in interest rates • find out about the drivers of demand for residential property in London, and how the supply of homes has responded to changing conditions

London Property Prices Dataset 200k+ records Overview This dataset offers a comprehensive snapshot of residential properties in London, capturing both historical and current market data. It includes property-specific information such as address, geographic coordinates, and various price estimates. Data spans from past transaction prices to present estimates for sale and rental values, making it ideal for real estate analysis, investment modeling, and trend forecasting.

Key Columns fullAddress: Complete address of the property. postcode: Postal code identifying specific areas in London. outcode: First part of the postcode, grouping properties into broader geographic zones. latitude & longitude: Geographic coordinates for mapping or location-based analysis. property details: Includes bathrooms, bedrooms, floorAreaSqM, livingRooms, tenure (e.g., leasehold or freehold), and propertyType (e.g., flat, maisonette). energy rating: Current energy rating, indicating the property’s energy efficiency. Pricing Information Rental Estimates: Ranges for estimated rental values (rentEstimate_lowerPrice, rentEstimate_currentPrice, rentEstimate_upperPrice). Sale Estimates: Current sale price estimates with confidence levels and historical changes. saleEstimate_currentPrice: Current estimated sale price. saleEstimate_confidenceLevel: Confidence in the sale price estimate (LOW, MEDIUM, HIGH). saleEstimate_valueChange: Numeric and percentage change in sale value over time. Transaction History: Date-stamped sale prices with historic price changes, providing insight into property appreciation or depreciation. Potential Applications This dataset enables a variety of analyses:

Market Trend Analysis: Track how property values and rents have evolved over time. Investment Insights: Identify high-growth areas and property types based on historical and estimated price changes. Geospatial Analysis: Use location data to visualize price distributions and trends across London. Usage Recommendations This dataset is well-suited for machine learning projects predicting property values, rent estimations, or analyzing urban property trends. With rich details spanning multiple facets of the real estate market, it’s an essential resource for data scientists, analysts, and investors exploring the London property market.

The number of completed build-to-rent home starts in London declined in 2023, while the rest of the UK observed the opposite trend. In London, there were ** starts in the third quarter of the year compared to ***** in the rest of the country. Build-to-rent refers to homes that are built specifically for renting rather than for sale. They differentiate from traditional rent homes with their focus on the provision of as services, i.e. professional on-site management, shared spaces, work zones, fitness centers. In the past four years, the build to rent sector has fluctuated, with a drastic decline in 2022 .

The UK residential real estate market, valued at £360.27 million in 2025, is projected to experience robust growth, driven by several key factors. A consistently strong CAGR of 5.75% indicates a healthy and expanding market over the forecast period (2025-2033). This growth is fueled by increasing urbanization, a growing population, and a persistent demand for housing, particularly in major cities like London. Furthermore, government initiatives aimed at boosting homeownership and infrastructure development contribute positively to market expansion. The market is segmented by property type, with apartments and condominiums, and landed houses and villas representing significant segments. Key players such as Bellway PLC, Barratt Developments PLC, and Berkeley Group dominate the market, while a competitive landscape also includes numerous smaller developers and housing associations. While rising interest rates and construction costs present challenges, the overall outlook remains positive due to the enduring demand and limited housing supply, particularly in desirable areas. However, several factors could influence the market's trajectory. Fluctuations in the national economy, changes in government regulations concerning mortgages and property taxation, and global economic uncertainty could impact buyer confidence and investment. Regional variations also exist, with market dynamics differing across England, Scotland, Wales, and Northern Ireland. Understanding these regional nuances is crucial for targeted investment strategies. The market's resilience will depend on the ability of developers to adapt to changing market conditions and meet evolving consumer preferences for sustainable and energy-efficient housing. The continuous evolution of consumer preferences towards specific types of housing and location preferences will further shape the market's future growth. Recent developments include: May 2023: A UAE-based investment manager, Rasmala Investment Bank, has launched a USD 2bn ( €1.8bn) UK multifamily strategy for a five-year period to build a USD 2bn portfolio of UK residential properties. The strategy is focused on the UK market for multifamily properties through a Shariah-compliant investment vehicle, initially targeting the serviced apartment (SAP) and BTR (build-to-rent) subsectors within and around London. Seeded by Rasmala Group, the strategy is backed by an active investment pipeline for the next 12 – 18 months., November 2022: ValuStrat, a Middle East consulting company, increased its foothold in the UK by acquiring an interest in Capital Value Surveyors, a real estate advisory services company with offices in London. The UK continues to be one of the most established real estate markets worldwide and attracts foreign investors regularly. They are excited to expand their presence there to better serve all of their clients, both in the UK and the Middle East.. Key drivers for this market are: Demand for New Dwellings Units, Government Initiatives are driving the market. Potential restraints include: Demand for New Dwellings Units, Government Initiatives are driving the market. Notable trends are: Increasing in the United Kingdom House Prices.

This Power BI project analyzes London housing data to uncover patterns and trends in pricing, borough-wise distribution, affordability, and market growth over time. The dashboard is designed for anyone interested in property investment, urban planning, or simply understanding how the London housing market behaves.

✅ Key Features:

📍 Borough-wise Price Distribution Understand how average property prices vary across different London boroughs.

📈 Trend Analysis Visualize long-term price trends with dynamic line and area charts to observe how the market has evolved over time.

🧮 Affordability Index A calculated metric to measure housing affordability based on price vs income estimations.

🏘️ Property Type Breakdown Interactive visuals showing trends across Flats, Detached, Semi-Detached, and Terraced houses.

🗓️ Time Filters & Slicers Easily filter by year, month, or borough to explore specific time periods or locations.

Update 29-04-2020: The data is now split into two files based on the variable collection frequency (monthly and yearly). Additional variables added: area size in hectares, number of jobs in the area, number of people living in the area.

Context

I have been inspired by Xavier and his work on Barcelona to explore the city of London! 🇬🇧 💂

Content

The datasets is primarily centered around the housing market of London. However, it contains a lot of additional relevant data: - Monthly average house prices - Yearly number of houses - Yearly number of houses sold - Yearly percentage of households that recycle - Yearly life satisfaction - Yearly median salary of the residents of the area - Yearly mean salary of the residents of the area - Monthly number of crimes committed - Yearly number of jobs - Yearly number of people living in the area - Area size in hectares

The data is split by areas of London called boroughs (a flag exists to identify these), but some of the variables have other geographical UK regions for reference (like England, North East, etc.). There have been no changes made to the data except for melting it into a long format from the original tables.

Acknowledgements

The data has been extracted from London Datastore. It is released under UK Open Government License v2 and v3. The underlining datasets can be found here: https://data.london.gov.uk/dataset/uk-house-price-index https://data.london.gov.uk/dataset/number-and-density-of-dwellings-by-borough https://data.london.gov.uk/dataset/subjective-personal-well-being-borough https://data.london.gov.uk/dataset/household-waste-recycling-rates-borough https://data.london.gov.uk/dataset/earnings-place-residence-borough https://data.london.gov.uk/dataset/recorded_crime_summary https://data.london.gov.uk/dataset/jobs-and-job-density-borough https://data.london.gov.uk/dataset/ons-mid-year-population-estimates-custom-age-tables

Cover photo by Frans Ruiter from Unsplash

Inspiration

The dataset lends itself for extensive exploratory data analysis. It could also be a great supervised learning regression problem to predict house price changes of different boroughs over time.

Dataset Overview

This dataset provides a snapshot of properties listed for sale in London, sourced from the Rightmove website. It includes various property details such as the number of bedrooms, bathrooms, type of property, and price. The dataset is designed for educational purposes, offering insights into real estate trends and allowing data science enthusiasts to apply their skills in the context of property analysis.

Data Science Applications

This dataset is a valuable resource for students and researchers to practice various data science and analytics techniques. Potential applications include: - Exploratory Data Analysis (EDA): Understanding property distribution across London, price trends, and property types. - Price Prediction Models: Building machine learning models to estimate property prices based on available features. - Real Estate Trend Analysis: Analyzing trends in London’s real estate market, such as price fluctuations or differences in property features by neighborhood. - Text Analysis: Using the property descriptions for natural language processing (NLP) to extract keywords or sentiment related to property value or appeal.

Column Descriptions

• addedOn: Date when the property listing was added or updated on the website.
• title: Brief listing title describing the property, typically including the number of bedrooms and the location.
• descriptionHtml: Detailed description of the property, including features and potentially some promotional language.
• propertyType: Type of property, such as House, Terraced, or Detached.
• sizeSqFeetMax: Maximum size of the property in square feet, if provided.
• bedrooms: Number of bedrooms in the property.
• bathrooms: Number of bathrooms in the property.
• listingUpdateReason: Reason for updating the listing (e.g., new listing, price reduction).
• price: Price at which the property is listed for sale.

Ethically Mined Data

This dataset was ethically mined from a publicly accessible website using the APIFY API. All data in this dataset reflects publicly available information about properties listed for sale, with no Personally Identifiable Information (PII) included. The dataset does not include any data that could infringe on individual privacy.

Acknowledgements

• Data Source: Rightmove for providing publicly accessible real estate listings.
• Image Credit: Photo by Douglas Sheppard on Unsplash.

The booming robot rental market is projected to reach significant value by 2033, driven by surging automation demand and flexible rental options. Learn about market trends, key players (like Universal Robots and Robot Rentals), and regional growth in this comprehensive analysis.