The Zoopla Dataset provides a detailed repository of information covering property listings available on the Zoopla platform. Tailored to support businesses, researchers, and analysts in the real estate sector, this dataset delivers valuable insights into market trends, property valuations, and consumer preferences within the real estate market.

With key attributes such as property details, pricing data, location information, and listing history, users can conduct thorough analyses to refine property investment strategies, assess market demand, and identify emerging trends.

Whether you're a real estate agent seeking to enhance your property listings, a researcher investigating trends in the housing market, or an analyst aiming to refine investment strategies, the Zoopla Dataset serves as an essential resource for unlocking opportunities and driving success in the competitive landscape of real estate

In 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.

***Overview: Dataset contains recent properties sold in England from Zoopla listings.

***Data Science Applications and tasks possible * Analyse average pricing and trends * Geo- Spatial analysis * Feature extraction/Engineering *Data Cleaning

***Ethically mined data Data has been mined ethically using API for Publicly available data only.

***Main Data Columns: bathrooms ,bedrooms ,country ,currentEnergyRating ,floorAreaSqM ,fullAddress ,historicListings/0/date ,historicListings/0/price historicListings/1/date ,historicListings/1/price ... .saleEstimate/ingestedAt ,saleEstimate/lowerPrice ,saleEstimate/upperPrice .saleEstimate/valueChange/numericChange ,saleEstimate/valueChange/percentageChange ,saleEstimate/valueChange/saleDate , soldPricesDataSource ,tenure ,uprn .

***Note ---(Requires Data Cleaning to remove unwanted columns)

These Kaggle datasets provide downloaded real-estate listings from the UK real estate market, capturing data from a leading platform in the UK (Zoopla), reminiscent of the approach taken for the US dataset from Redfin and French dataset from Seloger. It encompasses detailed property listings, pricing, and market trends across UK, stored in weekly CSV snapshots. The cleaned and merged version of all the snapshots is named as UK_clean_unique.csv.

The cleaning process mirrored that of the US and French datasets, involving removing irrelevant features, normalizing variable names for dataset consistency with the USA and France, and adjusting variable value ranges to get rid of extreme outliers. To augment the dataset's depth, external factors like inflation rates, stock market volatility, and macroeconomic indicators have been integrated, offering a multifaceted perspective on the UK's real estate market drivers.

For exact column descriptions, see columns for UK_clean_unique.csv and my thesis.

Table 2.6 and Section 2.2.2, which I refer to in the column descriptions, can be found in my thesis; see University Library. Click on Online Access->Hlavni prace.

If you want to continue generating datasets yourself, see my Github Repository for code inspiration.

Let me know if you want to see how I got from raw data to France_clean_unique.csv. There are multiple steps, including cleaning Tableau Prep and R, downloading and merging external variables to the dataset, removing duplicates, and renaming some columns.

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.

Discover the booming UK real estate services market! This in-depth analysis reveals a £32.45 billion industry with a 3% CAGR, driven by urbanization and proptech. Explore market trends, key players (Rightmove, British Land, Hammerson), and regional insights for 2025-2033. 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: Improvements in Infrastructure and New Development, Population Growth and Demographic Changes. Notable trends are: Increasing in the United Kingdom House Prices.

Discover the booming MLS Listing Software market! This comprehensive analysis reveals a $5B market in 2025, projected to reach $14B by 2033, driven by cloud adoption and real estate tech advancements. Explore key trends, regional insights, and leading companies shaping this dynamic sector.

These Kaggle datasets provide downloaded real estate listings from the French real estate market, capturing data from a leading platform in France (Seloger), reminiscent of the approach taken for the US dataset from Redfin and UK dataset from Zoopla. It encompasses detailed property listings, pricing, and market trends across France, stored in weekly CSV snapshots. The cleaned and merged version of all the snapshots is named as France_clean_unique.csv.

The cleaning process mirrored that of the US dataset, involving removing irrelevant features, normalizing variable names for dataset consistency with USA and UK, and adjusting variable value ranges to get rid of extreme outliers. To augment the dataset's depth, external factors like inflation rates, stock market volatility, and macroeconomic indicators have been integrated, offering a multifaceted perspective on France's real estate market drivers.

For exact column descriptions, see columns for France_clean_unique.csv and my thesis.

Table 2.5 and Section 2.2.1, which I refer to in the column descriptions, can be found in my thesis; see University Library. Click on Online Access->Hlavni prace.

If you want to continue generating datasets yourself, see my Github Repository for code inspiration.

Let me know if you want to see how I got from raw data to France_clean_unique.csv. There are multiple steps, including cleaning Tableau Prep and R, downloading and merging external variables to the dataset, removing duplicates, and renaming some columns.

Discover the booming online classified advertising market! Explore its growth trajectory, key players (Schibsted-Adevinta, OLX Group, eBay Classifieds), regional trends, and future projections to 2033. Learn about market segmentation, driving forces, and challenges facing this dynamic sector.

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.