The average for 2021 based on 165 countries was 79.81 index points. The highest value was in Bermuda: 212.7 index points and the lowest value was in Syria: 33.25 index points. The indicator is available from 2017 to 2021. Below is a chart for all countries where data are available.

Portugal, Canada, and the United States were the countries with the highest house price to income ratio in 2024. In all three countries, the index exceeded 130 index points, while the average for all OECD countries stood at 116.2 index points. The index measures the development of housing affordability and is calculated by dividing nominal house price by nominal disposable income per head, with 2015 set as a base year when the index amounted to 100. An index value of 120, for example, would mean that house price growth has outpaced income growth by 20 percent since 2015. How have house prices worldwide changed since the COVID-19 pandemic? House prices started to rise gradually after the global financial crisis (2007–2008), but this trend accelerated with the pandemic. The countries with advanced economies, which usually have mature housing markets, experienced stronger growth than countries with emerging economies. Real house price growth (accounting for inflation) peaked in 2022 and has since lost some of the gain. Although, many countries experienced a decline in house prices, the global house price index shows that property prices in 2023 were still substantially higher than before COVID-19. Renting vs. buying In the past, house prices have grown faster than rents. However, the home affordability has been declining notably, with a direct impact on rental prices. As people struggle to buy a property of their own, they often turn to rental accommodation. This has resulted in a growing demand for rental apartments and soaring rental prices.

Graph and download economic data for Real Residential Property Prices for United Kingdom (QGBR628BIS) from Q2 1968 to Q1 2025 about United Kingdom, residential, HPI, housing, real, price index, indexes, and price.

Saint Laurent web scraped data

  About the website

Saint Laurent operates within the luxury fashion industry in the Europe, the Middle East and Africa (EMEA) region, with significant impact in the United Kingdom. This industry is characterised by prestigious brands offering high-quality, expensive products which are often seen as a status symbol. There has notably been a shift in the industry towards Ecommerce sales, owing to customers’ increasing preference for online… See the full description on the dataset page: https://huggingface.co/datasets/DBQ/Saint.Laurent.Product.prices.United.Kingdom.

MealMe offers in-depth restaurant menu data, including prices, from the top 100,000 restaurants across the USA and Canada. Our proprietary technology collects accurate, real-time menu and pricing information, enabling businesses to make data-driven decisions in competitive intelligence, pricing optimization, and market research. With comprehensive coverage that spans major restaurant platforms and chains, MealMe ensures your business has access to the most reliable data to excel in a rapidly evolving industry.

Platforms and Restaurants Covered: MealMe's database includes data from leading restaurant platforms such as UberEats, Postmates, ToastTakeout, SkipTheDishes, Square, Appfront, Olo, TouchBistro, and Clover, as well as direct menu data from major restaurant chains including Raising Cane’s, Panda Express, Popeyes, Burger King, and Subway. This extensive coverage ensures a detailed view of the market, helping businesses monitor trends, pricing, and availability across a broad spectrum of restaurant types and sizes.

Key Features: Comprehensive Menu Data: Access detailed menu information, including item descriptions, categories, sizes, and customizations. Real-Time Pricing: Monitor up-to-date menu prices for accurate competitive analysis. Restaurant-Specific Insights: Analyze individual restaurant chains such as Raising Cane’s and Panda Express, or platforms like UberEats, for market trends and pricing strategies. Cross-Platform Analysis: Compare menu items and pricing across platforms like ToastTakeout, Olo, and SkipTheDishes for a holistic industry view. Regional Data: Understand geographic variations in menu offerings and pricing across the USA and Canada.

Use Cases: Competitive Intelligence: Track menu offerings, pricing strategies, and seasonal trends across platforms like UberEats and Postmates or chains like Popeyes and Subway. Market Research: Identify gaps in the market by analyzing menus and pricing from top restaurants. Pricing Optimization: Use real-time pricing data to inform dynamic pricing strategies and promotions. Trend Monitoring: Stay ahead by tracking popular menu items, regional preferences, and emerging food trends. Platform Analysis: Assess how restaurants perform across delivery platforms such as SkipTheDishes, Olo, and Square. Industries Benefiting from Our Data Restaurant Chains: Optimize menu offerings and pricing strategies with detailed competitor data. Food Delivery Platforms: Benchmark menu pricing and availability across competitive platforms. Market Research Firms: Conduct detailed analyses to identify opportunities and market trends. AI & Analytics Companies: Power recommendation engines and predictive models with robust menu data. Consumer Apps: Enhance app experiences with accurate menu and pricing data. Data Delivery and Integration

MealMe offers flexible integration options to ensure seamless access to our comprehensive menu data. Whether you need bulk exports for in-depth research or real-time updates via API, our solutions are designed to scale with your business needs.

Why Choose MealMe? Extensive Coverage: Menu data from 100,000+ restaurants, including major chains like Burger King and Raising Cane’s. Real-Time Accuracy: Up-to-date pricing and menu details for actionable insights. Customizable Solutions: Tailored datasets to meet your specific business objectives. Proven Expertise: Trusted by top companies for delivering reliable, actionable data. MealMe empowers businesses with the data needed to thrive in a competitive restaurant and food delivery market. For more information or to request a demo, contact us today!

There are six diferent kinds of widgets we have;

Ticker - This Widget is used for your websites top or bottom for navigation bar. It is horizontal bar with symbols last prices, daily changes and daily percentage changes.

Tape Ticker - This is a stock market classic widget that simply displays symbols (prices, daily changes and daily changes of percentages ) with a sliding cursor that stops when your cursor stops in a position it will stop too. Simple, fancy and useful.

Single Ticker - It's a simple one-symbol sized ticker.

Converter - This widget works best on the right or left sidebar of your website with a fast, useful currency converter with the latest updates and unit prices.

Mini Converter - It’s also simple and beautiful converter best for mobile websites.

Historical Chart - You can view the historical data details for a single symbol with the Historical Chart Widget.

Net-a-Porter web scraped data

  About the website

Net-a-Porter operates in the highly competitive e-commerce industry in EMEA, particularly in the United Kingdom. This vibrant industry is characterized by a dynamic digital environment encompassing various segments, notably fashion, luxury goods, and retail. These segments continue to witness significant growth, driven by advancements in technology and changing consumer behaviors. Net-a-Porter, being a premium online luxury… See the full description on the dataset page: https://huggingface.co/datasets/DBQ/Net.a.Porter.Product.prices.United.Kingdom.

Food purchases differ substantially across countries. We use detailed household level data from the US, France and the UK to (i) document these differences; (ii) estimate a demand system for food and nutrients, and (iii) simulate counterfactual choices if households faced prices and nutritional characteristics from other countries. We find that differences in prices and characteristics are important and can explain some difference (e.g., US-France difference in caloric intake), but generally cannot explain many of the compositional patterns by themselves. Instead, it seems an interaction between the economic environment and differences in preferences is needed to explain cross country differences.

This data package contains UK controlled drugs database, US food prices database, US nationwide food consumption survey, US national health and nutrition examination survey, US healthy eating index and data on food affordability for households led by females.

ZARA UK Fashion Dataset offers an extensive collection of fashion product data from ZARA's UK online store, providing a detailed overview of available items. This dataset is valuable for analyzing the European fashion retail market, particularly in the UK, and includes fields such as product titles, URLs, SKUs, MPNs, brands, prices, currency, images, breadcrumbs, country, availability, unique IDs, and timestamps for when the data was scraped.

Key Features:

• Product Details: Includes title, URL, SKU (Stock Keeping Unit), MPN (Manufacturer Part Number), and brand for each product, helping to uniquely identify and differentiate items.
• Pricing Information: Features the price of each product along with the currency used (GBP) to understand the pricing strategies of ZARA in the UK market.
• Visual Data: High-quality images of each product, essential for visual merchandising analysis and online consumer behavior studies.
• Categorical Information: Breadcrumbs data provide context on the product's placement within ZARA's website structure, helping to analyze navigation and product hierarchy.
• Geographical Focus: Specific to the UK market, making it relevant for studies on British fashion retail and consumer trends.
• Availability Status: Includes real-time availability data, which is crucial for understanding stock levels, popular products, and restocking practices.
• Unique Identifiers: Each product is tagged with a uniq_id, ensuring data integrity and making it easier to track and analyze over time.
• Data Collection Timestamp: The scraped_at field records the exact time and date when the data was collected, aiding in time-based analysis of inventory and pricing.

Potential Use Cases:

• Market Research: Analyze UK and European fashion trends, consumer preferences, and competitive positioning within the fast fashion sector.
• E-commerce Analysis: Study ZARA's product placement, pricing, and availability to optimize online retail strategies.
• Stock Management: Use SKU and availability data to predict inventory needs and enhance supply chain efficiency.
• Brand Analysis: Examine the impact of brand identity on consumer choices and product performance in the UK market.
• Academic Research: Ideal for research projects focused on fashion retail, marketing strategies, and consumer behavior in Europe.

Data Sources:

The data is meticulously collected from ZARA's official UK website and other reliable retail databases, reflecting the latest product offerings and market dynamics specific to the UK and European fashion markets.

• ZARA US Retail Products Dataset: Explore over 10,000 product records from ZARA's USA online store, including titles, prices, images, and availability.
  
  
• Fashion Products Dataset from GAP.com: Access detailed product information from GAP's online store, featuring over 4,500 fashion items with attributes like price, brand, color, reviews, and images.
  
  
• Myntra Fashion Products Dataset: A comprehensive dataset from Myntra.com, offering over 12,000 fashion products with detailed attributes for in-depth analysis.

Price Paid Data tracks the residential property sales in England and Wales that are lodged with HM Land Registry for registration.

Our price paid data tracks the residential property sales in England and Wales that are lodged with us for registration. The dataset is a reliable source of house price information and consists of more than 24 million definitive records dating back to January 1995. For more information on this dataset and what it does and doesn't include, visit https://www.gov.uk/about-the-price-paid-data

Choose from three options to select the data that best meets your requirements:

• monthly file: contains a single monthly file of the transactions received in the period from the first to the last day of the corresponding month, including any changes or deletions to previously downloaded data. The data is updated monthly and the average size of this file is 11 MB.

• single file: contains all the up to date data from 1995 to the current date. The data is updated monthly and the average size of this file is 2.86 GB.

• yearly files: contains annual files of up to date data, ranging from 1995 to the current date. Unlike the monthly files described above, yearly files are collated on the date of the transaction/deed date rather than the date that the information was lodged with HM Land Registry. The data is updated monthly and the sizes of these files range from 87 MB to 222 MB. If you are having trouble downloading any of the year files in full, they are also available as two smaller, evenly split CSV files.

We try to make sure that our public data is accurate, but cannot guarantee that it is free from errors or fit for your purpose or use. Reports are based on data collected at the time a property transaction is registered with us and will not necessarily be up to date with the most recent information. For more information, read https://www.gov.uk/government/statistical-data-sets/price-paid-data-downloads#when-using-or-publishing-our-price-paid-data

Celine web scraped data

  About the website

The Ecommerce industry in the EMEA region, particularly in the United Kingdom, has shown a significant growth rate in recent years, becoming a pivotal element in the regions economic landscape. The rise of digital technologies and change in consumer behavior has further accelerated this upward trend. In this digital marketplace, Celine, a well-known high-end fashion brand, has maintained its mark. The dataset at-hand encompasses… See the full description on the dataset page: https://huggingface.co/datasets/DBQ/Celine.Product.prices.United.Kingdom.

The Open Economics project provides open content, data and code related to Economics. This site itself provides interfaces to some (though not all) of the Open Economics datasets and models.

Current datasets (all available as csv):

• Bank of England Interest Rate
• CIA World Factbook Data (Various Years)
• Copyright Registrations in the United States 1790-2000
• Country and Regional Analyses (CRA) - UK Government Finances
• Daily Wages of Thatchers in the Middle Ages
• Distribution of Estimated Patent Values in Various European Countries
• Gold Prices 1950-2008 (Monthly)
• Government revenue (for 17 Countries in the period 1880-1913)
• Gross value added at basic prices: Output Index: CVM SA
• Hard Drive Capacities and Costs (1955-2000)
• Income Distribution in Hamburg for Occupied Persons in 1890
• Millenium Development Goals Dataset
• Monthly stock price, dividends, and earnings data and the consumer price index from January 1871
• Number of Published Articles in Economics (1970-2006)
• Patents Enrolled in England 1660-1799
• Penn World Table of PPP and National Income Accounts
• Population, Landscape and Climate Estimates
• Recorded Music Sales 1969-2004 Worldwide (in millions)
• UK Government Finances - Public Expenditure Statistical Analyses
• UK House Price Data
• UK Population Estimates 1520 to 1851
• UK Price Index 1850-2002 (Annual)
• US Population Estimates (mid year) 1790 to 2005
• US Wheat Production and Prices
• USA Employment status of the civilian noninstitutional population, 1940 to date
• W3Schools Browser Statistics (Monthly)
• Wheat, barley, oat, mutton and wool prices, and agricultural wages, 1500-1849 (10 year averages 1700-49 = 100)
• World Population Historical

We are in the process of merging this data catalog in CKAN (so each dataset will become a package on CKAN).

Openness

All Open Economics datasets are openly licensed though not always possible to gauge status of underlying data used. Individual datasets have more information about their license status.

MealMe provides comprehensive grocery and retail SKU-level product data, including real-time pricing, from the top 100 retailers in the USA and Canada. Our proprietary technology ensures accurate and up-to-date insights, empowering businesses to excel in competitive intelligence, pricing strategies, and market analysis.

Retailers Covered: MealMe’s database includes detailed SKU-level data and pricing from leading grocery and retail chains such as Walmart, Target, Costco, Kroger, Safeway, Publix, Whole Foods, Aldi, ShopRite, BJ’s Wholesale Club, Sprouts Farmers Market, Albertsons, Ralphs, Pavilions, Gelson’s, Vons, Shaw’s, Metro, and many more. Our coverage spans the most influential retailers across North America, ensuring businesses have the insights needed to stay competitive in dynamic markets.

Key Features: SKU-Level Granularity: Access detailed product-level data, including product descriptions, categories, brands, and variations. Real-Time Pricing: Monitor current pricing trends across major retailers for comprehensive market comparisons. Regional Insights: Analyze geographic price variations and inventory availability to identify trends and opportunities. Customizable Solutions: Tailored data delivery options to meet the specific needs of your business or industry. Use Cases: Competitive Intelligence: Gain visibility into pricing, product availability, and assortment strategies of top retailers like Walmart, Costco, and Target. Pricing Optimization: Use real-time data to create dynamic pricing models that respond to market conditions. Market Research: Identify trends, gaps, and consumer preferences by analyzing SKU-level data across leading retailers. Inventory Management: Streamline operations with accurate, real-time inventory availability. Retail Execution: Ensure on-shelf product availability and compliance with merchandising strategies. Industries Benefiting from Our Data CPG (Consumer Packaged Goods): Optimize product positioning, pricing, and distribution strategies. E-commerce Platforms: Enhance online catalogs with precise pricing and inventory information. Market Research Firms: Conduct detailed analyses to uncover industry trends and opportunities. Retailers: Benchmark against competitors like Kroger and Aldi to refine assortments and pricing. AI & Analytics Companies: Fuel predictive models and business intelligence with reliable SKU-level data. Data Delivery and Integration MealMe offers flexible integration options, including APIs and custom data exports, for seamless access to real-time data. Whether you need large-scale analysis or continuous updates, our solutions scale with your business needs.

Why Choose MealMe? Comprehensive Coverage: Data from the top 100 grocery and retail chains in North America, including Walmart, Target, and Costco. Real-Time Accuracy: Up-to-date pricing and product information ensures competitive edge. Customizable Insights: Tailored datasets align with your specific business objectives. Proven Expertise: Trusted by diverse industries for delivering actionable insights. MealMe empowers businesses to unlock their full potential with real-time, high-quality grocery and retail data. For more information or to schedule a demo, contact us today!