House Prices Datasets: Best Property Price Databases & Providers for Real Estate Projects
House prices datasets are comprehensive collections of property value records across various geographic locations and time frames. They encompass variables such as location, size, age, features, and the sale price of houses. These datasets are vital resources for researchers, real estate professionals, economists, and policy makers. Check out our selection of databases that can help you with your project.
Recommended House Prices Datasets
Bright Data | House Price Data | Custom Dataset of House and Real Estate Pricing, Web-Scraped - Available at scale for any use case
Crawlbee | Consumer Marketing Data | Versatile B2C Contact Data | API & Dataset | US Household, Housing, Mortgage Data
Grepsr | Real Estate Products, Property Listing, Sold Properties, Rankings, Agent Datasets | Global Coverage with Custom and On-demand Datasets
House Price Index in the Netherlands (10 years history)
Autoscraping's Idealista Real Estate Data for Spain - 5M Property Listings with Prices, Detailed Descriptions & Key Features
Related searches
Bright Data | Real Estate Price Data | Custom Dataset of House and Real Estate Pricing, Web-Scraped - Available at scale for any use case
Factori AI & ML Training Data | Consumer Data | USA | Machine Learning Data
Web Scraping Data | Real Estate Market Data | No Infra Cost | Real-time & Historical | Pre-built AI & Automation | 50% Cost Saving | Free Samples
Canaria | Salary Data | US | 25M+ Monthly Job Postings & 2 Year Historical | AI-LLM Enhanced Salary Data
Developer Community and Code Datasets
House prices datasets play an instrumental role in analyzing real estate trends, informing investment decisions, influencing government housing policies, and powering predictive modeling for future property values. They offer a rich source of quantitative information, casting light on market dynamics and consumer behavior.
Best House Prices Databases
| Rank | Provider Name | Dataset Name | Scope | Key Features | Remarks |
|---|---|---|---|---|---|
| 1 | Bright Data | Custom Dataset of House and Real Estate Pricing | Australian Market | Room size, past sales, location | Comprehensive dataset for Australian housing market |
| 2 | Matrixian | House Price Index in the Netherlands (10 years history) | Dutch Market | Housing types, construction periods | Useful for risk analysis, ROI determination, forecasts |
| 3 | RateSpot | Mortgage Rates - Hourly Historical Prices (6am - 10pm EST) | Global Market | Hourly mortgage rates | Valuable for monitoring mortgage rate fluctuations |
| 4 | Canari | Historical volatility time series and Live prices on Equity Options | Global Market | Live prices, historical volatility | Useful for options traders |
| 5 | Grepsr | Real Estate Products, Property, Rankings, Agent Datasets | Global Market | Property data, agent rankings | Good for real estate marketing and development strategies |
| 6 | xavvy | Gas Station POI Data USA - 113k+ Stations with 75+ Attributes | US Market | Brand, address, geo-coordinates, services | Comprehensive dataset for gas stations in USA |
| 7 | xavvy | Gas Station POI Data Europe - 140k+ Stations with 400+ Attributes | European Market | Brand, address, geo-coordinates, services | Comprehensive dataset for gas stations in Europe |
| 8 | Skuuudle | Price Intelligence - Competitor Monitoring - Price Scraping | Global Market | Price scraping, product matching, data delivery | Good for businesses looking to gain a competitive edge |
| 9 | Pynk | Bitcoin Price Daily Signal based on 75k Users | Global Market | Daily Bitcoin price signals | Useful for Bitcoin market analysis |
| 10 | Pynk | Bitcoin Price Predictions based on 75k Users daily | Global Market | Daily Bitcoin price predictions | Offers a daily overview of potential Bitcoin market movements |
House Prices Datasets Use Cases
House prices datasets find application in a multitude of sectors beyond real estate.
Machine Learning and Predictive Analysis
Data scientists and researchers use these datasets as training data for machine learning models that predict house prices based on various features.
Urban Planning and Development
City planners use these datasets to gain insights into patterns of urban development and gentrification.
Fueling Real Estate Market Analysis
House prices datasets provide a real-time picture of property market trends. They aid in identifying booming areas, undervalued properties, and potential investment opportunities. They also help in understanding the impact of macroeconomic variables, like interest rates and unemployment, on housing prices.
Shaping Housing Policies
Government bodies and policy makers leverage these datasets to formulate effective housing policies. They help identify areas of housing shortages or excess, gentrification trends, and the influence of socio-economic factors on property values.
FAQs About House Prices Data
What does a typical house prices dataset contain?
A typical house prices dataset contains records of individual property sales, with features such as the sale price, location, size (square footage), number of bedrooms and bathrooms, age of the house, and other amenities.
How are house prices datasets collected?
Most house prices datasets are collated from public records, real estate listing websites, and governmental bodies involved in housing and urban development.
How can property prices datasets influence investment decisions?
Investors can use house prices datasets to analyze market trends, spot undervalued properties, and predict future growth areas. These insights can guide investment strategies and property portfolio management.