Dataset Introduction

This dataset contains property listings from various cities across Bangladesh, specifically including Dhaka, Chattogram, Cumilla, Narayanganj City, and Gazipur, with prices listed in Bangladeshi Taka (৳). The dataset provides valuable insights into various features of the properties, including the number of bedrooms, bathrooms, floor number, floor area in square feet, and their respective prices. The data has been collected from a real estate website, offering a comprehensive view of the housing market across these key cities in Bangladesh.

Feature Description

Title: The title or description of the property listing.

Bedrooms: The number of bedrooms in the property.

Bathrooms: The number of bathrooms in the property.

Floor_no: The floor number on which the property is located.

Occupancy_status: Indicates whether the property is vacant or occupied.

Floor_area: The total floor area of the property in square feet.

City: The city where the property is located. This dataset includes listings from Dhaka, Chattogram, Cumilla, Narayanganj City, and Gazipur.

Price_in_taka: The listing price of the property in Bangladeshi Taka (৳).

Location: The specific location or address within the city.

Usages and Applications

This dataset can be utilized in several ways:

Market Analysis: Understanding the pricing trends across different cities in Bangladesh. It can help identify which cities or neighborhoods are more expensive and which are more affordable.

Investment Decisions: Investors can use this data to evaluate potential real estate investments by comparing properties in terms of price, size, and location across different cities.

Real Estate Valuation: Property developers and agents can assess the market value of similar properties, enabling them to set competitive prices for new developments or resale properties in various regions.

Machine Learning Opportunities

This dataset presents several opportunities for applying machine learning techniques:

Price Prediction: Using features such as floor area, number of bedrooms, and location, machine learning models can be trained to predict the price of a property. This can be especially useful for buyers and sellers looking for price guidance across different cities.

Clustering: By clustering properties based on features like location, size, and price, one could identify distinct property segments or neighborhoods in Dhaka, Chattogram, Cumilla, Narayanganj City, and Gazipur with similar characteristics.

Demand Forecasting: Analyzing trends in the dataset over time can help predict future demand for housing in these cities, which could be valuable for both real estate developers and policymakers.

Anomaly Detection: Identifying properties that are significantly over- or under-priced compared to similar properties, which could indicate potential issues or opportunities in the market.

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.

House Price Index YoY in the United States decreased to 1.80 percent in December from 2.10 percent in November of 2025. This dataset includes a chart with historical data for the United States FHFA House Price Index YoY.

Graph and download economic data for All-Transactions House Price Index for the United States (USSTHPI) from Q1 1975 to Q4 2025 about appraisers, HPI, housing, price index, indexes, price, and USA.

Housing Index in the United Kingdom increased to 519.30 points in February from 517.80 points in January of 2026. This dataset provides - United Kingdom House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Real Residential Property Prices for United States (QUSR628BIS) from Q1 1970 to Q3 2025 about residential, HPI, housing, real, price index, indexes, price, and USA.

This dataset provides insights into the global housing market, covering various economic factors from 2015 to 2024. It includes details about property prices, rental yields, interest rates, and household income across multiple countries. This dataset is ideal for real estate analysis, financial forecasting, and market trend visualization.

📑 Column Descriptions

View monthly updates and historical trends for US House Price Index. from United States. Source: Federal Housing Finance Agency. Track economic data with …

Average House Prices in Canada decreased to 661100 CAD in February from 665000 CAD in January of 2026. This dataset includes a chart with historical data for Canada Average House Prices.

After a period of rapid increase, house price growth in the UK has moderated. In 2025, house prices are forecast to increase by ****percent. Between 2025 and 2029, the average house price growth is projected at *** percent. According to the source, home building is expected to increase slightly in this period, fueling home buying. On the other hand, higher borrowing costs despite recent easing of mortgage rates and affordability challenges may continue to suppress transaction activity. Historical house price growth in the UK House prices rose steadily between 2015 and 2020, despite minor fluctuations. In the following two years, prices soared, leading to the house price index jumping by about 20 percent. As the market stood in April 2025, the average price for a home stood at approximately ******* British pounds. Rents are expected to continue to grow According to another forecast, the prime residential market is also expected to see rental prices grow in the next five years. Growth is forecast to be stronger in 2025 and slow slightly until 2029. The rental market in London is expected to follow a similar trend, with Outer London slightly outperforming Central London.

In 2022, house price growth in the UK slowed, after a period of decade-long increase. Nevertheless, in November 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.

Housing Index in Netherlands increased to 153.50 points in February from 153.30 points in January of 2026. This dataset provides - Netherlands House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Global house prices experienced a significant shift in 2022, with advanced economies seeing a notable decline after a prolonged period of growth. The real house price index (adjusted for inflation) for advanced economies peaked at nearly *** index points in early 2022 before falling to around ***** points by the second quarter of 2023. In the second quarter of 2025, the index reached ***** points. This represents a reversal of the upward trend that had characterized the housing market for roughly a decade. Likewise, real house prices in emerging economies declined after reaching a high of ***** points in the third quarter of 2021. What is behind the slowdown? Inflation and slow economic growth have been the primary drivers for the cooling of the housing market. Secondly, the growing gap between incomes and house prices since 2012 has decreased the affordability of homeownership. Last but not least, homebuyers in 2024 faced dramatically higher mortgage interest rates, further contributing to worsening sentiment and declining transactions. Some markets continue to grow While many countries witnessed a deceleration in house price growth in 2022, some markets continued to see substantial increases. Turkey, in particular, stood out with a nominal increase in house prices of over ** percent in the first quarter of 2025. Other countries that recorded a two-digit growth include North Macedonia and Russia. When accounting for inflation, the three countries with the fastest growing residential prices in early 2025 were North Macedonia, Portugal, and Bulgaria.

View quarterly updates and historical trends for Florida House Price Index. Source: Federal Housing Finance Agency. Track economic data with YCharts analy…

Housing Index in Romania increased to 166.14 points in the third quarter of 2025 from 162.38 points in the second quarter of 2025. This dataset provides - Romania House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The average house price in the UK increased by 2.5 percent year-on-year in November 2025, according to the monthly house price index. The index is calculated using data on housing transactions and measures the development of house prices, with 2023 chosen as a base year when the index value was set to 100. In November 2025, the index reached 103.9 index points, meaning that house prices have grown by almost four percent since January 2023.The house price index is an important measure for the residential real estate market. It is used to show changes in the value of residential properties in England, Scotland, Wales, and Northern Ireland. This upward trend in house price index, and therefore the value of residential properties, has also been observed by other measurers of house price index in the United Kingdom.

According to ValuStrat, the average residential prices in Dubai reached around 1,448 United Arab Emirates dirhams (AED) in December 2024, rising from around 894 AED in 2020. Real estate market in Dubai Despite the impact of the global COVID-19 pandemic on the real estate market, Dubai's real estate sector continues to show resilience and remains a lucrative investment option. In the first quarter of 2021, the real estate transactions in Dubai amounted to approximately 25 billion U.S. dollars in value. With its emphasis on the goal of transforming into a high-end tourist destination, Dubai has become an appealing choice for real estate investors. In 2019, investment villas made up most urban buildings in the emirate, with around 72,000 units. Residential market outlook The residential market in Dubai has experienced substantial growth in recent years. In 2022, it was projected to witness the addition of approximately 45 thousand new apartments and seven thousand new villas. These additions contribute to the existing supply of 743,000 residential units in the emirate for that year. According to the same source, in December 2022, the capital prices of residential apartments in Jumeirah Beach Residence, Dubai, stood at approximately 2.5 million United Arab Emirates dirhams. This represented a 5.7 percent growth in capital values compared to the prior year. With its strong market presence and attractive investment opportunities, Dubai's residential market remains a key player in the region.

View quarterly updates and historical trends for Minnesota House Price Index. Source: Federal Housing Finance Agency. Track economic data with YCharts ana…

ATTOM’s Home Sales Trends dataset delivers reliable Real Estate Market Data by summarizing historical residential sales activity across the United States. Built from ATTOM’s proprietary database of verified deed transactions, it provides consistent House Price Data, Property Market Data, and Residential Real Estate Data across more than 2,700 counties.

What the Dataset Includes • Aggregated residential sales counts • Average sale prices • Median sale prices • Historical sales trends typically dating back to 2005 • Extended history to 2000 in select markets • Multi-level geographic aggregation from state to tract

How the Data Is Calculated • Derived from ATTOM’s verified property transaction database • Includes only arm’s-length residential transactions • Transaction types limited to: – Construction sales – Transfers and resales – Subdivision transfers • Residential property types only, including: – Single-family homes – Condo and townhome units • Sale price outliers removed to eliminate data errors

Why It Matters • Reflects true market-driven pricing and volume trends • Removes distressed and non-market transactions • Enables accurate comparison across markets and time periods • Supports consistent residential market analysis nationwide

Delivery & Cadence • Statistics typically delivered quarterly • Monthly or annual delivery available depending on use case

ATTOM’s Home Sales Trends dataset provides a clean, consistent, and historically rich foundation for analyzing residential market activity, price movement, and long-term housing trends across the U.S.