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A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to mainroad, etc. The dataset is small yet, it's complexity arises due to the fact that it has strong multicollinearity. Can you overcome these obstacles & build a decent predictive model?
Harrison, D. and Rubinfeld, D.L. (1978) Hedonic prices and the demand for clean air. J. Environ. Economics and Management 5, 81–102. Belsley D.A., Kuh, E. and Welsch, R.E. (1980) Regression Diagnostics. Identifying Influential Data and Sources of Collinearity. New York: Wiley.
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TwitterIn 2025, India was the country with the highest increase in house prices since 2010 among the Asia-Pacific (APAC) countries under observation. In the second quarter of the year, the nominal house price index in India reached over 359 index points. This suggests an increase of 259 percent since 2010, the baseline year when the index value was set to 100. It is important to note that the nominal index does not account for the effects of inflation, meaning when adjusted for inflation, price growth in real terms was slower.
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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 Name | Description |
|---|---|
Country | The country where the housing market data is recorded 🌍 |
Year | The year of observation 📅 |
Average House Price ($) | The average price of houses in USD 💰 |
Median Rental Price ($) | The median monthly rent for properties in USD 🏠 |
Mortgage Interest Rate (%) | The average mortgage interest rate percentage 📉 |
Household Income ($) | The average annual household income in USD 🏡 |
Population Growth (%) | The percentage increase in population over the year 👥 |
Urbanization Rate (%) | Percentage of the population living in urban areas 🏙️ |
Homeownership Rate (%) | The percentage of people who own their homes 🔑 |
GDP Growth Rate (%) | The annual GDP growth percentage 📈 |
Unemployment Rate (%) | The percentage of unemployed individuals in the labor force 💼 |
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TwitterGlobal 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.
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TwitterIn the second quarter of 2025, North Macedonia, Portugal, and Bulgaria registered the highest house price increase in real terms (adjusted for inflation). In North Macedonia, house prices outgrew inflation by nearly ** percent. When comparing the nominal price change, which does not take inflation into consideration, the average house price growth was even higher.
Meanwhile, many countries experienced declining prices, with Hong Kong recording the biggest decline, at ***** percent. That has to do with a broader trend of a slowing global housing market.
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Key information about House Prices Growth
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TwitterTurkey experienced the highest annual change in house prices in 2025, followed by North Macedonia and Portugal. In the second quarter of the year, the nominal house price in Turkey grew by **** percent, while in North Macedonia and Portugal, the increase was **** and **** percent, respectively. Meanwhile, some countries saw prices fall throughout the year. That has to do with an overall cooling of the global housing market that started in 2022. When accounting for inflation, house price growth was slower, and even more countries saw the market shrink.
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Trends in House price index. The latest data for over 100 countries around the world.
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Key information about House Prices Growth
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TwitterIn 2020, Hong Kong had the most expensive residential property market worldwide, with an average property price of 1.25 million U.S. dollars. The government of Hong Kong provide public housing for lower-income residents and almost 45 percent of the Hong Kong population lived in public permanent housing in 2018.
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The Global Housing Watch tracks developments in housing markets across the world on a quarterly basis. It provides current data on house prices as well as metrics used to assess valuation in housing markets, such as house price‑to‑rent and house-price‑to‑income ratios. This collection includes only a subset of indicators from the source dataset.
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Key information about House Prices Growth
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Key information about House Prices Growth
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India's residential house prices - quarterly and annual changes in house prices across cities, expert analysis and comparison with global peers.
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Global House Standardised Price-Income Ratio by Country, 2023 Discover more data with ReportLinker!
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TwitterGeneva stands out as Europe's most expensive city for apartment purchases in early 2025, with prices reaching a staggering 15,720 euros per square meter. This Swiss city's real estate market dwarfs even high-cost locations like Zurich and London, highlighting the extreme disparities in housing affordability across the continent. The stark contrast between Geneva and more affordable cities like Nantes, France, where the price was 3,700 euros per square meter, underscores the complex factors influencing urban property markets in Europe. Rental market dynamics and affordability challenges While purchase prices vary widely, rental markets across Europe also show significant differences. London maintained its position as the continent's priciest city for apartment rentals in 2023, with the average monthly costs for a rental apartment amounting to 36.1 euros per square meter. This figure is double the rent in Lisbon, Portugal or Madrid, Spain, and substantially higher than in other major capitals like Paris and Berlin. The disparity in rental costs reflects broader economic trends, housing policies, and the intricate balance of supply and demand in urban centers. Economic factors influencing housing costs The European housing market is influenced by various economic factors, including inflation and energy costs. As of April 2025, the European Union's inflation rate stood at 2.4 percent, with significant variations among member states. Romania experienced the highest inflation at 4.9 percent, while France and Cyprus maintained lower rates. These economic pressures, coupled with rising energy costs, contribute to the overall cost of living and housing affordability across Europe. The volatility in electricity prices, particularly in countries like Italy where rates are projected to reach 153.83 euros per megawatt hour by February 2025, further impacts housing-related expenses for both homeowners and renters.
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Housing Index in South Korea increased to 94 points in October from 93 points in September of 2025. This dataset provides - South Korea House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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A dataset that tracks property prices in major cities around the world. It includes data on housing types, square footage, and sale prices. Columns: City, Year, Property Type (e.g., Apartment, House), Square Footage, Sale Price ($), Property Age, Neighborhood.
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The allure of Swiss houses lies in their harmonious integration with the breathtaking natural surroundings, offering residents a unique blend of tranquility and cosmopolitan living.
Switzerland's renowned stability, both economically and politically, adds a layer of desirability to its real estate market. The country's commitment to quality living is reflected not only in its efficient infrastructure but also in its high standards of education, healthcare, and overall well-being.
However, such a high quality of life and the unparalleled Swiss experience come at a cost. Swiss house prices reflect the exclusivity and desirability of the real estate market, positioning it as an investment in both luxury and lifestyle. In this journey through Swiss real estate, I unravel the layers of this captivating narrative, helping you exploring not just the numbers but the essence of what makes owning a house in Switzerland an aspirational dream for many - probably also yours!?
house_price_switzerland.csv - The complete dataset with 11 columns.ID - A unique identifier for each object in the dataset.HouseType - Describes the type of the house, such as "Villa".Size - Represents a categorical size classification, for example, "L".Price - Indicates the value of the house in Swiss Francs (CHF). If NaN the price is "Price on Request".LotSize - Specifies the surrounding area of the property in square meters.Balcony - Binary indicator of whether the object has a balcony (Yes/No).LivingSpace - Denotes the living area of the house in square meters.NumberRooms - Indicates the total number of rooms in the house.YearBuilt - Represents the year in which the house was constructed.Locality - Specifies the city or town where the object is situated.PostalCode - Corresponds to the postal code of the locality where the object is located.
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TwitterHow have house prices evolved over the long run? This paper presents annual house prices for 14 advanced economies since 1870. We show that real house prices stayed constant from the nineteenth to the mid-twentieth century, but rose strongly and with substantial cross-country variation in the second half of the twentieth century. Land prices, not replacement costs, are the key to understanding the trajectory of house prices. Rising land prices explain about 80 percent of the global house price boom that has taken place since World War II. Our findings have implications for the evolution of wealth-to-income ratios, the growth effects of agglomeration, and the price elasticity of housing supply.
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A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to mainroad, etc. The dataset is small yet, it's complexity arises due to the fact that it has strong multicollinearity. Can you overcome these obstacles & build a decent predictive model?
Harrison, D. and Rubinfeld, D.L. (1978) Hedonic prices and the demand for clean air. J. Environ. Economics and Management 5, 81–102. Belsley D.A., Kuh, E. and Welsch, R.E. (1980) Regression Diagnostics. Identifying Influential Data and Sources of Collinearity. New York: Wiley.