In 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.

In 2024, San Francisco, was the most expensive metro area for buying a luxury property. The median sale price of the single family homes in the top five percent of the market by market price was *** million U.S. dollars. In Detroit, on the other hand, the median sales price of a luxury housing unit was approximately ******* U.S. dollars.

Geneva 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.

Innsbruck was the most expensive Austrian city to buy an apartment in, with average values of 7,700 euros per square meter in the first quarter of 2025. The price of an apartment in Graz was significantly lower at 4,590 euros per square meter.

House Price Prediction Dataset.

The dataset contains 2000 rows of house-related data, representing various features that could influence house prices. Below, we discuss key aspects of the dataset, which include its structure, the choice of features, and potential use cases for analysis.

1. Dataset Features

The dataset is designed to capture essential attributes for predicting house prices, including:

Area: Square footage of the house, which is generally one of the most important predictors of price. Bedrooms & Bathrooms: The number of rooms in a house significantly affects its value. Homes with more rooms tend to be priced higher. Floors: The number of floors in a house could indicate a larger, more luxurious home, potentially raising its price. Year Built: The age of the house can affect its condition and value. Newly built houses are generally more expensive than older ones. Location: Houses in desirable locations such as downtown or urban areas tend to be priced higher than those in suburban or rural areas. Condition: The current condition of the house is critical, as well-maintained houses (in 'Excellent' or 'Good' condition) will attract higher prices compared to houses in 'Fair' or 'Poor' condition. Garage: Availability of a garage can increase the price due to added convenience and space. Price: The target variable, representing the sale price of the house, used to train machine learning models to predict house prices based on the other features.

2. Feature Distributions

Area Distribution: The area of the houses in the dataset ranges from 500 to 5000 square feet, which allows analysis across different types of homes, from smaller apartments to larger luxury houses. Bedrooms and Bathrooms: The number of bedrooms varies from 1 to 5, and bathrooms from 1 to 4. This variance enables analysis of homes with different sizes and layouts. Floors: Houses in the dataset have between 1 and 3 floors. This feature could be useful for identifying the influence of multi-level homes on house prices. Year Built: The dataset contains houses built from 1900 to 2023, giving a wide range of house ages to analyze the effects of new vs. older construction. Location: There is a mix of urban, suburban, downtown, and rural locations. Urban and downtown homes may command higher prices due to proximity to amenities. Condition: Houses are labeled as 'Excellent', 'Good', 'Fair', or 'Poor'. This feature helps model the price differences based on the current state of the house. Price Distribution: Prices range between $50,000 and $1,000,000, offering a broad spectrum of property values. This range makes the dataset appropriate for predicting a wide variety of housing prices, from affordable homes to luxury properties.

3. Correlation Between Features

A key area of interest is the relationship between various features and house price: Area and Price: Typically, a strong positive correlation is expected between the size of the house (Area) and its price. Larger homes are likely to be more expensive. Location and Price: Location is another major factor. Houses in urban or downtown areas may show a higher price on average compared to suburban and rural locations. Condition and Price: The condition of the house should show a positive correlation with price. Houses in better condition should be priced higher, as they require less maintenance and repair. Year Built and Price: Newer houses might command a higher price due to better construction standards, modern amenities, and less wear-and-tear, but some older homes in good condition may retain historical value. Garage and Price: A house with a garage may be more expensive than one without, as it provides extra storage or parking space.

4. Potential Use Cases

The dataset is well-suited for various machine learning and data analysis applications, including:

House Price Prediction: Using regression techniques, this dataset can be used to build a model to predict house prices based on the available features. Feature Importance Analysis: By using techniques such as feature importance ranking, data scientists can determine which features (e.g., location, area, or condition) have the greatest impact on house prices. Clustering: Clustering techniques like k-means could help identify patterns in the data, such as grouping houses into segments based on their characteristics (e.g., luxury homes, affordable homes). Market Segmentation: The dataset can be used to perform segmentation by location, price range, or house type to analyze trends in specific sub-markets, like luxury vs. affordable housing. Time-Based Analysis: By studying how house prices vary with the year built or the age of the house, analysts can derive insights into the trends of older vs. newer homes.

5. Limitations and ...

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Context:

My dataset is a valuable collection of real estate information sourced from REALTING.com, an international affiliate sales system known for facilitating safe and convenient property transactions worldwide. REALTING.com has a strong foundation, with its founders boasting approximately 20 years of experience in creating information technologies for the real estate market. This dataset offers insights into various properties across the globe, making it a valuable resource for real estate market analysis, property valuation, and trend prediction.

Content:

The dataset contains information on a diverse range of properties, each represented by a row of data. Here are the key columns and their contents:

• Title: A brief description or name of the property listing.
• Country: The country where the property is located.
• Location: The specific address or location of the property within the country.
• Building Construction Year: The year in which the building was constructed.
• Building Total Floors: The total number of floors or stories in the building.
• Apartment Floor: The floor on which the apartment is situated within the building.
• Apartment Rooms: The total number of rooms in the apartment.
• Apartment Bedrooms: The number of bedrooms in the apartment.
• Apartment Bathrooms: The number of bathrooms in the apartment.
• Apartment Total Area: The total area of the apartment in square meters.
• Apartment Living Area: The living area of the apartment in square meters.
• Price in USD: The price of the property listed in United States Dollars (USD).
• Image: References or links to images associated with the property listing.
• URL: Web links to the full property listing or more detailed information.

This dataset is rich in real estate-related information, making it suitable for various analytical tasks such as market research, property comparison, geographical analysis, and more. The dataset's global scope and diverse property attributes provide a comprehensive view of the international real estate market, offering ample opportunities for data-driven insights and decision-making.

The Mexican residential real estate market, valued at $14.51 billion in 2025, exhibits a promising growth trajectory with a Compound Annual Growth Rate (CAGR) of 4.14% projected from 2025 to 2033. This robust expansion is fueled by several key drivers. A growing middle class with increasing disposable income is a significant factor, alongside government initiatives promoting affordable housing and infrastructure development. Urbanization continues to drive demand, particularly in major metropolitan areas like Mexico City, Guadalajara, and Monterrey. Furthermore, the tourism sector's influence on secondary housing markets in coastal and resort regions contributes significantly to the overall market dynamism. However, challenges exist; fluctuations in the Mexican Peso against the US dollar can affect investment sentiment, and interest rate changes impact mortgage accessibility. Regulatory hurdles and bureaucratic processes related to land ownership and construction permits sometimes impede development. The market is segmented by property type, with apartments and condominiums likely holding the largest share, followed by landed houses and villas, reflecting diverse consumer preferences and housing needs. Competition is intense, with a mix of both large national developers like Grupo Lar and Grupo Sordo Madaleno, alongside smaller regional players vying for market share. The market's future success depends on navigating these challenges effectively while capitalizing on the underlying growth opportunities. The projected market expansion will likely see a more pronounced increase in higher-value segments (landed houses and villas) as rising incomes fuel demand for luxury properties. Geographical variations are expected; while urban centers will experience sustained growth, resort areas might see more volatile fluctuations influenced by tourism trends. The market's resilience will be tested by its ability to adapt to potential economic shifts and effectively address regulatory constraints. Continuous investment in infrastructure and supportive government policies will be pivotal in fostering sustainable and inclusive growth across all market segments within the forecast period. The presence of both large and small players ensures a competitive landscape, promoting innovation and diversification within the industry. Recent developments include: June 2023: Habi, a prominent real estate technology platform, is set to receive a substantial financial boost of USD 15 million from IDB Invest. This funding, spread over four years, aims to fuel Habi's expansion plans in Mexico. While the structured loan has the potential to reach USD 50 million, its primary focus is to cater to Habi's working capital needs. IDB Invest's strategic move is not just about bolstering Habi's growth; it also aims to leverage technology to enhance liquidity and agility in Mexico's secondary real estate markets. By addressing the housing gap in Mexico, this funding initiative is poised to elevate market efficiency, bolster transparency, encourage local contractors for home renovations, and expand Habi's corridor network., June 2023: Celaya Tequila, a premium tequila brand crafted in small batches and co-founded by brothers Matt & Ryan Kalil, is forging a philanthropic alliance with New Story, a non-profit dedicated to eradicating global homelessness. In a groundbreaking move, Celaya Tequila pledges to contribute a percentage of sales from every bottle towards an affordable housing endeavor in Jalisco, Mexico. This endeavor aims to empower underprivileged families in Jalisco by enhancing their access to homes and land ownership.. Key drivers for this market are: 4., Increasing Residential Real Estate Demand by Young People4.; Increase in Average Housing Price in Mexico. Potential restraints include: 4., Increasing Residential Real Estate Demand by Young People4.; Increase in Average Housing Price in Mexico. Notable trends are: Demand for Residential Real Estate Witnessing Notable Surge, Primarily Driven by Young Homebuyers.

Canada Luxury Residential Real Estate Market Report is Segmented by Property Type (Apartments & Condominiums, Villas & Landed Houses), by Business Model (Sales and Rental), by Mode of Sale (Primary (New-Build) and Secondary (Existing-Home Resale)), and by Province (Ontario, British Columbia, and More). The Report Offers Market Size and Forecasts in Value (USD) for all the Above Segments.

According to Cognitive Market Research, the global Residential Real Estate market size was USD 32651.6 million in 2024. It will expand at a compound annual growth rate (CAGR) of 5.50% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 13060.64 million in 2024 and will grow at a compound annual growth rate (CAGR) of 3.7% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 9795.48 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 7509.87 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.5% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 1632.58 million in 2024 and will grow at a compound annual growth rate (CAGR) of 4.9% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 653.03 million in 2024 and will grow at a compound annual growth rate (CAGR) of 5.2% from 2024 to 2031.
The single-family homes category is the fastest growing segment of the Residential Real Estate industry

Market Dynamics of Residential Real Estate Market

Key Drivers for Residential Real Estate Market

Increasing population drives housing demand to Boost Market Growth

Increasing population drives housing demand by creating a need for more residential spaces to accommodate growing numbers of people. As population rises, particularly in urban and suburban areas, demand for housing expands, fueling the residential real estate market. This is especially evident in countries experiencing rapid urbanization, where people move to cities seeking better job opportunities, education, and lifestyle options, further increasing housing needs. Additionally, population growth often correlates with the formation of new households, such as young families or individuals moving out on their own, intensifying the demand for housing units. In response, developers and investors are motivated to build more residential properties, ranging from single-family homes to multifamily units, contributing to market growth and driving real estate values upward. For instance, The Ashwin Sheth Group aims to broaden its residential and commercial offerings in the Mumbai Metropolitan Region (MMR) of India.

Rising incomes and economic stability to Drive Market Growth

Rising incomes and economic stability drive the residential real estate market by boosting consumers’ purchasing power and confidence in long-term investments like homeownership. As incomes increase, people can afford larger down payments, qualify for higher loan amounts, and manage mortgage payments more comfortably, making home buying a more viable option. Economic stability, characterized by low unemployment rates and steady GDP growth, reinforces this confidence, as individuals feel secure in their financial situations. With greater disposable income, many consumers seek to upgrade to larger homes, buy second properties, or invest in luxury real estate, further fueling demand. This economic backdrop attracts both local and foreign investors, leading to more housing developments, increased property values, and a flourishing residential real estate market.

Restraint Factor for the Residential Real Estate Market

High Property Prices will Limit Market Growth

High property prices restrain the residential real estate market by making homeownership unaffordable for a significant portion of the population. As prices rise, potential buyers, particularly first-time homeowners and low- to middle-income families, may find it challenging to secure adequate financing or meet the necessary down payment requirements. This affordability crisis limits the pool of qualified buyers, leading to slower sales and potential stagnation in market growth. Additionally, high property prices can prompt increased demand for rental properties, shifting focus away from home purchases. In markets where prices escalate rapidly, even affluent buyers may hesitate, fearing potential market corrections. Consequently, elevated property values can create a barrier to entry, ultimately restricting the overall health and vibrancy of the residential real estate market.

Impact of Covid-19 on the Residential Real Estate Market

The COVI...

The Latin America Residential Real Estate Market Report is Segmented by Business Model (Sales and Rental), by Property Type (Apartments & Condominiums and Villas & Landed Houses), by Price Band (Affordable, Mid-Market and Luxury), by Mode of Sale (Primary New-Build, and More), and by Country (Brazil, Mexico, Colombia, Argentina, Chile, and the Rest of Latin America). The Market Forecasts are Provided in Terms of Value (USD).

This statistic shows the most costly housing markets in the United States in the first quarter of 2018, by income spent on mortgage. The average mortgage payment in San Diego, California amounted to **** percent of the average income in that period.

Prices & Characteristics of Spanish Homes

Uncovering Market Trends in Spain

By [source]

About this dataset

This dataset provides a wealth of information about the current Spanish housing market for potential buyers. This comprehensive data set includes research-level information about region, number of rooms, size, price, photos and more for different available properties across the country. This data can help researchers understand the wide pricing range and characteristics associated with these homes in great detail. For example, it allows us to uncover average price per square meter as well as differences in prices between larger and smaller locations. Further exploration also reveals correlations between price and surface area as well as number of rooms and pricing models - all immensely helpful to those wishing to purchase or rent properties in Spain! By further investigating this rich set of information provided by this dataset, prospective property buyers can be more informed when making decisions regarding their next home or investment opportunities within the Spanish housing market

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For more datasets, click here.

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How to use the dataset

Welcome to the Prices and Characteristics of Spanish Houses for Sale dataset! This data set contains comprehensive information about Spanish houses for sale, including location, price, size, and number of rooms. Here’s a guide to help you get started.

• Explore the columns included in this dataset: the summary column provides an overview of the property while description provides more in-depth details. The location column offers geographical details about each house; photo displays a picture of each property; recomendado indicates whether or not it has been recommended; price gives you an idea of how much each house costs; size determines how large or small it is; rooms tells you how many bedrooms it has to offer; price/m2 states the Square Meter Price for each home; bathrooms lets you know how many bathrooms it has on the premises; Num Photos shows you the exact number of images available for that home and type directs which type it is (apartment); region helps pinpoint exactly where these homes are located.

• Analyze relationships between variables: use this dataset to uncover interesting correlations between pricing and other characteristics such as size and number of rooms, or between prices in different regions within Spain. You can also gain insight into average pricing by square meter across various locations - this data might be useful if you're looking at making a real estate investment decision based on market trends around Spain's housing sector!

• Research current market trends: review historical data points from within this dataset with regards to pricing changes over time, as well as differences in supply/demand dynamics across distinct locations within Spain's housing market - all these insights can be used when deciding whether or not now would be an ideal time to purchase property in certain areas!
  Overall, we hope that with this information at hand your research into Spain's current housing market will provide useful results and lend insight that may assist your purchase decision process when considering buying S[anish homes!

Research Ideas

• Comparing the average Spanish house price in different regions to determine if prices are more expensive in certain regions.
• Examining the correlation between size and number of rooms to understand which properties would be a better investment given their size.
• Analyzing the relationship between number of photos uploaded for a property and its price, to determine if there is any correlation between them or not

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: pisos.csv | Column name | Description | |:----------------|:------------------------------------------------------------| | summary | A brief description of the property. (Text) | | location | The geographical area or postcode of the property. (Text) | | photo...

The South Korean luxury real estate market, valued at $43.56 billion in 2025, is poised for robust growth, projected to achieve a Compound Annual Growth Rate (CAGR) of 10% from 2025 to 2033. This expansion is driven by several key factors. Firstly, a rising high-net-worth individual (HNWI) population in South Korea, fueled by economic growth and a thriving tech sector, is increasing demand for premium properties. Secondly, the increasing preference for larger, more luxurious homes, particularly in prime locations like Seoul and Busan, is a significant driver. Finally, government policies aimed at stimulating the economy, though potentially impacting affordability in some segments, indirectly support the luxury market by bolstering overall economic confidence. The market is segmented by property type (apartments & condominiums, villas & landed houses) and city (Seoul, Busan, other cities), with Seoul and Busan consistently commanding the highest prices due to their central location and established infrastructure. Major players like Samsung C&T Corporation, Bando Engineering & Construction, and Ssangyong Engineering & Construction are shaping the market through high-end development projects. While the market shows strong potential, challenges like fluctuating interest rates and potential government regulations aimed at controlling property prices could pose some restraints to growth in the coming years. However, the long-term outlook for the South Korean luxury real estate market remains positive due to the continued growth of the affluent population and sustained demand for upscale properties. The international influence on South Korea's luxury real estate market is noticeable, but currently secondary to domestic demand. While data on specific regional contributions isn't provided, it's reasonable to assume that Asia-Pacific regions, particularly those with strong economic ties to South Korea, contribute significantly to foreign investment in luxury properties. North American and European investors also likely play a role, though potentially to a lesser degree compared to other Asian markets. The presence of established global developers also highlights the international appeal of the market. Further research would be needed to quantify the precise influence of each region, but the trend towards globalization points to a gradual increase in international investment over the forecast period. Future analysis may consider factors like exchange rate fluctuations and global economic conditions, as they impact foreign investors' participation. Unlocking the Potential: A Deep Dive into South Korea's Luxury Real Estate Market (2019-2033) This comprehensive report provides an in-depth analysis of South Korea's burgeoning luxury real estate market, covering the period from 2019 to 2033. With a base year of 2025 and an estimated year of 2025, the report offers valuable insights for investors, developers, and industry professionals seeking to navigate this dynamic sector. High-search-volume keywords such as South Korea luxury apartments, Seoul luxury real estate, Busan luxury villas, and Korean luxury property investment are strategically integrated throughout the report to maximize search engine optimization (SEO). Key drivers for this market are: 4., South Korea's status as a global business hub can attract expatriates and foreign executives seeking high-end accommodation options4.; Incorporating advanced technology and smart home features making luxury properties more appealing to tech-savvy buyers. Potential restraints include: 4., Lack of foreign investment4.; Stricter government regulation inhibiting the growth. Notable trends are: Reduction in prices creating demand for low-priced luxury real estate.

Explore the Redfin Canada Properties Dataset, available in CSV format and extracted in April 2022. This comprehensive dataset offers detailed insights into the Canadian real estate market, including property listings, prices, square footage, number of bedrooms and bathrooms, and more. Covering various cities and provinces, it’s ideal for market analysis, investment research, and financial modeling.

Key Features:

• Property Details: Includes crucial data such as listing price, property type, square footage, number of bedrooms and bathrooms, and more.
• Geo-Location Data: Provides geographical coordinates, allowing for spatial analysis and mapping.
• Market Trends: Offers historical data to analyze price trends and market fluctuations.

Who Can Use This Dataset:

• Real Estate Professionals: Evaluate market trends and property values to better advise clients or guide investment decisions.
• Investors: Analyze the Canadian housing market to identify investment opportunities and potential returns.
• Data Analysts and Researchers: Use this dataset to study market dynamics, urban development, or economic factors influencing the real estate sector.
• Financial Analysts: Incorporate the data into financial models to forecast market behavior and investment outcomes.

Download the Redfin Canada Properties Dataset to access valuable information on the Canadian housing market, perfect for anyone involved in real estate, finance, or data analysis.

Discover the booming South Korean luxury real estate market! This in-depth analysis reveals a $43.56B market with a 10% CAGR, driven by HNWIs and prime Seoul locations. Explore key trends, challenges, and top companies shaping this lucrative sector. Recent developments include: August 2023: A new development project calls for turning the Songdo International City R2 Block of the Incheon Free Economic Zone (IFEZ) into a "K-Contents City," according to local sources. As a shareholder in this development project, HYBE will see the construction of multiple expansive residential complexes throughout the city., September 2023: South Korea's real estate landscape as it comes to light that a mere 30 individuals have managed to acquire a staggering 8,000 homes in the country over the past five and a half years. These eyebrow-raising acquisitions, totaling nearly INR 7,446 crore (USD 0.89 billion), have raised concerns and questions about the state of the housing market and the potential implications for average citizens.. Key drivers for this market are: 4., South Korea's status as a global business hub can attract expatriates and foreign executives seeking high-end accommodation options4.2.1.2 Incorporating advanced technology and smart home features making luxury properties more appealing to tech-savvy buyers. Potential restraints include: 4., South Korea's status as a global business hub can attract expatriates and foreign executives seeking high-end accommodation options4.2.1.2 Incorporating advanced technology and smart home features making luxury properties more appealing to tech-savvy buyers. Notable trends are: Reduction in prices creating demand for low-priced luxury real estate.

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.

The Canadian housing market, particularly in major urban centers, has experienced a prolonged period of rapid price appreciation, driven by factors such as low interest rates, strong population growth, and limited supply. According to the Canada Mortgage and Housing Corporation (CMHC), the national average house price rose by more than 50% between 2020 and 2022, with prices in some major cities, such as Toronto and Vancouver, increasing by even more. This rapid price growth has made it increasingly difficult for many Canadians to afford a home, especially in the country's most desirable markets. However, the Canadian housing market is starting to show signs of cooling in 2023, as rising interest rates and stricter mortgage lending rules from the government begin to take effect. The CMHC predicts that the national average house price will decline by 7.6% in 2023, with prices in some markets, such as Toronto and Vancouver, expected to fall by even more. This cooling is expected to continue in 2024, with the CMHC predicting a further decline in the national average house price of 3.2%. The long-term outlook for the Canadian housing market is more uncertain, but the CMHC expects that prices will continue to rise, albeit at a more moderate pace. The Canadian housing market is one of the most expensive in the world, with prices in major cities like Toronto and Vancouver soaring to record highs in recent years. This has led to a growing concern about affordability, as many Canadians are being priced out of the market. Key drivers for this market are: Increasing Adoption of Remote and Hybrid Work Model. Potential restraints include: Lack of Privacy. Notable trends are: Pandemic Accelerated Luxury Home Sales in Major Canadian Markets.

The data was extracted from Zillow.. Zillow is a prominent online real estate marketplace and has data on around 100 million homes The goal is to create a rich and diverse dataset that encompasses a wide range of housing characteristics across different states, cities, and neighborhoods in the United States.This dataset provides valuable insights into real estate trends and property features. Each record represents a unique house listing and includes details such as location, property specifications, market estimates, and more. A total of 3 files are included, more about them in the file description.

Feature Description:

1. State: The state in which the property is located (AL:Alabama) . Includes all US states except Hawaii.
2. City: The city where the property is situated.
3. Street: The street address of the property.
4. Zipcode: The postal code associated with the property.
5. Bedroom: The number of bedrooms in the house.
6. Bathroom: The number of bathrooms in the house.
7. Area(sqft): The total area of the house.
8. PPSq(Price Per Square Foot): The cost per square foot of the property.
9. LotArea(acres): The total land area associated with the property.
10. MarketEstimate(Dollars $): Estimated market value of the property. This value is estimated using Zillow's own algorithm.
11. RentEstimate:(Dollars $) Estimated rental value of the property. This value is estimated using Zillow's own algorithm.
12. Latitude: The latitude coordinates of the property.
13. Longitude: The longitude coordinates of the property.
14. ListedPrice:(Dollars $) The listed price of the property.

Potential Use Cases:

• Real Estate Market Analysis: Explore trends in housing prices, market estimates, and rental values across different states and cities.
• Predictive Modeling: Build predictive models to estimate property prices or rental values based on various features.
• Feature Engineering: Create new features or derive insights to enhance machine learning models.

The Denmark luxury residential real estate market exhibits robust growth potential, projected to expand significantly over the forecast period (2025-2033). A compound annual growth rate (CAGR) exceeding 5% indicates a consistently increasing market value, driven by several key factors. Strong economic performance in Denmark, coupled with a limited supply of high-end properties, particularly in prime locations like Copenhagen, Aarhus, and Odense, fuels heightened demand. Increasing high-net-worth individuals (HNWIs) seeking prestigious residences contribute to this upward trend. Furthermore, Denmark's attractive lifestyle, strong social infrastructure, and political stability further enhance the market's appeal to both domestic and international buyers. While rising construction costs and potential regulatory changes pose some challenges, the overall market outlook remains positive. The segment breakdown reveals a preference for villas and landed houses, with Copenhagen commanding the largest market share due to its concentration of affluent residents and business opportunities. Leading developers such as NRE Group, Rodgaard Ejendomme, and others play a crucial role in shaping the market's dynamics. The market's historical performance (2019-2024) likely showcased a similar growth trajectory, setting a strong foundation for future expansion. The continued growth in the Danish luxury residential market is anticipated to be fueled by ongoing investment in infrastructure, particularly in sustainable and smart home technologies within new developments. The increasing popularity of eco-friendly and energy-efficient luxury homes will likely further drive demand. While the "Rest of Denmark" segment will show growth, it will likely lag behind the major cities due to differences in population density and economic activity. Analyzing the performance of individual developers and their project pipelines will offer more granular insights into future market trends. Future research should focus on assessing the impact of potential economic fluctuations and interest rate changes on the market's growth trajectory. The competitive landscape, with established players alongside emerging developers, warrants close observation to understand market share dynamics and strategic partnerships. This comprehensive report provides an in-depth analysis of the Denmark luxury residential real estate market, covering the period from 2019 to 2033. With a focus on high-value properties in key cities like Copenhagen, Aarhus, Odense, and Aalborg, this report offers invaluable insights for investors, developers, and industry professionals seeking to navigate this dynamic market. The study period spans from 2019-2033, with 2025 serving as the base and estimated year, and a forecast period from 2025-2033. Historical data from 2019-2024 provides a robust foundation for future projections. Key Search Terms: Denmark luxury real estate, Copenhagen luxury apartments, Aarhus luxury villas, Danish real estate market, luxury property investment Denmark, residential real estate Denmark, Danish luxury homes, high-end real estate Denmark. Recent developments include: November 2022: The AkademikerPension expands real estate allocation. Whereas the portfolio currently consists primarily of offices in Copenhagen, the distribution in 2026 should be 50% residential, 30% offices, and various construction projects. Most investments will be made in Copenhagen and Aarhus, but approximately 25% of the real estate investments will be made in smaller Danish cities., June 2022: Orange Capital Partners, a European real estate investment firm, has purchased a portfolio of seven residential blocks in Denmark from NREP for an undisclosed sum. NREP stated that its Nordic Strategies Fund II held the 110,000 sqm residential portfolio. The portfolio comprises 1,220 modern rental apartments spread across seven residential buildings in Copenhagen and Aarhus. Teglgrdshusene, Green Square Garden, Nordhuset, Restad Have, Resource Rows, Risskov Brynet, and Lisbjerg are among the properties.. Key drivers for this market are: 4., Increasing manufacturing sites4.; The increasing middle-income group and access to mortgage finance. Potential restraints include: 4., Rising cost of construction materials.. Notable trends are: Increasing demand for luxury residences driving the market.

Context

The dataset consist listings from popular real estate portals of Madrid.

LOCATION Madrid is one of the most visited cities in Europe both by tourists and businesspeople, and it’s where many important local and multinational companies have their headquarters. Therefore Madrid enjoys both a large influx of tourists as well as people seeking to live and work in the city to give their professional careers a boost.

ATTRACTIVE PRICES The real estate market has been in a growth phase for a few years now, which means that you can still find properties at very attractive prices (especially compared to other European capitals) but with still good chances of their value appreciating in the future.

HOUSE TYPES Individual homes are not common in the city center but do exist in the suburbs. Madrid also has a mix of new construction and existing apartments. Real estate prices in capital cities are generally the most expensive in a country, but it's not the case in Spain. The cost of property in Madrid is well below that of Barcelona and coastal areas.

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