D.R. Horton was the homebuilder with the highest gross revenue in the United States in 2024. The Texas-based company reached a homebuilding revenue of 33.83 billion U.S. dollars. It was closely followed by D.R. Horton, which had its headquarters in Florida and generated a revenue of 33.78 billion U.S. dollars. Challenges to the residential construction marketThe number of private housing units started fell around the time of the global financial crisis (2007-2009), but has since recovered – though not to the heights of 2006. The value of residential construction in the U.S. fell in 2023, but it is expected to start growing again in the next years.New home sales follow the same trend After a fall in the number of new houses sold in 2021 and 2022, home sales have increased again, with those figures in the U.S. expected to reach 683,000 in 2024. The number of single-family homes started has followed a similar trend, and it is expected to increase in the next couple of years.

Hand Crafted Log Homes Market size was valued at USD 3.14 Billion in 2023 and is projected to reach USD 4.14 Billion by 2030, growing at a CAGR of 4.2% during the forecast period 2024-2030.Global Hand Crafted Log Homes Market DriversThe market for hand-crafted log homes is fueled by a number of reasons that increase demand for these distinctive and customized residential buildings. Potential market drivers for hand-crafted log homes include the following:Need for Specialized and Tailored Houses: Handcrafted log homes have a distinct charm and beauty that appeals to consumers looking for unique and personalized living spaces.Relationship between Rustic Living and Nature: Because log homes offer a strong connection to nature and the outdoors, they are in high demand due to the growing interest in a rustic and natural lifestyle.Sustainable and Eco-Friendly Construction Techniques: Since log homes are made of wood, which is a renewable resource, and they are built with sustainable building techniques, they are popular among eco-aware homeowners.Efficiency in Energy Use and Natural Insulation: Log homes are a popular choice for individuals seeking energy-efficient housing options because of its natural insulating qualities, which improve energy efficiency and lessen dependency on artificial heating and cooling systems.Durability and Extended Life: Reputably strong and long-lasting, well-maintained log homes can last for many generations. One of the main factors influencing buyers who want to make a long-term investment in their homes is durability.Growing Market for Luxury and Affluent Homes: Rich purchasers who are looking for distinctive and opulent living spaces are part of the market for luxury homes, which includes high-end custom homes. This drives up demand for hand-crafted log homes.The allure of customary craftsmanship: Those who value traditional building techniques and the artistry of experienced artisans will find great satisfaction in the craftsmanship involved in creating handcrafted log homes.Demand for Second Homes and Vacations: Popular options for vacation and second homes are log cabins, particularly in picturesque and recreational locations where buyers are looking for a cozy and rustic haven.Historical and Cultural Connections: Buyers seeking homes with a sense of history and heritage are drawn to log homes due to their cultural and historical relevance, which is rooted in pioneer traditions in North America.Trends in Architecture and Design: Log homes are in line with current trends in architecture and design, which highlight open floor plans, natural materials, and a smooth transition from the built environment to the surrounding one.Packages for Log Homes Are Available: Businesses that sell pre-cut logs and building materials as part of their log home packages streamline the construction process and increase the accessibility of log homes for a wider spectrum of customers.Encouragement of Lifestyles in Log Homes: Log home builders and enthusiasts market and promote their lifestyles, showcasing the benefits of log homes and persuading prospective customers to select this type of living.

The most expensive phases of building a single-family home in the United States during 2022 were framing and interior finishing. Meanwhile, major system rough-ins such as plumbing, electrical lines, and HVAC were the third phase with the highest construction costs. The weight of interior finishes within the overall construction costs has declined every year since 2015. The total cost of building a house in the U.S. increased significantly in the past years.

In the first quarter of 2025, San Francisco, Chicago, New York, and Honolulu were some of the U.S. cities with the highest housing construction costs. Meanwhile, Phoenix had one of the lowest construction costs for high-end multifamily homes at *** U.S. dollars per square foot and Las Vegas for single-family homes between *** and *** U.S. dollars per square foot. Construction cost disparities As seen here, the construction cost for a high-end multi-family home in San Francisco in the first quarter of 2024 was over ***** more expensive than in Phoenix. Meanwhile, there were also great differences in the cost of building a single-family house in New York and in Portland or Seattle. Some factors that may cause these disparities are the construction materials, installation, and composite costs, differing land values, wages, etc. For example, although the price of construction materials in the U.S. was rising at a slower level than in 2022 and 2023, several materials that are essential in most construction projects had growth rates of over **** percent in 2024. Growing industry revenue Despite the economic uncertainty and other challenges, the size of the private construction market in the U.S. rose during the past years. It is important to consider that supply and demand for housing influences the revenue of this segment of the construction market. On the supply side, single-family home construction fell in 2023, but it is expected to rise in 2024 and 2025. On the demand side, some of the U.S. metropolitan areas with the highest sale prices of single-family homes were located in California, with San Jose-Sunnyvale-Santa Clara at the top of the ranking.

In the United States, the projected number of single-family housing unit starts in 2026 is estimated to increase. After a peak in 2021, the number of home construction starts decreased two years in a row. However, those figures are expected to pick back up in the next years. Single-family homes are the preferred option for Americans Single-family homes were the most common type of home purchased in 2023 in the United States, making up roughly ** percent of all purchases, showing that demand for single-family units remains strong. That explains why there is usually a far higher number of single-family homes than of other type of homes being built any given year. There were roughly *** multifamily homes whose construction started in 2024. Single family housing units in the United States The median size of a single family housing unit in the United States based on square footage has remained relatively consistent over the past two decades. The cost of housing varies around the United States. In 2023, the most expensive median price of an existing single-family home was on the West coast. However, it was in the Northeast where the median price of a new single-family home was the most expensive.

Residential foundation selection is critical for the lifetime performance of the project, but the type of foundation selected can depend on cost. This study aims to compare the new construction costs of residential slab-on-fill and four types of crawl space foundations for residential projects by quantifying the material quantities for each and exploring the effect of building characteristics on material quantities and total costs. The building characteristics selected are size (139 m2, 186 m2, and 232 m2), footprint aspect ratio (1:1, 1:2.5, and 1:5) and first floor elevation (0 m–1.2 m in 0.3 m increments). We find that material quantities and total costs change not only with building size and elevation, but also with footprint aspect ratio. Applying 2022 RSMeans Building Construction Cost data, the results show that for any building size, aspect ratio, or elevation, raised wood flooring on pier foundations ($118–$180 per m2) and slab on fill ($103–$211 per m2) are the least expensive, while crawl space foundations with stemwalls are the most expensive ($147–$280 per m2). The results of this study can be used by residential builders, developers and designers in evaluating foundation costs and design alternatives. The methodology may also be adapted for use in other applications such as flood mitigation or energy efficiency projects or environmental sustainability assessments.

The North America Luxury Residential Real Estate Market is poised for substantial growth, projected to reach an estimated market size of USD 350,000 million by 2025, with a Compound Annual Growth Rate (CAGR) exceeding 2.50% throughout the forecast period of 2025-2033. This robust expansion is fueled by a confluence of factors, including an increasing number of high-net-worth individuals (HNWIs) actively seeking premium living spaces, a sustained demand for larger, more amenity-rich properties, and a growing preference for bespoke architectural designs and exclusive community living. The market's dynamism is further propelled by evolving lifestyle aspirations, where luxury is increasingly defined by convenience, security, smart home technology integration, and access to unparalleled recreational facilities. Key drivers include the continued economic stability in major North American economies, the influx of foreign investment into prime real estate markets, and a generational shift where younger affluent buyers are increasingly influencing market trends with their emphasis on sustainability and modern amenities. Segmentation of the market reveals significant opportunities across both property types and geographies. Within property types, Villas and Landed Houses are expected to lead the market, driven by a desire for space, privacy, and customizable living environments. Apartments and Condominiums, however, will also witness considerable traction, particularly in urban centers, appealing to those seeking sophisticated, low-maintenance lifestyles with access to a vibrant city life. Geographically, the United States is anticipated to dominate the market, owing to its sheer economic scale and concentration of wealth, followed by Canada and Mexico, each presenting unique growth opportunities influenced by local economic conditions and real estate development. Major players like PulteGroup, Lennar Corporation, and D.R. Horton are actively shaping the market landscape, with strategic investments in developing high-end communities and embracing innovative construction techniques to cater to the discerning tastes of affluent buyers. Key drivers for this market are: Increase in GDP contribution from Construction Industry, Increase in Number of Building Permits. Potential restraints include: High Initial Investments. Notable trends are: Emergence of the Millennial Generation in USA.

South Carolina Real Estate Dataset 2025

Dataset Overview

This comprehensive real estate dataset contains over 5,000 property listings from South Carolina, collected in 2025 from Realtor.com using apify api. The dataset captures diverse property types including single-family homes, condominiums, land parcels, townhomes, and other residential properties. This dataset provides a rich snapshot of South Carolina's real estate market suitable for predictive modeling, market analysis, and investment research.

Data Science Applications

• Price Prediction Models: Build regression models (Random Forest, XGBoost, Neural Networks) to predict property values based on size, location, bedrooms, and age
• Property Type Classification: Develop multi-class classifiers to categorize properties based on physical characteristics
• Market Segmentation: Apply clustering algorithms (K-means, DBSCAN) to identify distinct property segments and price brackets
• Time Series Analysis: Analyze construction trends and property age distributions to forecast future development patterns
• Investment Opportunity Detection: Create anomaly detection models to identify undervalued properties or outliers
• Feature Engineering: Generate derived features like price per square foot, bathroom-to-bedroom ratios for enhanced model performance

Column Descriptors

• type: Primary property category (single_family, condos, land, townhomes, multi_family, farm)
• sub_type: Detailed property classification (condo, townhouse, co_op)
• sqft: Property size in square feet
• baths: Number of bathrooms (decimal values indicate half baths)
• beds: Number of bedrooms
• stories: Number of floors/stories in the property
• year_built: Construction year of the property
• listPrice: Property listing price in USD

Ethically Obtained Data

This dataset was ethically scraped from publicly available listings on Realtor.com and is provided strictly for educational and learning purposes only. The data collection complied with ethical web scraping practices and contains only publicly accessible information. Users should utilize this dataset exclusively for academic research, educational projects, and learning data science techniques. Any commercial use is strictly prohibited.

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 ...

The European style cable junction box market is experiencing robust growth, driven by increasing demand for aesthetically pleasing and high-quality electrical installations in residential and commercial buildings across Europe and beyond. The market is characterized by a preference for sleek designs that seamlessly integrate with modern architectural styles. This trend is further fueled by stringent building codes and regulations emphasizing safety and efficient electrical wiring solutions. Key growth drivers include the rising construction activity in both new and renovation projects, particularly in regions with a strong emphasis on sustainable building practices. Furthermore, technological advancements, such as the integration of smart home technologies within junction boxes, are expanding market applications and driving demand for sophisticated, feature-rich products. Competitive intensity is moderate, with a mix of established international players and regional manufacturers vying for market share. Pricing strategies are influenced by material costs, manufacturing complexities, and brand recognition. The market is segmented by material type (plastic, metal), application (residential, commercial, industrial), and size, with plastic boxes currently holding the largest market segment due to their cost-effectiveness and versatility. Future growth is projected to be influenced by factors including economic conditions, material price fluctuations, and evolving consumer preferences. Looking ahead to 2033, the market is expected to witness continued expansion, albeit at a potentially moderating CAGR compared to the initial high-growth phase. This moderation may be attributable to market saturation in certain regions and potential economic headwinds. However, emerging trends, such as the incorporation of IoT capabilities into junction boxes and the increasing focus on energy-efficient designs, are anticipated to offset these challenges and sustain long-term market growth. The competitive landscape will likely remain dynamic, with ongoing innovation in product design, functionality, and materials driving the need for manufacturers to continuously adapt and differentiate their offerings. Successful players will prioritize sustainable practices, quality assurance, and robust supply chain management to remain competitive in this evolving market.

Music Studio Construction Services Market Outlook

According to our latest research, the global music studio construction services market size reached USD 1.47 billion in 2024, reflecting robust demand from both emerging and established markets. The industry is poised to expand at a CAGR of 6.8% from 2025 to 2033, with a forecasted value of USD 2.85 billion by 2033. This growth trajectory is underpinned by rising investments in the music and entertainment sectors, increasing adoption of advanced acoustic technologies, and a surge in home-based and professional studio setups worldwide.

One of the primary growth factors driving the music studio construction services market is the exponential increase in content creation, fueled by the proliferation of digital music streaming platforms and social media channels. As independent artists, podcasters, and music producers seek to differentiate their sound quality, the demand for professionally designed and acoustically treated studios has intensified. Additionally, the democratization of music production tools has enabled a broader spectrum of creators to invest in high-quality studio environments, further expanding the market’s customer base. The integration of cutting-edge acoustic materials and soundproofing solutions has become a pivotal selling point, as clients prioritize optimal sound isolation and clarity for both recording and mixing purposes.

Technological advancements have also played a crucial role in shaping the music studio construction services market. The adoption of smart building technologies, such as automated climate control, advanced noise cancellation systems, and digital monitoring, has elevated client expectations for studio functionality and energy efficiency. Furthermore, the shift toward hybrid and remote music production models has led to a rise in demand for modular and adaptable studio spaces that can support various recording, mixing, and broadcasting activities. Companies specializing in studio construction are leveraging these trends by offering bespoke services that cater to diverse client needs, from small-scale home studios to large commercial facilities.

Another significant growth driver is the increasing focus on sustainability and eco-friendly construction practices. As environmental regulations become more stringent and clients grow more conscious of their ecological footprint, there is a heightened demand for green building materials, energy-efficient lighting, and sustainable acoustic treatments. Studio construction service providers are responding by incorporating recycled and low-emission materials, as well as implementing waste reduction strategies during the build process. This shift not only meets regulatory requirements but also enhances brand reputation and attracts environmentally conscious clients, further propelling market expansion.

From a regional perspective, North America continues to dominate the music studio construction services market, accounting for the largest share in 2024. The region’s leadership is attributed to a vibrant music industry, high levels of disposable income, and a strong presence of both independent and major recording labels. Europe follows closely, driven by a rich cultural heritage in music and ongoing investments in creative infrastructure. Meanwhile, the Asia Pacific region is rapidly emerging as a lucrative market, buoyed by a growing middle class, increasing government support for the arts, and the rising popularity of local music genres. Latin America and the Middle East & Africa are also witnessing steady growth, albeit from a smaller base, as local talent and entertainment industries continue to flourish.

Service Type Analysis

The music studio construction services market is segmented by service type, encompassing design & consultation, acoustic treatment, soundproofing, equipment installation, renovation & remodeling, and other specialized services. Design & consultation services form the foundation of any studi

This dataset provides a rich, time-series view of how key macroeconomic indicators have shaped the U.S. housing market over the last 20 years. It is built around the S&P Case-Shiller U.S. National Home Price Index (CSUSHPISA) — a widely trusted benchmark for tracking national home price trends — and enhanced with a curated selection of economic factors sourced from the Federal Reserve Economic Database (FRED).

What's Inside? The dataset spans January 2004 to June 2024 (monthly frequency), and includes the following: Feature Description

Home_Price_Index Case-Shiller Home Price Index (target)
Interest_Rate Federal Funds Rate
Mortgage_Rate 30-Year Fixed Mortgage Average
Unemployment_Rate National unemployment rate
Median_Income Median personal income (annual, forward-filled monthly) Inflation_CPI Consumer Price Index
Building_Permits Housing construction permit approvals
Housing_Starts New housing construction starts
US_Population Monthly estimated population
Consumer_Sentiment University of Michigan Consumer Sentiment Index

In addition to these core features, we’ve added: --Lag features (1-month, 3-month) to capture trend memory --Rolling averages to smooth volatility --Ratios like income-to-mortgage and permit-to-population --Percentage change columns to measure economic shifts over time These transformations make the dataset ideal for predictive modeling, exploratory data analysis, and economic storytelling.

Source --All raw data was retrieved via FRED (Federal Reserve Economic Data), ensuring official, up-to-date, and well-maintained inputs.

Use Cases --Time series forecasting (e.g., Ridge, ARIMA, XGBoost) --Macroeconomic trend analysis --Housing market dashboards --Educational projects on feature engineering --Model interpretability experiments

Frequency --All data is aggregated/resampled to monthly granularity for consistency.

License CC BY 4.0 — free to use with attribution

Home Design Software Market Outlook

According to our latest research, the global Home Design Software market size reached USD 3.8 billion in 2024, reflecting a robust expansion driven by the increasing adoption of digital tools in architecture and interior design. The market is projected to grow at a CAGR of 7.6% from 2025 to 2033, reaching an estimated value of USD 7.4 billion by 2033. This growth trajectory is primarily propelled by rising demand for efficient home planning solutions, advancements in 3D visualization technologies, and the growing trend of home customization. As per our latest research, the market is witnessing significant transformation, with both professionals and consumers seeking intuitive, feature-rich platforms to streamline the design process and enhance project outcomes.

One of the foremost growth factors for the Home Design Software market is the increasing integration of advanced technologies such as artificial intelligence (AI), virtual reality (VR), and augmented reality (AR) within design platforms. These technologies have revolutionized the way users conceptualize and visualize spaces, offering immersive experiences that significantly reduce errors and improve design accuracy. The ability to conduct virtual walkthroughs, automate measurements, and generate detailed renderings has not only enhanced the efficiency of professional architects and designers but also empowered homeowners to participate actively in the design process. This democratization of design, enabled by user-friendly interfaces and cloud-based collaboration tools, is fueling widespread adoption across both developed and emerging markets.

Another critical driver is the surge in residential and commercial construction activities worldwide, particularly in urbanizing regions. As cities expand and populations grow, there is a heightened need for innovative, scalable, and sustainable architectural solutions. Home design software platforms are increasingly being leveraged to optimize space planning, comply with regulatory standards, and ensure energy efficiency in new constructions and renovations. Furthermore, the rise of remote work and changing lifestyle preferences post-pandemic have led to a spike in home improvement projects, with consumers seeking to redesign interiors for multifunctional use. The convenience and cost-effectiveness offered by digital design tools are thus becoming indispensable for homeowners, remodelers, and builders alike.

The proliferation of cloud-based deployment models is also a pivotal factor contributing to the growth of the Home Design Software market. Cloud-based solutions offer unparalleled accessibility, scalability, and collaboration capabilities, enabling stakeholders to work seamlessly from different locations and devices. This has proven particularly advantageous for design firms managing multiple projects or distributed teams, as well as for clients who wish to be involved in real-time decision-making. The shift towards subscription-based pricing and software-as-a-service (SaaS) models is further enhancing market penetration, as it lowers upfront costs and ensures continuous updates and technical support. As a result, both small and large enterprises are increasingly investing in cloud-based home design platforms to stay competitive and agile in a rapidly evolving industry landscape.

From a regional perspective, North America continues to dominate the Home Design Software market, accounting for the largest share in 2024, followed closely by Europe and Asia Pacific. The high concentration of tech-savvy consumers, established real estate and construction sectors, and strong presence of leading software vendors are key contributors to North America's market leadership. Meanwhile, Asia Pacific is emerging as the fastest-growing region, driven by rapid urbanization, rising disposable incomes, and government initiatives promoting smart cities and digital infrastructure. Latin America, the Middle East, and Africa are also witnessing steady growth, albeit from a smaller base, as increasing internet penetration and digital literacy unlock new opportunities for market expansion. Regional dynamics are expected to continue evolving, with local customization and strategic partnerships playing a crucial role in shaping future growth trajectories.

Colonial/Traditional-style homes make up approximately half of all single-family home listings in the U.S. as of May 2025.

This statistic shows the most expensive residential real estate sales worldwide as of April 2019. The most expensive residential property sold globally was Ho Tung Gardens on the Peak, Hong Kong, which was sold for 657.9 million U.S. dollars. The three-acre property was sold without the main building, which was demolished in 2013.

This Dataset is a rich collection of real estate listings sourced from the popular real estate website, Bina.az. This dataset comprises 39,300 rows and includes 10 columns, each containing essential information about properties available for sale various locations. This valuable dataset serves as a foundational resource for comprehensive real estate market analysis, property valuation, and housing market research.

Dataset Details:

Number of Rows: 39,300 Number of Columns: 10 Column Names and Descriptions:

1.Price: This column indicates the listed price of the property, offering insights into market trends and pricing variations.

2.Location: The "Location" column specifies the geographical details of the property, including the city, district, nearest metro stations. Location is a critical factor for real estate decision-making.

3.Rooms: This column represents the number of rooms in the property. Knowing the room count is crucial for prospective buyers or renters to assess the property's suitability for their needs.

4.Square: The "Square" column contains information about the total area of the property in square meters. Property size is an essential factor for assessing space and value.

5.Floor: This column indicates the floor on which the property is situated. For those interested in apartments, the floor number can be a critical factor.

6.New Building: The "New Building" column contains binary values (e.g., 0 or 1) to indicate whether the property is in a newly constructed building. This information is valuable for those seeking modern or recently built properties.

7.Has Repair: This column contains binary values to indicate whether the property has undergone any repairs or renovations. Repair status can influence a buyer's decision.

8.Has Bill of Sale: This column contain binary values to indicate whether a legal bill of sale exists for the property, ensuring the legitimacy of the transaction.

9.Has Mortgage: The "Has Mortgage" column contains binary values to indicate whether the property has an existing mortgage.

This dataset is a powerful tool for a wide range of applications, including:

Market Analysis: Real estate professionals and analysts can leverage this dataset to conduct market research, assess pricing dynamics, and understand property preferences.

Property Valuation: Property appraisers and valuation experts can use this data to estimate property values based on attributes like location, size, and condition.

Housing Market Research: Academics, policymakers, and researchers can explore this dataset to gain insights into housing market trends, affordability, and the prevalence of mortgages and repairs.

Homebuyers and Renters: Individuals seeking properties can filter and search through the dataset to identify suitable homes based on their specific criteria, such as price, location, room count, and more.

The Bina.az Real Estate Dataset empowers data-driven decision-making within the real estate sector and serves as a valuable resource for anyone interested in the real estate market.

If you want to see scraping code follow this link: https://github.com/AzadShahvaladov/Bina.azDataScraping

In the presented European countries, the homeownership rate extended from 42.6 percent in Switzerland to as much as 95.9 percent in Albania. Countries with more mature rental markets, such as France, Germany, the UK, and Switzerland, tended to have a lower homeownership rate compared to the frontier countries, such as Lithuania or Slovakia. The share of house owners among the population of all 20 euro area countries stood at 64.5 percent in 2024. Average cost of housing Countries with lower homeownership rates tend to have higher house prices. In 2024, the average transaction price for a house was notably higher in Western and Northern Europe than in Eastern and Southern Europe. In Austria, one of the most expensive European countries to buy a new dwelling in, the average price was three times higher than in Greece. Looking at house price growth, however, the most expensive markets recorded slower house price growth compared to the mid-priced markets. Housing supply With population numbers rising across Europe, the need for affordable housing continues. In 2024, European countries completed between one and six housing units per 1,000 citizens, with Ireland, Poland, and Denmark responsible for heading the ranking. One of the major challenges for supplying the market with more affordable homes is the rising construction costs. In 2021 and 2022, housing construction costs escalated dramatically due to soaring inflation, which has had a significant effect on new supply.

The first five entries in the ranking of the 100 largest construction firms worldwide in 2024 had their headquarters in China. The combined revenue of the Chinese companies included in the list was higher than that of all other firms combined. China State Construction Engineering Corporation Ltd. (CSCEC) generated ****** billion U.S. dollars worth of revenue in 2024. When construction companies were compared based on market capitalization, however, France's Vinci dominated the construction market in the past years. Global Construction Industry There are many types of construction sectors that are considered part of the industry. Building, engineering, specialty construction and planning and development are a few sectors that comprise this booming industry. A large construction company like Vinci generated over half of its revenue from its energy segment, which is focused on the design, construction, operation, and maintenance of infrastructure, as well as on providing other related services. In general, China and Europe were the regions with the largest construction contractors by revenue. Construction Workers One of the most important aspects of construction is the workers and laborers that manage the industry on-the-ground. Hourly labor costs for construction industry workers are highest in the United States and Japan. In the U.S., weekly earnings of construction workers have increased dramatically since 1965, indicating their value to society and the industry.

The number of housing units constructed in Hungary fluctuated over the period under consideration. In 2020, over ****** dwellings were built, which was the highest figure recorded over the observed time. In the same year, the construction production value of residential buildings totaled *** billion forints. However, by 2023, the number of houses built in the country decreased to approximately **** thousand. Houses’ characteristics Houses constructed in Hungary have a relatively large floor space, measuring at ** square meters on average in 2023, while the highest figure was recorded at *** square meters in 2012. The vast majority of dwellings are supplied with piped water, reaching **** percent in 2023, while in the same year, the share of dwellings with a bathroom or lavatory totaled under **** percent.  House and apartment prices The Hungarian real estate market has been characterized by increasing prices lately. It comes as no surprise, that the country’s capital, Budapest has the most expensive housing on the market. In 2023, the average price of new apartments per square meter was the highest in District V, totaling **** million euros. In comparison, the average square meter price of new apartments reached only **** million euros in District XXI.

The quarterly pulse monitor expects the Dutch house prices to climb by *** percent in 2025 due to the decline in purchasing power, higher cost of borrowing and worsening economic conditions. The price of Dutch residential property in 2025 was approximately ******* euros. These developments came on top of other issues that were already prevalent in the Dutch housing market, such as the discussion about nitrogen and its effect on housing construction. The effects of nitrogen on the price of a house At the end of 2019, months before the coronavirus, there was already a lot of uncertainty whether their predictions would hold true. This had to do with the so-called “nitrogen decision” (in Dutch: stikstofbesluit) in May 2019. Simply put, a Dutch advisory body found that the domestic policy for nitrogen emission (formally known as Programmatische Aanpak Stikstof or Programmatic Approach Nitrogen) went against European rules. As of August 2019, a sizable share of the Dutch population was not familiar with this nitrogen policy. However, the advisory body’s decision led to an immediate stop to all construction in the country (amongst other things). By the end of 2019, this stop was still in place. For 2020, newly to be constructed houses have to comply to new rules regarding nitrogen emission. This puts new pressure on a housing market that already had to keep with increasing demand. How about the housing market in Amsterdam? In the year 2022, Amsterdam ranked as the most expensive city in the Netherlands to acquire an apartment, with an average price per square meter that was ***** euros more expensive than in Utrecht. Amsterdam was also well above the average rents found in other cities. A house in Amsterdam had a rent of approximately ** euros per square meter in 2023, whereas rents in Rotterdam cost roughly ** euros per square meter. It should be noted, however, that rent changes in the Dutch capital are significantly lower than those found in Rotterdam and especially Utrecht.