Graph and download economic data for Housing Inventory: Median Home Size in Square Feet in the United States (MEDSQUFEEUS) from Jul 2016 to Oct 2025 about square feet, median, and USA.

The majority of home buyers in the United States in 2024 across all age groups purchased a home between ***** and ***** square feet in size. ** percent of the young millennials (26 to 34 years old) and ** percent of the silent generation (79 to 99 years old) purchased a home about the same feet in size.

In 2017, Australia had the largest homes out of the countries surveyed. Australian homes measured, on average, ***** square feet, and were closely followed by U.S. homes at ***** square feet. Canadian homes were also quite large at ***** square feet.

In 2024, the average size of a single-family home built for sale in the United States amounted to ***** square feet. Although in the past five years American homes have been shrinking, since 1975, they have almost doubled in size. This trend towards larger homes seems illogical given that the average size of families has shrunk over the same period. Why are American homes so large? Homes in the U.S. are among the largest in the world, only surpassed by Australia. There are thought to be several reasons for this, including the concentration of wealth in the country and the deeply engrained driving culture, which means that cheaper land outside city centers is easily accessible. Where are the largest homes located? The size of homes also varies regionally, with the largest homes being located in wealthy, urban areas and in the South. Large homes, or McMansions as they’re often called, are especially popular in Texas. In 2024, Milwaukee and Omaha had the largest average home size.

The Housing Data Extracted from Homes.com (USA) dataset is a comprehensive collection of 2 million real estate listings sourced from Homes.com, one of the leading real estate platforms in the United States. This dataset offers detailed insights into the U.S. housing market, making it an invaluable resource for real estate professionals, investors, researchers, and analysts.

The dataset contains extensive property details, including location, price, property type (single-family homes, condos, apartments), number of bedrooms and bathrooms, square footage, lot size, year built, and availability status. Organized in CSV format, it provides users with easy access to structured data for analyzing trends, developing investment strategies, or building real estate applications.

Key Features:

• Record Count: 2 million housing listings from across the USA.
• Data Fields: Property address, price, property type, bedrooms, bathrooms, square footage, lot size, year built, and availability.
• Format: CSV format for easy integration with data analysis platforms, machine learning models, and real estate tools.
• Source: Directly sourced from Homes.com’s USA real estate listings.
• Geographical Focus: Comprehensive coverage of properties across all regions of the United States.

Use Cases:

• Real Estate Market Research: Analyze property prices, market trends, and housing demand in various U.S. regions.
• Investment Analysis: Use data to identify high-potential properties and regions for real estate investments.
• Property Comparison: Compare listings by price, location, and features to evaluate market conditions across different cities and states.
• Machine Learning Models: Build predictive models for price forecasting, property valuation, and real estate recommendation systems.
• Content Creation: Create real estate-related content, reports, and insights for the U.S. housing market using up-to-date data.

Graph and download economic data for Housing Inventory: Median Home Size in Square Feet in Florida (MEDSQUFEEFL) from Jul 2016 to Oct 2025 about square feet, FL, median, and USA.

In 2018, the average home size in the United States was ***** square feet, and the size of the average home is set to fall to ***** square feet by 2023.

Graph and download economic data for Housing Inventory: Median Home Size in Square Feet in San Francisco County/city, CA (MEDSQUFEE6075) from Jul 2016 to Oct 2025 about San Francisco County/City, CA; square feet; median; and USA.

Graph and download economic data for Housing Inventory: Median Home Size in Square Feet in New York (MEDSQUFEENY) from Jul 2016 to Oct 2025 about square feet, NY, median, and USA.

https://raw.githubusercontent.com/Masterx-AI/Project_Housing_Price_Prediction_/main/hs.jpg" alt="">

Description:

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?

Acknowledgement:

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.

Objective:

• Understand the Dataset & cleanup (if required).
• Build Regression models to predict the sales w.r.t a single & multiple feature.
• Also evaluate the models & compare thier respective scores like R2, RMSE, etc.

Housing Inventory: Median Home Size in Square Feet Year-Over-Year in Michigan was -1.02% in October of 2025, according to the United States Federal Reserve. Historically, Housing Inventory: Median Home Size in Square Feet Year-Over-Year in Michigan reached a record high of 3.43 in July of 2017 and a record low of -8.46 in August of 2021. Trading Economics provides the current actual value, an historical data chart and related indicators for Housing Inventory: Median Home Size in Square Feet Year-Over-Year in Michigan - last updated from the United States Federal Reserve on December of 2025.

In 2023, the average size per dwelling in Japan was ***** square meters. When broken down by prefecture, ****** stood out as the prefecture with the largest average floor area per housing unit, while ***** had the smallest average floor area in the same year. Real estate in Japan The real estate industry is an important pillar of the Japanese economy and ranked as the third-largest industry in Japan in terms of value added in 2022. Despite this, the number of unoccupied dwellings in Japan has been steadily increasing for over thirty years. Many unoccupied homes are empty and abandoned. This trend can be attributed to two primary factors: the aging of the population and the challenges faced by empty house owners in managing and utilizing properties, as most of these homes are either managed by older individuals or family inheritance. Housing in Tokyo The monthly residential property price index in Tokyo Prefecture has experienced a significant upward trend in the past years. Tokyo holds the largest population in Japan, with approximately ** million inhabitants, making it the world’s largest urban agglomeration. The city’s appeal lies in its many renowned universities and corporate headquarters, which draws migrants from other prefectures, particularly young individuals. However, Japan is currently experiencing an investment boom in real estate, fueled by overseas investment. This has resulted in central Tokyo apartments becoming less affordable for many people.

Home Value Insights: A Beginner's Regression Dataset

This dataset is designed for beginners to practice regression problems, particularly in the context of predicting house prices. It contains 1000 rows, with each row representing a house and various attributes that influence its price. The dataset is well-suited for learning basic to intermediate-level regression modeling techniques.

Features:

1. Square_Footage: The size of the house in square feet. Larger homes typically have higher prices.
2. Num_Bedrooms: The number of bedrooms in the house. More bedrooms generally increase the value of a home.
3. Num_Bathrooms: The number of bathrooms in the house. Houses with more bathrooms are typically priced higher.
4. Year_Built: The year the house was built. Older houses may be priced lower due to wear and tear.
5. Lot_Size: The size of the lot the house is built on, measured in acres. Larger lots tend to add value to a property.
6. Garage_Size: The number of cars that can fit in the garage. Houses with larger garages are usually more expensive.
7. Neighborhood_Quality: A rating of the neighborhood’s quality on a scale of 1-10, where 10 indicates a high-quality neighborhood. Better neighborhoods usually command higher prices.
8. House_Price (Target Variable): The price of the house, which is the dependent variable you aim to predict.

Potential Uses:

1. Beginner Regression Projects: This dataset can be used to practice building regression models such as Linear Regression, Decision Trees, or Random Forests. The target variable (house price) is continuous, making this an ideal problem for supervised learning techniques.

2. Feature Engineering Practice: Learners can create new features by combining existing ones, such as the price per square foot or age of the house, providing an opportunity to experiment with feature transformations.

3. Exploratory Data Analysis (EDA): You can explore how different features (e.g., square footage, number of bedrooms) correlate with the target variable, making it a great dataset for learning about data visualization and summary statistics.

4. Model Evaluation: The dataset allows for various model evaluation techniques such as cross-validation, R-squared, and Mean Absolute Error (MAE). These metrics can be used to compare the effectiveness of different models.

Versatility:

• The dataset is highly versatile for a range of machine learning tasks. You can apply simple linear models to predict house prices based on one or two features, or use more complex models like Random Forest or Gradient Boosting Machines to understand interactions between variables.

• It can also be used for dimensionality reduction techniques like PCA or to practice handling categorical variables (e.g., neighborhood quality) through encoding techniques like one-hot encoding.

• This dataset is ideal for anyone wanting to gain practical experience in building regression models while working with real-world features.

Snapshot img

Tiny Homes Market Size 2025-2029

The tiny homes market size is valued to increase USD 3.71 billion, at a CAGR of 4.2% from 2024 to 2029. Affordable by mass section of population will drive the tiny homes market.

Major Market Trends & Insights

North America dominated the market and accounted for a 55% growth during the forecast period.
By Product - Mobile tiny homes segment was valued at USD 9.64 billion in 2023
By Application - Home use segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 37.94 million
Market Future Opportunities: USD 3713.10 million
CAGR : 4.2%
North America: Largest market in 2023

Market Summary

The market represents a burgeoning sector in the residential real estate industry, characterized by its focus on compact, affordable living solutions. This market encompasses a range of core technologies and applications, from innovative building materials and modular construction methods to renewable energy systems and smart home automation. Service types and product categories include design and construction services, as well as the sale of prefabricated tiny homes and accessories. Despite regulatory challenges in some regions, the market continues to expand, driven by the growing trend of customization and the affordable nature of tiny homes, making them an attractive option for a mass section of the population. However, limited demand from developing economies presents a significant challenge. In the United States, for instance, the American Tiny House Association reports that the number of tiny homes registered with the organization has grown by over 50% since 2019. This underscores the evolving nature of the market and the opportunities it presents for businesses and consumers alike.

What will be the Size of the Tiny Homes Market during the forecast period?

Get Key Insights on Market Forecast (PDF) Request Free Sample

How is the Tiny Homes Market Segmented and what are the key trends of market segmentation?

The tiny homes industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. ProductMobile tiny homesStationary tiny homesApplicationHome useCommercial useAreaLess Than 130 Sq. Ft.130-500 Sq. Ft.More Than 500 Sq. Ft.Less Than 130 Sq. Ft.130-500 Sq. Ft.More Than 500 Sq. Ft.Price RangeBudgetMid-rangePremiumMaterialWoodMetalRecycledGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalySpainUKMiddle East and AfricaUAEAPACChinaIndiaJapanSouth KoreaSouth AmericaBrazilRest of World (ROW)

By Product Insights

The mobile tiny homes segment is estimated to witness significant growth during the forecast period.

The market has experienced significant expansion in recent years, with mobile tiny homes, characterized by permanently affixed chassis, witnessing substantial growth. These homes are manufactured in factories and transported to their intended sites via wheels or trucks. The affordability of mobile tiny homes makes them a popular solution in the affordable housing sector in various countries. The increasing cost of conventional houses in numerous nations is driving the demand for these compact living solutions. Young adults and retirees, seeking to save on housing expenses, are the primary consumer groups fueling the market's growth. According to recent data, the adoption of tiny homes has risen by approximately 18%, and it is projected to expand further, reaching around 25% in the upcoming five years. In terms of market trends, green building practices and energy-efficient appliances are gaining traction. Interior finishing materials, such as reclaimed wood and recycled materials, are increasingly popular. Water conservation methods, like rainwater harvesting and greywater recycling, are being integrated into tiny home designs. Site preparation techniques, like minimal excavation and foundation system designs, are being optimized for efficient construction. Structural engineering designs focus on maximizing space through innovative layouts and smart home integration. Prefabricated housing and alternative building methods, like modular construction, are streamlining the construction process. Plumbing system installations and wastewater treatment systems are being designed for off-grid living. Insulation techniques, transportation logistics, permitting and approvals, and building code compliance are all crucial aspects of the market. The durability and longevity of tiny homes are essential considerations, with sustainable building materials and hvac system optimization being key factors. Cost estimation models, downsizing and minimalism, and mobile home foundations are also significant market trends. Electrical system designs prioritize fire s

The average size of newly built houses in Ireland shrunk by about ** square meters between 2011 and 2024. Conversely, scheme dwellings decreased in size slightly, while apartments remained stable. In 2024, the average size of newly completed single-family houses was *** square meters. Scheme dwellings had *** square meters, and apartments ** square meters.

Housing Inventory: Median Home Size in Square Feet Year-Over-Year in South Carolina was 1.69% in October of 2025, according to the United States Federal Reserve. Historically, Housing Inventory: Median Home Size in Square Feet Year-Over-Year in South Carolina reached a record high of 7.09 in February of 2022 and a record low of -9.37 in April of 2024. Trading Economics provides the current actual value, an historical data chart and related indicators for Housing Inventory: Median Home Size in Square Feet Year-Over-Year in South Carolina - last updated from the United States Federal Reserve on December of 2025.

Toyama was the Japanese prefecture with the largest average floor area per dwelling in 2023. Compared to an average floor space of around *** square meters in Toyama Prefecture, the average dwelling in Tokyo covered a floor area of about ** square meters.

Graph and download economic data for Housing Inventory: Median Home Size in Square Feet in Houston-the Woodlands-Sugar Land, TX (CBSA) (MEDSQUFEE26420) from Jul 2016 to Oct 2025 about Houston, square feet, TX, median, and USA.

The Prefabricated Housing Market Report is Segmented by Material Type (Concrete, Glass, Metal, Timber and Other Materials), by Type (Single-Family and Multi-Family), by Product Type (Modular Homes, Panelised & Componentised Systems, Manufactured Homes and Other Prefab Types), and by Geography (North America, South America, Europe, and More). The Market Forecasts are Provided in Terms of Value (USD).

Housing Inventory: Median Home Size in Square Feet Month-Over-Month in Oklahoma City, OK (CBSA) was -0.41% in October of 2025, according to the United States Federal Reserve. Historically, Housing Inventory: Median Home Size in Square Feet Month-Over-Month in Oklahoma City, OK (CBSA) reached a record high of 6.08 in June of 2020 and a record low of -3.97 in August of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for Housing Inventory: Median Home Size in Square Feet Month-Over-Month in Oklahoma City, OK (CBSA) - last updated from the United States Federal Reserve on December of 2025.