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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.

In this Economic Commentary , we compare characteristics of the 2000–2006 house-price boom that preceded the Great Recession to the house-price boom that began in 2020 during the COVID-19 pandemic. These two episodes of high house-price growth have important differences, including the behavior of rental rates, the dynamics of housing supply and demand, and the state of the mortgage market. The absence of changes in fundamentals during the 2000s is consistent with the literature emphasizing house-price beliefs during this prior episode. In contrast to during the 2000s boom, changes in fundamentals (including rent and demand growth) played a more dominant role in the 2020s house-price boom.

Graph and download economic data for Average Sales Price of Houses Sold for the United States (ASPUS) from Q1 1963 to Q2 2025 about sales, housing, and USA.

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.

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 ...

Key information about House Prices Growth

• US house prices grew 3.3% YoY in Sep 2025, following an increase of 4.1% YoY in the previous quarter.
• YoY growth data is updated quarterly, available from Mar 1992 to Sep 2025, with an average growth rate of -12.4%.
• House price data reached an all-time high of 17.7% in Sep 2021 and a record low of -12.4% in Dec 2008.

The average sales price of new homes in the United States experienced a slight decrease in 2024, dropping to 512,2000 U.S. dollars from the peak of 521,500 U.S. dollars in 2022. This decline came after years of substantial price increases, with the average price surpassing 400,000 U.S. dollars for the first time in 2021. The recent cooling in the housing market reflects broader economic trends and changing consumer sentiment towards homeownership. Factors influencing home prices and affordability The rapid rise in home prices over the past few years has been driven by several factors, including historically low mortgage rates and increased demand during the COVID-19 pandemic. However, the market has since slowed down, with the number of home sales declining by over two million between 2021 and 2023. This decline can be attributed to rising mortgage rates and decreased affordability. The Housing Affordability Index hit a record low of 98.1 in 2023, indicating that the median-income family could no longer afford a median-priced home. Future outlook for the housing market Despite the recent cooling, experts forecast a potential recovery in the coming years. The Freddie Mac House Price Index showed a growth of 6.5 percent in 2023, which is still above the long-term average of 4.4 percent since 1990. However, homebuyer sentiment remains low across all age groups, with people aged 45 to 64 expressing the most pessimistic outlook. The median sales price of existing homes is expected to increase slightly until 2025, suggesting that affordability challenges may persist in the near future.

In 2022, house price growth in the UK slowed, after a period of decade-long increase. Nevertheless, in June 2025, prices reached a new peak, with the average home costing ******* British pounds. This figure refers to all property types, including detached, semi-detached, terraced houses, and flats and maisonettes. Compared to other European countries, the UK had some of the highest house prices. How have UK house prices increased over the last 10 years? Property prices have risen dramatically over the past decade. According to the UK house price index, the average house price has grown by over ** percent since 2015. This price development has led to the gap between the cost of buying and renting a property to close. In 2023, buying a three-bedroom house in the UK was no longer more affordable than renting one. Consequently, Brits have become more likely to rent longer and push off making a house purchase until they have saved up enough for a down payment and achieved the financial stability required to make the step. What caused the recent fluctuations in house prices? House prices are affected by multiple factors, such as mortgage rates, supply, and demand on the market. For nearly a decade, the UK experienced uninterrupted house price growth as a result of strong demand and a chronic undersupply. Homebuyers who purchased a property at the peak of the housing boom in July 2022 paid ** percent more compared to what they would have paid a year before. Additionally, 2022 saw the most dramatic increase in mortgage rates in recent history. Between December 2021 and December 2022, the **-year fixed mortgage rate doubled, adding further strain to prospective homebuyers. As a result, the market cooled, leading to a correction in pricing.

Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q2 2025 about sales, median, housing, and USA.

Average house prices are derived from data supplied by the mortgage lending agencies on loans approved by them rather than loans paid. In comparing house prices figures from one period to another, account should be taken of the fact that changes in the mix of houses (incl apartments) will affect the average figures. The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change. Excluding apartments, measured in € Figure changed on the 27/6/16 as revised data received from the Local authority .hidden { display: none }

This dataset provides values for AVERAGE HOUSE PRICES reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

The U.S. housing market has slowed, after ** consecutive years of rising home prices. In 2021, house prices surged by an unprecedented ** percent, marking the highest increase on record. However, the market has since cooled, with the Freddie Mac House Price Index showing more modest growth between 2022 and 2024. In 2024, home prices increased by *** percent. That was lower than the long-term average of *** percent since 1990. Impact of mortgage rates on homebuying The recent cooling in the housing market can be partly attributed to rising mortgage rates. After reaching a record low of **** percent in 2021, the average annual rate on a 30-year fixed-rate mortgage more than doubled in 2023. This significant increase has made homeownership less affordable for many potential buyers, contributing to a substantial decline in home sales. Despite these challenges, forecasts suggest a potential recovery in the coming years. How much does it cost to buy a house in the U.S.? In 2023, the median sales price of an existing single-family home reached a record high of over ******* U.S. dollars. Newly built homes were even pricier, despite a slight decline in the median sales price in 2023. Naturally, home prices continue to vary significantly across the country, with West Virginia being the most affordable state for homebuyers.

Graph and download economic data for Real Residential Property Prices for United States (QUSR628BIS) from Q1 1970 to Q2 2025 about residential, HPI, housing, real, price index, indexes, price, and USA.

Purpose and brief description The house price index measures the inflation in the residential property market. The house price index reflects price developments for all residential properties purchased by households (apartments, terraced houses, detached houses), regardless of whether they are new or existing. Only market prices are taken into account, so self-build homes are excluded. The price of the land is included in the price of the properties. Population Real estate transactions involving residential properties Periodicity Quarterly. Release calendar Results available 3 months after the reference period Definitions House price index: The house price index measures changes in the prices of new or existing dwellings, regardless of their use or previous owner. Inflation - house price index: Inflation is defined as the ratio between the value of a given quarter and that of the same quarter of the previous year. Weighting - house price index: Weighting based on the national accounts (gross fixed capital formation in housing) and the total number of real estate transactions involving residential properties. Type of dwelling according to the classification set out in Regulation (EU) No 93/2013 on housing price indices. Technical information The house price index measures the price evolution of real estate prices on the market of private property. The index follows price changes of new or existing residential real estate purchased by households, irrespective of their purpose (letting or owner-occupying). Only market prices are taken into account. Houses built by their owners are therefore not included. The price of the building plot is included in the house price. The house price index is based on real estate transaction data from the General Administration of the Patrimonial Documentation of the FPS Finances. The prices used are those included in the deeds of sale. Given the time between the date on which the preliminary sales agreement is signed and the date on which the deed is executed (between three and four months), this index measures the price evolution with a delay compared to the actual date on which the sales price is set. This delay is inherent to the data source. The house price index is calculated by the European Union Member States, Norway and Iceland. Eurostat calculates the index for the Euro area (as well as for the European Union as a whole) using the harmonised indices of the Member States. Given the role of the housing market in the economic and financial crisis of 2008, the house price index was included in the indicators used in the procedure to prevent and correct macroeconomic imbalances in the European Union. The house price index is calculated under the European Regulation 2016/792 on harmonised indices of consumer prices and the house price index and 2023/1470 laying down the methodological and technical specifications as regards the house price index and the owner-occupied housing price index. Data are available from 2005 onward for Belgium as well as for the European Union and the majority of European countries. The house price index can be broken down by new houses and existing houses. The weights of these two items in the overall index are determined by the gross fixed capital formation in houses (for the new houses) and the total value of transactions of the previous year (for the existing houses). Until 2013, the house price index of new houses was roughly estimated based on the output price index in the construction sector. Since 2014, it is also based on real estate transaction data. House price index for existing houses is available per region since 2010. The data have therefore been completely reviewed when the results for the fourth quarter of 2023 were published in March 2024. Since the houses that are put up for sale differ from one quarter to another, the changes in characteristics are processed with hedonic regression models to eliminate price fluctuations due to changes in characteristics of the properties sold. These models aim to estimate the theoretical price based on the characteristics and location of the houses sold. The index is then calculated based on changes in the average prices observed and adjusted by a factor depending on the differences in quality observed between dwellings sold during the different periods.

View monthly updates and historical trends for US Existing Home Median Sales Price. from United States. Source: National Association of Realtors. Track ec…

House prices in the UK rose dramatically during the coronavirus pandemic, with growth slowing down in 2022 and turning negative in 2023. The year-on-year annual house price change peaked at 14 percent in July 2022. In April 2025, house prices increased by 3.5 percent. As of late 2024, the average house price was close to 290,000 British pounds. Correction in housing prices: a European phenomenon The trend of a growing residential real estate market was not exclusive to the UK during the pandemic. Likewise, many European countries experienced falling prices in 2023. When comparing residential property RHPI (price index in real terms, e.g. corrected for inflation), countries such as Germany, France, Italy, and Spain also saw prices decline. Sweden, one of the countries with the fastest growing residential markets, saw one of the largest declines in prices. How has demand for UK housing changed since the outbreak of the coronavirus? The easing of the lockdown was followed by a dramatic increase in home sales. In November 2020, the number of mortgage approvals reached an all-time high of over 107,000. One of the reasons for the housing boom were the low mortgage rates, allowing home buyers to take out a loan with an interest rate as low as 2.5 percent. That changed as the Bank of England started to raise the base lending rate, resulting in higher borrowing costs and a decline in homebuyer sentiment.

House Price Index YoY in the United States decreased to 1.70 percent in September from 2.40 percent in August of 2025. This dataset includes a chart with historical data for the United States FHFA House Price Index YoY.

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.

Average House Prices in Canada increased to 688800 CAD in October from 687600 CAD in September of 2025. This dataset includes a chart with historical data for Canada Average House Prices.

Single Family Home Prices in the United States increased to 415200 USD in October from 412300 USD in September of 2025. This dataset provides - United States Existing Single Family Home Prices- actual values, historical data, forecast, chart, statistics, economic calendar and news.