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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.

Turkey experienced the highest annual change in house prices in 2025, followed by North Macedonia and Portugal. In the second quarter of the year, the nominal house price in Turkey grew by **** percent, while in North Macedonia and Portugal, the increase was **** and **** percent, respectively. Meanwhile, some countries saw prices fall throughout the year. That has to do with an overall cooling of the global housing market that started in 2022. When accounting for inflation, house price growth was slower, and even more countries saw the market shrink.

This dataset provides insights into the global housing market, covering various economic factors from 2015 to 2024. It includes details about property prices, rental yields, interest rates, and household income across multiple countries. This dataset is ideal for real estate analysis, financial forecasting, and market trend visualization.

📑 Column Descriptions

Column Name	Description
Country	The country where the housing market data is recorded 🌍
Year	The year of observation 📅
Average House Price ($)	The average price of houses in USD 💰
Median Rental Price ($)	The median monthly rent for properties in USD 🏠
Mortgage Interest Rate (%)	The average mortgage interest rate percentage 📉
Household Income ($)	The average annual household income in USD 🏡
Population Growth (%)	The percentage increase in population over the year 👥
Urbanization Rate (%)	Percentage of the population living in urban areas 🏙️
Homeownership Rate (%)	The percentage of people who own their homes 🔑
GDP Growth Rate (%)	The annual GDP growth percentage 📈
Unemployment Rate (%)	The percentage of unemployed individuals in the labor force 💼

Context

This dataset was actually made to check the correlations between a housing price index and its crime rate. Rise and fall of housing prices can be due to various factors with obvious reasons being the facilities of the house and its neighborhood. Think of a place like Detroit where there are hoodlums and you don't want to end up buying a house in the wrong place. This data set will serve as historical data for crime rate data and this in turn can be used to predict whether the housing price will rise or fall. Rise in housing price will suggest decrease in crime rate over the years and vice versa.

Content

The headers are self explanatory. index_nsa is the housing price non seasonal index.

Acknowledgements

Thank you to my team who helped in achieving this.

Inspiration

https://www.kaggle.com/marshallproject/crime-rates https://catalog.data.gov/dataset/fhfa-house-price-indexes-hpis Data was collected from these 2 sources and merged to get the resulting dataset.

In December 2024, the average house price in England was pricier than in any other country. This considerable disparity in average house prices is in no small part down to the country's capital city, where the average asking price was more than double that of the UK’s average. Even in London, for those who can afford a mortgage, the savings made through buying over renting can be beneficial. What drives house prices? Average house prices are affected by several factors, including economic growth, unemployment, and interest rates. Housing supply also plays a considerable role, with a shortage of supply leading to increased competition and an upward push in prices. Conversely, an excess of housing means prices fall to stimulate buyers. House prices still set to grow The housing market in the UK is expected to continue to grow in the next years. By 2029,.the annual number of housing transactions is set to reach *** million. With transactions on the rise, the average house price is also set to rise.

ttd22/house-price dataset hosted on Hugging Face and contributed by the HF Datasets community

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.

Task Description: Real Estate Price Prediction

This task involves predicting the price of real estate properties based on various features that influence the value of a property. The dataset contains several attributes of real estate properties such as square footage, the number of bedrooms, bathrooms, floors, the year the property was built, whether the property has a garden or pool, the size of the garage, the location score, and the distance from the city center.

The goal is to build a regression model that can predict the Price of a property based on the provided features.

Dataset Columns:

ID: A unique identifier for each property.

Square_Feet: The area of the property in square meters.

Num_Bedrooms: The number of bedrooms in the property.

Num_Bathrooms: The number of bathrooms in the property.

Num_Floors: The number of floors in the property.

Year_Built: The year the property was built.

Has_Garden: Indicates whether the property has a garden (1 for yes, 0 for no).

Has_Pool: Indicates whether the property has a pool (1 for yes, 0 for no).

Garage_Size: The size of the garage in square meters.

Location_Score: A score from 0 to 10 indicating the quality of the neighborhood (higher scores indicate better neighborhoods).

Distance_to_Center: The distance from the property to the city center in kilometers.

Price: The target variable that represents the price of the property. This is the value we aim to predict.

Objective: The goal of this task is to develop a regression model that predicts the Price of a real estate property using the other features as inputs. The model should be able to learn the relationship between these features and the price, providing an accurate prediction for unseen data.

Most of the public concern about housing markets is based on claims that house prices have increased at historically anomalous rates and that house prices have outpaced incomes. The first claim is based on inaccurate historical data. The second is linked to relaxed credit constraints. House prices are likely to fall further, but not for the reasons usually proposed.

View monthly updates and historical trends for US House Price Index. from United States. Source: Federal Housing Finance Agency. Track economic data with …

Graph and download economic data for All-Transactions House Price Index for the United States (USSTHPI) from Q1 1975 to Q3 2025 about appraisers, HPI, housing, price index, indexes, price, and USA.

The average resale house price in Canada was forecast to reach nearly ******* Canadian dollars in 2026, according to a January forecast. In 2024, house prices increased after falling for the first time since 2019. One of the reasons for the price correction was the notable drop in transaction activity. Housing transactions picked up in 2024 and are expected to continue to grow until 2026. British Columbia, which is the most expensive province for housing, is projected to see the average house price reach *** million Canadian dollars in 2026. Affordability in Vancouver Vancouver is the most populous city in British Columbia and is also infamously expensive for housing. In 2023, the city topped the ranking for least affordable housing market in Canada, with the average homeownership cost outweighing the average household income. There are a multitude of reasons for this, but most residents believe that foreigners investing in the market cause the high housing prices. Victoria housing market The capital of British Columbia is Victoria, where housing prices are also very high. The price of a single family home in Victoria's most expensive suburb, Oak Bay was *** million Canadian dollars in 2024.

Graph and download economic data for All-Transactions House Price Index for North Dakota (NDSTHPI) from Q1 1975 to Q3 2025 about ND, appraisers, HPI, housing, price index, indexes, price, and USA.

After a period of rapid increase, house price growth in the UK has moderated. In 2025, house prices are forecast to increase by ****percent. Between 2025 and 2029, the average house price growth is projected at *** percent. According to the source, home building is expected to increase slightly in this period, fueling home buying. On the other hand, higher borrowing costs despite recent easing of mortgage rates and affordability challenges may continue to suppress transaction activity. Historical house price growth in the UK House prices rose steadily between 2015 and 2020, despite minor fluctuations. In the following two years, prices soared, leading to the house price index jumping by about 20 percent. As the market stood in April 2025, the average price for a home stood at approximately ******* British pounds. Rents are expected to continue to grow According to another forecast, the prime residential market is also expected to see rental prices grow in the next five years. Growth is forecast to be stronger in 2025 and slow slightly until 2029. The rental market in London is expected to follow a similar trend, with Outer London slightly outperforming Central London.

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.

Key information about House Prices Growth

• Canada house prices dropped 1.8% YoY in Oct 2025, following a decrease of 1.8% YoY in the previous month.
• YoY growth data is updated monthly, available from Jan 1982 to Oct 2025, with an average growth rate of 5.1%.
• House price data reached an all-time high of 16.5% in Mar 1989 and a record low of -9.7% in Apr 1991.

CEIC calculates House Prices Growth from monthly House Price Index. Statistics Canada provides House Price Index with base December 2016=100. House Price Index covers New Housing only.

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

Key information about House Prices Growth

• China house prices dropped 2.5% YoY in Oct 2025, following a decrease of 1.9% YoY in the previous month.
• YoY growth data is updated monthly, available from Mar 1999 to Oct 2025, with an average growth rate of 5.3%.
• House price data reached an all-time high of 25.0% in Feb 2010 and a record low of -12.6% in Apr 1999.

CEIC calculates House Prices Growth from monthly Average Residential Property Price per Square Meter. The National Bureau of Statistics provides year-to-date Average Residential Property Price per Square Meter in local currency.

The real estate prices in Sweden increased significantly between 2008 and 2023. In 2023, the price index reached 455, with 1990 as base year. This was the first decrease in house prices since 2012. Despite the decline, prices in 2023 were still notably higher than before the COVID-19 pandemic. One of the reasons was the slowdown in construction, which hampered the supply of new homes. Rented dwellings are popular among Swedes Sweden is one of the countries in Europe with the most renters among the population. Only about 64 percent of people lived in an owner-occupied home in 2022. Only a few countries, such as France, Denmark, Germany, and Austria, had lower homeownership rates. How many rooms do Europeans have at home? As of 2021, the European countries which had been reported to have the highest number of rooms per person were Ireland and Malta, with 2.3 rooms per person on average. Sweden ranked fifteenth on the list, where the average number of rooms per person was 1.9.

In 2025, Turkey had the highest inflation-adjusted house price index out of the ** European countries under observation, making it the country where house prices have increased the most since 2010. In Turkey, the house price index exceeded *** index points in the second quarter of 2025, showing an increase in real terms of *** percent since 2010, the baseline year for the index. Iceland and Hungary completed the top three, with an index value of *** and *** index points. In the past year, however, many European countries saw house prices decline in real terms. Where can I find other metrics on different housing markets in Europe? To assess the valuation in different housing markets, one can compare the house-price-to-income ratios of different countries worldwide. These ratios are calculated by dividing nominal house prices by nominal disposable income per head. There are also ratios that look at how residential property prices relate to domestic rents, such as the house-price-to-rent ratio for the United Kingdom. Unfortunately, these numbers are not available in a European overview. An overview of the price per square meter of an apartment in the EU-28 countries is available, however. One region, different markets An important trait of the European housing market is that there is not one market, but multiple. Property policy in Europe lies with the domestic governments, not with the European Union. This leads to significant differences between European countries, which shows in, for example, the homeownership rate (the share of owner-occupied dwellings of all homes). These differences also lead to another problem: the availability of data. Non-Europeans might be surprised to see that house price statistics vary in depth, as every country has their own methodology and no European body exists that tracks this data for the whole continent.