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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.

Geneva stands out as Europe's most expensive city for apartment purchases in early 2025, with prices reaching a staggering 15,720 euros per square meter. This Swiss city's real estate market dwarfs even high-cost locations like Zurich and London, highlighting the extreme disparities in housing affordability across the continent. The stark contrast between Geneva and more affordable cities like Nantes, France, where the price was 3,700 euros per square meter, underscores the complex factors influencing urban property markets in Europe. Rental market dynamics and affordability challenges While purchase prices vary widely, rental markets across Europe also show significant differences. London maintained its position as the continent's priciest city for apartment rentals in 2023, with the average monthly costs for a rental apartment amounting to 36.1 euros per square meter. This figure is double the rent in Lisbon, Portugal or Madrid, Spain, and substantially higher than in other major capitals like Paris and Berlin. The disparity in rental costs reflects broader economic trends, housing policies, and the intricate balance of supply and demand in urban centers. Economic factors influencing housing costs The European housing market is influenced by various economic factors, including inflation and energy costs. As of April 2025, the European Union's inflation rate stood at 2.4 percent, with significant variations among member states. Romania experienced the highest inflation at 4.9 percent, while France and Cyprus maintained lower rates. These economic pressures, coupled with rising energy costs, contribute to the overall cost of living and housing affordability across Europe. The volatility in electricity prices, particularly in countries like Italy where rates are projected to reach 153.83 euros per megawatt hour by February 2025, further impacts housing-related expenses for both homeowners and renters.

This table contains data on the percent of households paying more than 30% (or 50%) of monthly household income towards housing costs for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Department of Housing and Urban Development (HUD), Consolidated Planning Comprehensive Housing Affordability Strategy (CHAS) and the U.S. Census Bureau, American Community Survey (ACS). The table is part of a series of indicators in the [Healthy Communities Data and Indicators Project of the Office of Health Equity] Affordable, quality housing is central to health, conferring protection from the environment and supporting family life. Housing costs—typically the largest, single expense in a family's budget—also impact decisions that affect health. As housing consumes larger proportions of household income, families have less income for nutrition, health care, transportation, education, etc. Severe cost burdens may induce poverty—which is associated with developmental and behavioral problems in children and accelerated cognitive and physical decline in adults. Low-income families and minority communities are disproportionately affected by the lack of affordable, quality housing. More information about the data table and a data dictionary can be found in the Attachments.

Graph and download economic data for All-Transactions House Price Index for Baltimore city, MD (ATNHPIUS24510A) from 1975 to 2024 about Baltimore City, MD; Baltimore; MD; HPI; housing; price index; indexes; price; and USA.

Out of a total of *** million housing units in New York City in 2021, approximately ******* homes had housing costs between ** and ** percent of the household budget. New York City is notoriously known for its shortage of affordable housing: Overall, for a large percentage of New York City residents, housing costs exceeded ** percent.

Poland - Median of the housing cost burden distribution: Cities was 13.50% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Poland - Median of the housing cost burden distribution: Cities - last updated from the EUROSTAT on November of 2025. Historically, Poland - Median of the housing cost burden distribution: Cities reached a record high of 20.40% in December of 2014 and a record low of 13.50% in December of 2024.

Sydney had the highest median house value compared to other capital cities in Australia as of April 2025, with a value of over **** million Australian dollars. Brisbane similarly had relatively high average residential housing values, passing Canberra and Melbourne to top the pricing markets for real estate across the country alongside Sydney. Housing affordability in Australia Throughout 2024, the average price of residential dwellings remained high across Australia, with several capital cities breaking price records. Rising house prices continue to be an issue for potential homeowners, with many low- and middle-income earners priced out of the market. In the fourth quarter of 2024, Australia’s house price-to-income ratio declined slightly to ***** index points. With the share of household income spent on mortgage repayments increasing alongside the disparity in supply and demand, inflating construction costs, and low borrowing capacity, the homeownership dream has become an unattainable prospect for the average person in Australia. Does the rental market offer better prospects? Renting for prolonged periods has become inevitable for many Australians due to the country’s largely inaccessible property ladder. However, record low vacancy rates and elevated median weekly house and unit rent prices within Australia’s rental market are making renting a less appealing prospect. In financial year 2024, households in the Greater Sydney metropolitan area reported spending around ** percent of their household income on rent.

In the third quarter of 2025, Mexicans paid on average **** million Mexican pesos to acquire a residential property. Compared to the same period of the previous year, the nominal price increased by nearly ******* pesos. Mexico City registered the highest price for this type of property, with an average exceeding ***** million pesos per residential unit. Housing tenureCompared to renting or borrowing, house ownership is the favored form of housing tenure in Mexico. In 2022, nearly ** percent of all Mexican households owned their homes, while only ** percent rented them. Moreover, roughly ** percent of the owned households in the country were completely paid off, while the remaining households were still in the payment process. Mortgages in MexicoMortgages, or homeownership loans, are debt instruments used by individuals to acquire real estate property, without needing to pay the total cost upfront. Mortgages are universally common and important for Mexico’s residential real estate industry. In 2024, almost ********mortgage loans were granted in Mexico, increasing from the lowest amount the country had seen in the past decade a year earlier. From the mortgage value granted in 2022, approximately ** percent came from private banks.

Spain - Median of the housing cost burden distribution: Cities was 11.60% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Spain - Median of the housing cost burden distribution: Cities - last updated from the EUROSTAT on December of 2025. Historically, Spain - Median of the housing cost burden distribution: Cities reached a record high of 13.10% in December of 2015 and a record low of 10.90% in December of 2020.

Median Home Sale Price: All Residential: Bridgeport, CT data was reported at 493.000 USD th in Jul 2020. This records an increase from the previous number of 485.000 USD th for Jun 2020. Median Home Sale Price: All Residential: Bridgeport, CT data is updated monthly, averaging 385.000 USD th from Feb 2015 (Median) to Jul 2020, with 66 observations. The data reached an all-time high of 493.000 USD th in Jul 2020 and a record low of 336.000 USD th in Feb 2019. Median Home Sale Price: All Residential: Bridgeport, CT data remains active status in CEIC and is reported by Redfin. The data is categorized under Global Database’s United States – Table US.EB056: Median Home Sale Price: by Metropolitan Areas.

VITAL SIGNS INDICATOR Home Prices (EC7)

FULL MEASURE NAME Home Prices

LAST UPDATED August 2019

DESCRIPTION Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.

DATA SOURCE Zillow Median Sale Price (1997-2018) http://www.zillow.com/research/data/

Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1997-2018; specific to each metro area) http://data.bls.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Median housing price estimates for the region, counties, cities, and zip code come from analysis of individual home sales by Zillow. The median sale price is the price separating the higher half of the sales from the lower half. In other words, 50 percent of home sales are below or above the median value. Zillow defines all homes as single-family residential, condominium, and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that you own in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums where the homeowners own shares in the corporation that owns the building, not the actual units themselves.

For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Home sales prices are not reliably available for Houston, because Texas is a non-disclosure state. For more information on non-disclosure states, see: http://www.zillow.com/blog/chronicles-of-data-collection-ii-non-disclosure-states-3783/

Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.

Median Home Sale Price: All Residential: Bonham, TX data was reported at 209.000 USD th in Jul 2020. This records an increase from the previous number of 167.000 USD th for Jun 2020. Median Home Sale Price: All Residential: Bonham, TX data is updated monthly, averaging 115.000 USD th from Feb 2012 (Median) to Jul 2020, with 102 observations. The data reached an all-time high of 209.000 USD th in Jul 2020 and a record low of 46.000 USD th in Jan 2013. Median Home Sale Price: All Residential: Bonham, TX data remains active status in CEIC and is reported by Redfin. The data is categorized under Global Database’s United States – Table US.EB056: Median Home Sale Price: by Metropolitan Areas.

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.

Home prices in the U.S. reach new heights The American housing market continues to show remarkable resilience, with the S&P/Case Shiller U.S. National Home Price Index reaching an all-time high of 331.69 in June 2025. This figure represents a significant increase from the index value of 166.23 recorded in January 2015, highlighting the substantial growth in home prices over the past decade. The S&P Case Shiller National Home Price Index is based on the prices of single-family homes and is the leading indicator of the American housing market and one of the indicators of the state of the broader economy. The S&P Case Shiller National Home Price Index series also includes S&P/Case Shiller 20-City Composite Home Price Index and S&P/Case Shiller 10-City Composite Home Price Index – measuring the home price changes in the major U.S. metropolitan areas, as well as twenty composite indices for the leading U.S. cities. Market fluctuations and recovery Despite the overall upward trend, the housing market has experienced some fluctuations in recent years. During the housing boom in 2021, the number of existing home sales reached the highest level since 2006. However, transaction volumes quickly plummeted, as the soaring interest rates and out-of-reach prices led to housing sentiment deteriorating. Factors influencing home prices Several factors have contributed to the rise in home prices, including a chronic supply shortage, the gradual decline in interest rates, and the spike in demand during the COVID-19 pandemic. During the subprime mortgage crisis (2007-2010), the construction of new homes declined dramatically. Although it has gradually increased since then, the number of new building permits, home starts, and completions are still shy from the levels before the crisis. With demand outweighing supply, competition for homes can be fierce, leading to bidding wars and soaring prices. The supply of existing homes is further constrained, as homeowners are less likely to sell and move homes due to the worsened lending conditions.

Median Home Sale Price: All Residential: Brenham, TX data was reported at 275.000 USD th in Jul 2020. This records an increase from the previous number of 231.000 USD th for Jun 2020. Median Home Sale Price: All Residential: Brenham, TX data is updated monthly, averaging 211.000 USD th from Feb 2012 (Median) to Jul 2020, with 102 observations. The data reached an all-time high of 319.000 USD th in Mar 2019 and a record low of 115.000 USD th in Feb 2013. Median Home Sale Price: All Residential: Brenham, TX data remains active status in CEIC and is reported by Redfin. The data is categorized under Global Database’s United States – Table US.EB056: Median Home Sale Price: by Metropolitan Areas.

Hungary - Housing cost overburden rate: Cities was 10.80% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Hungary - Housing cost overburden rate: Cities - last updated from the EUROSTAT on November of 2025. Historically, Hungary - Housing cost overburden rate: Cities reached a record high of 15.80% in December of 2012 and a record low of 3.40% in December of 2021.

Italy - Housing cost overburden rate: Cities was 6.60% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Italy - Housing cost overburden rate: Cities - last updated from the EUROSTAT on November of 2025. Historically, Italy - Housing cost overburden rate: Cities reached a record high of 12.90% in December of 2016 and a record low of 6.60% in December of 2024.

Montevideo, Uruguay's capital, leads Latin American cities with the highest apartment sale prices in 2025, averaging ***** U.S. dollars per square meter. This figure surpasses other major metropolitan areas like Mexico City and Buenos Aires, highlighting significant disparities in real estate markets across the region. The data underscores the varying economic conditions and housing demand in different Latin American urban centers. Regional housing market trends While Montevideo tops the list for apartment prices, other countries in Latin America have experienced notable changes in their housing markets. Chile, for instance, saw the most substantial increase in house prices since 2010, with its nominal house price index surpassing *** points in early 2025. However, when adjusted for inflation, Mexico showed the highest inflation-adjusted percentage increase in house prices, growing by nearly *** percent in the first quarter of 2025, contrasting with a global decline of one percent. Home financing in Mexico The methods of home financing vary across Latin America. A breakdown of homeownership by financing method in Mexico reveals that about two-thirds of owner-occupied housing units were financed through personal resources in 2022. Nevertheless, government-backed loans such as Infonavit (Mexico’s National Housing Fund Institute), Fovissste (Housing Fund of the Institute for Social Security and Services for State Workers), and Fonhapo (National Fund for Popular Housing), play an important role for homebuyers, with just over ** percent of home purchases relying on such finance. Bank credit, which offers mortgage loans with interest rates ranging between **** and ** percent, appeared as a less popular option.

Finland - Housing cost overburden rate: Cities was 7.70% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Finland - Housing cost overburden rate: Cities - last updated from the EUROSTAT on December of 2025. Historically, Finland - Housing cost overburden rate: Cities reached a record high of 7.80% in December of 2023 and a record low of 5.10% in December of 2012.

VITAL SIGNS INDICATOR Home Prices (EC7)

FULL MEASURE NAME Home Prices

LAST UPDATED August 2019

DESCRIPTION Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.

DATA SOURCE Zillow Median Sale Price (1997-2018) http://www.zillow.com/research/data/

Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1997-2018; specific to each metro area) http://data.bls.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Median housing price estimates for the region, counties, cities, and zip code come from analysis of individual home sales by Zillow. The median sale price is the price separating the higher half of the sales from the lower half. In other words, 50 percent of home sales are below or above the median value. Zillow defines all homes as single-family residential, condominium, and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that you own in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums where the homeowners own shares in the corporation that owns the building, not the actual units themselves.

For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Home sales prices are not reliably available for Houston, because Texas is a non-disclosure state. For more information on non-disclosure states, see: http://www.zillow.com/blog/chronicles-of-data-collection-ii-non-disclosure-states-3783/

Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.