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.

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.

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.

This dataset contains 2,000 entries of house price data from all states in Malaysia, providing a comprehensive overview of the country’s real estate market for 2025. Sourced from Brickz, a trusted platform for property transaction insights, it includes detailed information such as property location, tenure, type, median prices, and transaction counts. This dataset is ideal for real estate market analysis, predictive modeling, and exploring trends across Malaysia’s diverse property market.

https://encrypted-tbn1.gstatic.com/licensed-image?q=tbn:ANd9GcR8ttDRWTx7dIxuUegBTsggS4a6tQrnNA6DEW_HJu2DphQNsverV0PYsSkdbSdqm4qRaRuBOh4Txbv11yXMxIKWqh-_WAkeTuQI8Diu-Q" alt="Kuala Lumpur, Malaysia">

Data Columns (Total 8 Columns):

1. Township: The specific township where the property is located (e.g., Cheras, Subang Jaya).
2. Area: The locality or broader area encompassing the township (e.g., Klang Valley, Penang Island).
3. State: The Malaysian state where the property is situated (e.g., Selangor, Johor, Penang).
4. Tenure: The property ownership type (e.g., Freehold, Leasehold).
5. Type: The category of property (e.g., Terrace, Condominium, Semi-Detached).
6. Median_Price: The median price (in MYR) for properties in the specified township or area.
7. Median_PSF: The median price per square foot (in MYR) for properties.
8. Transactions: The number of recorded property transactions.

Future Plans:

• Expanded Coverage: This dataset will be regularly updated with additional property data to make it even more versatile.
• Enhanced Features: Future updates may include rental prices, amenities, or property-specific details to offer deeper insights into Malaysia’s housing market.

During the COVID-19 pandemic, the number of house sales in the UK spiked, followed by a period of decline. In 2023 and 2024, the housing market slowed notably, and in January 2025, transaction volumes fell to 46,774. House sales volumes are impacted by a number of factors, including mortgage rates, house prices, supply, demand, as well as the overall health of the market. The economic uncertainty and rising unemployment rates has also affected the homebuyer sentiment of Brits. How have UK house prices developed over the past 10 years? House prices in the UK have increased year-on-year since 2015, except for a brief period of decline in the second half of 2023 and the beginning of 2024. That is based on the 12-month percentage change of the UK house price index. At the peak of the housing boom in 2022, prices soared by nearly 14 percent. The decline that followed was mild, at under three percent. The cooling in the market was more pronounced in England and Wales, where the average house price declined in 2023. Conversely, growth in Scotland and Northern Ireland continued. What is the impact of mortgage rates on house sales? For a long period, mortgage rates were at record-low, allowing prospective homebuyers to take out a 10-year loan at a mortgage rate of less than three percent. In the last quarter of 2021, this period came to an end as the Bank of England rose the bank lending rate to contain the spike in inflation. Naturally, the higher borrowing costs affected consumer sentiment, urging many homebuyers to place their plans on hold and leading to a decline in sales.

Median Sales Price of Houses Sold for the United States was 410800.00000 $ in April of 2025, according to the United States Federal Reserve. Historically, Median Sales Price of Houses Sold for the United States reached a record high of 442600.00000 in October of 2022 and a record low of 17800.00000 in January of 1963. Trading Economics provides the current actual value, an historical data chart and related indicators for Median Sales Price of Houses Sold for the United States - last updated from the United States Federal Reserve on December of 2025.

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.

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.

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.

House prices in England have increased notably in the last 10 years, despite a slight decline in 2023. In December 2024, London retained its position as the most expensive regional market, with the average house price at ******* British pounds. According to the UK regional house price index, Northern Ireland saw the highest increase in house prices since 2023.

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.

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.

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.

Key information about House Prices Growth

• Japan house prices grew 3.4% YoY in Aug 2025, following an increase of 4.7% YoY in the previous month.
• YoY growth data is updated monthly, available from Apr 2009 to Aug 2025, with an average growth rate of 1.3%.
• House price data reached an all-time high of 10.2% in Apr 2022 and a record low of -9.4% in Apr 2009.

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.

Graph and download economic data for All-Transactions House Price Index for Las Vegas-Henderson-Paradise, NV (MSA) (ATNHPIUS29820Q) from Q1 1978 to Q3 2025 about Las Vegas, NV, appraisers, HPI, housing, price index, indexes, price, and USA.

Key information about House Prices Growth

• Taiwan house prices grew 0.1% YoY in Sep 2025, following a decrease of 0.1% YoY in the previous quarter.
• YoY growth data is updated quarterly, available from Mar 2002 to Sep 2025, with an average growth rate of 15.1%.
• House price data reached an all-time high of 20.9% in Mar 2010 and a record low of -6.0% in Mar 2016.

Key information about House Prices Growth

• Morocco house prices grew 1.2% YoY in Sep 2025, following remained the same 0.0% YoY in the previous quarter.
• YoY growth data is updated quarterly, available from Mar 2007 to Sep 2025, with an average growth rate of -0.9%.
• House price data reached an all-time high of 7.6% in Mar 2017 and a record low of -6.0% in Dec 2021.

This dataset gives the house prices of 50 European cities, plus other features (like local GDP per capita, population density, ...). This can be used either for data analysis or for linear regression.

In the quarter ending December 2024, the house price index in Portugal was recorded at 235.68 points, having increased by nearly six index points from the previous quarter. That was the highest value over the period under consideration.