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Same dataset as "House Sales in King County, USA", but with treated content and with a split version (train-test) allowing direct use in machine learning models.

We have 14 columns in the dataset, as it follows:

• date: Date of the home sale
• price: Price of each home sold
• bedrooms: Number of bedrooms
• bathrooms: Number of bathrooms
• living_in_m2: Square meters of the apartments interior living space
• nice_view: A flag that indicates the view's quality of a property
• perfect_condition: A flag that indicates the maximum index of the apartment condition
• grade: An index from 1 to 5, where 1 falls short of quality level and 5 have a high quality level of construction and design
• has_basement: A flag indicating whether or not a property has a basement
• renovated: A flag if the property was renovated
• has_lavatory: Check for the presence of these incomplete/secondary bathrooms (bathtub, sink, toilet)
• single_floor: A flag indicating whether the property had only one floor
• month: The month of the home sale
• quartile_zone: A quartile distribution index of the most expensive zip codes, where 1 means less expansive and 4 most expansive.

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.

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.

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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.

Housing Index in Hong Kong increased to 143.46 points in November 23 from 142.49 points in the previous week. This dataset provides - Hong Kong House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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.

The average Canadian house price declined slightly in 2023, after four years of consecutive growth. The average house price stood at ******* Canadian dollars in 2023 and was forecast to reach ******* Canadian dollars by 2026. Home sales on the rise The number of housing units sold is also set to increase over the two-year period. From ******* units sold, the annual number of home sales in the country is expected to rise to ******* in 2025. British Columbia and Ontario have traditionally been housing markets with prices above the Canadian average, and both are set to witness an increase in sales in 2025. How did Canadians feel about the future development of house prices? When it comes to consumer confidence in the performance of the real estate market in the next six months, Canadian consumers in 2024 mostly expected that the market would go up. A slightly lower share of the respondents believed real estate prices would remain the same.

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.

Content

The dataset consists of Price of Houses in King County , Washington from sales between May 2014 and May 2015. Along with house price it consists of information on 18 house features, date of sale and ID of sale.

Attribute information

1. id - Unique id for each home sold
2. date - Date of the home saled
3. price - Price of each home sold
4. bedrooms - Number of bedrooms
5. bathrooms - Number of bathrooms
6. sqft _ living - Square footage of the apartments interior living space
7. sqft _ lot - Square footage of the land space
8. floors - Number of floors
9. waterfront - A dummy variable for whether the apartment was overlooking the waterfront or not
10. view - An index from 0 to 4 of how good the view of the property was
11. condition - an index from 1 to 5 on the condition of the apartment
12. grade - An index from 1 to 13 , where 1-3falls short of building construction and design, 7 has an average level of construction and design , and 11-13 have a high quality level of construction and design
13. sqft _ above - the square footage of the interior housing space that is above ground level
14. sqft _ basement - the square footage of the inerior housing space that is below ground level
15. yr _ built - The year of the house was initially built
16. yr _ renovated - The year of the house's last renovation
17. zipcode - What zipcode area the house is in
18. lat - Lattitude
19. long - Longitude
20. sqft _ living15 - The square footage of inerior housing living space for the nearest nearest 15 neighbours
21. sqft _ lot15 - the square footage of the land lots of the nearest 15 neighbours

The number of U.S. home sales in the United States declined in 2024, after soaring in 2021. A total of four million transactions of existing homes, including single-family, condo, and co-ops, were completed in 2024, down from 6.12 million in 2021. According to the forecast, the housing market is forecast to head for recovery in 2025, despite transaction volumes expected to remain below the long-term average. Why have home sales declined? The housing boom during the coronavirus pandemic has demonstrated that being a homeowner is still an integral part of the American dream. Nevertheless, sentiment declined in the second half of 2022 and Americans across all generations agreed that the time was not right to buy a home. A combination of factors has led to house prices rocketing and making homeownership unaffordable for the average buyer. A survey among owners and renters found that the high home prices and unfavorable economic conditions were the two main barriers to making a home purchase. People who would like to purchase their own home need to save up a deposit, have a good credit score, and a steady and sufficient income to be approved for a mortgage. In 2022, mortgage rates experienced the most aggressive increase in history, making the total cost of homeownership substantially higher. Are U.S. home prices expected to fall? The median sales price of existing homes stood at 413,000 U.S. dollars in 2024 and was forecast to increase slightly until 2026. The development of the S&P/Case Shiller U.S. National Home Price Index shows that home prices experienced seven consecutive months of decline between June 2022 and January 2023, but this trend reversed in the following months. Despite mild fluctuations throughout the year, home prices in many metros are forecast to continue to grow, albeit at a much slower rate.

Key information about House Prices Growth

• Portugal house prices grew 17.2% YoY in Jun 2025, following an increase of 16.3% YoY in the previous quarter.
• YoY growth data is updated quarterly, available from Mar 2010 to Jun 2025, with an average growth rate of 10.4%.
• House price data reached an all-time high of 17.2% in Jun 2025 and a record low of -8.3% in Jun 2012.

Dataset Description:

This dataset has been meticulously pre-processed from the official UK government’s Price Paid Data, available for research purposes. The original dataset contains millions of rows spanning from 1995 to 2024, which posed significant challenges for machine learning operations due to its large size. For this project, we focused on house price predictions and filtered the data to only include transactions from 2015 to 2024. The final dataset contains 90,000 randomly sampled records, which should be ideal for training machine learning models efficiently. The goal of this dataset is to provide a well-structured, pre-processed dataset for students, researchers, and developers interested in creating house price prediction models using UK data. There are limited UK house price datasets available on Kaggle, so this contribution aims to fill that gap, offering a reliable dataset for dissertations, academic projects, or research purposes. This dataset is tailored for use in supervised learning models and has been cleaned, ensuring the removal of missing values and encoding of categorical variables. We hope this serves as a valuable resource for anyone studying house price prediction or real estate trends in the UK. In the future, I plan to provide an even larger dataset for more detailed and comprehensive predictions.

Features:

Feature Name - Description - Price - Sale price of the property (target variable). - Date - Date of the property transaction. Converted to datetime format for easier handling. - Postcode - Postcode of the property, offering location-based information. - property_type - Type of property (Detached, Semi-detached, Terraced, Flat, etc.). - new_build - Indicator whether the property was newly built at the time of sale (Yes or No). - freehold - Indicator whether the property was sold as freehold or leasehold (Freehold, Leasehold). - Street - Street name of the property location. - Locality - Locality of the property. - Town - Town or city where the property is located. - District - Administrative district of the property. - County - County where the property is located.

File Information:

The dataset is saved as a CSV file with 90,000 records, each representing a property transaction in the UK from 2015 to 2024. Feel free to explore this dataset and use it for any academic, research, or machine learning projects related to housing price predictions!

The UK house price index (UK HPI) represents changes in the value of UK residential properties (i.e., detached houses, semi-detached houses, terraced houses, flats and maisonettes) and indicates trends in the UK housing market. The UK HPI applies a hedonic regression model that utilises the various sources of data on property price (e.g., HM Land Registry's Price Paid dataset) to allow for a true comparison of UK property prices in each period. The data is sourced from the Office for National Statistics (ONS) and HM Land Registry, using house sales data from HM Land Registry, Registers of Scotland, and Land and Property Services Northern Ireland. Forecast data is estimated by IBISWorld, with reference to Office for Budget Responsibility (OBR) forecasts submitted in its 'Economic and fiscal outlook – March 2022' publication. The figures are presented with a base month in 2015 (i.e., January 2015 = 100) and are averages of the UK HPI over each financial year (i.e., April-March).

Dataset

This dataset was created by Engineer ImtiazAhmad

Released under CC0: Public Domain

Contents

Dataset includes house sale prices for King County in USA. Homes that are sold in the time period: May, 2014 and May, 2015.

Columns: - ida: notation for a house - date: Date house was sold - price: Price is prediction target - bedrooms: Number of Bedrooms/House - bathrooms: Number of bathrooms/House - sqft_living: square footage of the home - sqft_lot: square footage of the lot - floors: Total floors (levels) in house - waterfront: House which has a view to a waterfront - view: Has been viewed - condition: How good the condition is ( Overall ) - grade: overall grade given to the housing unit, based on King County grading system - sqft_abovesquare: footage of house apart from basement - sqft_basement: square footage of the basement - yr_built: Built Year - yr_renovated: Year when house was renovated - zipcode: zip - lat: Latitude coordinate - long: Longitude coordinate - sqft_living15: Living room area in 2015(implies-- some renovations) - sqft_lot15: lotSize area in 2015(implies-- some renovations)

Housing Index in Qatar decreased to 217.87 points in October from 226.08 points in September of 2025. This dataset provides - Qatar Housing Index- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Housing developers have navigated pronounced economic swings over the past five years, as borrowing environments and Federal Reserve rate policy have dictated industry growth and contraction. Early pandemic-era interest rate cuts and remote work fueled a boom in home building, especially in suburban and affordable regions, but subsequent rate hikes sharply reversed momentum. Developers enjoyed robust sales from projects initiated during the low-rate period, even as new housing starts declined under pressure from rising mortgage costs and weakening consumer demand. The struggle has been particularly acute for small and medium-sized housing developers, which continue to close their doors or merge as cost pressures mount and competition from large developers intensifies. Persistent labor shortages and escalating input costs, driven partly by tariffs, have prevented profit growth, boosting the market share and pricing power of prominent developers able to pass costs to buyers or access strategic partners. Overall, industry revenue has been increasing at a CAGR of 5.2% over the past five years to total an estimated $324.2 billion in 2025, including an estimated decrease of 0.7% in 2025. Single-family construction marked a bright spot in 2024, with leading developers like DR Horton capitalizing on demand for space and affordability. However, the pipeline for single-family projects has been hindered by high rates and tariff uncertainty that persisted throughout most of 2025. Multifamily development endured deeper contractions, particularly in 2023 and 2024, with vacancy rates and losses intensifying among even the largest developers before rebounding in 2025 as starts and demand recovered. Continued rate cuts by the Federal Reserve will set the stage for housing developers to regain growth momentum. Developers are poised to benefit from pent-up demand, housing shortages and renewed construction activity, particularly in the single-family segment, where affordability remains critical. However, rising material and labor costs will continue to pose operational challenges, leading developers to seek efficiencies or pass costs downstream. The expiration of federal green building credits in 2026 will prompt a rush to complete qualifying projects, but may curb longer-term investment in sustainable construction unless new incentives emerge. Expansions near newly announced manufacturing hubs are expanding, with developers acquiring land and prepping communities to meet workforce housing needs as the national focus on domestic manufacturing spurs regional population inflows and rising housing demand. Overall, industry revenue is forecast to climb at a CAGR of 1.8% to total an estimated $354.7 billion through the end of 2030.

China's Multi-City House Prices 2015-2023

Context

The purpose of this kernel is to predict the price of a house that a realtor can charge, or a customer can invest to buy a house by considering multiple input factors. Also, to classify the houses into Good and Excellent category based on the input variables by using best machine learning classification and regression algorithms with more efficiency.

Content

This dataset contains house sale prices for King County, which includes Seattle. It includes homes sold between May 2014 and May 2015. The dataset is pretty unbalanced with wide range of houses information that are built and renovated from the year 1990 to 2015. The dataset has total 21 variables including price,price, condition, number of bedrooms, bathrooms and other features of house.

Inspiration

I was inspired by the House sales dataset in King County, USA (https://www.kaggle.com/harlfoxem/housesalesprediction) and House Sales in Ontario (https://www.kaggle.com/mnabaee/ontarioproperties) datasets and the predictions and classifiers used.

Sale of Houses can go high and low depending on the market and multiple factors like location, number of bedrooms, year built etc. All these factors help in deriving the sale price of the house and grading of the house. Millions of houses information can be stored with all the details and factors in the historical timelines. Using machine learning techniques, we can analyze the data and predict the price of new houses and also classify the houses and fix a price value by calculating all the factors that directly or indirectly impact on the overall sale of house.

Companies operating in the third-party real estate industry have had to navigate numerous economic headwinds in recent years, notably rising interest rates, spiralling inflation and muted economic growth. Revenue is projected to sink at a compound annual rate of 0.6% over the five years through 2025, including an estimated jump of 1.2% in 2025 to €207.6 billion, while the average industry profit margin is forecast to reach 35.1%. Amid spiralling inflation, central banks across Europe ratcheted up interest rates, resulting in borrowing costs skyrocketing over the two years through 2023. In residential markets, elevated mortgage rates combined with tightening credit conditions eventually ate into demand, inciting a drop in house prices. Rental markets performed well when house prices were elevated (2021-2023), being the cheaper alternative for cash-strapped buyers. However, even lessors felt the pinch of rising mortgage rates, forcing them to hoist rent prices to cover costs and pricing out potential buyers. This led to a slowdown in rental markets in 2023, weighing on revenue growth. However, this has started to turn around in 2025 as interest rates have been falling across Europe in the two years through 2025, reducing borrowing costs for buyers and boosting property transactions. This has helped revenue to rebound slightly in 2025 as estate agents earn commission from property transactions. Revenue is forecast to swell at a compound annual rate of 3.7% over the five years through 2030 to €249.5 billion. Housing prices are recovering in 2025 as fixed-rate mortgages begin to drop and economic uncertainty subsides, aiding revenue growth in the short term. Over the coming years, PropTech—technology-driven innovations designed to improve and streamline the real estate industry—will force estate agents to adapt, shaking up the traditional real estate sector. A notable application of PropTech is the use of AI and data analytics to predict a home’s future value and speed up the process of retrofitting properties to become more sustainable.