Graph and download economic data for Housing Inventory: Price Reduced Count in the United States (PRIREDCOUUS) from Jul 2016 to Oct 2025 about reduced count, price, and USA.

About Dataset

All the following text is copied directly from the original dataset used: https://www.kaggle.com/datasets/fedesoriano/the-boston-houseprice-data
The only difference is that features 12 and 13 have been removed for simplicity. See original link for a version with those features in place.

Similar Datasets

Gender Pay Gap Dataset: https://www.kaggle.com/fedesoriano/gender-pay-gap-dataset
California Housing Prices Data (5 new features!): https://www.kaggle.com/fedesoriano/california-housing-prices-data-extra-features
Company Bankruptcy Prediction: https://www.kaggle.com/fedesoriano/company-bankruptcy-prediction
Spanish Wine Quality Dataset: https://www.kaggle.com/datasets/fedesoriano/spanish-wine-quality-dataset

Context

The Boston house-price data of Harrison, D. and Rubinfeld, D.L. 'Hedonic prices and the demand for clean air', J. Environ. Economics & Management, vol.5, 81-102, 1978.

Attribute Information

Input features in order: 1) CRIM: per capita crime rate by town
2) ZN: proportion of residential land zoned for lots over 25,000 sq.ft.
3) INDUS: proportion of non-retail business acres per town
4) CHAS: Charles River dummy variable (1 if tract bounds river; 0 otherwise)
5) NOX: nitric oxides concentration (parts per 10 million) [parts/10M]
6) RM: average number of rooms per dwelling
7) AGE: proportion of owner-occupied units built prior to 1940
8) DIS: weighted distances to five Boston employment centres
9) RAD: index of accessibility to radial highways
10) TAX: full-value property-tax rate per $10,000 [$/10k]
11) PTRATIO: pupil-teacher ratio by town
[Original features 12 and 13 have been deliberately removed from this version of the dataset]

Output variable:
1) MEDV: Median value of owner-occupied homes in $1000's [k$]

Source

StatLib - Carnegie Mellon University

Relevant Papers

Harrison, David & Rubinfeld, Daniel. (1978). Hedonic housing prices and the demand for clean air. Journal of Environmental Economics and Management. 5. 81-102. 10.1016/0095-0696(78)90006-2. https://www.researchgate.net/profile/Daniel-Rubinfeld/publication/4974606_Hedonic_housing_prices_and_the_demand_for_clean_air/links/5c38ce85458515a4c71e3a64/Hedonic-housing-prices-and-the-demand-for-clean-air.pdf

Belsley, David A. & Kuh, Edwin. & Welsch, Roy E. (1980). Regression diagnostics: identifying influential data and sources of collinearity. New York: Wiley https://www.wiley.com/en-us/Regression+Diagnostics%3A+Identifying+Influential+Data+and+Sources+of+Collinearity-p-9780471691174

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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.

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.

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.

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.

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.

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.

Housing Index in China remained unchanged at -2.20 percent in October. This dataset provides the latest reported value for - China Newly Built House Prices YoY Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Portugal, Italy, Ireland, Greece, and Spain were widely considered the Eurozone's weakest economies during the Great Recession and subsequent Eurozone debt crisis. These countries were grouped together due to the similarities in their economic crises, with much of them driven by house price bubbles which had inflated over the early 2000s, before bursting in 2007 due to the Global Financial Crisis. Entry into the Euro currency by 2002 had meant that banks could lend to house buyers in these countries at greatly reduced rates of interest.

This reduction in the cost of financing contributed to creating housing bubbles, which were further boosted by pro-cyclical housing policies among many of the countries' governments. In spite of these economies experiencing similar economic problems during the crisis, Italy and Portugal did not experience housing bubbles in the same way in which Greece, Ireland, and Spain did. In the latter countries, their real housing prices (which are adjusted for inflation) peaked in 2007, before quickly declining during the recession. In particular, house prices in Ireland dropped by over 40 percent from their peak in 2007 to 2011.

Graph and download economic data for Housing Inventory: Price Reduced Count in Miami-Dade County, FL (PRIREDCOU12086) from Jul 2016 to Oct 2025 about Miami-Dade County, FL; reduced count; Miami; FL; price; and USA.

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.

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.

Housing Index in Germany increased to 220.43 points in October from 219.91 points in September of 2025. This dataset provides the latest reported value for - Germany House Price Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

House Price Index YoY in Indonesia decreased to 0.84 percent in the third quarter of 2025 from 0.90 percent in the second quarter of 2025. This dataset includes a chart with historical data for Indonesia House Price Index YoY.

Graph and download economic data for Housing Inventory: Price Reduced Count in Androscoggin County, ME (PRIREDCOU23001) from Jul 2016 to Oct 2025 about Androscoggin County, ME; Lewiston; reduced count; ME; price; and USA.

Housing Inventory: Price Reduced Count Year-Over-Year in Milwaukee County, WI was 17.89% in October of 2025, according to the United States Federal Reserve. Historically, Housing Inventory: Price Reduced Count Year-Over-Year in Milwaukee County, WI reached a record high of 90.54 in July of 2021 and a record low of -54.86 in February of 2021. Trading Economics provides the current actual value, an historical data chart and related indicators for Housing Inventory: Price Reduced Count Year-Over-Year in Milwaukee County, WI - last updated from the United States Federal Reserve on November of 2025.

Mexico's housing market demonstrates significant regional price variations, with Mexico City emerging as the most expensive area for residential property in the third quarter of 2025. The capital city's average house price of 3.93 million Mexican pesos far exceeds the national average of 1.86 million pesos, highlighting the stark contrast in property values across the country. This disparity reflects broader economic and demographic trends shaping Mexico's real estate landscape. Sustained growth in housing prices The Mexican housing market has experienced substantial growth over the past decade, with home prices more than doubling since 2010. By the second quarter of 2025, the nominal house price index reached 287 points, representing a 187 percent increase from the baseline year. Even when adjusted for inflation, the real house price index showed a notable 50 percent growth, underscoring the market's resilience and attractiveness to investors. The mortgage market is dominated by three main player types: Infonavit, Fovissste, and commercial banks including Sofomes. In 2023, Infonavit, a scheme by Mexico's National Housing Fund Institute which provides lending to workers in the formal sector, was responsible for the majority of mortgages granted to individuals. Challenges in mortgage lending Despite the overall growth in housing prices, Mexico's mortgage market has faced challenges in recent years. The number of new mortgage loans granted has declined over the past decade, falling by approximately 200,000 loans between 2008 and 2023. This decrease in lending activity may be attributed to various factors, including economic uncertainties and changing consumer preferences. The state of Mexico, which is home to 13 percent of the country's population, likely plays a significant role in shaping these trends given its large demographic influence on the national housing market.

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.

Existing Home Sales in the United States increased to 4100 Thousand in October from 4050 Thousand in September of 2025. This dataset provides the latest reported value for - United States Existing Home Sales - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.