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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?
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.
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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.
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Key information about House Prices Growth
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Twitterttd22/house-price dataset hosted on Hugging Face and contributed by the HF Datasets community
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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.
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Average House Prices in the United States increased to 534100 USD in August from 478200 USD in July of 2025. This dataset includes a chart with historical data for the United States New Home Average Sales Price.
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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.
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View monthly updates and historical trends for US House Price Index. from United States. Source: Federal Housing Finance Agency. Track economic data with …
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View monthly updates and historical trends for US Existing Home Median Sales Price. from United States. Source: National Association of Realtors. Track ec…
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TwitterHouse prices in the second most populous state in the United States, Texas, have increased more than two-fold since 2011. In 2023, the median house price reached ******* U.S. dollars, a decrease of *** percent from the previous year. Texas is one of the more affordable states for buying a home with house prices below the national average.
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This dataset was created by ditsa pandey
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Single Family Home Prices in the United States increased to 415200 USD in October from 412300 USD in September of 2025. This dataset provides - United States Existing Single Family Home Prices- actual values, historical data, forecast, chart, statistics, economic calendar and news.
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TwitterThe U.S. housing market has seen significant price growth since 2011, with the median sales price of existing single-family homes reaching a record high of ******* U.S. dollars in 2024. This represents a substantial increase of ******* over the past five years, highlighting the rapid appreciation of home values across the country. The trend of rising prices can also be observed in the new homes sold. Regional variations and housing shortage While the national median price provides a broad overview, regional differences in home prices are notable. The West remains the most expensive region, with prices twice higher than in the more affordable Midwest. This disparity persists despite efforts to increase housing supply. In 2024, approximately ******* building permits for single-family housing units were granted, showing a slight increase from previous years but still well below the 2005 peak of **** million permits. The ongoing housing shortage continues to drive prices upward across all regions. Market dynamics and future outlook The number of existing home sales has plummeted since 2020, reflecting the growing cost of homeownership. Factors such as high home prices, unfavorable economic conditions, and aggressive increases in mortgage rates have contributed to affordability challenges for many potential homebuyers. Despite these challenges, forecasts suggest a potential recovery in the housing market by 2025, though transaction volumes are expected to remain below long-term averages.
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Case-Shiller Index of US residential house prices. Data comes from S&P Case-Shiller data and includes both the national index and the indices for 20 metropolitan regions. The indices are created us...
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TwitterThe median sales price of new homes sold in the United States increased steadily from 1965 to 2022, followed by two years of decline. In 2024, a newly built home cost approximately ******* U.S. dollars. That was a decline from the peak price of 434,500 U.S. dollars in 2022. Prices varied greatly across different regions in the country, with the most expensive housing found in the Northeast region.
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TwitterMontevideo, 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.
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TwitterThe S&P Case Shiller Cleveland Home Price Index has increased steadily in recent years. The index measures changes in the prices of existing single-family homes. The index value was equal to 100 as of January 2000, so if the index value is equal to *** in a given month, for example, it means that the house prices have increased by ** percent since 2000. The value of the S&P Case Shiller Cleveland Home Price Index amounted to ****** in August 2024. That was significantly below the national average.
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Residential Property Prices in the United States increased 1.66 percent in June of 2025 over the same month in the previous year. This dataset includes a chart with historical data for the United States Residential Property Prices.
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The Housing Data Extracted from Homes.com (USA) dataset is a comprehensive collection of 2 million real estate listings sourced from Homes.com, one of the leading real estate platforms in the United States. This dataset offers detailed insights into the U.S. housing market, making it an invaluable resource for real estate professionals, investors, researchers, and analysts.
The dataset contains extensive property details, including location, price, property type (single-family homes, condos, apartments), number of bedrooms and bathrooms, square footage, lot size, year built, and availability status. Organized in CSV format, it provides users with easy access to structured data for analyzing trends, developing investment strategies, or building real estate applications.
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Graph and download economic data for All-Transactions House Price Index for Dallas-Plano-Irving, TX (MSAD) (ATNHPIUS19124Q) from Q4 1975 to Q3 2025 about Dallas, appraisers, TX, HPI, housing, price index, indexes, price, and USA.
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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?
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.