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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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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.
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TwitterIn 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.
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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.
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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.
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This dataset provides values for AVERAGE HOUSE PRICES reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
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TwitterThe 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.
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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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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.
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Graph and download economic data for Housing Inventory: Median Listing Price in San Francisco-Oakland-Hayward, CA (CBSA) (MEDLISPRI41860) from Jul 2016 to Oct 2025 about San Francisco, CA, listing, median, price, and USA.
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TwitterHouse 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.
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This dataset was obtained from the StatLib repository: https://www.dcc.fc.up.pt/~ltorgo/Regression/cal_housing.html
The target variable is the median house value for California districts, expressed in hundreds of thousands of dollars ($100,000).
This dataset was derived from the 1990 U.S. census, using one row per census block group. A block group is the smallest geographical unit for which the U.S. Census Bureau publishes sample data (a block group typically has a population of 600 to 3,000 people).
A household is a group of people residing within a home. Since the average number of rooms and bedrooms in this dataset are provided per household, these columns may take surprisingly large values for block groups with few households and many empty houses, such as vacation resorts.
The dataset can also be downloaded/loaded using the sklearn.datasets.fetch_california_housing function.
Pace, R. Kelley and Ronald Barry, Sparse Spatial Autoregressions, Statistics and Probability Letters, 33 (1997) 291-297
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Median price paid for new residential property in England and Wales, by property type and administrative geographies. Quarterly rolling annual data. Formerly HPSSA dataset 10.
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Graph and download economic data for Housing Inventory: Median Listing Price in Dallas-Fort Worth-Arlington, TX (CBSA) (MEDLISPRI19100) from Jul 2016 to Oct 2025 about Dallas, TX, listing, median, price, and USA.
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Average House Price
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Graph and download economic data for Housing Inventory: Average Listing Price in New Jersey (AVELISPRINJ) from Jul 2016 to Oct 2025 about NJ, average, listing, price, and USA.
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Graph and download economic data for All-Transactions House Price Index for Colorado Springs, CO (MSA) (ATNHPIUS17820Q) from Q1 1979 to Q3 2025 about Colorado Springs, CO, appraisers, HPI, housing, price index, indexes, price, and USA.
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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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Key information about House Prices Growth
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Key information about House Prices Growth
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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.