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Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q2 2025 about sales, median, housing, and USA.
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Key information about House Prices Growth
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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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Graph and download economic data for Average Sales Price of Houses Sold for the United States (ASPUS) from Q1 1963 to Q2 2025 about sales, housing, and USA.
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TwitterThe 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.
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Key information about House Prices Growth
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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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The dataset contains 2000 rows of house-related data, representing various features that could influence house prices. Below, we discuss key aspects of the dataset, which include its structure, the choice of features, and potential use cases for analysis.
The dataset is designed to capture essential attributes for predicting house prices, including:
Area: Square footage of the house, which is generally one of the most important predictors of price. Bedrooms & Bathrooms: The number of rooms in a house significantly affects its value. Homes with more rooms tend to be priced higher. Floors: The number of floors in a house could indicate a larger, more luxurious home, potentially raising its price. Year Built: The age of the house can affect its condition and value. Newly built houses are generally more expensive than older ones. Location: Houses in desirable locations such as downtown or urban areas tend to be priced higher than those in suburban or rural areas. Condition: The current condition of the house is critical, as well-maintained houses (in 'Excellent' or 'Good' condition) will attract higher prices compared to houses in 'Fair' or 'Poor' condition. Garage: Availability of a garage can increase the price due to added convenience and space. Price: The target variable, representing the sale price of the house, used to train machine learning models to predict house prices based on the other features.
Area Distribution: The area of the houses in the dataset ranges from 500 to 5000 square feet, which allows analysis across different types of homes, from smaller apartments to larger luxury houses. Bedrooms and Bathrooms: The number of bedrooms varies from 1 to 5, and bathrooms from 1 to 4. This variance enables analysis of homes with different sizes and layouts. Floors: Houses in the dataset have between 1 and 3 floors. This feature could be useful for identifying the influence of multi-level homes on house prices. Year Built: The dataset contains houses built from 1900 to 2023, giving a wide range of house ages to analyze the effects of new vs. older construction. Location: There is a mix of urban, suburban, downtown, and rural locations. Urban and downtown homes may command higher prices due to proximity to amenities. Condition: Houses are labeled as 'Excellent', 'Good', 'Fair', or 'Poor'. This feature helps model the price differences based on the current state of the house. Price Distribution: Prices range between $50,000 and $1,000,000, offering a broad spectrum of property values. This range makes the dataset appropriate for predicting a wide variety of housing prices, from affordable homes to luxury properties.
3. Correlation Between Features
A key area of interest is the relationship between various features and house price: Area and Price: Typically, a strong positive correlation is expected between the size of the house (Area) and its price. Larger homes are likely to be more expensive. Location and Price: Location is another major factor. Houses in urban or downtown areas may show a higher price on average compared to suburban and rural locations. Condition and Price: The condition of the house should show a positive correlation with price. Houses in better condition should be priced higher, as they require less maintenance and repair. Year Built and Price: Newer houses might command a higher price due to better construction standards, modern amenities, and less wear-and-tear, but some older homes in good condition may retain historical value. Garage and Price: A house with a garage may be more expensive than one without, as it provides extra storage or parking space.
The dataset is well-suited for various machine learning and data analysis applications, including:
House Price Prediction: Using regression techniques, this dataset can be used to build a model to predict house prices based on the available features. Feature Importance Analysis: By using techniques such as feature importance ranking, data scientists can determine which features (e.g., location, area, or condition) have the greatest impact on house prices. Clustering: Clustering techniques like k-means could help identify patterns in the data, such as grouping houses into segments based on their characteristics (e.g., luxury homes, affordable homes). Market Segmentation: The dataset can be used to perform segmentation by location, price range, or house type to analyze trends in specific sub-markets, like luxury vs. affordable housing. Time-Based Analysis: By studying how house prices vary with the year built or the age of the house, analysts can derive insights into the trends of older vs. newer homes.
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TwitterThe year-end value of the S&P Case Shiller National Home Price Index amounted to 321.45 in 2024. The index value was equal to 100 as of January 2000, so if the index value is equal to 130 in a given year, for example, it means that the house prices increased by 30 percent since 2000. S&P/Case Shiller U.S. home indices – additional informationThe S&P Case Shiller National Home Price Index is calculated on a monthly basis and is based on the prices of single-family homes in nine U.S. Census divisions: New England, Middle Atlantic, East North Central, West North Central, South Atlantic, East South Central, West South Central, Mountain and Pacific. The index is the leading indicator of the American housing market and one of the indicators of the state of the broader economy. The index illustrates the trend of home prices and can be helpful during house purchase decisions. When house prices are rising, a house buyer might want to speed up the house purchase decision as the transaction costs can be much higher in the future. The S&P Case Shiller National Home Price Index has been on the rise since 2011.The S&P Case Shiller National Home Price Index is one of the indices included in the S&P/Case-Shiller Home Price Index Series. Other indices are the S&P/Case Shiller 20-City Composite Home Price Index, the S&P/Case Shiller 10-City Composite Home Price Index and twenty city composite indices.
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TwitterThe UK House Price Index is a National Statistic.
Download the full UK House Price Index data below, or use our tool to https://landregistry.data.gov.uk/app/ukhpi?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=tool&utm_term=9.30_20_09_23" class="govuk-link">create your own bespoke reports.
Datasets are available as CSV files. Find out about republishing and making use of the data.
Google Chrome is blocking downloads of our UK HPI data files (Chrome 88 onwards). Please use another internet browser while we resolve this issue. We apologise for any inconvenience caused.
This file includes a derived back series for the new UK HPI. Under the UK HPI, data is available from 1995 for England and Wales, 2004 for Scotland and 2005 for Northern Ireland. A longer back series has been derived by using the historic path of the Office for National Statistics HPI to construct a series back to 1968.
Download the full UK HPI background file:
If you are interested in a specific attribute, we have separated them into these CSV files:
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Average-prices-2023-07.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=average_price&utm_term=9.30_20_09_23" class="govuk-link">Average price (CSV, 9.3MB)
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Average-prices-Property-Type-2023-07.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=average_price_property_price&utm_term=9.30_20_09_23" class="govuk-link">Average price by property type (CSV, 28MB)
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Sales-2023-07.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=sales&utm_term=9.30_20_09_23" class="govuk-link">Sales (CSV, 4.9MB)
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Cash-mortgage-sales-2023-07.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=cash_mortgage-sales&utm_term=9.30_20_09_23" class="govuk-link">Cash mortgage sales (CSV, 6.8MB)
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/First-Time-Buyer-Former-Owner-Occupied-2023-07.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=FTNFOO&utm_term=9.30_20_09_23" class="govuk-link">First time buyer and former owner occupier (CSV, 6.5MB)
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/New-and-Old-2023-07.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=new_build&utm_term=9.30_20_09_23" class="govuk-link">New build and existing resold property (CSV, 17MB)
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Indices-2023-07.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=index&utm_term=9.30_20_09_23" class="govuk-link">Index (CSV, 6MB)
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Indices-seasonally-adjusted-2023-07.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=index_season_adjusted&utm_term=9.30_20_09_23" class="govuk-link">Index seasonally adjusted (CSV, 207KB)
http://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Average-price-seasonally-adjusted-2023-07.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=average-price_season_adjusted&utm_term=9.30_20_09_23" class="govuk-link">Average price seasonally adjuste
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TwitterDescription: This dataset provides historical housing prices scraped from Centaline Property Hong Kong, one of the largest real estate agencies in Hong Kong. The dataset includes information on the date of the transaction, the property address, floor plan, saleable area, unit rate, source, and district. The dataset covers a period of time spanning several years, allowing for analysis of trends and changes in the Hong Kong housing market.
Columns: Date: the date of the property transaction Address: the address of the property Floor Plan: -- Price: the price of the property Changes: any changes made to the property since the last transaction Saleable Area: the area of the property that can be sold to a buyer Unit Rate: the price per square foot of saleable area Source: the source of the data (Centaline Property Hong Kong/ Land Registry) District: the district in which the property is located in Hong Kong
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Housing Index in the United States decreased to 435.40 points in September from 435.60 points in August of 2025. This dataset provides the latest reported value for - United States House Price Index MoM Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
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TwitterThe FHFA House Price Index (FHFA HPI®) is the nation’s only collection of public, freely available house price indexes that measure changes in single-family home values based on data from all 50 states and over 400 American cities that extend back to the mid-1970s. The FHFA HPI incorporates tens of millions of home sales and offers insights about house price fluctuations at the national, census division, state, metro area, county, ZIP code, and census tract levels. FHFA uses a fully transparent methodology based upon a weighted, repeat-sales statistical technique to analyze house price transaction data. What does the FHFA HPI represent? The FHFA HPI is a broad measure of the movement of single-family house prices. The FHFA HPI is a weighted, repeat-sales index, meaning that it measures average price changes in repeat sales or refinancings on the same properties. This information is obtained by reviewing repeat mortgage transactions on single-family properties whose mortgages have been purchased or securitized by Fannie Mae or Freddie Mac since January 1975. The FHFA HPI serves as a timely, accurate indicator of house price trends at various geographic levels. Because of the breadth of the sample, it provides more information than is available in other house price indexes. It also provides housing economists with an improved analytical tool that is useful for estimating changes in the rates of mortgage defaults, prepayments and housing affordability in specific geographic areas. U.S. Federal Housing Finance Agency, All-Transactions House Price Index for Connecticut [CTSTHPI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CTSTHPI, August 2, 2023.
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Housing Index in Sweden increased to 959 points in the third quarter of 2025 from 945 points in the second quarter of 2025. This dataset provides - Sweden House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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TwitterThe 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.
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Graph and download economic data for All-Transactions House Price Index for Massachusetts (MASTHPI) from Q1 1975 to Q3 2025 about MA, appraisers, HPI, housing, price index, indexes, price, and USA.
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TwitterThe 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.
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Graph and download economic data for All-Transactions House Price Index for Los Angeles County, CA (ATNHPIUS06037A) from 1975 to 2024 about Los Angeles County, CA; Los Angeles; CA; HPI; housing; price index; indexes; price; and USA.
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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.
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Graph and download economic data for All-Transactions House Price Index for Florida (FLSTHPI) from Q1 1975 to Q3 2025 about appraisers, FL, HPI, housing, price index, indexes, price, and USA.
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Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q2 2025 about sales, median, housing, and USA.