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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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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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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.
Key Features:
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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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TwitterOur Price Paid Data includes information on all property sales in England and Wales that are sold for value and are lodged with us for registration.
Get up to date with the permitted use of our Price Paid Data:
check what to consider when using or publishing our Price Paid Data
If you use or publish our Price Paid Data, you must add the following attribution statement:
Contains HM Land Registry data © Crown copyright and database right 2021. This data is licensed under the Open Government Licence v3.0.
Price Paid Data is released under the http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/">Open Government Licence (OGL). You need to make sure you understand the terms of the OGL before using the data.
Under the OGL, HM Land Registry permits you to use the Price Paid Data for commercial or non-commercial purposes. However, OGL does not cover the use of third party rights, which we are not authorised to license.
Price Paid Data contains address data processed against Ordnance Survey’s AddressBase Premium product, which incorporates Royal Mail’s PAF® database (Address Data). Royal Mail and Ordnance Survey permit your use of Address Data in the Price Paid Data:
If you want to use the Address Data in any other way, you must contact Royal Mail. Email address.management@royalmail.com.
The following fields comprise the address data included in Price Paid Data:
The October 2025 release includes:
As we will be adding to the October data in future releases, we would not recommend using it in isolation as an indication of market or HM Land Registry activity. When the full dataset is viewed alongside the data we’ve previously published, it adds to the overall picture of market activity.
Your use of Price Paid Data is governed by conditions and by downloading the data you are agreeing to those conditions.
Google Chrome (Chrome 88 onwards) is blocking downloads of our Price Paid Data. Please use another internet browser while we resolve this issue. We apologise for any inconvenience caused.
We update the data on the 20th working day of each month. You can download the:
These include standard and additional price paid data transactions received at HM Land Registry from 1 January 1995 to the most current monthly data.
Your use of Price Paid Data is governed by conditions and by downloading the data you are agreeing to those conditions.
The data is updated monthly and the average size of this file is 3.7 GB, you can download:
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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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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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Twitterttd22/house-price dataset hosted on Hugging Face and contributed by the HF Datasets community
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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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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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📝 Dataset Description: This synthetic dataset contains 3,000 residential property listings modeled after real U.S. house sales data (in a Zillow-style format). It is designed for use in real estate analysis, machine learning, data visualization, and web scraping practice.
Each row represents a unique property and includes 16 key features commonly used by real estate agents, investors, and analysts. The data spans multiple U.S. states and cities, with realistic values for price, square footage, bedroom/bathroom count, property type, and more.
✅ Included Fields: Price – Listing price (in USD)
Address, City, State, Zipcode – U.S. formatted property location
Bedrooms, Bathrooms, Area (Sqft) – Core home specs
Lot Size, Year Built, Days on Market
Property Type, MLS ID, Listing Agent, Status
Listing URL – Mock Zillow-style property link
⚙️ Use Cases: Exploratory data analysis (EDA)
Regression/classification model training
Feature engineering and preprocessing
Real estate dashboards and web app mockups
Practice with BeautifulSoup, Pandas, or Power BI
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Annual house price data based on a sub-sample of the Regulated Mortgage Survey.
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TwitterIn 2022, house price growth in the UK slowed, after a period of decade-long increase. Nevertheless, in June 2025, prices reached a new peak, with the average home costing ******* British pounds. This figure refers to all property types, including detached, semi-detached, terraced houses, and flats and maisonettes. Compared to other European countries, the UK had some of the highest house prices. How have UK house prices increased over the last 10 years? Property prices have risen dramatically over the past decade. According to the UK house price index, the average house price has grown by over ** percent since 2015. This price development has led to the gap between the cost of buying and renting a property to close. In 2023, buying a three-bedroom house in the UK was no longer more affordable than renting one. Consequently, Brits have become more likely to rent longer and push off making a house purchase until they have saved up enough for a down payment and achieved the financial stability required to make the step. What caused the recent fluctuations in house prices? House prices are affected by multiple factors, such as mortgage rates, supply, and demand on the market. For nearly a decade, the UK experienced uninterrupted house price growth as a result of strong demand and a chronic undersupply. Homebuyers who purchased a property at the peak of the housing boom in July 2022 paid ** percent more compared to what they would have paid a year before. Additionally, 2022 saw the most dramatic increase in mortgage rates in recent history. Between December 2021 and December 2022, the **-year fixed mortgage rate doubled, adding further strain to prospective homebuyers. As a result, the market cooled, leading to a correction in pricing.
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Looking for a place to rent or buy a house in Lagos, Nigeria? This dataset can help you identify the best places to live in the city! It includes information on housing prices, property names, addresses, and neighborhoods. With this data, you can figure out which areas are the most (and least) profitable for renting or buying a home. So whether you're looking for your next home or investment property, this dataset is a great resource
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- 🚨 Your notebook can be here! 🚨!
If you're looking for information on housing prices in Lagos, Nigeria, this dataset is a great resource. It includes the price, property name, address, and neighborhood for each listing. This information can be used to identify the most and least profitable neighborhoods in Lagos
- This dataset can be used to identify the most and least expensive neighborhoods in Lagos, Nigeria.
- This dataset can be used to identify the best places to rent or buy a house in Lagos, Nigeria.
- This dataset can be used to identify the most and least profitable neighborhoods in Lagos for real estate investors
If you use this dataset in your research, please credit the original authors.
License
License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.
File: d.csv | Column name | Description | |:------------------|:--------------------------------------------| | Price | The price of the housing listing. (Numeric) | | Property_name | The name of the property. (String) | | Address | The address of the property. (String) |
File: rent.csv | Column name | Description | |:------------------|:--------------------------------------------| | Price | The price of the housing listing. (Numeric) | | Property_name | The name of the property. (String) | | Address | The address of the property. (String) |
File: rent_2.csv | Column name | Description | |:------------------|:--------------------------------------------| | Price | The price of the housing listing. (Numeric) | | Property_name | The name of the property. (String) | | Address | The address of the property. (String) |
File: sale.csv | Column name | Description | |:------------------|:--------------------------------------------| | Price | The price of the housing listing. (Numeric) | | Property_name | The name of the property. (String) | | Address | The address of the property. (String) |
File: sale_2.csv | Column name | Description | |:------------------|:--------------------------------------------| | Price | The price of the housing listing. (Numeric) | | Property_name | The name of the property. (String) | | Address | The address of the property. (String) |
If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit .
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Median Home Sale Price: All Residential: Bend, OR data was reported at 470.000 USD th in Jul 2020. This records an increase from the previous number of 430.000 USD th for Jun 2020. Median Home Sale Price: All Residential: Bend, OR data is updated monthly, averaging 331.000 USD th from Feb 2012 (Median) to Jul 2020, with 102 observations. The data reached an all-time high of 470.000 USD th in Jul 2020 and a record low of 170.000 USD th in Mar 2012. Median Home Sale Price: All Residential: Bend, OR 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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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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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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TwitterAverage house prices are derived from data supplied by the mortgage lending agencies on loans approved by them rather than loans paid. In comparing house prices figures from one period to another, account should be taken of the fact that changes in the mix of houses (incl apartments) will affect the average figures. The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change. Excluding apartments, measured in € Figure changed on the 27/6/16 as revised data received from the Local authority
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TwitterMexico'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.
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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.