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This dataset provides a comprehensive snapshot of the Texas real estate market as of 2024, featuring a curated selection of 500 property listings. It encompasses a wide array of properties, reflecting the diverse real estate landscape across Texas. This dataset serves as a foundational tool for understanding market dynamics, property valuations, and regional housing trends within the state.
Given its breadth and depth, this dataset is poised to facilitate a multitude of data science applications. Researchers and analysts can leverage this dataset for exploratory data analysis (EDA) to identify patterns, trends, and anomalies within the Texas real estate market. It is particularly suited for regression analyses to predict property prices based on various features, classification tasks to categorize properties into different market segments, and geographical data analysis to understand regional market dynamics. Despite the dataset's modest size, it offers a rich source for machine learning models aimed at providing insights into price determinants and market trends, ensuring practical applications remain within realistic and achievable bounds.
url: Web address for the property listing on Realtor.com.status: Current status of the listing, indicating availability.id: Unique identifier for each property listing.listPrice: The asking price for the property.baths: Total number of bathrooms, including partials.baths_full: Number of full bathrooms.baths_full_calc: Calculated number of full bathrooms, for consistency.beds: Number of bedrooms in the property.sqft: Total square footage of the property.stories: Number of levels or floors in the property.sub_type: Specific sub-category of the property, if applicable.text: Descriptive narrative provided for the property listing.type: General category of the property (e.g., single-family, condo).year_built: Year the property was constructed.This dataset has been meticulously compiled, adhering to ethical standards and ensuring all data is sourced from publicly available information. It respects privacy and copyright considerations, utilizing data that is openly accessible and intended for public consumption.
Gratitude is extended to Realtor.com for serving as an invaluable resource in the compilation of this dataset. The platform's commitment to providing comprehensive and accessible real estate data has significantly contributed to the depth and quality of this dataset.
The dataset thumbnail image is credited to Realtor.com, as featured on their official Facebook page. The image serves as a visual representation of the diverse and dynamic nature of the Texas real estate market, captured in this comprehensive dataset. View Image
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This dataset contains detailed information on current real estate listings in Houston, Texas, sourced from Zillow, and provides a comprehensive snapshot of the Houston housing market as of 5th June 2024.
The data was extracted from Zillow using a combination of two scraping tools from Apify: Zillow ZIP Code Scraper ๐ https://apify.com/maxcopell/zillow-zip-search and Zillow Details Scraper ๐ https://apify.com/maxcopell/zillow-detail-scraper.
The data includes key details for each listing for sale, such as:
With 25,900 current listings, this dataset is ideal for in-depth analysis of the Houston housing market and the Houston real estate market. Potential use cases include:
Whether you're a real estate professional, market researcher, data scientist, or just curious about the Houston housing market, this dataset provides a wealth of information to explore. You can start investigating Houston real estate today.
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View monthly updates and historical trends for Case-Shiller Home Price Index: Dallas, TX. Source: Standard and Poor's. Track economic data with YCharts anโฆ
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Graph and download economic data for Housing Inventory: Median Listing Price per Square Feet in Texas (MEDLISPRIPERSQUFEETX) from Jul 2016 to Oct 2025 about square feet, TX, listing, median, price, and USA.
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TwitterThe average price per square foot of floor space in new single-family housing in the United States decreased after the great financial crisis, followed by several years of stagnation. Since 2012, the price has continuously risen, hitting ****** U.S. dollars per square foot in 2024. In 2024, the average sales price of a new home exceeded ******* U.S. dollars. Development of house sales in the U.S. One of the reasons for rising property prices is the gradual growth of house sales between 2011 and 2020. This period was marked by the gradual recovery following the subprime mortgage crisis and a growing housing sentiment. Another significant factor for the housing demand was the growing number of new household formations each year. Despite this trend, housing transactions plummeted in 2021, amid soaring prices and borrowing costs. In 2021, the average construction cost for single-family housing rose by nearly ** percent year-on-year, and in 2022, the increase was even higher, at close to ** percent. Financing a house purchase Mortgage interest rates in the U.S. rose dramatically in 2022 and remained elevated until 2024. In 2020, a homebuyer could lock in a 30-year fixed interest rate of under ***** percent, whereas in 2024, the average rate for the same mortgage type was more than twice higher. That has led to a decline in homebuyer sentiment, and an increasing share of the population pessimistic about buying a home in the current market.
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TwitterVITAL SIGNS INDICATOR Home Prices (EC7)
FULL MEASURE NAME Home Prices
LAST UPDATED August 2019
DESCRIPTION Home prices refer to the cost of purchasing oneโs own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.
DATA SOURCE Zillow Median Sale Price (1997-2018) http://www.zillow.com/research/data/
Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1997-2018; specific to each metro area) http://data.bls.gov
CONTACT INFORMATION vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator) Median housing price estimates for the region, counties, cities, and zip code come from analysis of individual home sales by Zillow. The median sale price is the price separating the higher half of the sales from the lower half. In other words, 50 percent of home sales are below or above the median value. Zillow defines all homes as single-family residential, condominium, and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that you own in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums where the homeowners own shares in the corporation that owns the building, not the actual units themselves.
For metropolitan area comparison values, the Bay Area metro areaโs median home sale price is the population-weighted average of the nine countiesโ median home prices. Home sales prices are not reliably available for Houston, because Texas is a non-disclosure state. For more information on non-disclosure states, see: http://www.zillow.com/blog/chronicles-of-data-collection-ii-non-disclosure-states-3783/
Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.
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TwitterVITAL SIGNS INDICATOR Home Prices (EC7)
FULL MEASURE NAME Home Prices
LAST UPDATED August 2019
DESCRIPTION Home prices refer to the cost of purchasing oneโs own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.
DATA SOURCE Zillow Median Sale Price (1997-2018) http://www.zillow.com/research/data/
Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1997-2018; specific to each metro area) http://data.bls.gov
CONTACT INFORMATION vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator) Median housing price estimates for the region, counties, cities, and zip code come from analysis of individual home sales by Zillow. The median sale price is the price separating the higher half of the sales from the lower half. In other words, 50 percent of home sales are below or above the median value. Zillow defines all homes as single-family residential, condominium, and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that you own in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums where the homeowners own shares in the corporation that owns the building, not the actual units themselves.
For metropolitan area comparison values, the Bay Area metro areaโs median home sale price is the population-weighted average of the nine countiesโ median home prices. Home sales prices are not reliably available for Houston, because Texas is a non-disclosure state. For more information on non-disclosure states, see: http://www.zillow.com/blog/chronicles-of-data-collection-ii-non-disclosure-states-3783/
Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.
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TwitterState-average cost ranges and payer responsibility for each common real-estate closing fee in Texas.
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The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of property tax rates for each city in Harris County, Texas. It's important to understand that tax rates can vary greatly and can change yearly.
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License information was derived automatically
The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of mortgage rates for each city in Harris County, Texas. It's important to understand that mortgage rates can vary greatly and can change yearly.
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TwitterThe monthly rent of mobile homes in the U.S. has gradually increased since 2010, peaking in 2024. In the third quarter of that year, the average monthly rent for manufactured homes was *** U.S. dollars. Similarly, apartment rents also soared in 2022, followed by a slight decline in the next two years. Where in the U.S. are manufactured homes most popular? States with a growing economy and large population provide the best opportunities for manufactured housing. In September 2023, Texas had the highest number of mobile homes in the United States. Other states with a high number of mobile homes were North Carolina and Florida. Moreover, Texas also boasted the highest number of manufactured home production plants. Affordability of mobile homes across the U.S. Manufactured homes are considerably less expensive than regular homes, which makes them an attractive option for people looking to purchase property without breaking the bank. Mobile homes are cheaper because manufacturers benefit from economies of scale due to large-scale production, which allows them to lower costs per unit. Additionally, mobile homes lose value faster than traditional homes, which can make them more affordable to purchase initially. The average sales price for a new mobile home has been on the rise, but during the housing boom in 2021, it increased dramatically.
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TwitterOpen Data Commons Attribution License (ODC-By) v1.0https://www.opendatacommons.org/licenses/by/1.0/
License information was derived automatically
This dataset provides a comprehensive snapshot of the Texas real estate market as of 2024, featuring a curated selection of 500 property listings. It encompasses a wide array of properties, reflecting the diverse real estate landscape across Texas. This dataset serves as a foundational tool for understanding market dynamics, property valuations, and regional housing trends within the state.
Given its breadth and depth, this dataset is poised to facilitate a multitude of data science applications. Researchers and analysts can leverage this dataset for exploratory data analysis (EDA) to identify patterns, trends, and anomalies within the Texas real estate market. It is particularly suited for regression analyses to predict property prices based on various features, classification tasks to categorize properties into different market segments, and geographical data analysis to understand regional market dynamics. Despite the dataset's modest size, it offers a rich source for machine learning models aimed at providing insights into price determinants and market trends, ensuring practical applications remain within realistic and achievable bounds.
url: Web address for the property listing on Realtor.com.status: Current status of the listing, indicating availability.id: Unique identifier for each property listing.listPrice: The asking price for the property.baths: Total number of bathrooms, including partials.baths_full: Number of full bathrooms.baths_full_calc: Calculated number of full bathrooms, for consistency.beds: Number of bedrooms in the property.sqft: Total square footage of the property.stories: Number of levels or floors in the property.sub_type: Specific sub-category of the property, if applicable.text: Descriptive narrative provided for the property listing.type: General category of the property (e.g., single-family, condo).year_built: Year the property was constructed.This dataset has been meticulously compiled, adhering to ethical standards and ensuring all data is sourced from publicly available information. It respects privacy and copyright considerations, utilizing data that is openly accessible and intended for public consumption.
Gratitude is extended to Realtor.com for serving as an invaluable resource in the compilation of this dataset. The platform's commitment to providing comprehensive and accessible real estate data has significantly contributed to the depth and quality of this dataset.
The dataset thumbnail image is credited to Realtor.com, as featured on their official Facebook page. The image serves as a visual representation of the diverse and dynamic nature of the Texas real estate market, captured in this comprehensive dataset. View Image