100+ datasets found
  1. Housing Real Estate Data from Indian Cities

    • kaggle.com
    zip
    Updated Dec 8, 2022
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    Rakkesh Aravind G (2022). Housing Real Estate Data from Indian Cities [Dataset]. https://www.kaggle.com/datasets/rakkesharv/real-estate-data-from-7-indian-cities
    Explore at:
    zip(1671735 bytes)Available download formats
    Dataset updated
    Dec 8, 2022
    Authors
    Rakkesh Aravind G
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    India
    Description

    Real Estate / Housing Dataset

    This dataset is web scrapped from a real estate website, collecting all the necessary infos on the resale and new properties. It has around 14000+ rows of data having properties from various Indian cities like Chennai, Mumbai, Bangalore, Delhi, Pune, Kolkata and Hyderabad. Columns:

    Name: Property Name, Property Title: Property Ad Title, Price: Property Price Location: Property Located Locality and Region Total Area: Total SQFT of the property Price Per SQFT: Price of Per SQFT of the property Description: Small paragraph about the property Baths: Number of baths in the property Balcony: Whether the Property has balcony or not

  2. b

    Real Estate Dataset

    • brightdata.com
    .json, .csv, .xlsx
    Updated Sep 11, 2022
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    Bright Data (2022). Real Estate Dataset [Dataset]. https://brightdata.com/products/datasets/real-estate
    Explore at:
    .json, .csv, .xlsxAvailable download formats
    Dataset updated
    Sep 11, 2022
    Dataset authored and provided by
    Bright Data
    License

    https://brightdata.com/licensehttps://brightdata.com/license

    Area covered
    Worldwide
    Description

    Real estate datasets from various websites cover all major real estate data points including: property type, size, location, price, bedrooms, baths, address, history, images, and much more. Popular use cases include: forecast housing demand, analyze price fluctuations, improve customer satisfaction, see past prices to monitor market trends, and more.

  3. Zillow: Real Estate Data

    • kaggle.com
    zip
    Updated Nov 30, 2024
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    Tony Gordon Jr. (2024). Zillow: Real Estate Data [Dataset]. https://www.kaggle.com/datasets/tonygordonjr/zillow-real-estate-data
    Explore at:
    zip(16472355 bytes)Available download formats
    Dataset updated
    Nov 30, 2024
    Authors
    Tony Gordon Jr.
    Description

    Hello my fellow data enthusiasts! I'm back!

    My journey into the world of real estate data has been nothing short of exciting, and I’m thrilled to share the fruits of that adventure with you all. After spending a few weeks tinkering with APIs, parsing responses, and structuring data into something meaningful, I'm excited to present the CLEANEST Zillow Dataset you've every seen!

    Analysts will be able to get actionable insights and a structured view into the fascinating world of property data.

    Here’s the story behind the dataset: Zillow’s data provides a treasure trove of information, but raw responses can be messy with nested structures, and scattered details. So, I rolled up my sleeves and built a robust pipeline to extract key data points from each response. From property details to price history, every piece of information was carefully categorized and mapped into logical fields. My goal was to create a dataset that feels as polished and user-friendly as the apps we rely on daily.

    What Makes This Dataset Special?

    • Structured & Clean Data: Every property in the dataset has been meticulously processed, cleaned, and formatted to make analysis seamless.
    • Comprehensive Coverage: Whether you're analyzing trends in property values or studying features that drive price differences, this dataset has you covered.
    • Accessible Layout: Tables are structured logically, with relationships that make sense for analysts at every level. This dataset is more than just numbers – it’s a toolkit for anyone looking to dive into real estate analysis, build predictive models, or simply explore trends in the housing market.

    If you have any questions, feedback, or just want to geek out about data, don’t hesitate to connect with me on LinkedIn or here on Kaggle. Let’s build something awesome together!

    NOTES: I use Google's Cloud Composer to request this data and due to costs, I'm only grabbing data for properties that were recently put up for sale or sold within the day of execution. If you're looking for historical data, please reach out!

    Disclaimer: This dataset is intended for non-commercial, academic purposes and does not infringe upon Zillow's intellectual property rights. For full details on Zillow's terms, please visit Zillow's Terms of Use.

    Dive in, explore, and let me know what you think. Happy analyzing!

    Other Datasets: - Spotify

  4. d

    Real estate data scraping - get property data from any website on the...

    • datarade.ai
    Updated Apr 17, 2023
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    ScrapeLabs (2023). Real estate data scraping - get property data from any website on the Internet | scrapelabs.io [Dataset]. https://datarade.ai/data-products/real-estate-data-scraping-get-property-data-from-any-websit-scrapelabs
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Apr 17, 2023
    Dataset authored and provided by
    ScrapeLabs
    Area covered
    Romania, Saint Vincent and the Grenadines, Morocco, Hong Kong, Guinea-Bissau, French Polynesia, Guadeloupe, Puerto Rico, Korea (Democratic People's Republic of), Canada
    Description

    We create tailor-made solutions for every customer, so there are no limits to how we can customize your scraper. You don't have to worry about buying and maintaining complex and expensive software, or hiring developers.

    You can get the data on a one-time or recurring (based on your needs) basis.

    Get the data in any format and to any destination you need: Excel, CSV, JSON, XML, S3, GCP, or any other.

  5. p

    Real Estate Email List

    • listtodata.com
    • st.listtodata.com
    • +2more
    .csv, .xls, .txt
    Updated Jul 17, 2025
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    List to Data (2025). Real Estate Email List [Dataset]. https://listtodata.com/real-estate-email-list
    Explore at:
    .csv, .xls, .txtAvailable download formats
    Dataset updated
    Jul 17, 2025
    Authors
    List to Data
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2025 - Dec 31, 2025
    Area covered
    Falkland Islands (Malvinas), Belarus, Cook Islands, Mongolia, France, Papua New Guinea, Malawi, Lesotho, Angola, Marshall Islands
    Variables measured
    phone numbers, Email Address, full name, Address, City, State, gender,age,income,ip address,
    Description

    Real Estate Email List is a premium mailing database for your needs. Most importantly, the list is the most popular site in the world. It is the largest data provider. Besides, the list is verified by human checks and automated software. You get new connections instantly. In addition, our expert team builds a qualified email list and checks the accuracy levels from millions of sources. The list is 95% accurate for giving the best results. Moreover, the dataset provides authentic service. This service can help you grow your business in a short time. Also, the leads link is ready for instant download. Furthermore, we give weekly updates and a bounce-back guarantee with Excel and CSV files. The leads give more information about your services. If you want a specific real estate email list, tell us. We make it for you properly. We provide new data for free to replace missing data.

    Real Estate Email List provides a free sample for marketing campaigns. You can create any custom order with your desired areas. The leads ensure that you never get inactive email data. After visiting our website, List to Data, contact us. You can purchase this email list to make your business more competitive. The dataset is profitable. In conclusion, you can get instant results for your products and services. Real Estate Email Database gives you verified and updated contact details. Also, it helps you connect with property owners, agents, and investors directly. In fact, this dataset includes names, phone numbers, email addresses, and postal details. Therefore, you can reach the right people in the real estate market quickly. So, you get high-quality leads that can help you grow your business. Likewise, it covers both residential and commercial real estate sectors. As a result, you can target your audience more effectively. Real Estate Email Database is fresh and regularly updated. This way, your campaigns always reach active contacts. Also, the affordable price makes it suitable for businesses of any size.

    Therefore, you can boost sales without spending too much. Furthermore, this Email database supports various marketing goals. For example, you can promote property listings, offer investment deals, or build long-term client relationships. Finally, choose our database to enjoy better leads, higher ROI, and steady business growth.

  6. C

    Allegheny County Property Sale Transactions

    • data.wprdc.org
    • s.cnmilf.com
    • +3more
    csv, html
    Updated Dec 2, 2025
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    Allegheny County (2025). Allegheny County Property Sale Transactions [Dataset]. https://data.wprdc.org/dataset/real-estate-sales
    Explore at:
    csv, htmlAvailable download formats
    Dataset updated
    Dec 2, 2025
    Dataset authored and provided by
    Allegheny County
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Allegheny County
    Description

    This dataset contains data on all Real Property parcels that have sold since 2013 in Allegheny County, PA.

    Before doing any market analysis on property sales, check the sales validation codes. Many property "sales" are not considered a valid representation of the true market value of the property. For example, when multiple lots are together on one deed with one price they are generally coded as invalid ("H") because the sale price for each parcel ID number indicates the total price paid for a group of parcels, not just for one parcel. See the Sales Validation Codes Dictionary for a complete explanation of valid and invalid sale codes.

    Sales Transactions Disclaimer: Sales information is provided from the Allegheny County Department of Administrative Services, Real Estate Division. Content and validation codes are subject to change. Please review the Data Dictionary for details on included fields before each use. Property owners are not required by law to record a deed at the time of sale. Consequently the assessment system may not contain a complete sales history for every property and every sale. You may do a deed search at http://www.alleghenycounty.us/re/index.aspx directly for the most updated information. Note: Ordinance 3478-07 prohibits public access to search assessment records by owner name. It was signed by the Chief Executive in 2007.

  7. Delhi -NCR real estate data

    • kaggle.com
    zip
    Updated Sep 12, 2023
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    Luv00679 (2023). Delhi -NCR real estate data [Dataset]. https://www.kaggle.com/datasets/luv00679/delhi-ncr-real-estate-data
    Explore at:
    zip(126391 bytes)Available download formats
    Dataset updated
    Sep 12, 2023
    Authors
    Luv00679
    License

    http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/

    Area covered
    National Capital Region
    Description

    Description

    Welcome to the "Real Estate Market Insights: Magic Bricks Web Scraped Dataset" available on Kaggle! This comprehensive dataset provides a wealth of information on real estate properties extracted from the popular real estate portal, Magic Bricks. With this dataset, you can explore and analyze the dynamic and ever-changing landscape of the real estate market.

    Dataset Overview:

    This dataset comprises meticulously scraped data from Magic Bricks, a prominent platform for buying, selling, and renting real estate properties in various regions. The dataset is regularly updated to ensure it reflects the most current market conditions and trends.

    Key Features:

    • Property Details: Gain access to a wide range of property details, including property type (apartment, house, commercial, etc.), location, size, and more.
    • Price Information: Explore property prices, including listing price, area-based pricing, and price trends.
    • Property Amenities: Discover the amenities and features associated with each property, from the number of bedrooms and bathrooms to parking availability and more.
    • Property Status: Determine whether a property is available for sale, rent, or lease.

    Use Cases:

    • Market Analysis: Use this dataset to perform in-depth market analysis to understand price trends, property demand, and supply dynamics.
    • Investment Opportunities: Identify potential investment opportunities in different regions based on price trends and property types.
    • Location-Based Insights: Explore how property prices and amenities vary across different localities and cities.
    • Real Estate Research: Use this dataset for academic research, business strategies, or data-driven decision-making.

    Data Collection Method:

    The dataset was collected using web scraping techniques, ensuring that it captures a wide array of properties listed on the Magic Bricks platform. Data integrity and accuracy are maintained through regular updates and quality checks.

    Data Format:

    The dataset is provided in a CSV format, making it easy to import and analyze using various data analysis tools and programming languages.

    Disclaimer:

    Please note that this dataset is for research and analytical purposes only. It is advisable to verify the data with Magic Bricks or other reliable sources before making any real estate transactions or investment decisions.

  8. f

    Yoursouthtampahome.com | Properties Data | Real Estate Data

    • datastore.forage.ai
    Updated Sep 22, 2024
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    (2024). Yoursouthtampahome.com | Properties Data | Real Estate Data [Dataset]. https://datastore.forage.ai/searchresults/?resource_keyword=Property%20Listings
    Explore at:
    Dataset updated
    Sep 22, 2024
    Description

    Yoursouthtampahome.com is a real estate company specializing in property listings and information for the South Tampa area. With a focus on providing detailed and up-to-date data, the company aims to help individuals and families find their dream homes. Their website is a valuable resource for anyone looking to buy, sell, or rent a property in South Tampa, offering a comprehensive view of the local real estate market.

    Yoursouthtampahome.com is a trusted source of information for property seekers, with a vast database of listings, sales data, and market trends. By providing easy access to this critical information, the company helps individuals make informed decisions in their home buying or selling journey.

  9. c

    Redfin usa properties dataset

    • crawlfeeds.com
    csv, zip
    Updated Jun 13, 2025
    + more versions
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    Crawl Feeds (2025). Redfin usa properties dataset [Dataset]. https://crawlfeeds.com/datasets/redfin-usa-properties-dataset
    Explore at:
    zip, csvAvailable download formats
    Dataset updated
    Jun 13, 2025
    Dataset authored and provided by
    Crawl Feeds
    License

    https://crawlfeeds.com/privacy_policyhttps://crawlfeeds.com/privacy_policy

    Description

    Explore the Redfin USA Properties Dataset, available in CSV format. This extensive dataset provides valuable insights into the U.S. real estate market, including detailed property listings, prices, property types, and more across various states and cities. Perfect for those looking to conduct in-depth market analysis, real estate investment research, or financial forecasting.

    Key Features:

    • Comprehensive Property Data: Includes essential details such as listing prices, property types, square footage, and the number of bedrooms and bathrooms.
    • Geographic Coverage: Encompasses a wide range of U.S. states and cities, providing a broad view of the national real estate market.
    • Historical Trends: Analyze past market data to understand price movements, regional differences, and market trends over time.
    • Geo-Location Details: Enables spatial analysis and mapping by including precise geographical coordinates of properties.

    Who Can Benefit From This Dataset:

    • Real Estate Investors: Identify lucrative opportunities by analyzing property values, market trends, and regional price variations.
    • Market Analysts: Gain a deeper understanding of the U.S. housing market dynamics to inform research and reporting.
    • Data Scientists and Researchers: Leverage detailed real estate data for modeling, urban studies, or economic analysis.
    • Financial Analysts: Utilize the dataset for financial modeling, helping to predict market behavior and assess investment risks.

    Download the Redfin USA Properties Dataset to access essential information on the U.S. housing market, ideal for professionals in real estate, finance, and data analytics. Unlock key insights to make informed decisions in a dynamic market environment.

    Looking for deeper insights or a custom data pull from Redfin?
    Send a request with just one click and explore detailed property listings, price trends, and housing data.
    🔗 Request Redfin Real Estate Data

  10. Commercial Real Estate Data | Global Real Estate Professionals | Work...

    • datarade.ai
    Updated Oct 27, 2021
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    Success.ai (2021). Commercial Real Estate Data | Global Real Estate Professionals | Work Emails, Phone Numbers & Verified Profiles | Best Price Guaranteed [Dataset]. https://datarade.ai/data-products/commercial-real-estate-data-global-real-estate-professional-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Oct 27, 2021
    Dataset provided by
    Area covered
    Bolivia (Plurinational State of), Hong Kong, Guatemala, Comoros, Burkina Faso, Korea (Republic of), Netherlands, Marshall Islands, El Salvador, Sierra Leone
    Description

    Success.ai’s Commercial Real Estate Data and B2B Contact Data for Global Real Estate Professionals is a comprehensive dataset designed to connect businesses with industry leaders in real estate worldwide. With over 170M verified profiles, including work emails and direct phone numbers, this solution ensures precise outreach to agents, brokers, property developers, and key decision-makers in the real estate sector.

    Utilizing advanced AI-driven validation, our data is continuously updated to maintain 99% accuracy, offering actionable insights that empower targeted marketing, streamlined sales strategies, and efficient recruitment efforts. Whether you’re engaging with top real estate executives or sourcing local property experts, Success.ai provides reliable and compliant data tailored to your needs.

    Key Features of Success.ai’s Real Estate Professional Contact Data

    • Comprehensive Industry Coverage Gain direct access to verified profiles of real estate professionals across the globe, including:
    1. Real Estate Agents: Professionals facilitating property sales and purchases.
    2. Brokers: Key intermediaries managing transactions between buyers and sellers.
    3. Property Developers: Decision-makers shaping residential, commercial, and industrial projects.
    4. Real Estate Executives: Leaders overseeing multi-regional operations and business strategies.
    5. Architects & Consultants: Experts driving design and project feasibility.
    • Verified and Continuously Updated Data

    AI-Powered Validation: All profiles are verified using cutting-edge AI to ensure up-to-date accuracy. Real-Time Updates: Our database is refreshed continuously to reflect the most current information. Global Compliance: Fully aligned with GDPR, CCPA, and other regional regulations for ethical data use.

    • Customizable Data Delivery Tailor your data access to align with your operational goals:

    API Integration: Directly integrate data into your CRM or project management systems for seamless workflows. Custom Flat Files: Receive detailed datasets customized to your specifications, ready for immediate application.

    Why Choose Success.ai for Real Estate Contact Data?

    • Best Price Guarantee Enjoy competitive pricing that delivers exceptional value for verified, comprehensive contact data.

    • Precision Targeting for Real Estate Professionals Our dataset equips you to connect directly with real estate decision-makers, minimizing misdirected efforts and improving ROI.

    • Strategic Use Cases

      Lead Generation: Target qualified real estate agents and brokers to expand your network. Sales Outreach: Engage with property developers and executives to close high-value deals. Marketing Campaigns: Drive targeted campaigns tailored to real estate markets and demographics. Recruitment: Identify and attract top talent in real estate for your growing team. Market Research: Access firmographic and demographic data for in-depth industry analysis.

    • Data Highlights 170M+ Verified Professional Profiles 50M Work Emails 30M Company Profiles 700M Global Professional Profiles

    • Powerful APIs for Enhanced Functionality

      Enrichment API Ensure your contact database remains relevant and up-to-date with real-time enrichment. Ideal for businesses seeking to maintain competitive agility in dynamic markets.

    Lead Generation API Boost your lead generation with verified contact details for real estate professionals, supporting up to 860,000 API calls per day for robust scalability.

    • Use Cases for Real Estate Contact Data
    1. Targeted Outreach for New Projects Connect with property developers and brokers to pitch your services or collaborate on upcoming projects.

    2. Real Estate Marketing Campaigns Execute personalized marketing campaigns targeting agents and clients in residential, commercial, or industrial sectors.

    3. Enhanced Sales Strategies Shorten sales cycles by directly engaging with decision-makers and key stakeholders.

    4. Recruitment and Talent Acquisition Access profiles of highly skilled professionals to strengthen your real estate team.

    5. Market Analysis and Intelligence Leverage firmographic and demographic insights to identify trends and optimize business strategies.

    • What Makes Us Stand Out? >> Unmatched Data Accuracy: Our AI-driven validation ensures 99% accuracy for all contact details. >> Comprehensive Global Reach: Covering professionals across diverse real estate markets worldwide. >> Flexible Delivery Options: Access data in formats that seamlessly fit your existing systems. >> Ethical and Compliant Data Practices: Adherence to global standards for secure and responsible data use.

    Success.ai’s B2B Contact Data for Global Real Estate Professionals delivers the tools you need to connect with the right people at the right time, driving efficiency and success in your business operations. From agents and brokers to property developers and executiv...

  11. Cotality Smart Data Platform: Historical Property

    • redivis.com
    application/jsonl +7
    Updated Aug 1, 2024
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    Stanford University Libraries (2024). Cotality Smart Data Platform: Historical Property [Dataset]. http://doi.org/10.57761/v1mj-g071
    Explore at:
    avro, sas, parquet, csv, spss, stata, application/jsonl, arrowAvailable download formats
    Dataset updated
    Aug 1, 2024
    Dataset provided by
    Redivis Inc.
    Authors
    Stanford University Libraries
    Description

    Abstract

    Title: Cotality Smart Data Platform (SDP): Historical Property

    Historical tax assessment data for all U.S. states, the U.S. Virgin Islands, Guam, and Washington, D.C. Each table represents a previous edition of Cotality's tax assessment data.

    Formerly known as CoreLogic Smart Data Platform: Historical Property.

    Methodology

    In the United States, parcel data is public record information that describes a division of land (also referred to as "property" or "real estate"). Each parcel is given a unique identifier called an Assessor’s Parcel Number or APN. The two principal types of records maintained by county government agencies for each parcel of land are deed and property tax records. When a real estate transaction takes place (e.g. a change in ownership), a property deed must be signed by both the buyer and seller. The deed will then be filed with the County Recorder’s offices, sometimes called the County Clerk-Recorder or other similar title. Property tax records are maintained by County Tax Assessor’s offices; they show the amount of taxes assessed on a parcel and include a detailed description of any structures or buildings on the parcel, including year built, square footages, building type, amenities like a pool, etc. There is not a uniform format for storing parcel data across the thousands of counties and county equivalents in the U.S.; laws and regulations governing real estate/property sales vary by state. Counties and county equivalents also have inconsistent approaches to archiving historical parcel data.

    To fill researchers’ needs for uniform parcel data, Cotality collects, cleans, and normalizes public records that they collect from U.S. County Assessor and Recorder offices. Cotality augments this data with information gathered from other public and non-public sources (e.g., loan issuers, real estate agents, landlords, etc.). The Stanford Libraries has purchased bulk extracts from Cotality's parcel data, including mortgage, owner transfer, pre-foreclosure, and historical and contemporary tax assessment data. Data is bundled into pipe-delimited text files, which are uploaded to Data Farm (Redivis) for preview, extraction and analysis.

    For more information about how the data was prepared for Redivis, please see Cotality 2024 GitLab.

    Usage

    Each table contains an archived snapshot of the property data, roughly corresponding to the following assessed years:

    • Historical Property 1 = 2022-2023
    • Historical Property 2 = 2021-2022
    • Historical Property 3 = 2020-2021
    • Historical Property 4 = 2019-2020
    • Historical Property 5 = 2018-2019
    • Historical Property 6 = 2017-2018
    • Historical Property 7 = 2016-2017
    • Historical Property 8 = 2015-2016
    • Historical Property 9 = 2014-2015
    • Historical Property 10 = 2013-2014
    • Historical Property 11 = 2012-2013
    • Historical Property 12 = 2011-2012
    • Historical Property 13 = 2010-2011
    • Historical Property 14 = 2009-2010
    • Historical Property 15 = 2008-2009

    %3C!-- --%3E

    Users can check theASSESSED_YEAR variable to confirm the year of assessment.

    Roughly speaking, the tables use the following census geographies:

    • 2020 Census Tract: Historical Property 1-2
    • 2010 Census Tract: Historical Property 3 – 12
    • 2000 Census Tract: Historical Property 13 – 15

    %3C!-- --%3E

    The Property, Mortgage, Owner Transfer, Historical Property and Pre-Foreclosure data can be linked on the CLIP, a unique identification number assigned to each property.

    For more information about included variables, please see **cotality_sdp_historical_property_data_dictionary_2024.txt **and Historical Property_v3.xlsx.

    Under Supporting files, users can also find record counts per FIPS code for each edition of the Historical Property data.

    For more information about how the Cotality Smart Data Platform: Historical Property data compares to legacy data, please see 2025_Legacy_Content_Mapping.pdf.

    Bulk Data Access

    Data access is required to view this section.

  12. C

    City-Owned Property (Real Estate Tax Database)

    • data.wprdc.org
    csv, xlsx
    Updated Nov 27, 2025
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    City of Pittsburgh (2025). City-Owned Property (Real Estate Tax Database) [Dataset]. https://data.wprdc.org/dataset/city-owned-property
    Explore at:
    csv, xlsxAvailable download formats
    Dataset updated
    Nov 27, 2025
    Dataset authored and provided by
    City of Pittsburgh
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset contains a listing of property owned by the City of Pittsburgh obtained from the City's Real Estate Database. For a more complete listing of City-owned properties obtained from the City's eProperties Plus database, please visit this WPRDC dataset: City-Owned Properties Dataset

    CHANGELOG

    2023-09-22: This dataset's feed was restored, with significant changes to the published fields. A sales price is now included among the fields, as well as four dates relevant to the history of the property.

  13. US National Property Data | 157M+ Records | 35+ Property Characteristics |...

    • data.thewarrengroup.com
    Updated Feb 13, 2025
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    The Warren Group (2025). US National Property Data | 157M+ Records | 35+ Property Characteristics | Ownership Information | Property Assessments [Dataset]. https://data.thewarrengroup.com/products/u-s-national-property-data-157-million-records-35-prop-the-warren-group
    Explore at:
    Dataset updated
    Feb 13, 2025
    Dataset authored and provided by
    The Warren Group
    Area covered
    United States
    Description

    Gain an in-depth view of property characteristics for more than 157 million properties across the United States (also available at the state- and county-level).

  14. f

    Santa Cruz Property Insights | Properties Data | Real Estate Data

    • datastore.forage.ai
    Updated Sep 22, 2024
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    (2024). Santa Cruz Property Insights | Properties Data | Real Estate Data [Dataset]. https://datastore.forage.ai/searchresults/?resource_keyword=Property%20Listings
    Explore at:
    Dataset updated
    Sep 22, 2024
    Description

    Santa Cruz Property Insights is a premier real estate marketplace, offering an extensive range of listings and data on residential and commercial properties in the Santa Cruz area. The company's vast database provides valuable information for potential buyers, sellers, and real estate professionals alike, making it an indispensable resource for anyone involved in the local market.

    With a focus on providing accurate and up-to-date information, Santa Cruz Property Insights has established itself as a trusted authority in the real estate industry. From property listings to market trends and analysis, the company's comprehensive data sets enable users to make informed decisions and navigate the complex landscape of real estate with confidence.

  15. f

    The Property Group | Properties Data | Real Estate Data

    • datastore.forage.ai
    Updated Sep 22, 2024
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    (2024). The Property Group | Properties Data | Real Estate Data [Dataset]. https://datastore.forage.ai/searchresults/?resource_keyword=Property%20Listings
    Explore at:
    Dataset updated
    Sep 22, 2024
    Description

    The Property Group is a leading real estate organization that provides expert guidance throughout the home buying and selling process. With a strong presence in Little Rock, Arkansas, the company has established itself as a trusted partner for individuals and families seeking to buy, sell, or rent properties. The Property Group's expert agents are well-versed in local market trends, ensuring that clients receive tailored solutions to their unique needs.

    Through their user-friendly website, The Property Group offers a range of resources and tools for homebuyers, including exclusive property listings, neighborhood information, and real-time market reports. Whether buying or selling a home, clients can rely on the company's dedicated professionals to navigate the complex process with ease. With a focus on transparency, efficiency, and personalized attention, The Property Group has earned a reputation as a top choice for those seeking a seamless and stress-free real estate experience.

  16. f

    TWT Property | Properties Data | Real Estate Data

    • datastore.forage.ai
    Updated Sep 22, 2024
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    (2024). TWT Property | Properties Data | Real Estate Data [Dataset]. https://datastore.forage.ai/searchresults/?resource_keyword=Property%20Listings
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    Dataset updated
    Sep 22, 2024
    Description

    TWT Property is a leading provider of real estate data and insights. As a renowned Australian property group, they have established themselves as a trusted source of information for the industry. Their vast database consists of property listings, market trends, and sales data, giving users a comprehensive view of the Australian real estate market.

    By tapping into TWT Property's data, users can gain valuable insights into the Australian real estate landscape. With a strong focus on providing accurate and up-to-date information, TWT Property's data is an essential tool for property developers, investors, and agents.

  17. Largest deals for data center property sales in Europe 2023-2024

    • statista.com
    Updated Nov 29, 2025
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    Statista (2025). Largest deals for data center property sales in Europe 2023-2024 [Dataset]. https://www.statista.com/statistics/1232893/largest-data-center-properties-sales-europe/
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    Dataset updated
    Nov 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Europe
    Description

    In 2023 and the first half of 2024, the largest property sale in the data center real estate market in Europe was DATA4 Paris-Saclay in Paris. In April 2023, Brookfield bought the ****** square meter property from AXA for an undisclosed price. The most expensive sale was Digital Frankfurt I. The valuation of the site was *** million U.S. dollars and Digital Core REIT obtained **** percent from Digital Realty.

  18. f

    LiveOverture | Properties Data | Real Estate Data

    • datastore.forage.ai
    Updated Sep 22, 2024
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    (2024). LiveOverture | Properties Data | Real Estate Data [Dataset]. https://datastore.forage.ai/searchresults/?resource_keyword=Property%20Listings
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    Dataset updated
    Sep 22, 2024
    Description

    LiveOverture is a reputable property data solutions provider that offers a wealth of information on property listings, market trends, and real estate data. The company's online presence provides insights into the property market, featuring thousands of listings, property sales data, and market analysis.

    By leveraging LiveOverture's online resources, users can gain a deeper understanding of property values, trends, and market conditions, making it an invaluable resource for real estate professionals, investors, and individuals looking to buy, sell, or rent properties.

  19. f

    LandSearch | Properties Data | Real Estate Data

    • datastore.forage.ai
    Updated Sep 22, 2024
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    (2024). LandSearch | Properties Data | Real Estate Data [Dataset]. https://datastore.forage.ai/searchresults/?resource_keyword=Property%20Listings
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    Dataset updated
    Sep 22, 2024
    Description

    LandSearch is a renowned organization specializing in property listings and real estate data. With its extensive database, the company provides a one-stop-shop for individuals seeking accurate and reliable information on properties for sale or rent. By aggregating data from various sources, LandSearch offers a vast array of listings, including residential, commercial, and industrial properties.

    As a leading provider of real estate information, LandSearch has established itself as a trusted source for property enthusiasts, investors, and professionals. The company's dedication to accuracy and quality has earned it a reputation for being a go-to destination for those seeking comprehensive property data. With its extensive reach and user-friendly interface, LandSearch has become an indispensable resource for those navigating the world of real estate.

  20. a

    Buy Real Estate Agent Data - United States (USA)

    • apiscrapy.com
    csv
    Updated Apr 29, 2025
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    APISCRAPY (2025). Buy Real Estate Agent Data - United States (USA) [Dataset]. https://apiscrapy.com/data-products/buy-real-estate-agent-data-usa/
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    csvAvailable download formats
    Dataset updated
    Apr 29, 2025
    Dataset authored and provided by
    APISCRAPY
    Area covered
    India, United States
    Description

    Buy real estate agent data in the USA with verified emails, phone numbers, and company details. Instantly download accurate, up-to-date realtor contact lists for marketing and lead generation.

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Rakkesh Aravind G (2022). Housing Real Estate Data from Indian Cities [Dataset]. https://www.kaggle.com/datasets/rakkesharv/real-estate-data-from-7-indian-cities
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Housing Real Estate Data from Indian Cities

City wise property data from Real Estate Website purpose of Data Cleaning

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zip(1671735 bytes)Available download formats
Dataset updated
Dec 8, 2022
Authors
Rakkesh Aravind G
License

https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

Area covered
India
Description

Real Estate / Housing Dataset

This dataset is web scrapped from a real estate website, collecting all the necessary infos on the resale and new properties. It has around 14000+ rows of data having properties from various Indian cities like Chennai, Mumbai, Bangalore, Delhi, Pune, Kolkata and Hyderabad. Columns:

Name: Property Name, Property Title: Property Ad Title, Price: Property Price Location: Property Located Locality and Region Total Area: Total SQFT of the property Price Per SQFT: Price of Per SQFT of the property Description: Small paragraph about the property Baths: Number of baths in the property Balcony: Whether the Property has balcony or not

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