100+ datasets found
  1. C

    City-Owned Property (Real Estate Tax Database)

    • data.wprdc.org
    csv, xlsx
    Updated Oct 16, 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
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    csv, xlsxAvailable download formats
    Dataset updated
    Oct 16, 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.

  2. m

    Scrape Real Estate Data 10x Faster From All Real Estate Sites & Database in...

    • apiscrapy.mydatastorefront.com
    Updated Feb 5, 2024
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    APISCRAPY (2024). Scrape Real Estate Data 10x Faster From All Real Estate Sites & Database in USA & Worldwide - Zillow.com, Realtor.com, trulia.com, Century21, Redfin [Dataset]. https://apiscrapy.mydatastorefront.com/products/scrape-data-10x-faster-from-all-real-estate-sites-database-apiscrapy
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    Dataset updated
    Feb 5, 2024
    Dataset authored and provided by
    APISCRAPY
    Area covered
    United States
    Description

    Gain access to comprehensive real estate data from all major real estate property listing sites in the USA, Canada, UK, and other countries with our expert real estate scraping service. Unlock valuable insights from Zillow, Realtor.com, Trulia, Redfin, and more.

  3. d

    Real Estate Sales 2001-2023 GL

    • catalog.data.gov
    • data.ct.gov
    Updated Sep 14, 2025
    + more versions
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    data.ct.gov (2025). Real Estate Sales 2001-2023 GL [Dataset]. https://catalog.data.gov/dataset/real-estate-sales-2001-2018
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    Dataset updated
    Sep 14, 2025
    Dataset provided by
    data.ct.gov
    Description

    The Office of Policy and Management maintains a listing of all real estate sales with a sales price of $2,000 or greater that occur between October 1 and September 30 of each year. For each sale record, the file includes: town, property address, date of sale, property type (residential, apartment, commercial, industrial or vacant land), sales price, and property assessment. Data are collected in accordance with Connecticut General Statutes, section 10-261a and 10-261b: https://www.cga.ct.gov/current/pub/chap_172.htm#sec_10-261a and https://www.cga.ct.gov/current/pub/chap_172.htm#sec_10-261b. Annual real estate sales are reported by grand list year (October 1 through September 30 each year). For instance, sales from 2018 GL are from 10/01/2018 through 9/30/2019. Some municipalities may not report data for certain years because when a municipality implements a revaluation, they are not required to submit sales data for the twelve months following implementation.

  4. 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
    Guatemala, Burkina Faso, Comoros, El Salvador, Bolivia (Plurinational State of), Hong Kong, Netherlands, Marshall Islands, Korea (Republic of), 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...

  5. p

    Real estate agents Business Data for India

    • poidata.io
    csv, json
    Updated Oct 20, 2025
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    Business Data Provider (2025). Real estate agents Business Data for India [Dataset]. https://www.poidata.io/report/real-estate-agent/india
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Oct 20, 2025
    Dataset authored and provided by
    Business Data Provider
    License

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

    Time period covered
    2025
    Area covered
    India
    Variables measured
    Website URL, Phone Number, Review Count, Business Name, Email Address, Business Hours, Customer Rating, Business Address, Business Categories, Geographic Coordinates
    Description

    Comprehensive dataset containing 9,397 verified Real estate agent businesses in India with complete contact information, ratings, reviews, and location data.

  6. p

    Real Estate Email List

    • listtodata.com
    .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
    Dataset authored and provided by
    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
    Lesotho, Angola, Malawi, Belarus, Cook Islands, France, Falkland Islands (Malvinas), Papua New Guinea, Mongolia, 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.

  7. S

    Active Real Estate Salespersons and Brokers

    • data.ny.gov
    • catalog.data.gov
    • +2more
    csv, xlsx, xml
    Updated Oct 19, 2025
    + more versions
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    New York State Department of State (DOS) (2025). Active Real Estate Salespersons and Brokers [Dataset]. https://data.ny.gov/Economic-Development/Active-Real-Estate-Salespersons-and-Brokers/yg7h-zjbf
    Explore at:
    xml, csv, xlsxAvailable download formats
    Dataset updated
    Oct 19, 2025
    Dataset authored and provided by
    New York State Department of State (DOS)
    Description

    This data contains active Real Estate Salesperson and Broker Licenses from New York State Department of State (DOS). Each line will be either an individual or business licensee which holds business address and license number information. If the license type is an individual, the business name that the individual works for will be listed.

  8. Real Estate Across the United States (REXUS) Inventory (Building)

    • catalog.data.gov
    • data.amerigeoss.org
    • +1more
    Updated Sep 3, 2025
    + more versions
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    General Services Administration (2025). Real Estate Across the United States (REXUS) Inventory (Building) [Dataset]. https://catalog.data.gov/dataset/real-estate-across-the-united-states-rexus-inventory-building
    Explore at:
    Dataset updated
    Sep 3, 2025
    Dataset provided by
    General Services Administrationhttp://www.gsa.gov/
    Area covered
    United States
    Description

    Real Estate Across the United States (REXUS) is the primary tool used by PBS to track and manage the government's real property assets and to store inventory data, building data, customer data, and lease information. STAR manages aspects of real property space management, including identification of all building space and daily management of 22,000 assignments for all property to its client Federal agencies. This data set contains PBS building inventory that consists of both owned and leased buildings with active and excess status.

  9. e

    Real estate price register database, Wejherowo district 2215

    • data.europa.eu
    Updated Nov 29, 2024
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    (2024). Real estate price register database, Wejherowo district 2215 [Dataset]. https://data.europa.eu/data/datasets/737d4f7a-f454-45cf-adcd-3b71b62b8aee?locale=en
    Explore at:
    Dataset updated
    Nov 29, 2024
    Description

    The property price register is kept on the basis of prices specified in notarial deeds. The following are also subject to registration: the location of the property, the numbers of the land plots included in the property, the type of property (with the distinction of undeveloped agricultural real estate, developed agricultural real estate, undeveloped real estate intended for development other than homesteads, real estate built on residential buildings, real estate built on buildings performing other functions than homesteads and housing, building real estate, residential real estate), the area of land property, the date of conclusion of a notarial deed or determination of value, other available data on real estate and its components.

  10. p

    Real estate agents Business Data for United States

    • poidata.io
    csv, json
    Updated Oct 6, 2025
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    Business Data Provider (2025). Real estate agents Business Data for United States [Dataset]. https://www.poidata.io/report/real-estate-agent/united-states
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Oct 6, 2025
    Dataset authored and provided by
    Business Data Provider
    License

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

    Time period covered
    2025
    Area covered
    United States
    Variables measured
    Website URL, Phone Number, Review Count, Business Name, Email Address, Business Hours, Customer Rating, Business Address, Business Categories, Geographic Coordinates
    Description

    Comprehensive dataset containing 331,575 verified Real estate agent businesses in United States with complete contact information, ratings, reviews, and location data.

  11. p

    Real estate developers Business Data for California, United States

    • poidata.io
    csv, json
    Updated Oct 8, 2025
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    Business Data Provider (2025). Real estate developers Business Data for California, United States [Dataset]. https://www.poidata.io/report/real-estate-developer/united-states/california
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Oct 8, 2025
    Dataset authored and provided by
    Business Data Provider
    License

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

    Time period covered
    2025
    Area covered
    California
    Variables measured
    Website URL, Phone Number, Review Count, Business Name, Email Address, Business Hours, Customer Rating, Business Address, Business Categories, Geographic Coordinates
    Description

    Comprehensive dataset containing 1,790 verified Real estate developer businesses in California, United States with complete contact information, ratings, reviews, and location data.

  12. e

    Real estate price and value register database, district węgorzewski 2819

    • data.europa.eu
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    Real estate price and value register database, district węgorzewski 2819 [Dataset]. https://data.europa.eu/data/datasets/1d6096bc-e5c4-4ecc-b253-58282dba5c63
    Explore at:
    Description

    The register of prices and value of immovable property shall be kept on the basis of the prices specified in the notarial deeds and the values determined by appraisers in estimates, the extracts of which are transmitted to the register of land and buildings under separate regulations. The following are also subject to registration: address of the location of the real estate, numbers of the cadastral plots included in the real estate, type of real estate (with distinction of undeveloped agricultural real estate, built-in agricultural property, undeveloped real estate for non-property development, real estate built with residential buildings, real estate built with buildings with functions other than farm and residential buildings, building real estate, residential real estate), land area, date of the notarial act or value determination, other available data on real estate and their components.

  13. C

    China CN: Real Estate Investment: Zhejiang

    • ceicdata.com
    Updated Feb 6, 2025
    + more versions
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    CEICdata.com (2025). China CN: Real Estate Investment: Zhejiang [Dataset]. https://www.ceicdata.com/en/china/real-estate-investment-summary
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    Dataset updated
    Feb 6, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2013 - Dec 1, 2024
    Area covered
    China
    Variables measured
    Real Estate Investment
    Description

    CN: Real Estate Investment: Zhejiang data was reported at 1,198,266.610 RMB mn in 2024. This records a decrease from the previous number of 1,319,792.000 RMB mn for 2023. CN: Real Estate Investment: Zhejiang data is updated yearly, averaging 522,627.000 RMB mn from Dec 2000 (Median) to 2024, with 25 observations. The data reached an all-time high of 1,319,792.000 RMB mn in 2023 and a record low of 36,218.000 RMB mn in 2000. CN: Real Estate Investment: Zhejiang data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Real Estate Sector – Table CN.RKA: Real Estate Investment: Summary.

  14. C

    China CN: Real Estate Investment: Residential: Anhui: Wuhu

    • ceicdata.com
    Updated Feb 4, 2025
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    CEICdata.com (2024). China CN: Real Estate Investment: Residential: Anhui: Wuhu [Dataset]. https://www.ceicdata.com/en/china/real-estate-investment-prefecture-level-city-residential/cn-real-estate-investment-residential-anhui-wuhu
    Explore at:
    Dataset updated
    Feb 4, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2012 - Dec 1, 2023
    Area covered
    China
    Variables measured
    Real Estate Investment
    Description

    Real Estate Investment: Residential: Anhui: Wuhu data was reported at 27,857.030 RMB mn in 2023. This records a decrease from the previous number of 42,710.530 RMB mn for 2022. Real Estate Investment: Residential: Anhui: Wuhu data is updated yearly, averaging 19,982.075 RMB mn from Dec 1996 (Median) to 2023, with 28 observations. The data reached an all-time high of 46,952.350 RMB mn in 2021 and a record low of 136.310 RMB mn in 1997. Real Estate Investment: Residential: Anhui: Wuhu data remains active status in CEIC and is reported by Wuhu Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Real Estate Sector – Table CN.RKG: Real Estate Investment: Prefecture Level City: Residential.

  15. T

    Real Estate Agents And Brokers Directory Utah

    • opendata.utah.gov
    csv, xlsx, xml
    Updated Sep 23, 2014
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    Utah Department of Commerce (2014). Real Estate Agents And Brokers Directory Utah [Dataset]. https://opendata.utah.gov/dataset/Real-Estate-Agents-And-Brokers-Directory-Utah/y5aq-ckub
    Explore at:
    xlsx, csv, xmlAvailable download formats
    Dataset updated
    Sep 23, 2014
    Dataset authored and provided by
    Utah Department of Commerce
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Area covered
    Utah
    Description

    Real Estate Agents And Brokers Directory Utah

  16. C

    City-Owned Land Inventory

    • chicago.gov
    • data.cityofchicago.org
    • +2more
    csv, xlsx, xml
    Updated Oct 17, 2025
    + more versions
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    Chicago Department of Planning and Development (2025). City-Owned Land Inventory [Dataset]. https://www.chicago.gov/city/en/depts/dcd/supp_info/city-owned_land_inventory.html
    Explore at:
    csv, xml, xlsxAvailable download formats
    Dataset updated
    Oct 17, 2025
    Dataset authored and provided by
    Chicago Department of Planning and Development
    Description

    Property currently or historically owned and managed by the City of Chicago. Information provided in the database, or on the City’s website generally, should not be used as a substitute for title research, title evidence, title insurance, real estate tax exemption or payment status, environmental or geotechnical due diligence, or as a substitute for legal, accounting, real estate, business, tax or other professional advice. The City assumes no liability for any damages or loss of any kind that might arise from the reliance upon, use of, misuse of, or the inability to use the database or the City’s web site and the materials contained on the website. The City also assumes no liability for improper or incorrect use of materials or information contained on its website. All materials that appear in the database or on the City’s web site are distributed and transmitted "as is," without warranties of any kind, either express or implied as to the accuracy, reliability or completeness of any information, and subject to the terms and conditions stated in this disclaimer.

    The following columns were added 4/14/2023:

    • Sales Status
    • Sale Offering Status
    • Sale Offering Reason
    • Square Footage - City Estimate
    • Land Value (2022) -- Note: The year will change over time.

    The following columns were added 3/19/2024:

    • Application Use
    • Grouped Parcels
    • Application Deadline
    • Offer Round
    • Application URL
  17. Database for Delhi homes

    • kaggle.com
    zip
    Updated Dec 23, 2020
    + more versions
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    Yasser Bader Ahmed (2020). Database for Delhi homes [Dataset]. https://www.kaggle.com/datasets/yasserbaderahmed/database-for-delhi-homes
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    zip(38398 bytes)Available download formats
    Dataset updated
    Dec 23, 2020
    Authors
    Yasser Bader Ahmed
    Area covered
    Delhi
    Description

    Dataset

    This dataset was created by Yasser Bader Ahmed

    Contents

  18. US Gross Rent ACS Statistics

    • kaggle.com
    Updated Aug 23, 2017
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    Golden Oak Research Group (2017). US Gross Rent ACS Statistics [Dataset]. https://www.kaggle.com/datasets/goldenoakresearch/acs-gross-rent-us-statistics
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 23, 2017
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Golden Oak Research Group
    Area covered
    United States
    Description

    What you get:

    Upvote! The database contains +40,000 records on US Gross Rent & Geo Locations. The field description of the database is documented in the attached pdf file. To access, all 325,272 records on a scale roughly equivalent to a neighborhood (census tract) see link below and make sure to upvote. Upvote right now, please. Enjoy!

    Get the full free database with coupon code: FreeDatabase, See directions at the bottom of the description... And make sure to upvote :) coupon ends at 2:00 pm 8-23-2017

    Gross Rent & Geographic Statistics:

    • Mean Gross Rent (double)
    • Median Gross Rent (double)
    • Standard Deviation of Gross Rent (double)
    • Number of Samples (double)
    • Square area of land at location (double)
    • Square area of water at location (double)

    Geographic Location:

    • Longitude (double)
    • Latitude (double)
    • State Name (character)
    • State abbreviated (character)
    • State_Code (character)
    • County Name (character)
    • City Name (character)
    • Name of city, town, village or CPD (character)
    • Primary, Defines if the location is a track and block group.
    • Zip Code (character)
    • Area Code (character)

    Abstract

    The data set originally developed for real estate and business investment research. Income is a vital element when determining both quality and socioeconomic features of a given geographic location. The following data was derived from over +36,000 files and covers 348,893 location records.

    License

    Only proper citing is required please see the documentation for details. Have Fun!!!

    Golden Oak Research Group, LLC. “U.S. Income Database Kaggle”. Publication: 5, August 2017. Accessed, day, month year.

    For any questions, you may reach us at research_development@goldenoakresearch.com. For immediate assistance, you may reach me on at 585-626-2965

    please note: it is my personal number and email is preferred

    Check our data's accuracy: Census Fact Checker

    Access all 325,272 location for Free Database Coupon Code:

    Don't settle. Go big and win big. Optimize your potential**. Access all gross rent records and more on a scale roughly equivalent to a neighborhood, see link below:

    A small startup with big dreams, giving the every day, up and coming data scientist professional grade data at affordable prices It's what we do.

  19. p

    Real estate agents Business Data for Russia

    • poidata.io
    csv, json
    Updated Sep 25, 2025
    + more versions
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    Business Data Provider (2025). Real estate agents Business Data for Russia [Dataset]. https://www.poidata.io/report/real-estate-agent/russia
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Sep 25, 2025
    Dataset authored and provided by
    Business Data Provider
    License

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

    Time period covered
    2025
    Area covered
    Russia
    Variables measured
    Website URL, Phone Number, Review Count, Business Name, Email Address, Business Hours, Customer Rating, Business Address, Business Categories, Geographic Coordinates
    Description

    Comprehensive dataset containing 1,086 verified Real estate agent businesses in Russia with complete contact information, ratings, reviews, and location data.

  20. T

    Land Database 2021

    • datahub.austintexas.gov
    • data.austintexas.gov
    • +3more
    Updated Nov 29, 2021
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    City of Austin, Texas - data.austintexas.gov (2021). Land Database 2021 [Dataset]. https://datahub.austintexas.gov/Housing-and-Real-Estate/Land-Database-2021/kk8y-6cmt
    Explore at:
    xml, kmz, application/geo+json, kml, xlsx, csvAvailable download formats
    Dataset updated
    Nov 29, 2021
    Dataset authored and provided by
    City of Austin, Texas - data.austintexas.gov
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    This data is provided as a one-off project and there are no plans to update it. The data is collected from the 3 main appraisal districts and users may go to them to obtain land records and appraisal data, or contact HPD staff for assistance. This layer contains land use, zoning, and appraisal data for the purposes of long-range planning and scenario modelling, current to October 2016, but based on a variety of sources with different capture dates. The land use information and parcel geography are based on a land use inventory. It also includes estimates of residential units based on building permit, appraisal data, aerials, and a variety of other sources. An ArcGIS lyr file is also provided to allow users to draw this GIS layer in ArcMap.

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City of Pittsburgh (2025). City-Owned Property (Real Estate Tax Database) [Dataset]. https://data.wprdc.org/dataset/city-owned-property

City-Owned Property (Real Estate Tax Database)

Explore at:
csv, xlsxAvailable download formats
Dataset updated
Oct 16, 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.

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