Context This dataset shows real estate listing in USA. It includes the price, zip codes etc

Sources This shows real estate data of company called Realtor - https://www.realtor.com. I downloaded the dataset from kaggle.

About Dataset 1 csv. file contains 10 columns - realtor-data.csv (100k+ entries) - status (Housing status - a. ready for sale or b. ready to build) - bed (# of beds) - bath (# of bathrooms) - acre_lot (Property / Land size in acres) - city (city name) - state (state name) - zip_code (postal code of the area) - house_size (house area/size/living space in square feet) - prev_sold_date (Previously sold date) - price (Housing price, it is either the current listing price or recently sold price if the house is sold recently)

Cover Image Downloaded from Google Stock images.

Disclaimer The data and information in the data set provided here are intended to use for educational purposes only. I do not own any data, and all rights are reserved to the respective owners.

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

Existing Home Sales in the United States decreased to 4000 Thousand in August from 4010 Thousand in July of 2025. This dataset provides the latest reported value for - United States Existing Home Sales - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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.

Abstract

Title: Cotality Multiple Listing Service (MLS)

A multiple listing service (MLS) is an exchange where real estate brokers share information about properties they are selling. Other real estate brokers review the listings, and are compensated if they can identify a buyer for a property. Multiple listing services promote cooperation and mutual benefit for real estate brokers representing buyers and sellers. The Cotality Multiple Listing Service data contains listings from 135 real estate boards utilizing Cotality's multiple listing service software. The data was produced in August 2024.

Formerly known as CoreLogic Multiple Listing Service (MLS).

Methodology

The data consists of listings from 135 real estate boards that use Cotality listing software. The data DOES NOT cover listings from all real estate boards in the United States. The National Association of Realtors maintains the most complete and up-to-date list of real estate boards; however, this information is only available to members of the National Association of Realtors.

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

Usage

Quick Search (QS) contains the most recent listing data (as of August 2024). In order to see the entire listing history of a property/record, you will need to search the Quick History (QH) table on the SysPropertyID, which is a unique key for a listing across multiple listing boards. You can use the variable FA_PostDate to see when updates occurred. Updates include name changes, price changes, etc.

During upload to Data Farm, a small number of invalid records were dropped from the Quick History (QH) table. For more information, see Cotality 2024 GitLab. To access the complete data (including invalid records), please see Bulk Data Access instructions, below.

Bulk Data Access

Data access is required to view this section.

Total Housing Inventory in the United States decreased to 1530 Thousands in August from 1550 Thousands in July of 2025. This dataset includes a chart with historical data for the United States Total Housing Inventory.

New Home Sales in the United States increased to 800 Thousand units in August from 664 Thousand units in July of 2025. This dataset provides the latest reported value for - United States New Home Sales - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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.

Nothing is more personal than home. In order to form a meaningful connection with a relevant audience, real estate and home services brands turn to data to fuel a wide variety of strategies.

TRAK's US Real Estate dataset includes enough rich home and real estate focused variables to power highly customizable analytics and direct marketing strategies. Our data is deep and wide, covering everything from financing information to the number of rooms in a home.

There are also the table stakes variables useful for a variety of industries like new movers, homeowners vs. renters, and in-market for a home purchase (premovers).

We work closely with marketers and data teams to recommend an ideal volume and depth of attributes to empower them to crush their goals. Whether it's limiting the geographic area to your market territories, or removing variables that won't have an impact on your business, we right size the data for your organization's needs. At a high level, key categories in our data set includes:

✔ Home Financing Details ✔ Home Ownership vs Renters ✔ In-Market for a Home ✔ Property Type ✔ Home Attributes ✔ Real Estate Investing ✔ New Mover

Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q2 2025 about sales, median, housing, and USA.

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:

• Website: Golden Oak Research make sure to upvote

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.

Graph and download economic data for Monthly Supply of New Houses in the United States (MSACSR) from Jan 1963 to Aug 2025 about supplies, new, housing, and USA.

Context

The purpose of this kernel is to predict the price of a house that a realtor can charge, or a customer can invest to buy a house by considering multiple input factors. Also, to classify the houses into Good and Excellent category based on the input variables by using best machine learning classification and regression algorithms with more efficiency.

Content

This dataset contains house sale prices for King County, which includes Seattle. It includes homes sold between May 2014 and May 2015. The dataset is pretty unbalanced with wide range of houses information that are built and renovated from the year 1990 to 2015. The dataset has total 21 variables including price,price, condition, number of bedrooms, bathrooms and other features of house.

Inspiration

I was inspired by the House sales dataset in King County, USA (https://www.kaggle.com/harlfoxem/housesalesprediction) and House Sales in Ontario (https://www.kaggle.com/mnabaee/ontarioproperties) datasets and the predictions and classifiers used.

Sale of Houses can go high and low depending on the market and multiple factors like location, number of bedrooms, year built etc. All these factors help in deriving the sale price of the house and grading of the house. Millions of houses information can be stored with all the details and factors in the historical timelines. Using machine learning techniques, we can analyze the data and predict the price of new houses and also classify the houses and fix a price value by calculating all the factors that directly or indirectly impact on the overall sale of house.

Probate, pre-probate, and divorce real estate data offers valuable insights and opportunities for real estate professionals to identify and pursue potential leads. These datasets provide information about properties involved in probate, pre-probate, and divorce cases, enabling professionals to target motivated sellers and navigate specialized market niches. In this brief, we will explore the concept of probate, pre-probate, and divorce data, and discuss their applications across various industries.

What is Probate, Pre-Probate, and Divorce Data?

Probate Data refers to the legal process of settling the estate of a deceased person. Probate data includes information about properties owned by individuals who have passed away and are being transferred to their heirs or beneficiaries through a court-supervised process. This dataset contains details about properties that may be sold to distribute the deceased person’s assets or resolve any outstanding debts.

Pre-Probate Data includes properties owned by individuals who are alive but have designated their assets to be transferred to their heirs upon their passing. This dataset allows real estate professionals to identify potential sellers who may be interested in selling their properties before going through the probate process.

Divorce Data pertains to properties involved in divorce proceedings. When couples go through a divorce, the division of assets often includes the sale or transfer of properties. This dataset provides information on properties that may become available for sale due to a divorce settlement, providing real estate professionals with opportunities to target motivated sellers.

Gain an in-depth view of probate, pre-probate and divorce characteristics for more than 155 million properties across the country (or at the state- and country-level), including: - Property Address - Owner First & Last Name - Mailing Address - Legal Description - Property Value - Property Use - Parcel ID - Year Built - Date Of Death (Probate & Pre-Probate) - Defendant Information (Divorce) - Plaintiff Information (Divorce) - Defendant Attorney Information (Divorce) - Plaintiff Attorney Information (Divorce)

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.

Housing Starts in the United States decreased to 1307 Thousand units in August from 1429 Thousand units in July of 2025. This dataset provides the latest reported value for - United States Housing Starts - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

SafeGraph Places provides baseline location information for every record in the SafeGraph product suite via the Places schema and polygon information when applicable via the Geometry schema. The current scope of a place is defined as any location humans can visit with the exception of single-family homes. This definition encompasses a diverse set of places ranging from restaurants, grocery stores, and malls; to parks, hospitals, museums, offices, and industrial parks. Premium sets of Places include apartment buildings, Parking Lots, and Point POIs (such as ATMs or transit stations).

SafeGraph Places is a point of interest (POI) data offering with varying coverage and properties depending on the country. Note that address conventions and formatting vary across countries. SafeGraph has coalesced these fields into the Places schema.

Single Family Home Prices in the United States decreased to 422600 USD in August from 425700 USD in July of 2025. This dataset provides - United States Existing Single Family Home Prices- actual values, historical data, forecast, chart, statistics, economic calendar and news.

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.

Context

For various project occasions, a comprehensive US listings dataset was created with a colleague. This dataset is a subset for the State of Georgia.

Content

This dataset shows real estate listing for Georgia (US) for the first 6 months of 2021. Prices are listed in USD.

Acknowledgements and Citation

This dataset is a co-production, thanks to my fellow mate Jordan for building a great comprehensive US dataset from which I could filter this.

Using this dataset requires citing the contributor.

Credits for the Cover Image

Thank you very much Christopher Alvarenga who provided this through Unsplash