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.

For every real estate property in Arlington which has been sold, this dataset includes property sales information and can be associated with other Real Estate datasets by the RPC (RealEstatePropertyCode).

Update 10/31/2023: Sales are no longer filtered out of this data set based on deed type, sale price, or recency of sale for a given PIN with the same price. If users wish to recreate the former filtering schema they should set sale_filter_same_sale_within_365, sale_filter_less_than_10k, and sale_filter_deed_type to False.

Parcel sales for real property in Cook County, from 1999 to present. The Assessor's Office uses this data in its modeling to estimate the fair market value of unsold properties.

When working with Parcel Index Numbers (PINs) make sure to zero-pad them to 14 digits. Some datasets may lose leading zeros for PINs when downloaded.

Sale document numbers correspond to those of the Cook County Clerk, and can be used on the Clerk's website to find more information about each sale.

NOTE: These sales are filtered, but likely include non-arms-length transactions - sales less than $10,000 along with quit claims, executor deeds, beneficial interests are excluded. While the Data Department will upload what it has access to monthly, sales are reported on a lag, with many records not populating until months after their official recording date.

Current property class codes, their levels of assessment, and descriptions can be found on the Assessor's website. Note that class codes details can change across time.

For more information on the sourcing of attached data and the preparation of this dataset, see the Assessor's Standard Operating Procedures for Open Data on GitHub.

Read about the Assessor's 2025 Open Data Refresh.

Like other Assessor and Recorder data sets from First American, BlackKnight, ATTOM or HouseCanary, we provide both residential real estate and commercial restate data on homes, properties and pracels nationally.

Over 250M parcels, updated daily.

Access detailed property and tax assessment records with our extensive nationwide database. This robust dataset provides comprehensive information about residential and commercial properties, including detailed ownership, valuation, and transaction history. Core Data Elements:

Complete property identification (APNs, Tax IDs) Full property addresses with geocoding Precise latitude/longitude coordinates FIPS codes and Census tract information School district assignments

Property Characteristics:

Detailed lot dimensions and size Building square footage breakdowns Living area measurements Basement and attic specifications Garage and parking information Year built and effective year Number of bedrooms and bathrooms Room counts and configurations Building class and condition codes Construction details and materials Property amenities and features

Valuation Information:

Current AVM (Automated Valuation Model) values Confidence scores and value ranges Market valuations with dates Assessed values (land and improvements) Tax amounts and years Tax rate codes and districts Various tax exemption statuses

Transaction History:

Current and previous sale details Recording dates and document numbers Sale prices and price codes Buyer and seller information Multiple mortgage records including:

Loan amounts and terms Lender information Recording dates Interest rates Due dates Loan types and positions

Ownership Details:

Current owner information Corporate ownership indicators Owner-occupied status Mailing addresses Care of names Foreign address indicators

Legal Information:

Complete legal descriptions Subdivision details Lot and block numbers Zoning information Land use codes HOA information and fees

Property Status Indicators:

Vacancy flags Pre-foreclosure status Current listing status Price ranges Market position

Perfect For:

Real Estate Professionals

Property researchers Title companies Real estate attorneys Appraisers Market analysts

Financial Services

Mortgage lenders Insurance companies Investment firms Risk assessment teams Portfolio managers

Government & Planning

Urban planners Tax assessors Economic developers Policy researchers Municipal agencies

Data Analytics

Market researchers Data scientists Economic analysts GIS specialists Demographics experts

Data Delivery Features:

Multiple format options Regular updates Bulk download capability Custom field selection Geographic filtering API access available Standardized formatting Quality assured data

Quality Assurance:

Verified against public records Regular updates Standardized formatting Address verification Geocoding validation Duplicate removal Data normalization Quality control processes

This comprehensive property database provides unprecedented access to detailed property information, perfect for industry professionals requiring in-depth property data for analysis, research, or business development. Our data undergoes rigorous quality control processes to ensure accuracy and completeness, making it an invaluable resource for real estate professionals, financial institutions, and government agencies. Updated continuously from authoritative sources, this dataset offers the most current and accurate property information available in the market. Custom data extracts and specific geographic coverage options are available to meet your exact needs.

Weekly/Quarterly/Annual and One-time options are available for sale.

See our sample

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.

Update Frequency: Yearly

Access to Residential, Condominium, Commercial, Apartment properties and vacant land sales history data.

To download XML and JSON files, click the CSV option below and click the down arrow next to the Download button in the upper right on its page.

This dataset, maintained by the Office of Policy and Management, includes real estate sales in Connecticut from 2001 to 2022, with a sales price of $2,000 or more. Each record provides details such as the town, property address, date of sale, property type (residential, apartment, commercial, industrial, or vacant land), sales price, and property assessment.

Data are collected annually for each Grand List (GL) year, spanning October 1 through September 30. For example, the 2018 GL covers sales from October 1, 2018, to September 30, 2019, in compliance with Connecticut General Statutes (sections 10-261a and 10-261b).

Note: Municipalities undergoing property revaluation are not required to submit sales data for the 12 months following implementation. Covering over two decades of data, this dataset is a vital resource for tracking real estate trends and property valuations across Connecticut.

The number of U.S. home sales in the United States declined in 2024, after soaring in 2021. A total of four million transactions of existing homes, including single-family, condo, and co-ops, were completed in 2024, down from 6.12 million in 2021. According to the forecast, the housing market is forecast to head for recovery in 2025, despite transaction volumes expected to remain below the long-term average. Why have home sales declined? The housing boom during the coronavirus pandemic has demonstrated that being a homeowner is still an integral part of the American dream. Nevertheless, sentiment declined in the second half of 2022 and Americans across all generations agreed that the time was not right to buy a home. A combination of factors has led to house prices rocketing and making homeownership unaffordable for the average buyer. A survey among owners and renters found that the high home prices and unfavorable economic conditions were the two main barriers to making a home purchase. People who would like to purchase their own home need to save up a deposit, have a good credit score, and a steady and sufficient income to be approved for a mortgage. In 2022, mortgage rates experienced the most aggressive increase in history, making the total cost of homeownership substantially higher. Are U.S. home prices expected to fall? The median sales price of existing homes stood at 413,000 U.S. dollars in 2024 and was forecast to increase slightly until 2026. The development of the S&P/Case Shiller U.S. National Home Price Index shows that home prices experienced seven consecutive months of decline between June 2022 and January 2023, but this trend reversed in the following months. Despite mild fluctuations throughout the year, home prices in many metros are forecast to continue to grow, albeit at a much slower rate.

This dataset represents real estate assessment and sales data that is updated on a quarterly basis by the Real Estate Assessor’s Office. This dataset contains information for properties in the city including: Acreage, Square footage, GPIN, Street Address, year built, current land value, current improvement values, and current total value. The information is obtained from Real Estate Assessor’s Office ProVal records database.

For data about this dataset, please click on the below link: https://data.norfolk.gov/Real-Estate/Property-Assessment-and-Sales-FY21/8bfx-a5g8/about_data

Existing Home Sales in the United States increased to 4100 Thousand in October from 4050 Thousand in September 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 dataset represents real estate assessment and sales data that is updated on a quarterly basis by the Real Estate Assessor’s Office. This dataset contains information for properties in the city including: Acreage, Square footage, GPIN, Street Address, year built, current land value, current improvement values, and current total value. The information is obtained from Real Estate Assessor’s Office ProVal records database.

DATA SOURCES:

1. ONLY state sources (city/county/state administration, federal agencies, ministries, etc.). We DO NOT use unverified databases
2. Over 2300 sources. We use even the smallest sources, because they contain valuable data. This allows us to provide our users with the most complete data

DATA RELEVANCE:

1. Our data is updated daily, weekly, monthly depending on the sources
2. We collect, process and store all data, regardless of their relevance. Historical data is also valuable

DATA TYPES:

1. Specifications
2. Owners
3. Permits
4. Sales
5. Inspections
6. Violations
7. Assessed values
8. Taxes
9. Risks
10. Foreclosures
11. Property Tax Liens
12. Deed Restrictions

NUMBERS:

1. 2300 data sources in total
2. 155,000,000 properties in total
3. 4 billion records (listed in the "data types" block above) in total
4. 2 million new records every day

DATA USAGE:

1. Property check, investigation (even the smallest events are stored in our database)
2. Prospecting (more than 100 parameters to find the required records)
3. Tracking (our data allows us to track any changes)

DATA SOURCES:

1. ONLY state sources (city/county/state administration, federal agencies, ministries, etc.). We DO NOT use unverified databases
2. Over 2300 sources. We use even the smallest sources, because they contain valuable data. This allows us to provide our users with the most complete data

DATA RELEVANCE:

1. Our data is updated daily, weekly, monthly depending on the sources
2. We collect, process and store all data, regardless of their relevance. Historical data is also valuable

DATA TYPES:

1. Specifications
2. Owners
3. Permits
4. Sales
5. Inspections
6. Violations
7. Assessed values
8. Taxes
9. Risks
10. Foreclosures
11. Property Tax Liens
12. Deed Restrictions

NUMBERS:

1. 2300 data sources in total
2. 155,000,000 properties in total
3. 4 billion records (listed in the "data types" block above) in total
4. 2 million new records every day

DATA USAGE:

1. Property check, investigation (even the smallest events are stored in our database)
2. Prospecting (more than 100 parameters to find the required records)
3. Tracking (our data allows us to track any changes)

Abstract

Title: Cotality Smart Data Platform (SDP): Owner Transfer and Mortgage

The Owner Transfer and Mortgage data covers over 450 million properties, and includes over 50 years of sales history. The tables were generated in June 2024, and cover all U.S. states, the U.S. Virgin Islands, Guam, and Washington, D.C.

Formerly known as CoreLogic Smart Data Platform: Owner Transfer & Mortgage.

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

The Owner Transfer and Mortgage data covers over 450 million properties, and includes over 50 years of sales history. The tables were generated in June 2024, and cover all U.S. states, the U.S. Virgin Islands, Guam, and Washington, D.C. The Owner Transfer data provides historical information about property sales and ownership-related transactions, including full, nominal, and quitclaim transactions (involving a change in title/ownership). It contains comprehensive property and transaction information, such as property characteristics, current ownership, transaction history, title company, cash purchase/foreclosure/resale/short sale indicators, and buyer information.

The Mortgage data provides historical information at the mortgage level, including purchase, refinance, equity, as well as details associated with each transaction, such as lender, loan amount, loan date, interest rate, etc. Mortgage details include mortgage amount, type of loan (conventional, FHA, VHA), mortgage rate type, mortgage purpose (cash out first, consolidation, standalone subordinate), mortgage ARM features, and mortgage indicators such as fixed-rate, conforming loan, construction loan, and private party. The Mortgage data also includes subordinate mortgage types, rate details, and lender details (NMLS ID, Loan Company, Loan Officers).

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.

Mortgage records can be linked to a transaction using the MORTGAGE_COMPOSITE_TRANSACTION_ID.

For more information about included variables, please see:

• cotality_sdp_owner_transfer_data_dictionary_2024.txt
• cotality_sdp_mortgage_data_dictionary_2024.txt
• Mortgage_v3.xlsx
• Owner Transfer_v3.xlsx

%3C!-- --%3E

For a count of records per FIPS code, please see cotality_sdp_owner_transfer_counts_2024.txt and cotality_sdp_mortgage_counts_2024.txt.

For more information about how the Cotality Smart Data Platform: Owner Transfer and Mortgage data compares to legacy data, please see 2025_Legacy_Content_Mapping.pdf.

Bulk Data Access

Data access is required to view this section.

Records as provided by education providers to PSI testing service. Records are not validated by the State. Data will be updated approximately quarterly.

The various houses and related buildings that increase the value of the houses on the land within this city's jurisdiction are the statistical objects.

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.

DATA SOURCES:

1. ONLY state sources (city/county/state administration, federal agencies, ministries, etc.). We DO NOT use unverified databases
2. Over 2300 sources. We use even the smallest sources, because they contain valuable data. This allows us to provide our users with the most complete data

DATA RELEVANCE:

1. Our data is updated daily, weekly, monthly depending on the sources
2. We collect, process and store all data, regardless of their relevance. Historical data is also valuable

DATA TYPES:

1. Specifications
2. Owners
3. Permits
4. Sales
5. Inspections
6. Violations
7. Assessed values
8. Taxes
9. Risks
10. Foreclosures
11. Property Tax Liens
12. Deed Restrictions

NUMBERS:

1. 2300 data sources in total
2. 155,000,000 properties in total
3. 4 billion records (listed in the "data types" block above) in total
4. 2 million new records every day

DATA USAGE:

1. Property check, investigation (even the smallest events are stored in our database)
2. Prospecting (more than 100 parameters to find the required records)
3. Tracking (our data allows us to track any changes)

Context

House Sale Data with more than 50 column and around 66000 rows

Content

House Sale Data with more than 50 column and around 66000 rows

Acknowledgements

Got the Data Set from Jigsaw

Inspiration

To predict house sale price

A polygon depiction of property sales from 2010 to the present that occurred in Stark County, Ohio. The Stark County Auditor's Office (SCAO) maintains records of property sales using a Computer-Assisted Mass Appraisal (CAMA) Database. This layer is a SQL view combining the sales records from the CAMA database with the Stark County parcel layer. A new view is created every morning through a combination of python scripts and SQL stored procedures. The data always reflects the most-recent information available from the previous day for both sources.