US National Property Listing Data | 50+ Property & Building Characteristics | Pricing & Real Estate Agent Information
The Warren Group
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Verified Data Provider
Verified Data Provider| # | PROPID |
SitusHouseNbr |
SitusDirectionLeft |
SitusStreet |
SitusMode |
SitusDirectionRight |
SitusUnitNbr |
SitusCity |
SitusZIP4 |
APN |
FIPS |
PropertyType |
PropertySubType |
LotSizeSqFt |
HomeSize |
Style |
HeatingFuelType |
CoolingType |
CoolingFuelType |
StoriesNbr |
YearBuilt |
RoofType |
ExteriorConstruction |
Bedrooms |
Heatingtype |
Bathrooms |
Garages |
GarageType |
PoolFeatures |
ViewFeatures |
PricePerSqFt |
Porch |
Patio |
Deck |
Basement |
AirConditioner |
FireplaceNbr |
Fireplace |
FireplaceDescription |
InteriorFeatures |
ExteriorFeatures |
ExistingStructures |
LotFeatures |
Zoning |
Neighborhood |
SchoolDistrict |
ElementarySchool |
MiddleSchool |
HighSchool |
Appliances |
ApproximateLotDimensions |
Topogrophy |
WaterfrontFeatures |
Water |
WaterSource |
WaterAmenities |
WaterAccess |
WaterHeater |
InitialListDate |
CalculatedDaysOnMarket |
CurrentOriginalListingDate |
InitialListStatus |
ListingNumber |
Status |
StatusSubType |
RentalIndicator |
CurrentListingPrice |
MaxListPrice |
MaxListPriceDate |
MinListPrice |
MinListPriceDate |
SoldPrice |
SoldDate |
AdjustedSoldPrice |
SoldPriceRange |
LastListingPriceChangeAmount |
LastListingPriceChangeDate |
PriorListingPriceChangeAmount |
PriorListingPriceChangeDate |
LastListingStatusChange |
LastListingStatusChangeDate |
LastListingStatusSubTypeChange |
LastListingStatusSubTypeChangeDate |
PriorListingStatusChange |
PriorListingStatusChangeDate |
PriorListingStatusSubTypeChange |
PriorListingStatusSubTypeChangeDate |
ListingAgentLicenseNumber |
ListingAgentName |
ListingAgentAddress |
ListingAgentPhone |
ListingAgentEmail |
OfficeName |
OfficeAddress |
OfficePhone |
OfficeEmail |
ListingTrackingID |
UpdateTimestamp |
CurrentListingInd |
CurrentRentalInd |
|||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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| 8 | xxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxx | xxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxx | Xxxxxxx | xxxxx | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxx | xxxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxx | xxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxx | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxx | xxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxx | xxxxxx | Xxxxx | xxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxx | xxxxxx | xxxxxx | xxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxx | Xxxxxx |
| 9 | xxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | xxxxxx | xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxx | xxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | Xxxxx | xxxxxxxxx | Xxxxx | Xxxxx | xxxxx | xxxxxx | xxxxxx | xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxx | xxxxx | xxxxxxxx | xxxxx | Xxxxx | xxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxx | Xxxxx | xxxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxx | xxxxxx | xxxxxx | xxxxxxxxx | Xxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxx | Xxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxx | xxxxx | xxxxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxxx |
| 10 | xxxxxx | Xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxx | Xxxxxx | xxxxx | xxxxx | Xxxxxxxx | Xxxxxx | Xxxxx | Xxxxx | xxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | xxxxxx | xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxx | xxxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxx | xxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | xxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxx | Xxxxxxxxxx | Xxxxxxxx |
| ... | Xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxx | xxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx | xxxxxx | Xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxx | xxxxx | Xxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxx | xxxxxx | xxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxx | xxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxx | Xxxxxx | xxxxx | xxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxx | xxxxxxxx | Xxxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxx | xxxxxxxxx | xxxxx | xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxx | xxxxx |
Volume
50
Property Characteristics
Data Quality
99%
Coverage
Avail. Formats
.csv, .xls, and .txt
File
Coverage
1
Country
Data Dictionary
[Sample] The-Warren-Group-Real-Estate-Listing-Data-Sample.csv
| Attribute | Type | Example | Mapping |
|---|---|---|---|
|
PROPID
|
String | LIST0600966585201 | |
| String | Address | ||
|
SitusHouseNbr
|
Integer | 1030 | |
|
SitusDirectionLeft
|
|||
|
SitusStreet
|
String | Bragg | |
|
SitusMode
|
String | Rd | |
|
SitusDirectionRight
|
|||
|
SitusUnitNbr
|
|||
|
SitusCity
|
String | Angels Camp | |
| String | CA | State Abbreviation | |
| Integer | 95222 | ZIP Code | |
|
SitusZIP4
|
Integer | 9393 | |
|
APN
|
String | 062-003-004 | |
|
FIPS
|
Integer | 6009 | |
|
PropertyType
|
String | SFR | |
|
PropertySubType
|
|||
|
LotSizeSqFt
|
Integer | 5663 | |
|
HomeSize
|
|||
|
Style
|
String | COTTAGE/BUNGALOW | |
|
HeatingFuelType
|
|||
|
CoolingType
|
String | EVAPORATIVE COOLER WINDOW UNIT(S) | |
|
CoolingFuelType
|
|||
|
StoriesNbr
|
|||
|
YearBuilt
|
Integer | 1921 | |
|
RoofType
|
String | SHINGLE ROOF | |
|
ExteriorConstruction
|
String | FRAME WOOD | |
|
Bedrooms
|
Integer | 2 | |
|
Heatingtype
|
String | ELECTRIC STOVE | |
|
Bathrooms
|
Integer | 2 | |
|
Garages
|
|||
|
GarageType
|
String | NO GARAGE | |
|
PoolFeatures
|
|||
|
ViewFeatures
|
|||
|
PricePerSqFt
|
|||
|
Porch
|
|||
|
Patio
|
|||
|
Deck
|
|||
|
Basement
|
|||
|
AirConditioner
|
|||
|
FireplaceNbr
|
|||
|
Fireplace
|
|||
|
FireplaceDescription
|
|||
|
InteriorFeatures
|
String | LAMINATE COUNTER TOPS | |
|
ExteriorFeatures
|
String | SIDING WOOD EXTERIOR | |
|
ExistingStructures
|
|||
|
LotFeatures
|
String | SLOPE WOODED / TREES | |
|
Zoning
|
String | SFR | |
|
Neighborhood
|
|||
|
SchoolDistrict
|
String | CALAVERAS | |
|
ElementarySchool
|
String | MARK TWAIN UNION | |
|
MiddleSchool
|
String | MARK TWAIN UNION | |
|
HighSchool
|
String | BRETT HARTE UNION | |
|
Appliances
|
String | DISHWASHER GAS RANGE MICROWAVE | |
|
ApproximateLotDimensions
|
|||
|
Topogrophy
|
|||
|
WaterfrontFeatures
|
|||
|
Water
|
String | METERED WATER PUBLIC WATER | |
|
WaterSource
|
|||
|
WaterAmenities
|
|||
|
WaterAccess
|
|||
|
WaterHeater
|
|||
|
InitialListDate
|
String | 12/12/19 | |
|
CalculatedDaysOnMarket
|
Integer | 316 | |
|
CurrentOriginalListingDate
|
String | 12/12/19 | |
|
InitialListStatus
|
String | Active | |
|
ListingNumber
|
Integer | 19081436 | |
|
Status
|
String | Sold | |
|
StatusSubType
|
|||
|
RentalIndicator
|
|||
|
CurrentListingPrice
|
Integer | 185000 | |
|
MaxListPrice
|
Integer | 195000 | |
|
MaxListPriceDate
|
String | 12/13/19 | |
|
MinListPrice
|
Integer | 185000 | |
|
MinListPriceDate
|
String | 6/1/20 | |
|
SoldPrice
|
Integer | 185000 | |
|
SoldDate
|
String | 10/23/20 | |
|
AdjustedSoldPrice
|
Integer | 186000 | |
|
SoldPriceRange
|
String | 184800-185200 | |
|
LastListingPriceChangeAmount
|
Integer | -10000 | |
|
LastListingPriceChangeDate
|
String | 8/5/20 | |
|
PriorListingPriceChangeAmount
|
Integer | 10000 | |
|
PriorListingPriceChangeDate
|
String | 7/31/20 | |
|
LastListingStatusChange
|
String | Fail | |
|
LastListingStatusChangeDate
|
String | 8/8/20 | |
|
LastListingStatusSubTypeChange
|
|||
|
LastListingStatusSubTypeChangeDate
|
|||
|
PriorListingStatusChange
|
String | Pending | |
|
PriorListingStatusChangeDate
|
String | 8/7/20 | |
|
PriorListingStatusSubTypeChange
|
|||
|
PriorListingStatusSubTypeChangeDate
|
|||
|
ListingAgentLicenseNumber
|
String | PersonLicenseNumber | |
|
ListingAgentName
|
String | Tamara Dillashaw | |
|
ListingAgentAddress
|
|||
|
ListingAgentPhone
|
String | (209) 743-0197 | |
|
ListingAgentEmail
|
String | tammy.dillashaw@gmail.com | |
|
OfficeName
|
String | NEXTHOME UTICA PROPERTIES | |
|
OfficeAddress
|
|||
|
OfficePhone
|
|||
|
OfficeEmail
|
|||
|
ListingTrackingID
|
Integer | 88398814 | |
|
UpdateTimestamp
|
String | 11/18/20 | |
|
CurrentListingInd
|
Boolean | t | |
|
CurrentRentalInd
|
Description
In a constantly changing marketplace, access to timely property listings data is crucial. With this robust data set, you can gain a complete view of a single property, market trends, and even buyer behavior.
Real estate is a dynamic and ever-evolving industry that relies heavily on data to make informed decisions. One of the fundamental aspects of this industry is real estate listing data. This data encompasses detailed information about properties that are available for sale or rent in a given market. It plays a pivotal role in assisting buyers, sellers, real estate professionals, and investors in making well-informed choices. In this data brief, we will provide an overview of what real estate listing data is and highlight five key industry use cases.
Real Estate Listings Data Includes:
- Property Location
- 50+ Property and Building Characteristics
- School District Information
- List Date
- Listing Price - Maximum, Minimum, Sold Price
- Listing Status
- Number of Days on Market
- Listing Agent and Office
Country Coverage
North America
(1)
United States of America
Volume
| 50 | Property Characteristics |
Pricing
| License | Starts at |
|---|---|
| One-off purchase | Available |
| Monthly License | Available |
| Yearly License | Available |
| Usage-based | Available |
Suitable Company Sizes
Small Business
Medium-sized Business
Enterprise
Quality
Self-reported by the provider
Coverage
Delivery
Methods
S3 Bucket
SFTP
Email
Frequency
weekly
monthly
Format
.csv
.xls
.txt
Use Cases
Property Valuation
Real Estate Investment
Real Estate Agencies
Real Estate Intelligence
Real Estate Insights
Categories
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Frequently asked questions
What is US National Property Listing Data 50+ Property & Building Characteristics Pricing & Real Estate Agent Information?
In a constantly changing marketplace, access to timely property listings data is crucial. With this robust data set, you can gain a complete view of a single property, market trends, and even buyer behavior.
What is US National Property Listing Data 50+ Property & Building Characteristics Pricing & Real Estate Agent Information used for?
This product has 5 key use cases. The Warren Group recommends using the data for Property Valuation, Real Estate Investment, Real Estate Agencies, Real Estate Intelligence, and Real Estate Insights. Global businesses and organizations buy Property Data from The Warren Group to fuel their analytics and enrichment.
Who can use US National Property Listing Data 50+ Property & Building Characteristics Pricing & Real Estate Agent Information?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Property Data. Get in touch with The Warren Group to see what their data can do for your business and find out which integrations they provide.
Which countries does US National Property Listing Data 50+ Property & Building Characteristics Pricing & Real Estate Agent Information cover?
This product includes data covering 1 country like USA. The Warren Group is headquartered in United States of America.
How much does US National Property Listing Data 50+ Property & Building Characteristics Pricing & Real Estate Agent Information cost?
Pricing information for US National Property Listing Data 50+ Property & Building Characteristics Pricing & Real Estate Agent Information is available by getting in contact with The Warren Group. Connect with The Warren Group to get a quote and arrange custom pricing models based on your data requirements.
How can I get US National Property Listing Data 50+ Property & Building Characteristics Pricing & Real Estate Agent Information?
Businesses can buy Property Data from The Warren Group and get the data via S3 Bucket, SFTP, and Email. Depending on your data requirements and subscription budget, The Warren Group can deliver this product in .csv, .xls, and .txt format.
What is the data quality of US National Property Listing Data 50+ Property & Building Characteristics Pricing & Real Estate Agent Information?
The Warren Group has reported that this product has the following quality and accuracy assurances: 99% Coverage. You can compare and assess the data quality of The Warren Group using Datarade’s data marketplace. The Warren Group appears on selected Datarade top lists ranking the best data providers, including Best 5 Mortgage APIs for Better Mortgage Servicing and Who’s New on Datarade? January Edition.
What are similar products to US National Property Listing Data 50+ Property & Building Characteristics Pricing & Real Estate Agent Information?
This product has 3 related products. These alternatives include US National MLS Property Listings Data Multiple Listing Service 60M+ Records Property & Building Characteristics, BatchService Commercial & Residential Real Estate Data + Property Listings Data 150 million US property records, and Realtor.com Dataset Property Listings MLS Data Real Estate Data Residential Data Realtime Real Estate Market Data. You can compare the best Property Data providers and products via Datarade’s data marketplace and get the right data for your use case.
The Warren Group
Trusted Real Estate & Financial Information Since 1872
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