17 datasets found
  1. USA Email List | USA Email Address List | 100M+ Business Emails

    • datacaptive.com
    Updated Mar 9, 2023
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    DataCaptive™ (2023). USA Email List | USA Email Address List | 100M+ Business Emails [Dataset]. https://www.datacaptive.com/usa-email-list/
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    Dataset updated
    Mar 9, 2023
    Dataset provided by
    DataCaptive
    Authors
    DataCaptive™
    Area covered
    United States
    Description

    Empower your outreach strategy with our exclusive USA Email Address List, featuring 100M+ business emails for unparalleled connection and impact.

  2. Domain Names with US Registrants — Registered between March 16, 2018 to...

    • dataandsons.com
    csv, zip
    Updated Apr 2, 2018
    + more versions
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    Jason Iverson Consulting (2018). Domain Names with US Registrants — Registered between March 16, 2018 to March 31, 2018 [Dataset]. https://www.dataandsons.com/data-market/lead-generation/domain-names-with-us-registrants-registered-between-march-16-2018-to-march-31-2018
    Explore at:
    csv, zipAvailable download formats
    Dataset updated
    Apr 2, 2018
    Dataset provided by
    Authors
    Jason Iverson Consulting
    License

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

    Time period covered
    Mar 16, 2018 - Mar 31, 2018
    Area covered
    United States
    Description

    About this Dataset

    For sale are domain names with WHO IS information that were registered between Mar 16, 2018 and Mar 31, 2018 by registrants in United States. Domains which obfuscate registrant, administrative, and other WHO IS contact details have been omitted from this dataset. The following information is availble for download in this dataset: - Domain name, Created Date, Updated Date, Expiration Date, Registrar Name- Registrant Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- Administrative Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- Technical Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- Billing Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- NameServer1, NameServer2, NameServer3, NameServer4, - DomainStatus1, DomainStatus2, DomainStatus3, DomainStatus4 Still unsure about purchasing this dataset? View and Download a free sample dataset of global domain name registrations in the Lead Generation category Are you interested in a more targeted domain name registration dataset? Select the "Ask Seller a Question" link, send me a message, and I'll get back to you as soon as I can.

    Category

    Lead Generation

    Keywords

    usa,united-states,newly-registered-domains,who-is-data

    Row Count

    220910

    Price

    $20.00

  3. Domain Names with US Registrants — Registered between Feb 24, 2018 to Feb...

    • dataandsons.com
    csv, zip
    Updated Mar 17, 2018
    + more versions
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    Jason Iverson Consulting (2018). Domain Names with US Registrants — Registered between Feb 24, 2018 to Feb 28, 2018 [Dataset]. https://www.dataandsons.com/categories/lead-generation/domain-names-with-us-registrants-registered-between-feb-24-2018-to-feb-28-2018
    Explore at:
    csv, zipAvailable download formats
    Dataset updated
    Mar 17, 2018
    Dataset provided by
    Authors
    Jason Iverson Consulting
    License

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

    Time period covered
    Feb 24, 2018 - Feb 28, 2018
    Area covered
    United States
    Description

    About this Dataset

    For sale are domain names that were registered between Feb 24, 2018 and Feb 28, 2018 by registrants in United States. Domains which obfuscate registrant, administrative, and other WHO IS contact details have been omitted from this dataset. The following information is availble for download in this dataset: - Domain name, Created Date, Updated Date, Expiration Date, Registrar Name- Registrant Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- Administrative Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- Technical Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- Billing Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- NameServer1, NameServer2, NameServer3, NameServer4, - DomainStatus1, DomainStatus2, DomainStatus3, DomainStatus4 Still unsure about purchasing this dataset? View and Download a free sample dataset of global domain name registrations - https://www.dataandsons.com/categories/lead_generation/domain-names-registered-between-feb-12-2018-to-feb-18-2018. Are you interested in a more targeted domain name registration dataset? Select the "Ask Seller a Question" link, send me a message, and I'll get back to you as soon as I can.

    Category

    Lead Generation

    Keywords

    USA,United-States,newly-registered-domain-names,recently-registered-domain-names,who-is-data

    Row Count

    84127

    Price

    $10.00

  4. d

    U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2020)

    • catalog.data.gov
    Updated Jun 15, 2024
    + more versions
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    National Renewable Energy Laboratory (NREL) (2024). U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2020) [Dataset]. https://catalog.data.gov/dataset/u-s-electric-utility-companies-and-rates-look-up-by-zipcode-2020
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    Dataset updated
    Jun 15, 2024
    Dataset provided by
    National Renewable Energy Laboratory (NREL)
    Area covered
    United States
    Description

    This dataset, compiled by NREL using data from ABB, the Velocity Suite and the U.S. Energy Information Administration dataset 861, provides average residential, commercial and industrial electricity rates with likely zip codes for both investor owned utilities (IOU) and non-investor owned utilities. Note: the files include average rates for each utility (not average rates per zip code), but not the detailed rate structure data found in the OpenEI U.S. Utility Rate Database.

  5. T

    Iowa Geographic Names

    • data.iowa.gov
    • s.cnmilf.com
    • +2more
    Updated May 23, 2025
    + more versions
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    U.S. Geological Survey, Geographic Names Project, U.S. Geographic Names Information System (GNIS), Address: 523 National Center, Reston, VA 20192, Phone: 703-648-4552 (2025). Iowa Geographic Names [Dataset]. https://data.iowa.gov/w/uedc-2fk7/9c2r-rgb3?cur=8n1YryWiIrB
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    csv, kml, tsv, application/rdfxml, kmz, application/rssxml, application/geo+json, xmlAvailable download formats
    Dataset updated
    May 23, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey, Geographic Names Project, U.S. Geographic Names Information System (GNIS), Address: 523 National Center, Reston, VA 20192, Phone: 703-648-4552
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Area covered
    Iowa
    Description

    This dataset provides the geographic names data for Iowa. All names data products are extracted from the Geographic Names Information System (GNIS), the Federal Government's repository of official geographic names.

    The GNIS contains the federally recognized name of each feature and defines its location by State, county, USGS topographic map, and geographic coordinates. GNIS also lists variant names, which are non-official names by which a feature is or was known. Other attributes include unique Feature ID and feature class. Feature classes under the purview of the U.S. Board on Geographic Names include natural features, unincorporated populated places, canals, channels, reservoirs, and more.

  6. o

    Counties - United States of America

    • public.opendatasoft.com
    • bfortune.opendatasoft.com
    csv, excel, geojson +1
    Updated Jun 6, 2024
    + more versions
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    (2024). Counties - United States of America [Dataset]. https://public.opendatasoft.com/explore/dataset/georef-united-states-of-america-county/
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    excel, json, geojson, csvAvailable download formats
    Dataset updated
    Jun 6, 2024
    License

    https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain

    Area covered
    United States
    Description

    This dataset is part of the Geographical repository maintained by Opendatasoft. This dataset contains data for counties and equivalent entities in United States of America. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities.Processors and tools are using this data. Enhancements Add ISO 3166-3 codes. Simplify geometries to provide better performance across the services. Add administrative hierarchy.

  7. NYCHA Residential Addresses

    • data.cityofnewyork.us
    • catalog.data.gov
    application/rdfxml +5
    Updated Jul 7, 2025
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    NYC Housing Authority (NYCHA) (2025). NYCHA Residential Addresses [Dataset]. https://data.cityofnewyork.us/Housing-Development/NYCHA-Residential-Addresses/3ub5-4ph8
    Explore at:
    json, application/rssxml, tsv, csv, application/rdfxml, xmlAvailable download formats
    Dataset updated
    Jul 7, 2025
    Dataset provided by
    New York City Housing Authorityhttp://topics.nytimes.com/top/reference/timestopics/organizations/n/new_york_city_housing_authority/index.html
    Authors
    NYC Housing Authority (NYCHA)
    Description

    List of NYCHA residential addresses.

  8. a

    2020 U.S. Census TIGER Roads

    • hub.arcgis.com
    • geo-massdot.opendata.arcgis.com
    • +1more
    Updated Dec 15, 2022
    + more versions
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    MassGIS - Bureau of Geographic Information (2022). 2020 U.S. Census TIGER Roads [Dataset]. https://hub.arcgis.com/maps/d7738b2d15044107bfc41b15a0f2e92d
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    Dataset updated
    Dec 15, 2022
    Dataset authored and provided by
    MassGIS - Bureau of Geographic Information
    Area covered
    Description

    The intended dual purpose of MassGIS’ efforts in processing this data is to both create a geocoding resource that can supplement the addressing data available in its Master Address Database, and compile a comprehensive set of Census Bureau road features for map display, query, and analysis. Linear road features attributed with street names, address ranges, and other useful information have been generated from a combination of Census Bureau layers. A full list of the various Census 2020 TIGER/Line layers available for download can be found in this summary. See the datalayer metadata for full details.

    Feature service also available.

  9. o

    Data from: US County Boundaries

    • public.opendatasoft.com
    csv, excel, geojson +1
    Updated Jun 27, 2017
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    (2017). US County Boundaries [Dataset]. https://public.opendatasoft.com/explore/dataset/us-county-boundaries/
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    json, csv, excel, geojsonAvailable download formats
    Dataset updated
    Jun 27, 2017
    License

    https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain

    Area covered
    United States
    Description

    The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for counties and equivalent entities are as of January 1, 2017, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

  10. N

    Civil List

    • data.cityofnewyork.us
    • gimi9.com
    • +3more
    application/rdfxml +5
    Updated Jul 8, 2024
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    Department of Citywide Administrative Services (DCAS) (2024). Civil List [Dataset]. https://data.cityofnewyork.us/City-Government/Civil-List/ye3c-m4ga
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    tsv, application/rdfxml, application/rssxml, xml, csv, jsonAvailable download formats
    Dataset updated
    Jul 8, 2024
    Dataset authored and provided by
    Department of Citywide Administrative Services (DCAS)
    License

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

    Description

    The Civil List reports the agency code (DPT), first initial and last name (NAME), agency name (ADDRESS), title code (TTL #), pay class (PC), and salary (SAL-RATE) of individuals who were employed by the City of New York at any given time during the indicated year.

  11. U

    United States Avg Sale To List: Townhouse: New York

    • ceicdata.com
    Updated Jun 3, 2017
    + more versions
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    CEICdata.com (2017). United States Avg Sale To List: Townhouse: New York [Dataset]. https://www.ceicdata.com/en/united-states/average-sales-to-list-by-states/avg-sale-to-list-townhouse-new-york
    Explore at:
    Dataset updated
    Jun 3, 2017
    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
    Aug 1, 2019 - Jul 1, 2020
    Area covered
    United States
    Description

    United States Avg Sale To List: Townhouse: New York data was reported at 98.622 % in Jul 2020. This records an increase from the previous number of 98.365 % for Jun 2020. United States Avg Sale To List: Townhouse: New York data is updated monthly, averaging 96.864 % from Feb 2012 to Jul 2020, with 102 observations. The data reached an all-time high of 98.866 % in Apr 2020 and a record low of 95.321 % in Feb 2012. United States Avg Sale To List: Townhouse: New York data remains active status in CEIC and is reported by Redfin. The data is categorized under Global Database’s United States – Table US.EB049: Average Sales to List: by States.

  12. a

    Complete List of Hot Topic Locations in the United States

    • aggdata.com
    csv
    Updated May 27, 2025
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    AggData (2025). Complete List of Hot Topic Locations in the United States [Dataset]. https://www.aggdata.com/aggdata/complete-list-hot-topic-locations-united-states
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    csvAvailable download formats
    Dataset updated
    May 27, 2025
    Dataset authored and provided by
    AggData
    Area covered
    United States
    Description

    Hot Topic is a retail chain that caters to alternative subcultures and fandoms, offering apparel, accessories, and merchandise related to music, gaming, anime, and pop culture trends. Hot Topic focuses on providing unique and expressive items that allow customers to showcase their individuality and passions. Think music band t-shirts, graphic tees with pop culture references, body jewelry, and accessories inspired by popular anime and video games. Hot Topic aims to create a welcoming space for those who embrace alternative styles and fandoms, fostering a sense of community among their customer base. The Hot Topic business model relies on staying ahead of trends by constantly updating their merchandise to reflect the latest in music, gaming, and pop culture. This ensures they remain relevant to their target audience and capture emerging interests. Hot Topic also leverages licensed merchandise, collaborating with popular franchises and brands to offer exclusive products that appeal to dedicated fans. You can download the complete list of key information about Hot Topic locations, contact details, services offered, and geographical coordinates, beneficial for various applications like store locators, business analysis, and targeted marketing. The Hot Topic data you can download includes:

    Identification & Location:
    
    
      Store_number, store_name, address, address_line_2, city, state, zip_code, latitude, longitude, country, country_code, county, geo_accuracy
    
    
    Contact Information:
    
    
       Phone_number, 
    
    
    Operational Details & Services:
    
    
      Store_hours,  
    
  13. TIGER/Line Shapefile, 2023, County, Harris County, TX, Feature Names...

    • catalog.data.gov
    Updated Dec 15, 2023
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geospatial Products Branch (Point of Contact) (2023). TIGER/Line Shapefile, 2023, County, Harris County, TX, Feature Names Relationship File [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2023-county-harris-county-tx-feature-names-relationship-file
    Explore at:
    Dataset updated
    Dec 15, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Harris County, Texas
    Description

    The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

  14. TIGER/Line Shapefile, 2023, County, Talladega County, AL, Feature Names...

    • catalog.data.gov
    Updated Dec 15, 2023
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geospatial Products Branch (Point of Contact) (2023). TIGER/Line Shapefile, 2023, County, Talladega County, AL, Feature Names Relationship File [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2023-county-talladega-county-al-feature-names-relationship-file
    Explore at:
    Dataset updated
    Dec 15, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Alabama, Talladega County
    Description

    The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

  15. TIGER/Line Shapefile, 2023, County, Des Moines County, IA, Feature Names...

    • catalog.data.gov
    Updated Dec 14, 2023
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geospatial Products Branch (Point of Contact) (2023). TIGER/Line Shapefile, 2023, County, Des Moines County, IA, Feature Names Relationship File [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2023-county-des-moines-county-ia-feature-names-relationship-file
    Explore at:
    Dataset updated
    Dec 14, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Des Moines County
    Description

    The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

  16. TIGER/Line Shapefile, 2023, County, Missaukee County, MI, Feature Names...

    • catalog.data.gov
    Updated Dec 14, 2023
    + more versions
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geospatial Products Branch (Point of Contact) (2023). TIGER/Line Shapefile, 2023, County, Missaukee County, MI, Feature Names Relationship File [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2023-county-missaukee-county-mi-feature-names-relationship-file
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    Dataset updated
    Dec 14, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Missaukee County, Michigan
    Description

    The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

  17. TIGER/Line Shapefile, 2023, County, Arkansas County, AR, Feature Names...

    • catalog.data.gov
    Updated Dec 15, 2023
    + more versions
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geospatial Products Branch (Point of Contact) (2023). TIGER/Line Shapefile, 2023, County, Arkansas County, AR, Feature Names Relationship File [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2023-county-arkansas-county-ar-feature-names-relationship-file
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    Dataset updated
    Dec 15, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Arkansas County
    Description

    The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

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DataCaptive™ (2023). USA Email List | USA Email Address List | 100M+ Business Emails [Dataset]. https://www.datacaptive.com/usa-email-list/
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USA Email List | USA Email Address List | 100M+ Business Emails

Explore at:
Dataset updated
Mar 9, 2023
Dataset provided by
DataCaptive
Authors
DataCaptive™
Area covered
United States
Description

Empower your outreach strategy with our exclusive USA Email Address List, featuring 100M+ business emails for unparalleled connection and impact.

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