6 datasets found
  1. d

    ZIP Code Population Weighted Centroids

    • catalog.data.gov
    Updated Mar 1, 2024
    + more versions
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    U.S. Department of Housing and Urban Development (2024). ZIP Code Population Weighted Centroids [Dataset]. https://catalog.data.gov/dataset/zip-code-population-weighted-centroids
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    Dataset updated
    Mar 1, 2024
    Dataset provided by
    U.S. Department of Housing and Urban Development
    Description

    This dataset denotes ZIP Code centroid locations weighted by population. Population weighted centroids are a common tool for spatial analysis, particularly when more granular data is unavailable or researchers lack sophisticated geocoding tools. The ZIP Code Population Weighted Centroids allows researchers and analysts to estimate the center of population in a given geography rather than the geometric center.

  2. f

    ACP Households by Zip Code Over Time

    • data.ferndalemi.gov
    Updated Jun 13, 2023
    + more versions
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    City of Detroit (2023). ACP Households by Zip Code Over Time [Dataset]. https://data.ferndalemi.gov/maps/34875fc6f5da4ec7af2e380b2323daa0
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    Dataset updated
    Jun 13, 2023
    Dataset authored and provided by
    City of Detroit
    Area covered
    Description

    Discounts for Internet service through the Affordable Connectivity Program (ACP) ended June 1, 2024 due to lack of additional funding. Whether the program will receive additional funding in the future is uncertain. Please see ACP program information from the FCC for more details.The Affordable Connectivity Program (ACP) households data set summarizes household enrollments and subscriptions by month and zip code for beneficiary households located in Detroit zip codes. The Affordable Connectivity Program (ACP) is a U.S. government program to help low-income households pay for Internet services and connected devices. Households that participate in ACP receive discounts on qualifying broadband Internet services of up to $30 per month and can also receive a one-time discount of up to $100 to purchase a laptop, desktop computer, or tablet. Households can qualify for ACP based on participation in Lifeline or other service provider programs for low-income households, income at or below 200% of the federal poverty guidelines, participation in other Lifeline-qualifying programs such as SNAP or Medicaid, or participation in free and reduced-price school lunch and breakfast programs. Additionally, service providers can ask the FCC to approve an alternative verification process and use that approved process to check consumer eligibility. ACP program discounts first became available to eligible enrolled households on January 1, 2022. The ACP claims process is built on the Lifeline Claims System and this data set is derived from snapshots of all subscribers entered in the National Lifeline Accountability Database (NLAD) as of the first of each month. The ACP was created under the Infrastructure Investment and Jobs Act, also known as the Bipartisan Infrastructure Law, and is administered by the independent not-for-profit Universal Service Access Co. under the direction of the Federal Communications Commission (FCC). Eligible beneficiaries who participated in the Emergency Broadband Benefit (EBB) program that was funded by the Coronavirus Aid, Relief, and Economic Security (CARES) Act, were transitioned to ACP between January 1 and March 1, 2022. EBB was ACP's predecessor program and ran from May 12, 2021 until it was phased out on February 28, 2022. Due to the granularity of available data, households located in communities adjacent to Detroit that share a zip code such as Hamtramck and Highland Park are included in this data set.Fieldsprogram - Associated program for the data (ACP or EBB)data_month - Data month is associated with the subscriber snapshot for each claim month. If data month is listed as '5/1/2022', then the subscriber snapshot was captured on June 1, and the data represents the number of households in ACP as of June 1. This is the universe of subscribers that providers can claim for the May 2022 data month.zipcode - Zip code where the enrolled household is located.net_new_enrollments_alternative_verification_process - Difference between the current month Total Subscribers who qualified using an alternative verification process and prior month Total Subscribers who qualified using an alternative verification process.net_new_enrollments_verified_by_school - Difference between the current month Total Subscribers who qualified using school lunch program verification and prior month Total Subscribers who qualified using school lunch program verification.net_new_enrollments_lifeline - Difference between the current month Total Subscribers who qualified using the Lifeline program and prior month Total Subscribers who qualified using the Lifeline program.net_new_enrollments_national_verifier_application - Difference between the current month Total Subscribers who qualified using a National Verifier application and prior month Total Subscribers who qualified using a National Verifier application.net_new_enrollments_total - Difference between the total number of subscribers in the current and prior months. Calculated based on the sum of net new monthly enrollments verified by the school, lifeline, alternative verification process, and national verifier application programs.total_alternative_verification_process - Number of households in the ACP on the first of the month snapshot whose eligibility was determined via an FCC-approved alternative verification process. total_verified_by_school - Number of households in the ACP on the first of the month snapshot whose eligibility was verified based on participation in a school lunch program.total_lifeline - Number of households in the ACP on the first of the month snapshot whose eligibility was determined based on participation in Lifeline, a federal program that lowers the monthly cost of phone or Internet services.total_national_verifier_application - Number of households in the ACP on of the first of the month snapshot whose eligibility was determined via the National Eligibility Verifier (National Verifier) system.total_subscribers - Number of total households participating in ACP on the first of the month snapshot. If, for example, there were 100 subscribers enrolled as of the June 1, 2022 snapshot, then Total Subscribers for the 05/01/2022 (May 2022) data month would be 100.

  3. w

    Broadband Speed Tests by Zip Code

    • data.wu.ac.at
    csv, json, xml
    Updated Jun 1, 2017
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    State of Colorado Governor's Office of Information Technology GIS Coordination and Development Program (2017). Broadband Speed Tests by Zip Code [Dataset]. https://data.wu.ac.at/schema/data_colorado_gov/cDQzZC1oYWJr
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    json, xml, csvAvailable download formats
    Dataset updated
    Jun 1, 2017
    Dataset provided by
    State of Colorado Governor's Office of Information Technology GIS Coordination and Development Program
    License

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

    Description

    All broadband speed tests performed using the http://maps.co.gov/publicspeed/ speed test. This data set begins in January 2012 and ends in May of 2016. The data consists of latency, download speed, upload speed, and the zip code in which the speed test was performed. More granular data can be made available by request and is considered on a case by case basis, please contact the Broadband Team leader for additional details.

  4. d

    Who drives electric vehicles in Alabama: a fusion of vehicle ownership,...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Oct 28, 2025
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    Ma, Muting; Hudnall, Matthew; Yavuz, Mesut (2025). Who drives electric vehicles in Alabama: a fusion of vehicle ownership, socio-economic, demographic, and political data [Dataset]. http://doi.org/10.7910/DVN/LGTJWN
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    Dataset updated
    Oct 28, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Ma, Muting; Hudnall, Matthew; Yavuz, Mesut
    Description

    We collect comprehensive data from multiple sources, including the Alabama Department of Revenue (ALDOR), American Community Survey (ACS), and POLK, all mapped with zipcode-level granularity to enable precise geospatial analysis. Our data organization strategy categorizes information by fuel types (focusing on BEVs compared to conventional vehicles), geographical units (zip codes as primary units), and different measurement types (including absolute counts, per capita values, and proportional measurements) to facilitate multi-dimensional analysis.

  5. d

    State, District and Post Office-wise PIN Codes with Latitude and Longitudes

    • dataful.in
    Updated Oct 31, 2025
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    Dataful (Factly) (2025). State, District and Post Office-wise PIN Codes with Latitude and Longitudes [Dataset]. https://dataful.in/datasets/19996
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    xlsx, csv, application/x-parquetAvailable download formats
    Dataset updated
    Oct 31, 2025
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Time period covered
    2025
    Area covered
    Postal Division, Districts of India, State of India, Postal Regions, Postal Circles
    Variables measured
    PIN Code, Coordinates
    Description

    This Dataset contains state, district, circle, region, division wise post office PIN codes with Latitude and Longitudes

    Note: Please note that the source itself has some errors and has a few latitude and longitude points which are plotted outside India's geographic borders

  6. Key Data | Real-Time API | Custom Mapping Breakdowns for hotels & short-term...

    • datarade.ai
    .csv
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    Key Data Dashboard, Key Data | Real-Time API | Custom Mapping Breakdowns for hotels & short-term rentals | Entertainment Data [Dataset]. https://datarade.ai/data-products/key-data-real-time-api-custom-mapping-breakdowns-for-hot-key-data-dashboard
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    .csvAvailable download formats
    Dataset provided by
    Key Data Dashboard, Inc.
    Authors
    Key Data Dashboard
    Area covered
    Palau, Zambia, Mauritania, Åland Islands, Tajikistan, Senegal, Peru, Vanuatu, Mexico, Jersey
    Description

    High-precision spatial intelligence with unmatched geographic accuracy. Our Custom Mapping Capabilities enable hyper-granular spatial alignment across hospitality and real estate datasets. Using proprietary geocoding frameworks and multi-source validation, we accurately map properties, markets, and performance metrics at any geographic level — from individual buildings and parcels to neighborhoods, ZIP codes, or global regions.

    Each mapping layer is constructed with verified geographic identifiers, ensuring precision even in dense urban environments or regions with inconsistent boundary data. By harmonizing disparate datasets — including OTA listings, PMS performance data, and regional economic indicators — our mapping infrastructure provides a unified spatial framework for robust analysis, benchmarking, and model development.

    Key Highlights: High-Resolution Accuracy: Geocoding precision down to the building or parcel level.

    Flexible Granularity: Customizable boundaries — neighborhood, ZIP code, municipality, or custom trade area.

    Verified Spatial Matching: Cross-validated against multiple data sources to eliminate boundary errors and duplicate entities.

    Consistent Global Framework: Enables cross-market comparison and seamless integration of diverse data assets.

    Custom Overlay Capabilities: Combine OTA, hotel, and STR datasets into cohesive geographic layers for advanced analysis.

    Use It To: Build consistent spatial models across global lodging markets.

    Align disparate datasets for accurate benchmarking and forecasting.

    Visualize property-level or area-level insights with precision geographic fidelity.

    Enable detailed submarket analysis, investment mapping, and data enrichment workflows.

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    Learn how you can add new datasets to our index.

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U.S. Department of Housing and Urban Development (2024). ZIP Code Population Weighted Centroids [Dataset]. https://catalog.data.gov/dataset/zip-code-population-weighted-centroids

ZIP Code Population Weighted Centroids

Explore at:
32 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Mar 1, 2024
Dataset provided by
U.S. Department of Housing and Urban Development
Description

This dataset denotes ZIP Code centroid locations weighted by population. Population weighted centroids are a common tool for spatial analysis, particularly when more granular data is unavailable or researchers lack sophisticated geocoding tools. The ZIP Code Population Weighted Centroids allows researchers and analysts to estimate the center of population in a given geography rather than the geometric center.

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