100+ datasets found
  1. Demographics API - Nation

    • s.cnmilf.com
    • catalog.data.gov
    • +1more
    Updated Mar 11, 2021
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    National Telecommunication and Information Administration, Department of Commerce (2021). Demographics API - Nation [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/demographics-api-nation
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    Dataset updated
    Mar 11, 2021
    Dataset provided by
    United States Department of Commercehttp://commerce.gov/
    Description

    This API returns a search for the demographic information for the whole nation.

  2. u

    Population by Tracts 2018

    • gstore.unm.edu
    Updated Mar 6, 2020
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    (2020). Population by Tracts 2018 [Dataset]. https://gstore.unm.edu/apps/rgis/datasets/adecfea6-fcd7-4c41-8165-165c4490a9da/metadata/ISO-19115:2003.html
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    Dataset updated
    Mar 6, 2020
    Time period covered
    2018
    Area covered
    West Bound -109.050173 East Bound -103.001964 North Bound 37.000293 South Bound 31.332172
    Description

    A broad and generalized selection of 2014-2018 US Census Bureau 2018 5-year American Community Survey population data estimates, obtained via Census API and joined to the appropriate geometry (in this case, New Mexico Census tracts). The selection is not comprehensive, but allows a first-level characterization of total population, male and female, and both broad and narrowly-defined age groups. In addition to the standard selection of age-group breakdowns (by male or female), the dataset provides supplemental calculated fields which combine several attributes into one (for example, the total population of persons under 18, or the number of females over 65 years of age). The determination of which estimates to include was based upon level of interest and providing a manageable dataset for users.The U.S. Census Bureau's American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. The ACS collects long-form-type information throughout the decade rather than only once every 10 years. The ACS combines population or housing data from multiple years to produce reliable numbers for small counties, neighborhoods, and other local areas. To provide information for communities each year, the ACS provides 1-, 3-, and 5-year estimates. ACS 5-year estimates (multiyear estimates) are “period” estimates that represent data collected over a 60-month period of time (as opposed to “point-in-time” estimates, such as the decennial census, that approximate the characteristics of an area on a specific date). ACS data are released in the year immediately following the year in which they are collected. ACS estimates based on data collected from 2009–2014 should not be called “2009” or “2014” estimates. Multiyear estimates should be labeled to indicate clearly the full period of time. While the ACS contains margin of error (MOE) information, this dataset does not. Those individuals requiring more complete data are directed to download the more detailed datasets from the ACS American FactFinder website. This dataset is organized by Census tract boundaries in New Mexico. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

  3. Demographics API - By Geography Type and Geography Name

    • s.cnmilf.com
    • catalog.data.gov
    • +1more
    Updated Mar 11, 2021
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    National Telecommunication and Information Administration, Department of Commerce (2021). Demographics API - By Geography Type and Geography Name [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/demographics-api-by-geography-type-and-geography-name
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    Dataset updated
    Mar 11, 2021
    Dataset provided by
    United States Department of Commercehttp://commerce.gov/
    Description

    This API returns a search for the demographic information for a particular geography type and geography name.

  4. o

    Population Distribution Workflow using Census API in Jupyter Notebook:...

    • openicpsr.org
    delimited
    Updated Jul 23, 2020
    + more versions
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    Cooper Goodman; Nathanael Rosenheim; Wayne Day; Donghwan Gu; Jayasaree Korukonda (2020). Population Distribution Workflow using Census API in Jupyter Notebook: Dynamic Map of Census Tracts in Boone County, KY, 2000 [Dataset]. http://doi.org/10.3886/E120382V1
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    delimitedAvailable download formats
    Dataset updated
    Jul 23, 2020
    Dataset provided by
    Texas A&M University
    Authors
    Cooper Goodman; Nathanael Rosenheim; Wayne Day; Donghwan Gu; Jayasaree Korukonda
    License

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

    Time period covered
    2000
    Area covered
    Boone County
    Description

    This archive reproduces a figure titled "Figure 3.2 Boone County population distribution" from Wang and vom Hofe (2007, p.60). The archive provides a Jupyter Notebook that uses Python and can be run in Google Colaboratory. The workflow uses the Census API to retrieve data, reproduce the figure, and ensure reproducibility for anyone accessing this archive.The Python code was developed in Google Colaboratory, or Google Colab for short, which is an Integrated Development Environment (IDE) of JupyterLab and streamlines package installation, code collaboration, and management. The Census API is used to obtain population counts from the 2000 Decennial Census (Summary File 1, 100% data). Shapefiles are downloaded from the TIGER/Line FTP Server. All downloaded data are maintained in the notebook's temporary working directory while in use. The data and shapefiles are stored separately with this archive. The final map is also stored as an HTML file.The notebook features extensive explanations, comments, code snippets, and code output. The notebook can be viewed in a PDF format or downloaded and opened in Google Colab. References to external resources are also provided for the various functional components. The notebook features code that performs the following functions:install/import necessary Python packagesdownload the Census Tract shapefile from the TIGER/Line FTP Serverdownload Census data via CensusAPI manipulate Census tabular data merge Census data with TIGER/Line shapefileapply a coordinate reference systemcalculate land area and population densitymap and export the map to HTMLexport the map to ESRI shapefileexport the table to CSVThe notebook can be modified to perform the same operations for any county in the United States by changing the State and County FIPS code parameters for the TIGER/Line shapefile and Census API downloads. The notebook can be adapted for use in other environments (i.e., Jupyter Notebook) as well as reading and writing files to a local or shared drive, or cloud drive (i.e., Google Drive).

  5. d

    Demographic Data Append (Age, Gender, Marital Status, etc) Append API, USA,...

    • datarade.ai
    .json, .csv
    Updated Mar 16, 2023
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    Versium (2023). Demographic Data Append (Age, Gender, Marital Status, etc) Append API, USA, CCPA Compliant [Dataset]. https://datarade.ai/data-products/versium-reach-consumer-basic-demographic-age-gender-mari-versium
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    .json, .csvAvailable download formats
    Dataset updated
    Mar 16, 2023
    Dataset authored and provided by
    Versium
    Area covered
    United States
    Description

    With Versium REACH Demographic Append you will have access to many different attributes for enriching your data.

    Basic, Household and Financial, Lifestyle and Interests, Political and Donor.

    Here is a list of what sorts of attributes are available for each output type listed above:

    Basic: - Senior in Household - Young Adult in Household - Small Office or Home Office - Online Purchasing Indicator
    - Language - Marital Status - Working Woman in Household - Single Parent - Online Education - Occupation - Gender - DOB (MM/YY) - Age Range - Religion - Ethnic Group - Presence of Children - Education Level - Number of Children

    Household, Financial and Auto: - Household Income - Dwelling Type - Credit Card Holder Bank - Upscale Card Holder - Estimated Net Worth - Length of Residence - Credit Rating - Home Own or Rent - Home Value - Home Year Built - Number of Credit Lines - Auto Year - Auto Make - Auto Model - Home Purchase Date - Refinance Date - Refinance Amount - Loan to Value - Refinance Loan Type - Home Purchase Price - Mortgage Purchase Amount - Mortgage Purchase Loan Type - Mortgage Purchase Date - 2nd Most Recent Mortgage Amount - 2nd Most Recent Mortgage Loan Type - 2nd Most Recent Mortgage Date - 2nd Most Recent Mortgage Interest Rate Type - Refinance Rate Type - Mortgage Purchase Interest Rate Type - Home Pool

    Lifestyle and Interests: - Mail Order Buyer - Pets - Magazines - Reading
    - Current Affairs and Politics
    - Dieting and Weight Loss - Travel - Music - Consumer Electronics - Arts
    - Antiques - Home Improvement - Gardening - Cooking - Exercise
    - Sports - Outdoors - Womens Apparel
    - Mens Apparel - Investing - Health and Beauty - Decorating and Furnishing

    Political and Donor: - Donor Environmental - Donor Animal Welfare - Donor Arts and Culture - Donor Childrens Causes - Donor Environmental or Wildlife - Donor Health - Donor International Aid - Donor Political - Donor Conservative Politics - Donor Liberal Politics - Donor Religious - Donor Veterans - Donor Unspecified - Donor Community - Party Affiliation

  6. d

    ACS 5-Year Demographic Characteristics DC

    • catalog.data.gov
    • datalumos.org
    • +6more
    Updated May 7, 2025
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    City of Washington, DC (2025). ACS 5-Year Demographic Characteristics DC [Dataset]. https://catalog.data.gov/dataset/acs-5-year-demographic-characteristics-dc
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    Dataset updated
    May 7, 2025
    Dataset provided by
    City of Washington, DC
    Area covered
    Washington
    Description

    Age, Sex, Race, Ethnicity, Total Housing Units, and Voting Age Population. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: District-wide. Current Vintage: 2019-2023. ACS Table(s): DP05. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2025. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  7. d

    ACS 5-Year Demographic Characteristics DC Census Tract

    • opendata.dc.gov
    • adoptablock.dc.gov
    • +4more
    Updated Feb 28, 2025
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    City of Washington, DC (2025). ACS 5-Year Demographic Characteristics DC Census Tract [Dataset]. https://opendata.dc.gov/datasets/62e1f639627342248a4d4027140a1935
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    Dataset updated
    Feb 28, 2025
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    Description

    Age, Sex, Race, Ethnicity, Total Housing Units, and Voting Age Population. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: Census Tracts. Current Vintage: 2019-2023. ACS Table(s): DP05. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2025. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  8. Demographics API - by Coordinates

    • s.cnmilf.com
    • catalog.data.gov
    • +2more
    Updated Mar 11, 2021
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    National Telecommunication and Information Administration, Department of Commerce (2021). Demographics API - by Coordinates [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/demographics-api-by-coordinates
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    Dataset updated
    Mar 11, 2021
    Dataset provided by
    United States Department of Commercehttp://commerce.gov/
    Description

    This API returns the demographics data from the coordinates.

  9. New York City Census Data

    • kaggle.com
    Updated Aug 4, 2017
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    MuonNeutrino (2017). New York City Census Data [Dataset]. https://www.kaggle.com/muonneutrino/new-york-city-census-data/discussion
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 4, 2017
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    MuonNeutrino
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    New York
    Description

    Context

    There are a number of Kaggle datasets that provide spatial data around New York City. For many of these, it may be quite interesting to relate the data to the demographic and economic characteristics of nearby neighborhoods. I hope this data set will allow for making these comparisons without too much difficulty.

    Exploring the data and making maps could be quite interesting as well.

    Content

    This dataset contains two CSV files:

    1. nyc_census_tracts.csv

      This file contains a selection of census data taken from the ACS DP03 and DP05 tables. Things like total population, racial/ethnic demographic information, employment and commuting characteristics, and more are contained here. There is a great deal of additional data in the raw tables retrieved from the US Census Bureau website, so I could easily add more fields if there is enough interest.

      I obtained data for individual census tracts, which typically contain several thousand residents.

    2. census_block_loc.csv

      For this file, I used an online FCC census block lookup tool to retrieve the census block code for a 200 x 200 grid containing New York City and a bit of the surrounding area. This file contains the coordinates and associated census block codes along
      with the state and county names to make things a bit more readable to users.

      Each census tract is split into a number of blocks, so one must extract the census tract code from the block code.

    Acknowledgements

    The data here was taken from the American Community Survey 2015 5-year estimates (https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml).

    The census block coordinate data was taken from the FCC Census Block Conversions API (https://www.fcc.gov/general/census-block-conversions-api)

    As public data from the US government, this is not subject to copyright within the US and should be considered public domain.

  10. Consumer Marketing Data API | Tailored Consumer Insights | Target with...

    • datarade.ai
    Updated Oct 27, 2021
    + more versions
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    Success.ai (2021). Consumer Marketing Data API | Tailored Consumer Insights | Target with Precision | Best Price Guarantee [Dataset]. https://datarade.ai/data-products/consumer-marketing-data-api-tailored-consumer-insights-ta-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Oct 27, 2021
    Dataset provided by
    Area covered
    United Arab Emirates, Senegal, Hong Kong, Sweden, Madagascar, Estonia, Vanuatu, Burundi, Turkey, Philippines
    Description

    Success.ai’s Consumer Marketing Data API empowers your marketing, analytics, and product teams with on-demand access to a vast and continuously updated dataset of consumer insights. Covering detailed demographics, behavioral patterns, and purchasing histories, this API enables you to go beyond generic outreach and craft tailored campaigns that truly resonate with your target audiences.

    With AI-validated accuracy and support for precise filtering, the Consumer Marketing Data API ensures you’re always equipped with the most relevant data. Backed by our Best Price Guarantee, this solution is essential for refining your strategies, improving conversion rates, and driving sustainable growth in today’s competitive consumer landscape.

    Why Choose Success.ai’s Consumer Marketing Data API?

    1. Tailored Consumer Insights for Precision Targeting

      • Access verified demographic, behavioral, and purchasing data to understand what consumers truly value.
      • AI-driven validation ensures 99% accuracy, minimizing wasted spend and improving engagement outcomes.
    2. Comprehensive Global Reach

      • Includes consumer profiles from diverse regions and markets, enabling you to scale campaigns and discover emerging opportunities.
      • Adapt swiftly to new markets, product launches, and shifting consumer preferences with real-time data at your fingertips.
    3. Continuously Updated and Real-Time Data

      • Receive ongoing updates that reflect evolving consumer behaviors, interests, and market trends.
      • Respond quickly to seasonal changes, competitor moves, and industry disruptions, ensuring your campaigns remain timely and relevant.
    4. Ethical and Compliant

      • Fully adheres to GDPR, CCPA, and other global data privacy regulations, guaranteeing responsible and lawful data usage.

    Data Highlights:

    • Detailed Demographics: Age, gender, location, and income levels to refine targeting and messaging.
    • Behavioral Insights: Interests, browsing patterns, and content consumption habits to anticipate consumer needs.
    • Purchasing History: Understand consumer spending, brand loyalty, and product preferences to tailor promotions effectively.
    • Real-Time Updates: Keep pace with evolving consumer tastes, ensuring your strategies remain forward-focused and competitive.

    Key Features of the Consumer Marketing Data API:

    1. Granular Targeting and Segmentation

      • Query the API to segment consumers by demographics, interests, past purchases, or engagement patterns.
      • Focus campaigns on the most receptive audiences, enhancing conversion rates and ROI.
    2. Flexible and Seamless Integration

      • Easily integrate the API into CRM systems, marketing automation tools, or analytics platforms.
      • Streamline workflows and eliminate manual data imports, freeing resources for strategic initiatives.
    3. Continuous Data Enrichment

      • Refresh consumer profiles with the latest data, ensuring every decision is backed by current insights.
      • Reduce data decay and maintain top-notch data hygiene to maximize long-term marketing effectiveness.
    4. AI-Driven Validation

      • Rely on advanced AI validation techniques to guarantee high-quality data accuracy and reliability.
      • Increase confidence in your campaigns and decrease budget wasted on irrelevant targets.

    Strategic Use Cases:

    1. Highly Personalized Marketing Campaigns

      • Deliver tailored offers, recommendations, and content that align with individual consumer preferences.
      • Boost engagement and loyalty by making every touchpoint relevant and meaningful.
    2. Market Expansion and Product Launches

      • Identify segments most receptive to new products or services, ensuring successful market entry.
      • Stay ahead of consumer demands, evolving your product line and marketing mix to meet changing preferences.
    3. Competitive Analysis and Trend Forecasting

      • Leverage consumer insights to anticipate emerging trends and outpace competitors in capturing new markets.
      • Adjust marketing strategies proactively to capitalize on seasonal, cultural, or economic shifts.
    4. Customer Retention and Loyalty Programs

      • Use historical purchase and engagement data to identify at-risk customers and implement retention strategies.
      • Cultivate brand advocates by delivering personalized offers and exclusive perks to loyal consumers.

    Why Choose Success.ai?

    1. Best Price Guarantee

      • Access premium-quality consumer marketing data at unmatched prices, ensuring maximum ROI for your outreach efforts.
    2. Seamless Integration

      • Easily incorporate the API into existing workflows, eliminating data silos and manual data management.
    3. Data Accuracy with AI Validation

      • Depend on 99% accuracy to guide data-driven decisions, refine targeting, and elevate your marketing initiatives.
    4. Customizable and Scalable Solutions

      • Tailor datasets to focus on specific demog...
  11. g

    Demographics API - By Geography Type and Geography Name | gimi9.com

    • gimi9.com
    + more versions
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    Demographics API - By Geography Type and Geography Name | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_demographics-api-by-geography-type-and-geography-name/
    Explore at:
    License

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

    Description

    🇺🇸 미국

  12. d

    San Francisco Population and Demographic Census Data

    • catalog.data.gov
    • data.sfgov.org
    Updated Mar 29, 2025
    + more versions
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    data.sfgov.org (2025). San Francisco Population and Demographic Census Data [Dataset]. https://catalog.data.gov/dataset/san-francisco-population-and-demographic-census-data
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    Dataset updated
    Mar 29, 2025
    Dataset provided by
    data.sfgov.org
    Area covered
    San Francisco
    Description

    A. SUMMARY This dataset contains population and demographic estimates and associated margins of error obtained and derived from the US Census. The data is presented over multiple years and geographies. The data is sourced primarily from the American Community Survey. B. HOW THE DATASET IS CREATED The raw data is obtained from the census API. Some estimates as published as-is and some are derived. C. UPDATE PROCESS New estimates and years of data are appended to this dataset. To request additional census data for San Francisco, email support@datasf.org D. HOW TO USE THIS DATASET The dataset is long and contains multiple estimates, years and geographies. To use this dataset, you can filter by the overall segment which contains information about the source, years, geography, demographic category and reporting segment. For census data used in specific reports, you can filter to the reporting segment. To use a subset of the data, you can create a filtered view. More information of how to filter data and create a view can be found here

  13. ACS Children in Immigrant Families Variables - Boundaries

    • demographics.roanokecountyva.gov
    • atlas-connecteddmv.hub.arcgis.com
    • +1more
    Updated Nov 27, 2018
    + more versions
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    Esri (2018). ACS Children in Immigrant Families Variables - Boundaries [Dataset]. https://demographics.roanokecountyva.gov/maps/71f0c22b02f54372a9e33bd5ec57fb79
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    Dataset updated
    Nov 27, 2018
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows children by nativity of parents by age group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of children who are in immigrant families (children who are foreign born or live with at least one parent who is foreign born). To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B05009Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  14. d

    Demografy's Consumer Demographics Prediction

    • datarade.ai
    .json, .csv
    Updated Jun 3, 2021
    + more versions
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    Demografy (2021). Demografy's Consumer Demographics Prediction [Dataset]. https://datarade.ai/data-products/demografy-s-consumer-demographics-prediction-demografy
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    .json, .csvAvailable download formats
    Dataset updated
    Jun 3, 2021
    Dataset authored and provided by
    Demografy
    Area covered
    Ireland, Norway, Bulgaria, New Zealand, United States of America, Switzerland, Poland, Montenegro, Finland, Bosnia and Herzegovina
    Description

    Demografy is a privacy by design customer demographics prediction AI platform.

    Core features: - Demographic segmentation - Demographic analytics - API integration - Data export

    Key advantages: - 100% coverage of lists - Accuracy estimate before purchase - GDPR-compliance as no sensitive data is required. Demografy can work with only first names or masked last names

    Use cases: - Actionable analytics about your customers to get demographic insights - Appending missing demographic data to your records for customer segmentation and targeted marketing campaigns - Enhanced personalization knowing you customer better

    Unlike traditional solutions, you don’t need to know and disclose your customer or prospect addresses, emails or other sensitive information. You can provide even masked last names keeping personal data in-house. This makes Demografy privacy by design and enables you to get 100% coverage of your audience since all you need to know is names.

  15. a

    Data from: Median Household Income

    • hub.arcgis.com
    • gis-kingcounty.opendata.arcgis.com
    Updated Aug 10, 2016
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    King County (2016). Median Household Income [Dataset]. https://hub.arcgis.com/datasets/294c704e32734e8ebcd030e535b841ce
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    Dataset updated
    Aug 10, 2016
    Dataset authored and provided by
    King County
    Area covered
    Description

    Income:Median Household Income: Basic demographics by census tracts in King County based on current American Community Survey 5 Year Average (ACS). Included demographics are: total population; foreign born; median household income; English language proficiency; languages spoken; race and ethnicity; sex; and age. Numbers and derived percentages are estimates based on the current year's ACS. GEO_ID_TRT is the key field and may be used to join to other demographic Census data tables.

  16. Census API - By Coordinates

    • catalog.data.gov
    • datasets.ai
    • +2more
    Updated Mar 11, 2021
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    National Telecommunication and Information Administration, Department of Commerce (2021). Census API - By Coordinates [Dataset]. https://catalog.data.gov/dataset/census-api-by-coordinates
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    Dataset updated
    Mar 11, 2021
    Dataset provided by
    United States Department of Commercehttp://commerce.gov/
    Description

    This API returns the US Census Block geography ID information given a passed Latitude and Longitude.

  17. d

    ACS Demographic Characteristics DC Experimental

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Feb 5, 2025
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    D.C. Office of the Chief Technology Officer (2025). ACS Demographic Characteristics DC Experimental [Dataset]. https://catalog.data.gov/dataset/acs-demographic-characteristics-dc-experimental
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    D.C. Office of the Chief Technology Officer
    Area covered
    Washington
    Description

    Experimental Age, Sex, Race, and Ethnicity variables. Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data. This includes a limited number of data tables for the nation, states, and the District of Columbia. Please visit the following webpage for details. https://www.census.gov/programs-surveys/acs/data/experimental-data.htmlContact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: District-wide. Current Vintage: 2020. ACS Table(s): Demographic - Experimental. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: March 18, 2022. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  18. D

    ACS 1-Year Demographic Characteristics DC

    • datalumos.org
    • opdatahub.dc.gov
    • +2more
    Updated Sep 19, 2025
    + more versions
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    City of Washington, DC (2025). ACS 1-Year Demographic Characteristics DC [Dataset]. http://doi.org/10.3886/E238111V1
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    Dataset updated
    Sep 19, 2025
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    Washington
    Description

    Age, Sex, Race, Ethnicity, Total Housing Units, and Voting Age Population. This service is updated annually with American Community Survey (ACS) 1-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: District-wide. Current Vintage: 2023. ACS Table(s): DP05. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 3, 2025. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  19. U.S. Census Blocks

    • hub.arcgis.com
    • colorado-river-portal.usgs.gov
    • +8more
    Updated Jun 30, 2021
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    Esri U.S. Federal Datasets (2021). U.S. Census Blocks [Dataset]. https://hub.arcgis.com/datasets/d795eaa6ee7a40bdb2efeb2d001bf823
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    Dataset updated
    Jun 30, 2021
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri U.S. Federal Datasets
    License

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

    Area covered
    Description

    U.S. Census BlocksThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Census Bureau (USCB), displays Census Blocks in the United States. A brief description of Census Blocks, per USCB, is that "Census blocks are statistical areas bounded by visible features such as roads, streams, and railroad tracks, and by nonvisible boundaries such as property lines, city, township, school district, county limits and short line-of-sight extensions of roads." Also, "the smallest level of geography you can get basic demographic data for, such as total population by age, sex, and race."Census Block 1007Data currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Census Blocks) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 69 (Series Information for 2020 Census Block State-based TIGER/Line Shapefiles, Current)OGC API Features Link: (U.S. Census Blocks - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: What are census blocksFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Governmental Units, and Administrative and Statistical Boundaries Theme Community. Per the Federal Geospatial Data Committee (FGDC), this theme is defined as the "boundaries that delineate geographic areas for uses such as governance and the general provision of services (e.g., states, American Indian reservations, counties, cities, towns, etc.), administration and/or for a specific purpose (e.g., congressional districts, school districts, fire districts, Alaska Native Regional Corporations, etc.), and/or provision of statistical data (census tracts, census blocks, metropolitan and micropolitan statistical areas, etc.). Boundaries for these various types of geographic areas are either defined through a documented legal description or through criteria and guidelines. Other boundaries may include international limits, those of federal land ownership, the extent of administrative regions for various federal agencies, as well as the jurisdictional offshore limits of U.S. sovereignty. Boundaries associated solely with natural resources and/or cultural entities are excluded from this theme and are included in the appropriate subject themes."For other NGDA Content: Esri Federal Datasets

  20. t

    Select Demographics - ACS 2012-2016, Census 2010 - Tempe Block Groups

    • performance.tempe.gov
    • datasets.ai
    • +12more
    Updated Nov 28, 2018
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    City of Tempe (2018). Select Demographics - ACS 2012-2016, Census 2010 - Tempe Block Groups [Dataset]. https://performance.tempe.gov/datasets/select-demographics-acs-2012-2016-census-2010-tempe-block-groups/api
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    Dataset updated
    Nov 28, 2018
    Dataset authored and provided by
    City of Tempe
    License

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

    Area covered
    Description

    This feature layer of Tempe's Census block groups are joined with the Census Bureau's data from the 2018 Planning Database (PDB), which was established to prepare for the upcoming 2020 Census. The 2018 PDB contains select operational, demographic, and socio-economic statistics from the 2010 Census and the 2012-2016 5-year ACS.For more information, see the United States Census Bureau 2018 Planning Database:https://www.census.gov/topics/research/guidance/planning-databases.html.

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National Telecommunication and Information Administration, Department of Commerce (2021). Demographics API - Nation [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/demographics-api-nation
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Demographics API - Nation

Explore at:
Dataset updated
Mar 11, 2021
Dataset provided by
United States Department of Commercehttp://commerce.gov/
Description

This API returns a search for the demographic information for the whole nation.

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