100+ datasets found
  1. n

    United States Census

    • datacatalog.med.nyu.edu
    Updated Jul 17, 2018
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    (2018). United States Census [Dataset]. https://datacatalog.med.nyu.edu/dataset/10026
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    Dataset updated
    Jul 17, 2018
    Area covered
    United States
    Description

    The Decennial Census provides population estimates and demographic information on residents of the United States.

    The Census Summary Files contain detailed tables on responses to the decennial census. Data tables in Summary File 1 provide information on population and housing characteristics, including cross-tabulations of age, sex, households, families, relationship to householder, housing units, detailed race and Hispanic or Latino origin groups, and group quarters for the total population. Summary File 2 contains data tables on population and housing characteristics as reported by housing unit.

    Researchers at NYU Langone Health can find guidance for the use and analysis of Census Bureau data on the Population Health Data Hub (listed under "Other Resources"), which is accessible only through the intranet portal with a valid Kerberos ID (KID).

  2. All Employee Census Survey (AES)

    • catalog.data.gov
    • data.va.gov
    • +2more
    Updated Apr 21, 2021
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    Department of Veterans Affairs (2021). All Employee Census Survey (AES) [Dataset]. https://catalog.data.gov/dataset/all-employee-census-survey-aes
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    Dataset updated
    Apr 21, 2021
    Dataset provided by
    United States Department of Veterans Affairshttp://va.gov/
    Description

    The Office of Personnel Management requires government agencies, at a minimum, to query employees on job satisfaction, organizational assessment and organizational culture. VHA maintains response data for all census surveys such as the Voice of VA as well as the VA Entrance and Exit surveys.

  3. T

    Census Variables (5-year Estimates)

    • citydata.mesaaz.gov
    • data.mesaaz.gov
    application/rdfxml +5
    Updated Jul 11, 2019
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    US Census (2019). Census Variables (5-year Estimates) [Dataset]. https://citydata.mesaaz.gov/Census/Census-Variables-5-year-Estimates-/9nqf-ygw6
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    application/rssxml, application/rdfxml, json, tsv, xml, csvAvailable download formats
    Dataset updated
    Jul 11, 2019
    Dataset authored and provided by
    US Census
    Description

    Selected American Community Survey (ACS) variables from Mesa and other nearby municipalities. Visit https://www.census.gov/data/developers/data-sets/acs-5year.html for more information about the US Census Bureau's ACS ongoing survey. See https://www.census.gov/programs-surveys/acs/news/data-releases.html for data annual release schedules. This dataset uses 5-year estimates.

    Disclaimer: The centroid, internal point, and geometry columns are not consistent across years. 2023 data uses the last geometries from https://data.mesaaz.gov/Census/Mesa-Census-Tracts-To-City-Boundary-v2022/cbxq-2sd2/about_data">Mesa Census Tracts to City Boundary v2022 and calculated centroids and internal points.

  4. D

    Census Tract Top 50 American Community Survey Data

    • data.seattle.gov
    • data-seattlecitygis.opendata.arcgis.com
    application/rdfxml +5
    Updated Feb 3, 2025
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    (2025). Census Tract Top 50 American Community Survey Data [Dataset]. https://data.seattle.gov/dataset/Census-Tract-Top-50-American-Community-Survey-Data/jya9-y5bv/data
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    application/rdfxml, csv, json, application/rssxml, tsv, xmlAvailable download formats
    Dataset updated
    Feb 3, 2025
    Description

    Data from: American Community Survey, 5-year Series


    King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010 of over 50 attributes of the most requested data derived from the U.S. Census Bureau's demographic profiles (DP02-DP05). Also includes the most recent release annually with the vintage identified in the "ACS Vintage" field.

    The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades.

    Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.

    Vintages: 2010, 2015, 2020, 2021, 2022, 2023
    ACS Table(s): DP02, DP03, DP04, DP05


    The United States Census Bureau's American Community Survey (ACS):
    This 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. 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:
  5. Census Data by Zip Code 2010-2014 Data Package

    • johnsnowlabs.com
    csv
    Updated Jan 20, 2021
    + more versions
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    John Snow Labs (2021). Census Data by Zip Code 2010-2014 Data Package [Dataset]. https://www.johnsnowlabs.com/marketplace/census-data-by-zip-code-2010-2014-data-package/
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    csvAvailable download formats
    Dataset updated
    Jan 20, 2021
    Dataset authored and provided by
    John Snow Labs
    Description

    This data package has the purpose to offer data for demographic indicators, part of 5-years American Community Census, that could be needed in the analysis made along with health-related data or alone. The American Community Survey based on 5-years estimates is, according to U.S Census Bureau, the most reliable, because the samples used are the largest and the data collected cover all country areas, regardless of the population number.

  6. 2021 Economic Surveys: AM1831ECOMM | Annual Survey of Manufactures:...

    • data.census.gov
    Updated Mar 23, 2023
    + more versions
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    ECN (2023). 2021 Economic Surveys: AM1831ECOMM | Annual Survey of Manufactures: E-Commerce Statistics for the U.S.: 2018 - 2021 (ECNSVY Annual Survey of Manufactures Annual Survey of Manufactures Area) [Dataset]. https://data.census.gov/cedsci/table?q=am1831&hidePreview=
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    Dataset updated
    Mar 23, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2021
    Area covered
    United States
    Description

    Release Date: 2023-03-23.Release Schedule:.The data in this file come from the 2021 Annual Survey of Manufactures data files released in March 2023. For more information about the Annual Survey of Manufactures data, see About: Annual Survey of Manufactures...Key Table Information:.Includes only establishments of firms with payroll..Data may be subject to employment- and/or sales-size minimums that vary by industry...Data Items and Other Identifying Records: .Sales, value of shipments, or revenue ($1,000) .Relative standard error for estimate of sales, value of shipments, or revenue (%) .E-Shipments value ($1,000) .Relative standard error for estimate of e-shipments value (%).E-Shipments as percent of total sales, value of shipments, or revenue (%).Relative standard error for estimate of e-shipments as percent of total sales, value of shipments, or revenue (%) ...Geography Coverage:.The data are shown for employer establishments and firms for the U.S. level that vary by industry..For information about 2021 Annual Survey of Manufactures, see About: Annual Survey of Manufactures...Industry Coverage:.The data are shown at the 2- through 3-digit 2017 NAICS code levels for the U.S. For information about NAICS, see Annual Survey of Manufactures (ASM): Technical Documentation: ASM Product Class Codes and Descriptions...Footnotes:.Not applicable...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/asm/data/2021/AM1831ECOMM.zip..API Information:.Annual Survey of Manufactures API data are housed in the Census Bureau API. For more information, see ASM API..Methodology:.To maintain confidentiality, the U.S. Census Bureau suppresses data to protect the identity of any business or individual. The census results in this file contain sampling and/or nonsampling error. Data users who create their own estimates using data from this file should cite the U.S. Census Bureau as the source of the original data only..To comply with disclosure avoidance guidelines, data rows with fewer than three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. For detailed information about the methods used to collect and produce statistics, including sampling, eligibility, questions, data collection and processing, data quality, review, weighting, estimation, coding operations, confidentiality protection, sampling error, nonsampling error, and more, see Annual Survey of Manufactures (ASM): Technical Documentation: Annual Survey of Manufactures Methodology...Symbols:.D - Withheld to avoid disclosing data of individual companies; data are included in higher level totals.N - Not available or not comparable.S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page..X - Not applicable.A - Relative standard error of 100% or more.r - Revised (represented as a superscript).s - Relative standard error is 40 percent or more and less than 100 percent (data variable displayed as a superscript).For a complete list of all economic programs symbols, see the Economic Census: Technical Documentation: Data Dictionary...Source:.U.S. Census Bureau, 2021 Annual Survey of Manufactures (ASM).For information about the Annual Survey of Manufactures (ASM), see Business and Economy: Annual Survey of Manufactures (ASM)..Contact Information:.U.S. Census Bureau.For general inquiries:.(800) 242-2184/ (301) 763-5154.ewd.surveys@census.gov.For specific data questions:.(844) 303-7713.For additional contacts, see Annual Survey of Manufactures (ASM): About: Contact Us

  7. Census of Finance Companies and Other Lenders; Survey of Finance Companies

    • catalog.data.gov
    • datasets.ai
    Updated Dec 18, 2024
    + more versions
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    Board of Governors of the Federal Reserve System (2024). Census of Finance Companies and Other Lenders; Survey of Finance Companies [Dataset]. https://catalog.data.gov/dataset/census-of-finance-companies-and-other-lenders-survey-of-finance-companies
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    Dataset updated
    Dec 18, 2024
    Dataset provided by
    Federal Reserve Systemhttp://www.federalreserve.gov/
    Federal Reserve Board of Governors
    Description

    The FR 3033p is the first part of a two-stage survey series, which has been conducted at regular five-year intervals since 1955. It is a census survey designed to identify the universe of finance companies eligible for potential inclusion in the FR 3033s. It gathers limited information including total assets, areas of specialization, and information on the corporate structure of such companies. The second part of these information collections, the FR 3033s, collects balance sheet data on major categories of consumer and business credit receivables and major liabilities, along with income and expenses, and is used to gather information on the scope of a company's operations and loan and lease servicing activities. In addition, additional questions were added to collect lending information related to the COVID-19 impacts.

  8. N

    Nome Census Area, AK Age Group Population Dataset: A Complete Breakdown of...

    • neilsberg.com
    csv, json
    Updated Feb 22, 2025
    + more versions
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    Neilsberg Research (2025). Nome Census Area, AK Age Group Population Dataset: A Complete Breakdown of Nome Census Area Age Demographics from 0 to 85 Years and Over, Distributed Across 18 Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/453abc4f-f122-11ef-8c1b-3860777c1fe6/
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    json, csvAvailable download formats
    Dataset updated
    Feb 22, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Nome Census Area
    Variables measured
    Population Under 5 Years, Population over 85 years, Population Between 5 and 9 years, Population Between 10 and 14 years, Population Between 15 and 19 years, Population Between 20 and 24 years, Population Between 25 and 29 years, Population Between 30 and 34 years, Population Between 35 and 39 years, Population Between 40 and 44 years, and 9 more
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the age groups. For age groups we divided it into roughly a 5 year bucket for ages between 0 and 85. For over 85, we aggregated data into a single group for all ages. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the Nome Census Area population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Nome Census Area. The dataset can be utilized to understand the population distribution of Nome Census Area by age. For example, using this dataset, we can identify the largest age group in Nome Census Area.

    Key observations

    The largest age group in Nome Census Area, AK was for the group of age 10 to 14 years years with a population of 1,058 (10.66%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Nome Census Area, AK was the 85 years and over years with a population of 45 (0.45%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

    Age groups:

    • Under 5 years
    • 5 to 9 years
    • 10 to 14 years
    • 15 to 19 years
    • 20 to 24 years
    • 25 to 29 years
    • 30 to 34 years
    • 35 to 39 years
    • 40 to 44 years
    • 45 to 49 years
    • 50 to 54 years
    • 55 to 59 years
    • 60 to 64 years
    • 65 to 69 years
    • 70 to 74 years
    • 75 to 79 years
    • 80 to 84 years
    • 85 years and over

    Variables / Data Columns

    • Age Group: This column displays the age group in consideration
    • Population: The population for the specific age group in the Nome Census Area is shown in this column.
    • % of Total Population: This column displays the population of each age group as a proportion of Nome Census Area total population. Please note that the sum of all percentages may not equal one due to rounding of values.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Nome Census Area Population by Age. You can refer the same here

  9. H

    Current Population Survey

    • data.niaid.nih.gov
    • dataverse.harvard.edu
    Updated May 31, 2011
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    (2011). Current Population Survey [Dataset]. http://doi.org/10.7910/DVN/35IUVQ
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    Dataset updated
    May 31, 2011
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Users can download data or view data tables on topics related to the labor force of the United States. Background Current Population Survey is a joint effort between the Bureau of Labor Statistics and the Census Bureau. It provides information and data on the labor force of the United States, such as: employment, unemployment, earnings, hours of work, school enrollment, health, employee benefits and income. The CPS is conducted monthly and has a sample of approximately 50,000 households. It is representative of the non-institutionalized US population. The sample provides estimates for the nation as a whole and serves as part of model-based estimates for individual states and other geographic areas. User Functionality Users can download data sets or view data tables on their topic of interest. Data can be organized by a variety of demographic variables, including: sex, age, race, marital status and educational attainment. Data is available on a national or state level. Data Notes The CPS is conducted monthly and has a sample of approximately 50,000 households. It is representative of the non-institutionalized US population. The sample provides estimates for th e nation as a whole and serves as part of model-based estimates for individual states and other geographic areas.

  10. 2010 Census Production Settings Redistricting Data (P.L. 94-171)...

    • registry.opendata.aws
    • icpsr.umich.edu
    Updated Nov 10, 2023
    + more versions
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    United States Census Bureau (2023). 2010 Census Production Settings Redistricting Data (P.L. 94-171) Demonstration Noisy Measurement File [Dataset]. https://registry.opendata.aws/census-2010-pl94-nmf/
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    Dataset updated
    Nov 10, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    The 2010 Census Production Settings Redistricting Data (P.L. 94-171) Demonstration Noisy Measurement File (2023-04-03) is an intermediate output of the 2020 Census Disclosure Avoidance System (DAS) TopDown Algorithm (TDA) (as described in Abowd, J. et al [2022] https://doi.org/10.1162/99608f92.529e3cb9 , and implemented in https://github.com/uscensusbureau/DAS_2020_Redistricting_Production_Code). The NMF was produced using the official “production settings,” the final set of algorithmic parameters and privacy-loss budget allocations, that were used to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File and the 2020 Census Demographic and Housing Characteristics File.

    The NMF consists of the full set of privacy-protected statistical queries (counts of individuals or housing units with particular combinations of characteristics) of confidential 2010 Census data relating to the redistricting data portion of the 2010 Demonstration Data Products Suite – Redistricting and Demographic and Housing Characteristics File – Production Settings (2023-04-03). These statistical queries, called “noisy measurements” were produced under the zero-Concentrated Differential Privacy framework (Bun, M. and Steinke, T [2016] https://arxiv.org/abs/1605.02065; see also Dwork C. and Roth, A. [2014] https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf) implemented via the discrete Gaussian mechanism (Cannone C., et al., [2023] https://arxiv.org/abs/2004.00010), which added positive or negative integer-valued noise to each of the resulting counts. The noisy measurements are an intermediate stage of the TDA prior to the post-processing the TDA then performs to ensure internal and hierarchical consistency within the resulting tables. The Census Bureau has released these 2010 Census demonstration data to enable data users to evaluate the expected impact of disclosure avoidance variability on 2020 Census data. The 2010 Census Production Settings Redistricting Data (P.L.94-171) Demonstration Noisy Measurement File (2023-04-03) has been cleared for public dissemination by the Census Bureau Disclosure Review Board (CBDRB-FY22-DSEP-004).

    The data includes zero-Concentrated Differentially Private (zCDP) (Bun, M. and Steinke, T [2016]) noisy measurements, implemented via the discrete Gaussian mechanism. These are estimated counts of individuals and housing units included in the 2010 Census Edited File (CEF), which includes confidential data initially collected in the 2010 Census of Population and Housing. The noisy measurements included in this file were subsequently post-processed by the TopDown Algorithm (TDA) to produce the 2010 Census Production Settings Privacy-Protected Microdata File - Redistricting (P.L. 94-171) and Demographic and Housing Characteristics File (2023-04-03) (https://www2.census.gov/programs-surveys/decennial/2020/program-management/data-product-planning/2010-demonstration-data-products/04-Demonstration_Data_Products_Suite/2023-04-03/). As these 2010 Census demonstration data are intended to support study of the design and expected impacts of the 2020 Disclosure Avoidance System, the 2010 CEF records were pre-processed before application of the zCDP framework. This pre-processing converted the 2010 CEF records into the input-file format, response codes, and tabulation categories used for the 2020 Census, which differ in substantive ways from the format, response codes, and tabulation categories originally used for the 2010 Census.

    The NMF provides estimates of counts of persons in the CEF by various characteristics and combinations of characteristics including their reported race and ethnicity, whether they were of voting age, whether they resided in a housing unit or one of 7 group quarters types, and their census block of residence after the addition of discrete Gaussian noise (with the scale parameter determined by the privacy-loss budget allocation for that particular query under zCDP). Noisy measurements of the counts of occupied and vacant housing units by census block are also included. Lastly, data on constraints—information into which no noise was infused by the Disclosure Avoidance System (DAS) and used by the TDA to post-process the noisy measurements into the 2010 Census Production Settings Privacy-Protected Microdata File - Redistricting (P.L. 94-171) and Demographic and Housing Characteristics File (2023-04-03) —are provided.

  11. D

    2020 Census Counties; PA, NJ, DE & MD

    • staging-catalog.cloud.dvrpc.org
    • catalog.dvrpc.org
    esri feature class +4
    Updated Feb 15, 2025
    + more versions
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    DVRPC (2025). 2020 Census Counties; PA, NJ, DE & MD [Dataset]. https://staging-catalog.cloud.dvrpc.org/dataset/2020-census-counties-pa-nj-de-md
    Explore at:
    geojson, xml, esri feature class, json, htmlAvailable download formats
    Dataset updated
    Feb 15, 2025
    Dataset authored and provided by
    DVRPC
    Area covered
    Pennsylvania, New Jersey
    Description

    *USE geoid TO JOIN DATA DOWNLOADED FROM DATA.CENSUS.GOV*

    The TIGER/Line Shapefiles are extracts of selected geographic and cartographic information from the Census Bureau's Master Address File (MAF)/Topologically Integrated Geographic Encoding and Referencing (TIGER) System (MTS).

    The TIGER/Line Shapefiles contain a standard geographic identifier (GEOID) for each entity that links to the GEOID in the data from censuses and surveys. The TIGER/Line Shapefiles do not include demographic data from surveys and censuses (e.g., Decennial Census, Economic Census, American Community Survey, and the Population Estimates Program). Other, non-census, data often have this standard geographic identifier as well. Data from many of the Census Bureau’s surveys and censuses, including the geographic codes needed to join to the TIGER/Line Shapefiles, are available at the Census Bureau’s public data dissemination website (https://data.census.gov/).

    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 census areas; the latter of which are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. Additionally, 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. 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 in decennial censuses. All of the counties in Connecticut and Rhode Island and nine counties in Massachusetts were dissolved as functioning governmental entities; however, the Census Bureau continues to present data for these historical entities in order to provide comparable geographic units at the county level of the geographic hierarchy for these states and represents them as nonfunctioning legal entities in data products. Each county or statistically equivalent entity is assigned a three-character numeric Federal Information Processing Series (FIPS) code based on alphabetical sequence that is unique within state, and an eight-digit National Standard (NS) code.

    Downloaded from https://www2.census.gov/geo/tiger/TIGER2022/COUNTY/ on June 22, 2023

  12. QuickFacts: Spring Valley village, New York

    • census.gov
    csv
    Updated Feb 25, 2022
    + more versions
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    United States Census Bureau > Communications Directorate - Center for New Media and Promotion (2022). QuickFacts: Spring Valley village, New York [Dataset]. https://www.census.gov/quickfacts/fact/faq/springvalleyvillagenewyork/AGE295223
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    csvAvailable download formats
    Dataset updated
    Feb 25, 2022
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    United States Census Bureau > Communications Directorate - Center for New Media and Promotion
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Spring Valley village, New York
    Description

    U.S. Census Bureau QuickFacts statistics for Spring Valley village, New York. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

  13. QuickFacts: Lake San Marcos CDP, California

    • census.gov
    • shutdown.census.gov
    csv
    Updated Feb 25, 2022
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    United States Census Bureau > Communications Directorate - Center for New Media and Promotion (2022). QuickFacts: Lake San Marcos CDP, California [Dataset]. https://www.census.gov/quickfacts/fact/faq/lakesanmarcoscdpcalifornia/HSG010224
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    csvAvailable download formats
    Dataset updated
    Feb 25, 2022
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    United States Census Bureau > Communications Directorate - Center for New Media and Promotion
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Lake San Marcos, California
    Description

    U.S. Census Bureau QuickFacts statistics for Lake San Marcos CDP, California. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

  14. 2019 American Community Survey: B19113 | MEDIAN FAMILY INCOME IN THE PAST 12...

    • data.census.gov
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    ACS, 2019 American Community Survey: B19113 | MEDIAN FAMILY INCOME IN THE PAST 12 MONTHS (IN 2019 INFLATION-ADJUSTED DOLLARS) (ACS 1-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table?q=b19113&tid=ACSDT1Y2019.B19113
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2019
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019 American Community Survey 1-Year Estimates.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 roughly 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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Between 2018 and 2019 the American Community Survey retirement income question changed. These changes resulted in an increase in both the number of households reporting retirement income and higher aggregate retirement income at the national level. For more information see Changes to the Retirement Income Question ..The categories for relationship to householder were revised in 2019. For more information see Revisions to the Relationship to Household item..The 2019 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:An "**" entry in 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.An "-" entry in the estimate column indicates that 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, or the margin of error associated with a median was larger than the median itself.An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.An "(X)" means that the estimate is not applicable or not available.

  15. i

    Surveying Japanese-Brazilian Households: Comparison of Census-Based,...

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    • +1more
    Updated Mar 29, 2019
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    David McKenzie (2019). Surveying Japanese-Brazilian Households: Comparison of Census-Based, Snowball and Intercept Point Surveys 2006 - Brazil [Dataset]. https://catalog.ihsn.org/index.php/catalog/6032
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    Dataset updated
    Mar 29, 2019
    Dataset provided by
    Johan Mistiaen
    David McKenzie
    Time period covered
    2006 - 2007
    Area covered
    Brazil
    Description

    Abstract

    This study is an experiment designed to compare the performance of three methodologies for sampling households with migrants:

    • a stratified sample using the census to sample census tracts randomly, in which each household is then listed and screened to determine whether or not it has a migrant, with the full length questionnaire then being applied in a second phase only to the households of interest;
    • a snowball survey in which households are asked to provide referrals to other households with migrant members;
    • an intercept point survey (or time-and-space sampling survey), in which individuals are sampled during set time periods at a prespecified set of locations where households in the target group are likely to congregate.

    Researchers from the World Bank applied these methods in the context of a survey of Brazilians of Japanese descent (Nikkei), requested by the World Bank. There are approximately 1.2-1.9 million Nikkei among Brazil’s 170 million population.

    The survey was designed to provide detail on the characteristics of households with and without migrants, to estimate the proportion of households receiving remittances and with migrants in Japan, and to examine the consequences of migration and remittances on the sending households.

    The same questionnaire was used for the stratified random sample and snowball surveys, and a shorter version of the questionnaire was used for the intercept surveys. Researchers can directly compare answers to the same questions across survey methodologies and determine the extent to which the intercept and snowball surveys can give similar results to the more expensive census-based survey, and test for the presence of biases.

    Geographic coverage

    Sao Paulo and Parana states

    Analysis unit

    Japanese-Brazilian (Nikkei) households and individuals

    The 2000 Brazilian Census was used to classify households as Nikkei or non-Nikkei. The Brazilian Census does not ask ethnicity but instead asks questions on race, country of birth and whether an individual has lived elsewhere in the last 10 years. On the basis of these questions, a household is classified as (potentially) Nikkei if it has any of the following: 1) a member born in Japan; 2) a member who is of yellow race and who has lived in Japan in the last 10 years; 3) a member who is of yellow race, who was not born in a country other than Japan (predominantly Korea, Taiwan or China) and who did not live in a foreign country other than Japan in the last 10 years.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    1) Stratified random sample survey

    Two states with the largest Nikkei population - Sao Paulo and Parana - were chosen for the study.

    The sampling process consisted of three stages. First, a stratified random sample of 75 census tracts was selected based on 2000 Brazilian census. Second, interviewers carried out a door-to-door listing within each census tract to determine which households had a Nikkei member. Third, the survey questionnaire was then administered to households that were identified as Nikkei. A door-to-door listing exercise of the 75 census tracts was then carried out between October 13th, 2006, and October 29th, 2006. The fieldwork began on November 19, 2006, and all dwellings were visited at least once by December 22, 2006. The second wave of surveying took place from January 18th, 2007, to February 2nd, 2007, which was intended to increase the number of households responding.

    2) Intercept survey

    The intercept survey was designed to carry out interviews at a range of locations that were frequented by the Nikkei population. It was originally designed to be done in Sao Paulo city only, but a second intercept point survey was later carried out in Curitiba, Parana. Intercept survey took place between December 9th, 2006, and December 20th, 2006, whereas the Curitiba intercept survey took place between March 3rd and March 12th, 2007.

    Consultations with Nikkei community organizations, local researchers and officers of the bank Sudameris, which provides remittance services to this community, were used to select a broad range of locations. Interviewers were assigned to visit each location during prespecified blocks of time. Two fieldworkers were assigned to each location. One fieldworker carried out the interviews, while the other carried out a count of the number of people with Nikkei appearance who appeared to be 18 years old or older who passed by each location. For the fixed places, this count was made throughout the prespecified time block. For example, between 2.30 p.m. and 3.30 p.m. at the sports club, the interviewer counted 57 adult Nikkeis. Refusal rates were carefully recorded, along with the sex and approximate age of the person refusing.

    In all, 516 intercept interviews were collected.

    3) Snowball sampling survey

    The questionnaire that was used was the same as used for the stratified random sample. The plan was to begin with a seed list of 75 households, and to aim to reach a total sample of 300 households through referrals from the initial seed households. Each household surveyed was asked to supply the names of three contacts: (a) a Nikkei household with a member currently in Japan; (b) a Nikkei household with a member who has returned from Japan; (c) a Nikkei household without members in Japan and where individuals had not returned from Japan.

    The snowball survey took place from December 5th to 20th, 2006. The second phase of the snowballing survey ran from January 22nd, 2007, to March 23rd, 2007. More associations were contacted to provide additional seed names (69 more names were obtained) and, as with the stratified sample, an adaptation of the intercept survey was used when individuals refused to answer the longer questionnaire. A decision was made to continue the snowball process until a target sample size of 100 had been achieved.

    The final sample consists of 60 households who came as seed households from Japanese associations, and 40 households who were chain referrals. The longest chain achieved was three links.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    1) Stratified sampling and snowball survey questionnaire

    This questionnaire has 36 pages with over 1,000 variables, taking over an hour to complete.

    If subjects refused to answer the questionnaire, interviewers would leave a much shorter version of the questionnaire to be completed by the household by themselves, and later picked up. This shorter questionnaire was the same as used in the intercept point survey, taking seven minutes on average. The intention with the shorter survey was to provide some data on households that would not answer the full survey because of time constraints, or because respondents were reluctant to have an interviewer in their house.

    2) Intercept questionnaire

    The questionnaire is four pages in length, consisting of 62 questions and taking a mean time of seven minutes to answer. Respondents had to be 18 years old or older to be interviewed.

    Response rate

    1) Stratified random sampling 403 out of the 710 Nikkei households were surveyed, an interview rate of 57%. The refusal rate was 25%, whereas the remaining households were either absent on three attempts or were not surveyed because building managers refused permission to enter the apartment buildings. Refusal rates were higher in Sao Paulo than in Parana, reflecting greater concerns about crime and a busier urban environment.

    2) Intercept Interviews 516 intercept interviews were collected, along with 325 refusals. The average refusal rate is 39%, with location-specific refusal rates ranging from only 3% at the food festival to almost 66% at one of the two grocery stores.

  16. American Community Survey: 1-Year Estimates: Detailed Tables 1-Year

    • datasets.ai
    • catalog.data.gov
    • +1more
    2
    Updated Sep 8, 2024
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    Department of Commerce (2024). American Community Survey: 1-Year Estimates: Detailed Tables 1-Year [Dataset]. https://datasets.ai/datasets/american-community-survey-1-year-estimates-detailed-tables-1-year-50326
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    2Available download formats
    Dataset updated
    Sep 8, 2024
    Dataset provided by
    United States Department of Commercehttp://www.commerce.gov/
    Authors
    Department of Commerce
    Description

    The American Community Survey (ACS) is an ongoing survey that provides data every year -- giving communities the current information they need to plan investments and services. The ACS covers a broad range of topics about social, economic, demographic, and housing characteristics of the U.S. population. Much of the ACS data provided on the Census Bureau's Web site are available separately by age group, race, Hispanic origin, and sex. Summary files, Subject tables, Data profiles, and Comparison profiles are available for the nation, all 50 states, the District of Columbia, Puerto Rico, every congressional district, every metropolitan area, and all counties and places with populations of 65,000 or more. Detail Tables contain the most detailed cross-tabulations published for areas 65k and more. The data are population counts. There are over 31,000 variables in this dataset.

  17. Economic Census: Economic Census of the United States: Commodity Flow Survey...

    • s.cnmilf.com
    • datasets.ai
    • +1more
    Updated Jul 19, 2023
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    U.S. Census Bureau (2023). Economic Census: Economic Census of the United States: Commodity Flow Survey Hazmat Data [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/economic-census-economic-census-of-the-united-states-commodity-flow-survey-hazmat-data
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    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    United States
    Description

    The Commodity Flow Survey (CFS) is undertaken through a partnership between the U.S. Census Bureau, U.S. Department of Commerce, and the Research and Innovation Technology Administration, Bureau of Transportation Statistics (BTS), U.S. Department of Transportation. This survey produces data on the movement of goods in the United States. It provides information on commodities shipped, their value, weight, and mode of transportation, as well as the origin and destination of shipments of manufacturing, mining, wholesale, and select retail and services establishments. The data from the CFS are used by public policy analysts and for transportation planning and decision making to access the demand for transportation facilities and services, energy use, and safety risk and environmental concerns. This dataset provides data for the Hazardous Materials Series.

  18. F

    Employed Persons in Northeast Census Region

    • fred.stlouisfed.org
    json
    Updated Jul 2, 2025
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    (2025). Employed Persons in Northeast Census Region [Dataset]. https://fred.stlouisfed.org/series/LAURD910000000000005
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    jsonAvailable download formats
    Dataset updated
    Jul 2, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Employed Persons in Northeast Census Region (LAURD910000000000005) from Jan 1976 to May 2025 about Northeast Census Region, household survey, employment, persons, and USA.

  19. N

    Sun, LA Age Group Population Dataset: A complete breakdown of Sun age...

    • neilsberg.com
    csv, json
    Updated Sep 16, 2023
    + more versions
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    Neilsberg Research (2023). Sun, LA Age Group Population Dataset: A complete breakdown of Sun age demographics from 0 to 85 years, distributed across 18 age groups [Dataset]. https://www.neilsberg.com/research/datasets/5fc13432-3d85-11ee-9abe-0aa64bf2eeb2/
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    json, csvAvailable download formats
    Dataset updated
    Sep 16, 2023
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Louisiana, Sun
    Variables measured
    Population Under 5 Years, Population over 85 years, Population Between 5 and 9 years, Population Between 10 and 14 years, Population Between 15 and 19 years, Population Between 20 and 24 years, Population Between 25 and 29 years, Population Between 30 and 34 years, Population Between 35 and 39 years, Population Between 40 and 44 years, and 9 more
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the age groups. For age groups we divided it into roughly a 5 year bucket for ages between 0 and 85. For over 85, we aggregated data into a single group for all ages. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the Sun population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Sun. The dataset can be utilized to understand the population distribution of Sun by age. For example, using this dataset, we can identify the largest age group in Sun.

    Key observations

    The largest age group in Sun, LA was for the group of age 30-34 years with a population of 73 (12.46%), according to the 2021 American Community Survey. At the same time, the smallest age group in Sun, LA was the 35-39 years with a population of 0 (0.00%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

    Age groups:

    • Under 5 years
    • 5 to 9 years
    • 10 to 14 years
    • 15 to 19 years
    • 20 to 24 years
    • 25 to 29 years
    • 30 to 34 years
    • 35 to 39 years
    • 40 to 44 years
    • 45 to 49 years
    • 50 to 54 years
    • 55 to 59 years
    • 60 to 64 years
    • 65 to 69 years
    • 70 to 74 years
    • 75 to 79 years
    • 80 to 84 years
    • 85 years and over

    Variables / Data Columns

    • Age Group: This column displays the age group in consideration
    • Population: The population for the specific age group in the Sun is shown in this column.
    • % of Total Population: This column displays the population of each age group as a proportion of Sun total population. Please note that the sum of all percentages may not equal one due to rounding of values.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Sun Population by Age. You can refer the same here

  20. QuickFacts: East San Gabriel CDP, California

    • census.gov
    • shutdown.census.gov
    csv
    Updated Feb 25, 2022
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    United States Census Bureau > Communications Directorate - Center for New Media and Promotion (2022). QuickFacts: East San Gabriel CDP, California [Dataset]. https://www.census.gov/quickfacts/fact/faq/eastsangabrielcdpcalifornia/BPS030224
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    csvAvailable download formats
    Dataset updated
    Feb 25, 2022
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    United States Census Bureau > Communications Directorate - Center for New Media and Promotion
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    East San Gabriel, California
    Description

    U.S. Census Bureau QuickFacts statistics for East San Gabriel CDP, California. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

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(2018). United States Census [Dataset]. https://datacatalog.med.nyu.edu/dataset/10026

United States Census

Explore at:
Dataset updated
Jul 17, 2018
Area covered
United States
Description

The Decennial Census provides population estimates and demographic information on residents of the United States.

The Census Summary Files contain detailed tables on responses to the decennial census. Data tables in Summary File 1 provide information on population and housing characteristics, including cross-tabulations of age, sex, households, families, relationship to householder, housing units, detailed race and Hispanic or Latino origin groups, and group quarters for the total population. Summary File 2 contains data tables on population and housing characteristics as reported by housing unit.

Researchers at NYU Langone Health can find guidance for the use and analysis of Census Bureau data on the Population Health Data Hub (listed under "Other Resources"), which is accessible only through the intranet portal with a valid Kerberos ID (KID).

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