100+ datasets found
  1. 2023 American Community Survey: CP05 | Comparative Demographic Estimates...

    • data.census.gov
    Updated Aug 15, 2021
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    ACS (2021). 2023 American Community Survey: CP05 | Comparative Demographic Estimates (ACS 1-Year Estimates Comparison Profiles) [Dataset]. https://data.census.gov/cedsci/table?q=demog
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    Dataset updated
    Aug 15, 2021
    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
    2023
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.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, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..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..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..For more information on understanding Hispanic origin and race data, please see the America Counts: Stories Behind the Numbers article entitled, 2020 Census Illuminates Racial and Ethnic Composition of the Country, issued August 2021..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..An * indicates that the estimate is significantly different (at a 90% confidence level) than the estimate from the most current year. A "c" indicates the estimates for that year and the current year are both controlled; a statistical test is not appropriate. A blank indicates that the estimate is not significantly different from the estimate of the most current year, or that a test could not be done because one or both of the estimates is displayed as "-", "N", or "(X)", or the estimate ends with a "+" or "-". (For more information on these symbols, see the Explanation of Symbols.).Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

  2. Number of households in the U.S. 1960-2023

    • statista.com
    Updated Jul 5, 2024
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    Statista (2024). Number of households in the U.S. 1960-2023 [Dataset]. https://www.statista.com/statistics/183635/number-of-households-in-the-us/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    How many households are in the U.S.?

    In 2023, there were 131.43 million households in the United States. This is a significant increase from 1960, when there were 52.8 million households in the U.S.

    What counts as a household?

    According to the U.S. Census Bureau, a household is considered to be all persons living within one housing unit. This includes apartments, houses, or single rooms, and consists of both related and unrelated people living together. For example, two roommates who share a living space but are not related would be considered a household in the eyes of the Census. It should be noted that group living quarters, such as college dorms, are not counted as households in the Census.

    Household changes

    While the population of the United States has been increasing, the average size of households in the U.S. has decreased since 1960. In 1960, there was an average of 3.33 people per household, but in 2023, this figure had decreased to 2.51 people per household. Additionally, two person households make up the majority of American households, followed closely by single-person households.

  3. 2022 American Community Survey: DP05 | ACS Demographic and Housing Estimates...

    • data.census.gov
    Updated Jun 20, 2022
    + more versions
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    ACS (2022). 2022 American Community Survey: DP05 | ACS Demographic and Housing Estimates (ACS 1-Year Estimates Data Profiles) [Dataset]. https://data.census.gov/table/ACSDP1Y2022.DP05?q=Norwalk+CT
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    Dataset updated
    Jun 20, 2022
    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
    2022
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program 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..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.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, 2022 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..For more information on understanding Hispanic origin and race data, please see the America Counts: Stories Behind the Numbers article entitled, 2020 Census Illuminates Racial and Ethnic Composition of the Country, issued August 2021..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..The 2022 American Community Survey (ACS) data generally reflect the March 2020 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 2020 Census 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:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

  4. K

    2010 U.S. Census Population Counts, King County and its Cities, April 1,...

    • data.kingcounty.gov
    • catalog.data.gov
    • +1more
    application/rdfxml +5
    Updated Aug 21, 2011
    + more versions
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    King County (2011). 2010 U.S. Census Population Counts, King County and its Cities, April 1, 2010 [Dataset]. https://data.kingcounty.gov/Demographics/2010-U-S-Census-Population-Counts-King-County-and-/cavj-x985
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    tsv, xml, csv, application/rdfxml, application/rssxml, jsonAvailable download formats
    Dataset updated
    Aug 21, 2011
    Dataset authored and provided by
    King County
    License

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

    Area covered
    King County, United States
    Description

    Source: U.S. Census Bureau, PL 94-171 Redistricting data, 2000 and 2010. Note: Census numbers for the cities of Burien and Kent do not include annexations that took place after March 31, 2010. These annexations would increase Burien to 48,072, Kent to 118,565, and decrease uninc King County to 284,089.

  5. Population Density in the US (2020 Census)

    • data-bgky.hub.arcgis.com
    • hub.arcgis.com
    Updated Jun 7, 2023
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    Esri (2023). Population Density in the US (2020 Census) [Dataset]. https://data-bgky.hub.arcgis.com/maps/a1926cb43e844c3f82275917d6eab47a
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    Dataset updated
    Jun 7, 2023
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This map shows population density of the United States. Areas in darker magenta have much higher population per square mile than areas in orange or yellow. Data is from the U.S. Census Bureau’s 2020 Census Demographic and Housing Characteristics. The map's layers contain total population counts by sex, age, and race groups for Nation, State, County, Census Tract, and Block Group in the United States and Puerto Rico. From the Census:"Population density allows for broad comparison of settlement intensity across geographic areas. In the U.S., population density is typically expressed as the number of people per square mile of land area. The U.S. value is calculated by dividing the total U.S. population (316 million in 2013) by the total U.S. land area (3.5 million square miles).When comparing population density values for different geographic areas, then, it is helpful to keep in mind that the values are most useful for small areas, such as neighborhoods. For larger areas (especially at the state or country scale), overall population density values are less likely to provide a meaningful measure of the density levels at which people actually live, but can be useful for comparing settlement intensity across geographies of similar scale." SourceAbout the dataYou can use this map as is and you can also modify it to use other attributes included in its layers. This map's layers contain total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, State, County, Census Tract, Block Group boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, State, County, Census Tract, Block GroupNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This map is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, 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 and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

  6. a

    COUNTIES

    • mce-data-uscensus.hub.arcgis.com
    • hub.arcgis.com
    • +1more
    Updated Feb 2, 2024
    + more versions
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    US Census Bureau (2024). COUNTIES [Dataset]. https://mce-data-uscensus.hub.arcgis.com/datasets/counties-41
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    Dataset updated
    Feb 2, 2024
    Dataset authored and provided by
    US Census Bureau
    Area covered
    Description

    This layer shows Population. This is shown by state and county boundaries. This service contains the 2018-2022 release of data from the 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 point by Population Density and size of the point by Total Population. The size of the symbol represents the total count of housing units. Population Density was calculated based on the total population and area of land fields, which both came from the U.S. Census Bureau. Formula used for Calculating the Pop Density (B01001_001E/GEO_LAND_AREA_SQ_KM). 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: 2018-2022ACS Table(s): B01001, B09020Data downloaded from: Census Bureau's API for American Community Survey Date of API call: January 18, 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. 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:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, 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 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). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. 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.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.

  7. US Census Bureau Intercensal Estimates of the Resident Population by Sex and...

    • data.subak.org
    • datasource.kapsarc.org
    csv
    Updated Feb 16, 2023
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    United States Census Bureau (USCB) (2023). US Census Bureau Intercensal Estimates of the Resident Population by Sex and Age [Dataset]. https://data.subak.org/dataset/us-census-bureau-intercensal-estimates-of-the-resident-population-by-sex-and-age
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    csvAvailable download formats
    Dataset updated
    Feb 16, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    License

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

    Area covered
    United States
    Description

    Intercensal estimates are produced once a decade by adjusting the existing time series of postcensal estimates for a decade to smooth the transition from one decennial census count to the next They differ from the postcensal estimates that are released annually because they rely on a formula that redistributes the difference between the April 1 postcensal estimate and April 1 census count for the end of the decade across the estimates for that decade Meanwhile, the nbsp postcensal estimates nbsp incorporate current data on births, deaths, and migration to produce each new vintage of estimates, and to revise estimates for years back to the last census Note Intercensal Estimates as of July 1 1 The April 1, 2000 Population Estimates base reflects changes to the Census 2000 population from the Count Question Resolution program, legal boundary updates, and other geographic program revisions 2 The data source for April 1, 2010 is the 2010 Census count 3 The values for 2010 were produced by applying estimates of change in the population between April 1 and July 1 of 2010 to the 2010 Census counts Further details on this methodology are available at http www census gov popest methodology intercensal nat meth pdf

  8. 2023 American Community Survey: DP05 | ACS Demographic and Housing Estimates...

    • data.census.gov
    Updated Aug 15, 2021
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    2023 American Community Survey: DP05 | ACS Demographic and Housing Estimates (ACS 5-Year Estimates Data Profiles) [Dataset]. https://data.census.gov/all/tables?q=Barbecues
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    Dataset updated
    Aug 15, 2021
    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
    2023
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.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, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..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..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..For more information on understanding Hispanic origin and race data, please see the America Counts: Stories Behind the Numbers article entitled, 2020 Census Illuminates Racial and Ethnic Composition of the Country, issued August 2021..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census 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:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

  9. r

    US Census 1990: Summary File 3 Indicators, Sample Count and Calculated...

    • rigis.org
    • hub.arcgis.com
    Updated Nov 1, 1992
    + more versions
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    Environmental Data Center (1992). US Census 1990: Summary File 3 Indicators, Sample Count and Calculated Percentages [Dataset]. https://www.rigis.org/maps/edc::us-census-1990-summary-file-3-indicators-sample-count-and-calculated-percentages
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    Dataset updated
    Nov 1, 1992
    Dataset authored and provided by
    Environmental Data Center
    Area covered
    Description

    U.S. Census 1990 population and housing information by town, tract, and block group level as derived from U.S. Census STF1a by source data count and calculated percentages. Intended for use in statistical analysis of demographic data tract.

  10. N

    Young America Township, Minnesota Population Breakdown By Race (Excluding...

    • neilsberg.com
    csv, json
    Updated Feb 21, 2025
    + more versions
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    Neilsberg Research (2025). Young America Township, Minnesota Population Breakdown By Race (Excluding Ethnicity) Dataset: Population Counts and Percentages for 7 Racial Categories as Identified by the US Census Bureau // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/young-america-township-mn-population-by-race/
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    json, csvAvailable download formats
    Dataset updated
    Feb 21, 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
    Minnesota, Young America Township
    Variables measured
    Asian Population, Black Population, White Population, Some other race Population, Two or more races Population, American Indian and Alaska Native Population, Asian Population as Percent of Total Population, Black Population as Percent of Total Population, White Population as Percent of Total Population, Native Hawaiian and Other Pacific Islander Population, and 4 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 racial categories idetified by the US Census Bureau. It is ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories, and do not rely on any ethnicity classification. 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 population of Young America township by race. It includes the population of Young America township across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Young America township across relevant racial categories.

    Key observations

    The percent distribution of Young America township population by race (across all racial categories recognized by the U.S. Census Bureau): 95.93% are white, 2.21% are Asian, 0.85% are some other race and 1.02% are multiracial.

    Content

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

    Racial categories include:

    • White
    • Black or African American
    • American Indian and Alaska Native
    • Asian
    • Native Hawaiian and Other Pacific Islander
    • Some other race
    • Two or more races (multiracial)

    Variables / Data Columns

    • Race: This column displays the racial categories (excluding ethnicity) for the Young America township
    • Population: The population of the racial category (excluding ethnicity) in the Young America township is shown in this column.
    • % of Total Population: This column displays the percentage distribution of each race as a proportion of Young America township 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 Young America township Population by Race & Ethnicity. You can refer the same here

  11. N

    American Fork, UT Non-Hispanic Population Breakdown By Race Dataset:...

    • neilsberg.com
    csv, json
    Updated Feb 21, 2025
    + more versions
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    Neilsberg Research (2025). American Fork, UT Non-Hispanic Population Breakdown By Race Dataset: Non-Hispanic Population Counts and Percentages for 7 Racial Categories as Identified by the US Census Bureau // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/american-fork-ut-population-by-race/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 21, 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
    Utah, American Fork
    Variables measured
    Non-Hispanic Asian Population, Non-Hispanic Black Population, Non-Hispanic White Population, Non-Hispanic Some other race Population, Non-Hispanic Two or more races Population, Non-Hispanic American Indian and Alaska Native Population, Non-Hispanic Native Hawaiian and Other Pacific Islander Population, Non-Hispanic Asian Population as Percent of Total Non-Hispanic Population, Non-Hispanic Black Population as Percent of Total Non-Hispanic Population, Non-Hispanic White Population as Percent of Total Non-Hispanic Population, and 4 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) Non-Hispanic population and (b) population as a percentage of the total Non-Hispanic population, we initially analyzed and categorized the data for each of the racial categories idetified by the US Census Bureau. It is ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories, and are part of Non-Hispanic classification. 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 Non-Hispanic population of American Fork by race. It includes the distribution of the Non-Hispanic population of American Fork across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of American Fork across relevant racial categories.

    Key observations

    Of the Non-Hispanic population in American Fork, the largest racial group is White alone with a population of 29,151 (91.56% of the total Non-Hispanic population).

    Content

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

    Racial categories include:

    • White
    • Black or African American
    • American Indian and Alaska Native
    • Asian
    • Native Hawaiian and Other Pacific Islander
    • Some other race
    • Two or more races (multiracial)

    Variables / Data Columns

    • Race: This column displays the racial categories (for Non-Hispanic) for the American Fork
    • Population: The population of the racial category (for Non-Hispanic) in the American Fork is shown in this column.
    • % of Total Population: This column displays the percentage distribution of each race as a proportion of American Fork total Non-Hispanic 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 American Fork Population by Race & Ethnicity. You can refer the same here

  12. Urban and Rural Population in US Legislative Districts (2020 Census)

    • data-bgky.hub.arcgis.com
    Updated Jun 8, 2023
    + more versions
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    Esri (2023). Urban and Rural Population in US Legislative Districts (2020 Census) [Dataset]. https://data-bgky.hub.arcgis.com/maps/497d1bb78d98438386fd6721b6c2c3aa
    Explore at:
    Dataset updated
    Jun 8, 2023
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This map's colors indicate which population is larger in each area: urban (green) or rural (yellow). The map's layers contain total population counts by sex, age, and race groups for Nation, State Legislative Districts Upper, State Legislative Districts Lower, Congressional District in the United States and Puerto Rico.The U.S. Census designates each census block as part of an urban area or as rural. Larger geographies in this map such as block group, tract, county and state can therefore have a mix of urban and rural population. This map illustrates the 100% urban areas in dark green, and 100% rural areas in dark yellow. Areas with mixed urban/rural population have softer shades of green or yellow, to give a visual indication of where change may be happening. From the Census:"The Census Bureau’s urban-rural classification is a delineation of geographic areas, identifying both individual urban areas and the rural area of the nation. The Census Bureau’s urban areas represent densely developed territory, and encompass residential, commercial, and other non-residential urban land uses. The Census Bureau delineates urban areas after each decennial census by applying specified criteria to decennial census and other data. Rural encompasses all population, housing, and territory not included within an urban area.For the 2020 Census, an urban area will comprise a densely settled core of census blocks that meet minimum housing unit density and/or population density requirements. This includes adjacent territory containing non-residential urban land uses. To qualify as an urban area, the territory identified according to criteria must encompass at least 2,000 housing units or have a population of at least 5,000." SourceAbout the dataYou can use this map as is and you can also modify it to use other attributes included in its layers. This map's layers contain total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, State, County, Census Tract, Block Group boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, State, County, Census Tract, Block GroupNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This map is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, 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 and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

  13. N

    Wall, SD Population Breakdown By Race (Excluding Ethnicity) Dataset:...

    • neilsberg.com
    csv, json
    Updated Feb 21, 2025
    + more versions
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    Neilsberg Research (2025). Wall, SD Population Breakdown By Race (Excluding Ethnicity) Dataset: Population Counts and Percentages for 7 Racial Categories as Identified by the US Census Bureau // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/wall-sd-population-by-race/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 21, 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
    Wall, South Dakota
    Variables measured
    Asian Population, Black Population, White Population, Some other race Population, Two or more races Population, American Indian and Alaska Native Population, Asian Population as Percent of Total Population, Black Population as Percent of Total Population, White Population as Percent of Total Population, Native Hawaiian and Other Pacific Islander Population, and 4 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 racial categories idetified by the US Census Bureau. It is ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories, and do not rely on any ethnicity classification. 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 population of Wall by race. It includes the population of Wall across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Wall across relevant racial categories.

    Key observations

    The percent distribution of Wall population by race (across all racial categories recognized by the U.S. Census Bureau): 80.17% are white, 2.69% are Black or African American, 2.69% are American Indian and Alaska Native, 1.85% are Asian, 0.67% are Native Hawaiian and other Pacific Islander, 1.18% are some other race and 10.76% are multiracial.

    Content

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

    Racial categories include:

    • White
    • Black or African American
    • American Indian and Alaska Native
    • Asian
    • Native Hawaiian and Other Pacific Islander
    • Some other race
    • Two or more races (multiracial)

    Variables / Data Columns

    • Race: This column displays the racial categories (excluding ethnicity) for the Wall
    • Population: The population of the racial category (excluding ethnicity) in the Wall is shown in this column.
    • % of Total Population: This column displays the percentage distribution of each race as a proportion of Wall 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 Wall Population by Race & Ethnicity. You can refer the same here

  14. g

    Chicago Population Counts | gimi9.com

    • gimi9.com
    + more versions
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    Chicago Population Counts | gimi9.com [Dataset]. https://www.gimi9.com/dataset/data-gov_chicago-population-counts/
    Explore at:
    Area covered
    Chicago
    Description

    Population totals for groupings commonly used in other datasets. Not all values are available for all years. Note that because the "Citywide" rows roll up the values from the individual ZIP Codes and the "Age 0-4," "Age 5-11," "Age 12-17," "Age 5+," "Age 18+," and "Age 65+" columns overlap other age categories, as well as each other in some cases, care should be taken in summing values to avoid accidental double-counting. The "Age 5-11" and "Age 12-17" columns only include children who live in households. Data Sources: U.S. Census Bureau American Community Survey (ACS) 5-year estimates (ZIP Code) and 1-year estimates (Citywide). The U.S. Census Bureau did not release standard 1-year estimates from the 2020 ACS. In 2020 only, 5-year estimates were used for the Citywide estimates.

  15. N

    American Fork, UT Population Breakdown By Race (Excluding Ethnicity)...

    • neilsberg.com
    csv, json
    Updated Jul 7, 2024
    + more versions
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    Neilsberg Research (2024). American Fork, UT Population Breakdown By Race (Excluding Ethnicity) Dataset: Population Counts and Percentages for 7 Racial Categories as Identified by the US Census Bureau // 2024 Edition [Dataset]. https://www.neilsberg.com/research/datasets/2d9a0b39-230c-11ef-bd92-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Jul 7, 2024
    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
    Utah, American Fork
    Variables measured
    Asian Population, Black Population, White Population, Some other race Population, Two or more races Population, American Indian and Alaska Native Population, Asian Population as Percent of Total Population, Black Population as Percent of Total Population, White Population as Percent of Total Population, Native Hawaiian and Other Pacific Islander Population, and 4 more
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 racial categories idetified by the US Census Bureau. It is ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories, and do not rely on any ethnicity classification. 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 population of American Fork by race. It includes the population of American Fork across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of American Fork across relevant racial categories.

    Key observations

    The percent distribution of American Fork population by race (across all racial categories recognized by the U.S. Census Bureau): 85.19% are white, 0.20% are Black or African American, 0.35% are American Indian and Alaska Native, 1.63% are Asian, 0.97% are Native Hawaiian and other Pacific Islander, 4.69% are some other race and 6.98% are multiracial.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

    Racial categories include:

    • White
    • Black or African American
    • American Indian and Alaska Native
    • Asian
    • Native Hawaiian and Other Pacific Islander
    • Some other race
    • Two or more races (multiracial)

    Variables / Data Columns

    • Race: This column displays the racial categories (excluding ethnicity) for the American Fork
    • Population: The population of the racial category (excluding ethnicity) in the American Fork is shown in this column.
    • % of Total Population: This column displays the percentage distribution of each race as a proportion of American Fork 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 American Fork Population by Race & Ethnicity. You can refer the same here

  16. Provisional COVID-19 death counts, rates, and percent of total deaths, by...

    • catalog.data.gov
    • data.virginia.gov
    • +2more
    Updated Mar 22, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). Provisional COVID-19 death counts, rates, and percent of total deaths, by jurisdiction of residence [Dataset]. https://catalog.data.gov/dataset/provisional-covid-19-death-counts-rates-and-percent-of-total-deaths-by-jurisdiction-of-res
    Explore at:
    Dataset updated
    Mar 22, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    This file contains COVID-19 death counts, death rates, and percent of total deaths by jurisdiction of residence. The data is grouped by different time periods including 3-month period, weekly, and total (cumulative since January 1, 2020). United States death counts and rates include the 50 states, plus the District of Columbia and New York City. New York state estimates exclude New York City. Puerto Rico is included in HHS Region 2 estimates. Deaths with confirmed or presumed COVID-19, coded to ICD–10 code U07.1. Number of deaths reported in this file are the total number of COVID-19 deaths received and coded as of the date of analysis and may not represent all deaths that occurred in that period. Counts of deaths occurring before or after the reporting period are not included in the file. Data during recent periods are incomplete because of the lag in time between when the death occurred and when the death certificate is completed, submitted to NCHS and processed for reporting purposes. This delay can range from 1 week to 8 weeks or more, depending on the jurisdiction and cause of death. Death counts should not be compared across states. Data timeliness varies by state. Some states report deaths on a daily basis, while other states report deaths weekly or monthly. The ten (10) United States Department of Health and Human Services (HHS) regions include the following jurisdictions. Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont; Region 2: New Jersey, New York, New York City, Puerto Rico; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, Texas; Region 7: Iowa, Kansas, Missouri, Nebraska; Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming; Region 9: Arizona, California, Hawaii, Nevada; Region 10: Alaska, Idaho, Oregon, Washington. Rates were calculated using the population estimates for 2021, which are estimated as of July 1, 2021 based on the Blended Base produced by the US Census Bureau in lieu of the April 1, 2020 decennial population count. The Blended Base consists of the blend of Vintage 2020 postcensal population estimates, 2020 Demographic Analysis Estimates, and 2020 Census PL 94-171 Redistricting File (see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/2020-2021/methods-statement-v2021.pdf). Rates are based on deaths occurring in the specified week/month and are age-adjusted to the 2000 standard population using the direct method (see https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-08-508.pdf). These rates differ from annual age-adjusted rates, typically presented in NCHS publications based on a full year of data and annualized weekly/monthly age-adjusted rates which have been adjusted to allow comparison with annual rates. Annualization rates presents deaths per year per 100,000 population that would be expected in a year if the observed period specific (weekly/monthly) rate prevailed for a full year. Sub-national death counts between 1-9 are suppressed in accordance with NCHS data confidentiality standards. Rates based on death counts less than 20 are suppressed in accordance with NCHS standards of reliability as specified in NCHS Data Presentation Standards for Proportions (available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf.).

  17. 2021 American Community Survey: DP05 | ACS DEMOGRAPHIC AND HOUSING ESTIMATES...

    • data.census.gov
    Updated Aug 15, 2021
    + more versions
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    ACS (2021). 2021 American Community Survey: DP05 | ACS DEMOGRAPHIC AND HOUSING ESTIMATES (ACS 5-Year Estimates American Indian and Alaska Native Data Profiles) [Dataset]. https://data.census.gov/table?q=United%20States%20Cree&t=Race%20and%20Ethnicity
    Explore at:
    Dataset updated
    Aug 15, 2021
    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
    2021
    Area covered
    United States
    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, 2017-2021 American Community Survey 5-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..For more information on understanding Hispanic origin and race data, please see the America Counts: Stories Behind the Numbers article entitled, 2020 Census Illuminates Racial and Ethnic Composition of the Country, issued August 2021..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 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 delineation lists 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:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

  18. Historic US Census - 1910

    • redivis.com
    application/jsonl +7
    Updated Jan 10, 2020
    + more versions
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    Stanford Center for Population Health Sciences (2020). Historic US Census - 1910 [Dataset]. http://doi.org/10.57761/n3ks-0444
    Explore at:
    spss, csv, parquet, arrow, stata, avro, sas, application/jsonlAvailable download formats
    Dataset updated
    Jan 10, 2020
    Dataset provided by
    Redivis Inc.
    Authors
    Stanford Center for Population Health Sciences
    Time period covered
    Jan 1, 1910 - Dec 31, 1910
    Area covered
    United States
    Description

    Abstract

    The Integrated Public Use Microdata Series (IPUMS) Complete Count Data include more than 650 million individual-level and 7.5 million household-level records. The microdata are the result of collaboration between IPUMS and the nation’s two largest genealogical organizations—Ancestry.com and FamilySearch—and provides the largest and richest source of individual level and household data.

    Before Manuscript Submission

    All manuscripts (and other items you'd like to publish) must be submitted to

    phsdatacore@stanford.edu for approval prior to journal submission.

    We will check your cell sizes and citations.

    For more information about how to cite PHS and PHS datasets, please visit:

    https:/phsdocs.developerhub.io/need-help/citing-phs-data-core

    Documentation

    Historic data are scarce and often only exists in aggregate tables. The key advantage of historic US census data is the availability of individual and household level characteristics that researchers can tabulate in ways that benefits their specific research questions. The data contain demographic variables, economic variables, migration variables and family variables. Within households, it is possible to create relational data as all relations between household members are known. For example, having data on the mother and her children in a household enables researchers to calculate the mother’s age at birth. Another advantage of the Complete Count data is the possibility to follow individuals over time using a historical identifier.

    In sum: the historic US census data are a unique source for research on social and economic change and can provide population health researchers with information about social and economic determinants.Historic data are scarce and often only exists in aggregate tables. The key advantage of historic US census data is the availability of individual and household level characteristics that researchers can tabulate in ways that benefits their specific research questions. The data contain demographic variables, economic variables, migration variables and family variables. Within households, it is possible to create relational data as all relations between household members are known. For example, having data on the mother and her children in a household enables researchers to calculate the mother’s age at birth. Another advantage of the Complete Count data is the possibility to follow individuals over time using a historical identifier. In sum: the historic US census data are a unique source for research on social and economic change and can provide population health researchers with information about social and economic determinants.

    The historic US 1910 census data was collected in April 1910. Enumerators collected data traveling to households and counting the residents who regularly slept at the household. Individuals lacking permanent housing were counted as residents of the place where they were when the data was collected. Household members absent on the day of data collected were either listed to the household with the help of other household members or were scheduled for the last census subdivision.

    Section 2

    This dataset was created on 2020-01-10 23:47:27.924 by merging multiple datasets together. The source datasets for this version were:

    IPUMS 1910 households: The Integrated Public Use Microdata Series (IPUMS) Complete Count Data are historic individual and household census records and are a unique source for research on social and economic change.

    IPUMS 1910 persons: This dataset includes all individuals from the 1910 US census.

  19. N

    Baton Rouge, LA Population Breakdown By Race (Excluding Ethnicity) Dataset:...

    • neilsberg.com
    csv, json
    Updated Feb 21, 2025
    + more versions
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    Neilsberg Research (2025). Baton Rouge, LA Population Breakdown By Race (Excluding Ethnicity) Dataset: Population Counts and Percentages for 7 Racial Categories as Identified by the US Census Bureau // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/baton-rouge-la-population-by-race/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 21, 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
    Baton Rouge, Louisiana
    Variables measured
    Asian Population, Black Population, White Population, Some other race Population, Two or more races Population, American Indian and Alaska Native Population, Asian Population as Percent of Total Population, Black Population as Percent of Total Population, White Population as Percent of Total Population, Native Hawaiian and Other Pacific Islander Population, and 4 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 racial categories idetified by the US Census Bureau. It is ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories, and do not rely on any ethnicity classification. 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 population of Baton Rouge by race. It includes the population of Baton Rouge across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Baton Rouge across relevant racial categories.

    Key observations

    The percent distribution of Baton Rouge population by race (across all racial categories recognized by the U.S. Census Bureau): 36.21% are white, 51.01% are Black or African American, 0.15% are American Indian and Alaska Native, 3.63% are Asian, 0.01% are Native Hawaiian and other Pacific Islander, 3.90% are some other race and 5.08% are multiracial.

    Content

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

    Racial categories include:

    • White
    • Black or African American
    • American Indian and Alaska Native
    • Asian
    • Native Hawaiian and Other Pacific Islander
    • Some other race
    • Two or more races (multiracial)

    Variables / Data Columns

    • Race: This column displays the racial categories (excluding ethnicity) for the Baton Rouge
    • Population: The population of the racial category (excluding ethnicity) in the Baton Rouge is shown in this column.
    • % of Total Population: This column displays the percentage distribution of each race as a proportion of Baton Rouge 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 Baton Rouge Population by Race & Ethnicity. You can refer the same here

  20. Tract

    • hub.arcgis.com
    Updated May 11, 2017
    + more versions
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    Esri U.S. Federal Datasets (2017). Tract [Dataset]. https://hub.arcgis.com/maps/fedmaps::tract-2
    Explore at:
    Dataset updated
    May 11, 2017
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri U.S. Federal Datasets
    Area covered
    Description

    Age and Gender Demographics in the 2010 CensusThis feature layer, utilizing data from the U.S. Census Bureau, displays 2010 demographics about age and gender in the U.S. for state, county, tract, and block group geographies. Per USCB, "Focusing on a population’s age and sex composition is one of the most basic ways to understand population change over time." The attributes cover topics such as population counts by 5-year age ranges, male and female population counts, and median age values. A small subset of attributes from the 2000 Census are also included as reference.The U.S. Census counts every resident in the United States. It is mandated by Article I, Section 2 of the Constitution and takes place every 10 years. The data collected by the decennial census determine the number of seats each state has in the U.S. House of Representatives and is also used to distribute billions in federal funds to local communities. Four layers are available: state, county, census tract, and census block group. Each layer contains the same set of demographic attributes. Each geography level has a viewing range optimal for the geography size, and the map has increasing detail as you zoom in to smaller areas. Only one geography is in view at any time.Wisconsin Census Tract: 550791851.00Data currency: 2010Data source: Explore Census DataData modification: NoneFor more information:Population Profiles 2010State and county boundaries are simplified representations offered from the Census Bureau's 2010 MAF/TIGER databaseTract and block group boundaries are 2010 TIGER boundaries with select water area boundaries erased (coastlines and major water bodies).For a list of fields and alias names, access the following excel document.For feedback please contact: ArcGIScomNationalMaps@esri.comU.S. Census BureauPer USCB, "the Census Bureau is the federal government’s largest statistical agency. We are dedicated to providing current facts and figures about America’s people, places, and economy. Federal law protects the confidentiality of all the information the Census Bureau collects."

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
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Close
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ACS (2021). 2023 American Community Survey: CP05 | Comparative Demographic Estimates (ACS 1-Year Estimates Comparison Profiles) [Dataset]. https://data.census.gov/cedsci/table?q=demog
Organization logo

2023 American Community Survey: CP05 | Comparative Demographic Estimates (ACS 1-Year Estimates Comparison Profiles)

2023: ACS 1-Year Estimates Comparison Profiles

Explore at:
Dataset updated
Aug 15, 2021
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
2023
Description

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.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, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..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..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..For more information on understanding Hispanic origin and race data, please see the America Counts: Stories Behind the Numbers article entitled, 2020 Census Illuminates Racial and Ethnic Composition of the Country, issued August 2021..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..An * indicates that the estimate is significantly different (at a 90% confidence level) than the estimate from the most current year. A "c" indicates the estimates for that year and the current year are both controlled; a statistical test is not appropriate. A blank indicates that the estimate is not significantly different from the estimate of the most current year, or that a test could not be done because one or both of the estimates is displayed as "-", "N", or "(X)", or the estimate ends with a "+" or "-". (For more information on these symbols, see the Explanation of Symbols.).Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

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