82 datasets found
  1. a

    Where do Black or African Americans not have an internet subscription at...

    • chi-phi-nmcdc.opendata.arcgis.com
    Updated Feb 15, 2021
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    New Mexico Community Data Collaborative (2021). Where do Black or African Americans not have an internet subscription at home?-Copy [Dataset]. https://chi-phi-nmcdc.opendata.arcgis.com/maps/5d3c114e42d444a58ef55ede9a87ec2e
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    Dataset updated
    Feb 15, 2021
    Dataset authored and provided by
    New Mexico Community Data Collaborative
    Area covered
    Description

    This map highlights where the Black/African American populations in households have a computer, but no internet subscription in their household. The brightest oranges show where there are a higher percentage of Black/African Americans without an internet subscription. The larger symbols show where there are more Black/African Americans without internet at home. Both of these factors highlight the at-risk population with unequal opportunities. This can be seen throughout the United States at the state, county, and tract levels. Search for your area, or explore one of the bookmarks within the map to see areas with stark patterns.The data in this map contains the most recent American Community Survey (ACS) data from the U.S. Census Bureau. The Living Atlas layer in this map updates annually when the Census releases their new figures. To learn more, visit this FAQ, or visit the ACS website. Data note: For the tract geography level, the margin of error (MOE) is included in the pop-up as reference. A note from the Census about MOEs: "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."

  2. 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
    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).

  3. 2023 Cartographic Boundary File (SHP), Census Tract for American Samoa,...

    • catalog.data.gov
    • datasets.ai
    Updated May 16, 2024
    + more versions
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division (Point of Contact) (2024). 2023 Cartographic Boundary File (SHP), Census Tract for American Samoa, 1:500,000 [Dataset]. https://catalog.data.gov/dataset/2023-cartographic-boundary-file-shp-census-tract-for-american-samoa-1-500000
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    Dataset updated
    May 16, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    American Samoa
    Description

    The 2023 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some states and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census and beyond, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

  4. a

    Somerset County Census Tracts

    • hub.arcgis.com
    • scogis-open-data-somerset.hub.arcgis.com
    Updated Jan 3, 2023
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    Somerset County GIS (2023). Somerset County Census Tracts [Dataset]. https://hub.arcgis.com/maps/somerset::somerset-county-census-tracts
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    Dataset updated
    Jan 3, 2023
    Dataset authored and provided by
    Somerset County GIS
    Area covered
    Description

    Census tracts are small and relatively permanent statistical subdivisions of a county or equivalent entity. Local participants review and update census tracts prior to each decennial census as part of the Census Bureau’s PSAP. The Census Bureau updates census tracts in situations where no local participant existed or where local or tribal governments declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of decennial census data. Census tracts generally have a population size of 1,200 to 8,000 people with an optimum size of 4,000 people. The spatial size of census tracts varies widely depending on the density of settlement. Ideally, census tract boundaries remain stable over time to facilitate statistical comparisons from census to census. However, physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, significant changes in population may result in splitting or combining census tracts. Census tract boundaries generally follow visible and identifiable features. Census tract boundaries may follow legal boundaries (e.g., MCD or incorporated place boundaries in some states to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses). State and county boundaries always are census tract boundaries in the standard census geographic hierarchy.In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. Census Tract Codes and Numbers—Census tract numbers have up to a 4-character basic number and may have an optional 2-character suffix. For example, 1457.02. The census tract numbers (used as names) eliminate any leading zeroes and append a suffix only if required. The 6-digit census tract codes, however, include leading zeroes and have an implied decimal point for the suffix. Census tract codes (000100 to 998999) are unique within a county or equivalent area. The Census Bureau assigned a census tract code of 9900 to represent census tracts delineated to cover large bodies of water. In addition, census tract codes in the 9400s represent American Indian Areas and codes in the 9800s represent special land use areas. The Census Bureau uses suffixes to help identify census tract changes for comparison purposes. Local participants have an opportunity to review the existing census tracts before each census. If local participants split a census tract, the split parts usually retain the basic number, but receive different suffixes. In a few counties, local participants request major changes to, and renumbering of, the census tracts. Changes to individual census tract boundaries usually do not result in census tract numbering changes. Relationship to Other Geographic Entities—Within the standard census geographic hierarchy, census tracts never cross state or county boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and AIANNH areas. Census Tract Numbers and Codes: 000100 to 939999 - Basic number range for census tracts940000 to 949999 - American Indian Areas950000 to 979999 - Basic number range for census tracts980000 to 989999 - Special land use areas990000 to 990099 - Basic number range for census tracts in water areas990100 to 998900 - Basic number range for census tracts 2020 Census legal boundaries (TIGER/Line Shapefiles) were downloaded from the Census website. Data pertaining to Somerset County was extracted and processed by the Somerset County Office of GIS Services (SCOGIS)

  5. American Community Survey (ACS)

    • console.cloud.google.com
    Updated Jul 16, 2018
    + more versions
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    https://console.cloud.google.com/marketplace/browse?filter=partner:United%20States%20Census%20Bureau&inv=1&invt=Abyneg (2018). American Community Survey (ACS) [Dataset]. https://console.cloud.google.com/marketplace/product/united-states-census-bureau/acs
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    Dataset updated
    Jul 16, 2018
    Dataset provided by
    Googlehttp://google.com/
    Description

    The American Community Survey (ACS) is an ongoing survey that provides vital information on a yearly basis about our nation and its people by contacting over 3.5 million households across the country. The resulting data provides incredibly detailed demographic information across the US aggregated at various geographic levels which helps determine how more than $675 billion in federal and state funding are distributed each year. Businesses use ACS data to inform strategic decision-making. ACS data can be used as a component of market research, provide information about concentrations of potential employees with a specific education or occupation, and which communities could be good places to build offices or facilities. For example, someone scouting a new location for an assisted-living center might look for an area with a large proportion of seniors and a large proportion of people employed in nursing occupations. Through the ACS, we know more about jobs and occupations, educational attainment, veterans, whether people own or rent their homes, and other topics. Public officials, planners, and entrepreneurs use this information to assess the past and plan the future. For more information, see the Census Bureau's ACS Information Guide . This public dataset is hosted in Google BigQuery as part of the Google Cloud Public Datasets Program , with Carto providing cleaning and onboarding support. It is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

  6. 2023 American Community Survey: B16002 | Detailed Household Language by...

    • data.census.gov
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    ACS, 2023 American Community Survey: B16002 | Detailed Household Language by Household Limited English Speaking Status (ACS 1-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT1Y2023.B16002?q=arabic%26
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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
    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..A "limited English speaking household" is one in which no member 14 years old and over (1) speaks only English or (2) speaks a non-English language and speaks English "very well." In other words, all members 14 years old and over have at least some difficulty with English. By definition, English-only households cannot belong to this group. Previous Census Bureau data products have referred to these households as "linguistically isolated" and "Households in which no one 14 and over speaks English only or speaks a language other than English at home and speaks English 'very well'." This table is directly comparable to tables from earlier years that used these labels..The household language assigned to the housing unit is the non-English language spoken by the first person with a non-English language in the following order: reference person, spouse, parent, sibling, child, grandchild, in-law, other relative, unmarried partner, housemate/roommate, roomer/boarder, foster child, or other nonrelative. If no member of the household age 5 and over speaks a language other than English at home then the household language is English only..In 2016, changes were made to the languages and language categories presented in tables B16001, C16001, and B16002. For more information, see: 2016 Language Data User note..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 obser...

  7. United States International Census

    • kaggle.com
    zip
    Updated Aug 30, 2019
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    US Census Bureau (2019). United States International Census [Dataset]. https://www.kaggle.com/census/census-bureau-international
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    zip(0 bytes)Available download formats
    Dataset updated
    Aug 30, 2019
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    US Census Bureau
    License

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

    Area covered
    United States
    Description

    Context

    The United States Census Bureau’s International Dataset provides estimates of country populations since 1950 and projections through 2050.

    Content

    The U.S. Census Bureau provides estimates and projections for countries and areas that are recognized by the U.S. Department of State that have a population of at least 5,000. Specifically, the data set includes midyear population figures broken down by age and gender assignment at birth. Additionally, they provide time-series data for attributes including fertility rates, birth rates, death rates, and migration rates.

    Fork this kernel to get started.

    Acknowledgements

    https://bigquery.cloud.google.com/dataset/bigquery-public-data:census_bureau_international

    https://cloud.google.com/bigquery/public-data/international-census

    Dataset Source: www.census.gov

    This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source -http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

    Banner Photo by Steve Richey from Unsplash.

    Inspiration

    What countries have the longest life expectancy?

    Which countries have the largest proportion of their population under 25?

    Which countries are seeing the largest net migration?

  8. a

    Population Density in the US 2020 Census

    • hub.arcgis.com
    • data-bgky.hub.arcgis.com
    Updated Jun 20, 2024
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    University of South Florida GIS (2024). Population Density in the US 2020 Census [Dataset]. https://hub.arcgis.com/maps/58e4ee07a0e24e28949903511506a8e4
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    Dataset updated
    Jun 20, 2024
    Dataset authored and provided by
    University of South Florida GIS
    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.

  9. D

    Census Tract Top 50 American Community Survey Data

    • data.seattle.gov
    • hub.arcgis.com
    • +1more
    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:
  10. F

    Homeownership Rate in the United States

    • fred.stlouisfed.org
    json
    Updated Apr 28, 2025
    + more versions
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    (2025). Homeownership Rate in the United States [Dataset]. https://fred.stlouisfed.org/series/RHORUSQ156N
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    jsonAvailable download formats
    Dataset updated
    Apr 28, 2025
    License

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

    Area covered
    United States
    Description

    Graph and download economic data for Homeownership Rate in the United States (RHORUSQ156N) from Q1 1965 to Q1 2025 about homeownership, housing, rate, and USA.

  11. n

    Census Microdata Samples Project

    • neuinfo.org
    • scicrunch.org
    • +2more
    Updated Jan 29, 2022
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    (2022). Census Microdata Samples Project [Dataset]. http://identifiers.org/RRID:SCR_008902
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    Dataset updated
    Jan 29, 2022
    Description

    A data set of cross-nationally comparable microdata samples for 15 Economic Commission for Europe (ECE) countries (Bulgaria, Canada, Czech Republic, Estonia, Finland, Hungary, Italy, Latvia, Lithuania, Romania, Russia, Switzerland, Turkey, UK, USA) based on the 1990 national population and housing censuses in countries of Europe and North America to study the social and economic conditions of older persons. These samples have been designed to allow research on a wide range of issues related to aging, as well as on other social phenomena. A common set of nomenclatures and classifications, derived on the basis of a study of census data comparability in Europe and North America, was adopted as a standard for recoding. This series was formerly called Dynamics of Population Aging in ECE Countries. The recommendations regarding the design and size of the samples drawn from the 1990 round of censuses envisaged: (1) drawing individual-based samples of about one million persons; (2) progressive oversampling with age in order to ensure sufficient representation of various categories of older people; and (3) retaining information on all persons co-residing in the sampled individual''''s dwelling unit. Estonia, Latvia and Lithuania provided the entire population over age 50, while Finland sampled it with progressive over-sampling. Canada, Italy, Russia, Turkey, UK, and the US provided samples that had not been drawn specially for this project, and cover the entire population without over-sampling. Given its wide user base, the US 1990 PUMS was not recoded. Instead, PAU offers mapping modules, which recode the PUMS variables into the project''''s classifications, nomenclatures, and coding schemes. Because of the high sampling density, these data cover various small groups of older people; contain as much geographic detail as possible under each country''''s confidentiality requirements; include more extensive information on housing conditions than many other data sources; and provide information for a number of countries whose data were not accessible until recently. Data Availability: Eight of the fifteen participating countries have signed the standard data release agreement making their data available through NACDA/ICPSR (see links below). Hungary and Switzerland require a clearance to be obtained from their national statistical offices for the use of microdata, however the documents signed between the PAU and these countries include clauses stipulating that, in general, all scholars interested in social research will be granted access. Russia requested that certain provisions for archiving the microdata samples be removed from its data release arrangement. The PAU has an agreement with several British scholars to facilitate access to the 1991 UK data through collaborative arrangements. Statistics Canada and the Italian Institute of statistics (ISTAT) provide access to data from Canada and Italy, respectively. * Dates of Study: 1989-1992 * Study Features: International, Minority Oversamples * Sample Size: Approx. 1 million/country Links: * Bulgaria (1992), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02200 * Czech Republic (1991), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06857 * Estonia (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06780 * Finland (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06797 * Romania (1992), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06900 * Latvia (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02572 * Lithuania (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03952 * Turkey (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03292 * U.S. (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06219

  12. N

    American Canyon, CA households by income brackets: family, non-family, and...

    • neilsberg.com
    csv, json
    Updated Mar 3, 2025
    + more versions
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    Neilsberg Research (2025). American Canyon, CA households by income brackets: family, non-family, and total, in 2023 inflation-adjusted dollars [Dataset]. https://www.neilsberg.com/research/datasets/661d64e7-f81d-11ef-a994-3860777c1fe6/
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    csv, jsonAvailable download formats
    Dataset updated
    Mar 3, 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
    American Canyon, California, United States
    Variables measured
    Income Level, All households, Family households, Non-Family households, Percent of All households, Percent of Family households, Percent of Non-Family households
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It delineates income distributions across income brackets (mentioned above) following an initial analysis and categorization. The percentage of all, family and nonfamily households were collected by grouping data as applicable. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents a breakdown of households across various income brackets in American Canyon, CA, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for American Canyon, CA reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of American Canyon households based on income levels.

    Key observations

    • For Family Households: In American Canyon, the majority of family households, representing 24.07%, earn $200,000 or more, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.67%, have incomes falling $35,000 to $39,999, representing a smaller but still significant segment of the community.
    • For Non-Family Households: In American Canyon, the majority of non-family households, accounting for 16.41%, have income $75,000 to $99,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.7%, earn $35,000 to $39,999, representing a smaller, yet notable, portion of non-family households in the community.
    Content

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

    Income Levels:

    • Less than $10,000
    • $10,000 to $14,999
    • $15,000 to $19,999
    • $20,000 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $59,999
    • $60,000 to $74,999
    • $75,000 to $99,999
    • $125,000 to $149,999
    • $150,000 to $199,999
    • $200,000 or more

    Variables / Data Columns

    • Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in American Canyon, CA (As mentioned above).
    • All Households: Count of households for the specified income level
    • % All Households: Percentage of households at the specified income level relative to the total households in American Canyon, CA
    • Family Households: Count of family households for the specified income level
    • % Family Households: Percentage of family households at the specified income level relative to the total family households in American Canyon, CA
    • Non-Family Households: Count of non-family households for the specified income level
    • % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in American Canyon, CA

    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 Canyon median household income. You can refer the same here

  13. 2022 American Community Survey: S1602 | Limited English Speaking Households...

    • data.census.gov
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    ACS, 2022 American Community Survey: S1602 | Limited English Speaking Households (ACS 1-Year Estimates Subject Tables) [Dataset]. https://data.census.gov/table/ACSST1Y2022.S1602?q=limited
    Explore at:
    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..A "limited English speaking household" is one in which no member 14 years old and over (1) speaks only English or (2) speaks a non-English language and speaks English "very well." In other words, all members 14 years old and over have at least some difficulty with English. By definition, English-only households cannot belong to this group. Previous Census Bureau data products have referred to these households as "linguistically isolated" and "Households in which no one 14 and over speaks English only or speaks a language other than English at home and speaks English 'very well'." This table is directly comparable to tables from earlier years that used these labels..The household language assigned to the housing unit is the non-English language spoken by the first person with a non-English language in the following order: reference person, spouse, parent, sibling, child, grandchild, in-law, other relative, unmarried partner, housemate/roommate, roomer/boarder, foster child, or other nonrelative. If no member of the household age 5 and over speaks a language other than English at home then the household language is English only..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.

  14. 2023 American Community Survey: B99281 | Allocation of Household Internet...

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    ACS, 2023 American Community Survey: B99281 | Allocation of Household Internet Access (ACS 1-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT1Y2023.B99281
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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
    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..An Internet "subscription" refers to a type of service that someone pays for to access the Internet such as a cellular data plan, broadband such as cable, fiber optic or DSL, or other type of service. This will normally refer to a service that someone is billed for directly for Internet alone or sometimes as part of a bundle.."Internet access" refers to whether or not a household uses or connects to the Internet, regardless of whether or not they pay for the service to do so. Data about Internet access was collected by asking if the respondent or any member of the household accessed the Internet. The respondent then selected one of the following three categories: "Yes, by paying a cell phone company or Internet service provider"; "Yes, without paying a cell phone company or Internet service provider"; or "No access to the Internet at the house, apartment or mobile home". Only respondents who answered "Yes, by paying a cell phone company or Internet service provider" were asked the subsequent question about the types of service they had access to such as dial-up, broadband (high speed) service such as cable, fiber-optic, or DSL, a cellular data plan, satellite or some other service..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..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 applicabl...

  15. 2022 American Community Survey: S1602 | Limited English Speaking Households...

    • data.census.gov
    Updated Apr 1, 2010
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    ACS (2010). 2022 American Community Survey: S1602 | Limited English Speaking Households (ACS 5-Year Estimates Subject Tables) [Dataset]. https://data.census.gov/table/ACSST5Y2022.S1602?q=United%20States&t=Populations%20and%20People&g=1400000US19103002300
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    Dataset updated
    Apr 1, 2010
    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, 2018-2022 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..A "limited English speaking household" is one in which no member 14 years old and over (1) speaks only English or (2) speaks a non-English language and speaks English "very well." In other words, all members 14 years old and over have at least some difficulty with English. By definition, English-only households cannot belong to this group. Previous Census Bureau data products have referred to these households as "linguistically isolated" and "Households in which no one 14 and over speaks English only or speaks a language other than English at home and speaks English 'very well'." This table is directly comparable to tables from earlier years that used these labels..The household language assigned to the housing unit is the non-English language spoken by the first person with a non-English language in the following order: reference person, spouse, parent, sibling, child, grandchild, in-law, other relative, unmarried partner, housemate/roommate, roomer/boarder, foster child, or other nonrelative. If no member of the household age 5 and over speaks a language other than English at home then the household language is English only..The 2018-2022 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 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 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.

  16. 2022 Cartographic Boundary File (SHP), Current Census Tract for Georgia,...

    • catalog.data.gov
    Updated Dec 14, 2023
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch (Point of Contact) (2023). 2022 Cartographic Boundary File (SHP), Current Census Tract for Georgia, 1:500,000 [Dataset]. https://catalog.data.gov/dataset/2022-cartographic-boundary-file-shp-current-census-tract-for-georgia-1-500000
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    Dataset updated
    Dec 14, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    The 2022 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some states and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census and beyond, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

  17. w

    R2 & NE: Tract Level 2006-2010 ACS Employment Summary

    • data.wu.ac.at
    tgrshp (compressed)
    Updated Jan 13, 2018
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    U.S. Environmental Protection Agency (2018). R2 & NE: Tract Level 2006-2010 ACS Employment Summary [Dataset]. https://data.wu.ac.at/odso/data_gov/OTFlNDhmN2UtZDY5MS00MTVlLWE5YzItODJlMTUxNGZlNWEz
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    tgrshp (compressed)Available download formats
    Dataset updated
    Jan 13, 2018
    Dataset provided by
    U.S. Environmental Protection Agency
    License

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

    Area covered
    0213f8db6f300fcc466293315bed3556da3a1590
    Description

    The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

    This table contains data on employment, commuting time and method, and participation of mothers in the labor force from the American Community Survey 2006-2010 database for states. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).

    The name for table 'ACS10EMPTRMOE' was added as a prefix to all field names imported from that table. Be sure to turn off 'Show Field Aliases' to see complete field names in the Attribute Table of this feature layer. This can be done in the 'Table Options' drop-down menu in the Attribute Table or with key sequence '[CTRL]+[SHIFT]+N'. Due to database restrictions, the prefix may have been abbreviated if the field name exceded the maximum allowed characters.

  18. 2010 American Community Survey: DP03 | SELECTED ECONOMIC CHARACTERISTICS...

    • data.census.gov
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    ACS, 2010 American Community Survey: DP03 | SELECTED ECONOMIC CHARACTERISTICS (ACS 5-Year Estimates Selected Population Data Profiles) [Dataset]. https://data.census.gov/table/ACSDP5YSPT2010.DP03?tid=ACSDP5YSPT2010.DP03
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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
    2010
    Description

    Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and 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..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2010, the 2010 Census provides the official counts of the population and housing units for the nation, states, counties, cities and towns. For 2006 to 2009, the Population Estimates Program provides intercensal estimates of the population for the nation, states, and counties..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..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..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2000 data. Boundaries for urban areas have not been updated since Census 2000. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2006-2010 American Community Survey (ACS) data generally reflect the December 2009 Office of Management and Budget (OMB) definitions 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 definitions due to differences in the effective dates of the geographic entities..Occupation codes are 4-digit codes and are based on the Standard Occupational Classification (SOC) 2010. The 2010 Census occupation codes were updated in accordance with the 2010 revision of the SOC. To allow for the creation of 2006-2010 and 2008-2010 tables, occupation data in the multiyear files (2006-2010 and 2008-2010) were recoded to 2010 Census occupation codes. We recommend using caution when comparing data coded using 2010 Census occupation codes with data coded using previous Census occupation codes. For more information on the Census occupation code changes, please visit our website at http://www.census.gov/hhes/www/ioindex/..Industry codes are 4-digit codes and are based on the North American Industry Classification System 2007. The Industry categories adhere to the guidelines issued in Clarification Memorandum No. 2, "NAICS Alternate Aggregation Structure for Use By U.S. Statistical Agencies," issued by the Office of Management and Budget..Workers include members of the Armed Forces and civilians who were at work last week..There were changes in the edit between 2009 and 2010 regarding Supplemental Security Income (SSI) and Social Security. The changes in the edit loosened restrictions on disability requirements for receipt of SSI resulting in an increase in the total number of SSI recipients in the American Community Survey. The changes also loosened restrictions on possible reported monthly amounts in Social Security income resulting in higher Social Security aggregate amounts. These results more closely match administrative counts compiled by the Social Security Administration..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 ...

  19. 2015 State Geodatabase for Pennsylvania

    • data.wu.ac.at
    html, pdf, zip
    Updated Dec 7, 2015
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    US Census Bureau, Department of Commerce (2015). 2015 State Geodatabase for Pennsylvania [Dataset]. https://data.wu.ac.at/schema/data_gov/Y2YzZWY2Y2QtMDIxZC00OWJjLTkzNDctOTI2YzZkN2NiZGI5
    Explore at:
    zip, pdf, htmlAvailable download formats
    Dataset updated
    Dec 7, 2015
    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
    Pennsylvania, b206ab532f5a91fb1af106f78860358a9056eb8e
    Description

    The 2015 TIGER Geodatabases are extracts of selected nation based and state based geographic and cartographic information from the U.S. Census Bureau's Master Address File/Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) database. The geodatabases include feature class layers of information for the fifty states, the District of Columbia, Puerto Rico, and the Island areas (American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the United States Virgin Islands). The geodatabases do not contain any sensitive data. The 2015 TIGER Geodatabases are designed for use with Esriâ s ArcGIS.

            The 2015 State Geodatabase for Pennsylvania contains multiple layers. These layers are the Block, Block Group, Census Designated Place, Census
            Tract, County Subdivision and Incorporated Place layers.
    
            Block Groups (BGs) are clusters of blocks within the same census tract. Each census tract contains at least one BG, and BGs are uniquely numbered
            within census tracts. BGs have a valid code range of 0 through 9. BGs have the same first digit of their 4-digit census block number from the same
            decennial census. For example, tabulation blocks numbered 3001, 3002, 3003,.., 3999 within census tract 1210.02 are also within BG 3 within that
            census tract. BGs coded 0 are intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and
            Great Lakes water areas. Block groups generally contain between 600 and 3,000 people. A BG usually covers a contiguous area but never crosses
            county or census tract boundaries. They may, however, cross the boundaries of other geographic entities like county subdivisions, places, urban
            areas, voting districts, congressional districts, and American Indian / Alaska Native / Native Hawaiian areas. The BG boundaries in this release
            are those that were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2010 Census. 
    
            The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to
            previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people.
            When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living
            conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by
            highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to
            population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable
            features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to
            allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and
            county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may
            consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities
            that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that
            include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American
            Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little
            or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial
            park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area. 
    
            An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD),
            which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state,
            but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have
            other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated
            to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state
            in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide
            with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial
            census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily
            have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. 
    
            The boundaries of most incorporated places in this shapefile are as of January 1, 2013, as reported through the Census Bureau's Boundary and
            Annexation Survey (BAS). Limited updates that occurred after January 1, 2013, such as newly incorporated places, are also included. The boundaries
            of all CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2010 Census.
    
            The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no
            counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The
            latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri,
            Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary
            divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data
            presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data
            presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto
            Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin
            Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for
            counties and equivalent entities are mostly as of January 1, 2013, primarily as reported through the Census Bureau's Boundary and
            Annexation Survey (BAS). However, some changes made after January 2013, including the addition and deletion of counties, are included.
    
            County subdivisions are the primary divisions of counties and their equivalent entities for the reporting of Census Bureau data. They include
            legally-recognized minor civil divisions (MCDs) and statistical census county divisions (CCDs), and unorganized territories. For the 2010 Census,
            the MCDs are the primary governmental and/or administrative divisions of counties in 29 States and Puerto Rico; Tennessee changed from having CCDs
            for Census 2000 to having MCDs for the 2010 Census. In MCD States where no MCD exists or is not defined, the Census Bureau creates statistical
            unorganized territories to complete coverage. The entire area of the United States, Puerto Rico, and the Island Areas are covered by county
            subdivisions. The boundaries of most legal MCDs are as of January 1, 2013, as reported through the Census Bureau's Boundary and Annexation Survey
            (BAS). The boundaries of all CCDs, delineated in 21 states, are those as reported as part of the Census Bureau's Participant Statistical Areas
            Program (PSAP) for the 2010 Census.
    
  20. 2015 State Geodatabase for Minnesota

    • data.wu.ac.at
    html, pdf, zip
    Updated Dec 7, 2015
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    US Census Bureau, Department of Commerce (2015). 2015 State Geodatabase for Minnesota [Dataset]. https://data.wu.ac.at/odso/data_gov/YmVmNjA4MGItM2Q1My00Y2M1LTgzNDktOTIwMDU2YjE3ZGNm
    Explore at:
    html, zip, pdfAvailable download formats
    Dataset updated
    Dec 7, 2015
    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
    Minnesota, 2c0e3d77a12b82c1b8d6cc86dd6ea7f21df0b9d5
    Description

    The 2015 TIGER Geodatabases are extracts of selected nation based and state based geographic and cartographic information from the U.S. Census Bureau's Master Address File/Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) database. The geodatabases include feature class layers of information for the fifty states, the District of Columbia, Puerto Rico, and the Island areas (American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the United States Virgin Islands). The geodatabases do not contain any sensitive data. The 2015 TIGER Geodatabases are designed for use with Esriâ s ArcGIS.

            The 2015 State Geodatabase for Minnesota contains multiple layers. These layers are the Block, Block Group, Census Designated Place, Census Tract,
            County Subdivision and Incorporated Place layers.
    
            Block Groups (BGs) are clusters of blocks within the same census tract. Each census tract contains at least one BG, and BGs are uniquely numbered
            within census tracts. BGs have a valid code range of 0 through 9. BGs have the same first digit of their 4-digit census block number from the same
            decennial census. For example, tabulation blocks numbered 3001, 3002, 3003,.., 3999 within census tract 1210.02 are also within BG 3 within that
            census tract. BGs coded 0 are intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and
            Great Lakes water areas. Block groups generally contain between 600 and 3,000 people. A BG usually covers a contiguous area but never crosses
            county or census tract boundaries. They may, however, cross the boundaries of other geographic entities like county subdivisions, places, urban
            areas, voting districts, congressional districts, and American Indian / Alaska Native / Native Hawaiian areas. 
    
            The BG boundaries in this release are those that were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the
            2010 Census. 
    
            The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to
            previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people.
            When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living
            conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by
            highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to
            population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable
            features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to
            allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and
            county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may
            consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities
            that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that
            include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American
            Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little
            or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial
            park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area. 
    
            An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD),
            which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state,
            but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have
            other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated
            to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state
            in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide
            with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial
            census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily
            have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. 
    
            The boundaries of most incorporated places in this shapefile are as of January 1, 2013, as reported through the Census Bureau's Boundary and
            Annexation Survey (BAS). Limited updates that occurred after January 1, 2013, such as newly incorporated places, are also included. The boundaries
            of all CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2010 Census.
    
            The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no
            counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The
            latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri,
            Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary
            divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data
            presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data
            presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto
            Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin
            Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. 
    
            The boundaries for counties and equivalent entities are mostly as of January 1, 2013, primarily as reported through the Census Bureau's Boundary and
            Annexation Survey (BAS). However, some changes made after January 2013, including the addition and deletion of counties, are included.
    
            County subdivisions are the primary divisions of counties and their equivalent entities for the reporting of Census Bureau data. They include
            legally-recognized minor civil divisions (MCDs) and statistical census county divisions (CCDs), and unorganized territories. For the 2010 Census,
            the MCDs are the primary governmental and/or administrative divisions of counties in 29 States and Puerto Rico; Tennessee changed from having CCDs
            for Census 2000 to having MCDs for the 2010 Census. In MCD States where no MCD exists or is not defined, the Census Bureau creates statistical
            unorganized territories to complete coverage. The entire area of the United States, Puerto Rico, and the Island Areas are covered by county
            subdivisions. The boundaries of most legal MCDs are as of January 1, 2013, as reported through the Census Bureau's Boundary and Annexation Survey
            (BAS). 
    
            The boundaries of all CCDs, delineated in 21 states, are those as reported as part of the Census Bureau's Participant Statistical Areas Program
            (PSAP) for the 2010 Census.
    
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New Mexico Community Data Collaborative (2021). Where do Black or African Americans not have an internet subscription at home?-Copy [Dataset]. https://chi-phi-nmcdc.opendata.arcgis.com/maps/5d3c114e42d444a58ef55ede9a87ec2e

Where do Black or African Americans not have an internet subscription at home?-Copy

Explore at:
Dataset updated
Feb 15, 2021
Dataset authored and provided by
New Mexico Community Data Collaborative
Area covered
Description

This map highlights where the Black/African American populations in households have a computer, but no internet subscription in their household. The brightest oranges show where there are a higher percentage of Black/African Americans without an internet subscription. The larger symbols show where there are more Black/African Americans without internet at home. Both of these factors highlight the at-risk population with unequal opportunities. This can be seen throughout the United States at the state, county, and tract levels. Search for your area, or explore one of the bookmarks within the map to see areas with stark patterns.The data in this map contains the most recent American Community Survey (ACS) data from the U.S. Census Bureau. The Living Atlas layer in this map updates annually when the Census releases their new figures. To learn more, visit this FAQ, or visit the ACS website. Data note: For the tract geography level, the margin of error (MOE) is included in the pop-up as reference. A note from the Census about MOEs: "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."

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