100+ datasets found
  1. o

    Counties - United States of America

    • public.opendatasoft.com
    • bfortune.opendatasoft.com
    csv, excel, geojson +1
    Updated Jun 6, 2024
    + more versions
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    (2024). Counties - United States of America [Dataset]. https://public.opendatasoft.com/explore/dataset/georef-united-states-of-america-county/
    Explore at:
    excel, json, geojson, csvAvailable download formats
    Dataset updated
    Jun 6, 2024
    License

    https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain

    Area covered
    United States
    Description

    This dataset is part of the Geographical repository maintained by Opendatasoft. This dataset contains data for counties and equivalent entities in United States of America. 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.Processors and tools are using this data. Enhancements Add ISO 3166-3 codes. Simplify geometries to provide better performance across the services. Add administrative hierarchy.

  2. o

    Data from: US County Boundaries

    • public.opendatasoft.com
    csv, excel, geojson +1
    Updated Jun 27, 2017
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    (2017). US County Boundaries [Dataset]. https://public.opendatasoft.com/explore/dataset/us-county-boundaries/
    Explore at:
    json, csv, excel, geojsonAvailable download formats
    Dataset updated
    Jun 27, 2017
    License

    https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain

    Area covered
    United States
    Description

    The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. 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 as of January 1, 2017, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

  3. d

    COVID-19 County Level Data - Archive

    • catalog.data.gov
    • data.ct.gov
    • +1more
    Updated Jun 21, 2025
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    data.ct.gov (2025). COVID-19 County Level Data - Archive [Dataset]. https://catalog.data.gov/dataset/covid-19-county-level-data
    Explore at:
    Dataset updated
    Jun 21, 2025
    Dataset provided by
    data.ct.gov
    Description

    Covid-19 Daily metrics at the county level As of 6/1/2023, this data set is no longer being updated. The COVID-19 Data Report is posted on the Open Data Portal every day at 3pm. The report uses data from multiple sources, including external partners; if data from external partners are not received by 3pm, they are not available for inclusion in the report and will not be displayed. Data that are received after 3pm will still be incorporated and published in the next report update. The cumulative number of COVID-19 cases (cumulative_cases) includes all cases of COVID-19 that have ever been reported to DPH. The cumulative number of COVID_19 cases in the last 7 days (cases_7days) only includes cases where the specimen collection date is within the past 7 days. While most cases are reported to DPH within 48 hours of specimen collection, there are a small number of cases that routinely are delayed, and will have specimen collection dates that fall outside of the rolling 7 day reporting window. Additionally, reporting entities may submit correction files to contribute historic data during initial onboarding or to address data quality issues; while this is rare, these correction files may cause a large amount of data from outside of the current reporting window to be uploaded in a single day; this would result in the change in cumulative_cases being much larger than the value of cases_7days. On June 4, 2020, the US Department of Health and Human Services issued guidance requiring the reporting of positive and negative test results for SARS-CoV-2; this guidance expired with the end of the federal PHE on 5/11/2023, and negative SARS-CoV-2 results were removed from the List of Reportable Laboratory Findings. DPH will no longer be reporting metrics that were dependent on the collection of negative test results, specifically total tests performed or percent positivity. Positive antigen and PCR/NAAT results will continue to be reportable.

  4. D

    2020 Census Counties; PA, NJ, DE & MD

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

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

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

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

    The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and census areas; the latter of which are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. Additionally, the Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: municipios in Puerto Rico, districts and islands in American Samoa, municipalities in the Commonwealth of the Northern Mariana Islands, and islands in the U.S. Virgin Islands. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and, thus, constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation in decennial censuses. All of the counties in Connecticut and Rhode Island and nine counties in Massachusetts were dissolved as functioning governmental entities; however, the Census Bureau continues to present data for these historical entities in order to provide comparable geographic units at the county level of the geographic hierarchy for these states and represents them as nonfunctioning legal entities in data products. Each county or statistically equivalent entity is assigned a three-character numeric Federal Information Processing Series (FIPS) code based on alphabetical sequence that is unique within state, and an eight-digit National Standard (NS) code.

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

  5. 2022 Cartographic Boundary File (SHP), Current County and Equivalent for...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Dec 14, 2023
    + more versions
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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 County and Equivalent for United States, 1:5,000,000 [Dataset]. https://catalog.data.gov/dataset/2022-cartographic-boundary-file-shp-current-county-and-equivalent-for-united-states-1-5000000
    Explore at:
    Dataset updated
    Dec 14, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    United States
    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. 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 generalized boundaries for counties and equivalent entities are based on those as of January 1, 2022, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

  6. Data from: US County Boundaries

    • mapdirect-fdep.opendata.arcgis.com
    • azgeo-data-hub-agic.hub.arcgis.com
    • +2more
    Updated Jun 5, 2024
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    GeoPlatform ArcGIS Online (2024). US County Boundaries [Dataset]. https://mapdirect-fdep.opendata.arcgis.com/datasets/geoplatform::us-county-boundaries-1/about
    Explore at:
    Dataset updated
    Jun 5, 2024
    Dataset provided by
    https://arcgis.com/
    Authors
    GeoPlatform ArcGIS Online
    Area covered
    Description

    The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and census areas; the latter of which are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. 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. All of the counties in Connecticut and Rhode Island and nine counties in Massachusetts were dissolved as functioning governmental entities; however, the Census Bureau continues to present data for these historical entities in order to provide comparable geographic units at the county level of the geographic hierarchy for these states and represents them as nonfunctioning legal entities in data products. 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.Download: https://www2.census.gov/geo/tiger/TGRGDB24/tlgdb_2024_a_us_substategeo.gdb.zip Layer: CountyMetadata: https://meta.geo.census.gov/data/existing/decennial/GEO/GPMB/TIGERline/Current_19115/series_tl_2023_county.shp.iso.xml

  7. a

    i16 Census County DisadvantagedCommunities 2020

    • hub.arcgis.com
    • cnra-gis-open-data-staging-cnra.hub.arcgis.com
    • +1more
    Updated Feb 8, 2023
    + more versions
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    Carlos.Lewis@water.ca.gov_DWR (2023). i16 Census County DisadvantagedCommunities 2020 [Dataset]. https://hub.arcgis.com/datasets/5bab40dc9cb54ccd9b2ef61b5bcc34e6
    Explore at:
    Dataset updated
    Feb 8, 2023
    Dataset authored and provided by
    Carlos.Lewis@water.ca.gov_DWR
    Area covered
    Description

    This is a copy of the statewide Census Place GIS Tiger file. It is used to determine if a place is DAC or not by adding ACS (American Community Survey) Median Household Income (MHI) data at the county level. The IRWM web based DAC mapping tool uses this GIS layer. Every year this table gets updated after ACS publishes their updated estimates. Created by joining ACS 2016-2020 5 year estimates to the 2020 Census Counties feature class. 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. 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, and 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 2020 Census boundaries for counties and equivalent entities are as of January 1, 2020, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

  8. N

    De Witt County, IL Population Pyramid Dataset: Age Groups, Male and Female...

    • neilsberg.com
    csv, json
    Updated Feb 22, 2025
    + more versions
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    Neilsberg Research (2025). De Witt County, IL Population Pyramid Dataset: Age Groups, Male and Female Population, and Total Population for Demographics Analysis // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/5247136b-f122-11ef-8c1b-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 22, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

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

    Context

    The dataset tabulates the data for the De Witt County, IL population pyramid, which represents the De Witt County population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

    Key observations

    • Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for De Witt County, IL, is 28.0.
    • Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for De Witt County, IL, is 32.1.
    • Total dependency ratio for De Witt County, IL is 60.1.
    • Potential support ratio, which is the number of youth (working age population) per elderly, for De Witt County, IL is 3.1.
    Content

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

    Age groups:

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

    Variables / Data Columns

    • Age Group: This column displays the age group for the De Witt County population analysis. Total expected values are 18 and are define above in the age groups section.
    • Population (Male): The male population in the De Witt County for the selected age group is shown in the following column.
    • Population (Female): The female population in the De Witt County for the selected age group is shown in the following column.
    • Total Population: The total population of the De Witt County for the selected age group is shown in the following column.

    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 De Witt County Population by Age. You can refer the same here

  9. a

    2020 U.S. Census County Boundaries

    • gis-bradd-ky.opendata.arcgis.com
    Updated Aug 18, 2021
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    Barren River Area Development District (2021). 2020 U.S. Census County Boundaries [Dataset]. https://gis-bradd-ky.opendata.arcgis.com/datasets/2020-u-s-census-county-boundaries
    Explore at:
    Dataset updated
    Aug 18, 2021
    Dataset authored and provided by
    Barren River Area Development District
    Area covered
    Description
    The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation.

    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 as of January 1, 2020, as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

  10. N

    Coos County, OR Population Pyramid Dataset: Age Groups, Male and Female...

    • neilsberg.com
    csv, json
    Updated Feb 22, 2025
    + more versions
    Share
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    Neilsberg Research (2025). Coos County, OR Population Pyramid Dataset: Age Groups, Male and Female Population, and Total Population for Demographics Analysis // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/coos-county-or-population-by-age/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 22, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

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

    Context

    The dataset tabulates the data for the Coos County, OR population pyramid, which represents the Coos County population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

    Key observations

    • Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Coos County, OR, is 25.6.
    • Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Coos County, OR, is 47.4.
    • Total dependency ratio for Coos County, OR is 73.0.
    • Potential support ratio, which is the number of youth (working age population) per elderly, for Coos County, OR is 2.1.
    Content

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

    Age groups:

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

    Variables / Data Columns

    • Age Group: This column displays the age group for the Coos County population analysis. Total expected values are 18 and are define above in the age groups section.
    • Population (Male): The male population in the Coos County for the selected age group is shown in the following column.
    • Population (Female): The female population in the Coos County for the selected age group is shown in the following column.
    • Total Population: The total population of the Coos County for the selected age group is shown in the following column.

    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 Coos County Population by Age. You can refer the same here

  11. F

    Number of Private Establishments for All Industries in Licking County, OH

    • fred.stlouisfed.org
    json
    Updated Jun 4, 2025
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    (2025). Number of Private Establishments for All Industries in Licking County, OH [Dataset]. https://fred.stlouisfed.org/series/ENU3908920510
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 4, 2025
    License

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

    Area covered
    Licking County, Ohio
    Description

    Graph and download economic data for Number of Private Establishments for All Industries in Licking County, OH (ENU3908920510) from Q1 1990 to Q4 2024 about Licking County, OH; Columbus; establishments; OH; private industries; private; industry; and USA.

  12. Weekly COVID-19 County Level of Community Transmission Historical Changes -...

    • data.cdc.gov
    • healthdata.gov
    • +1more
    application/rdfxml +5
    Updated Oct 6, 2022
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    CDC COVID-19 Response (2022). Weekly COVID-19 County Level of Community Transmission Historical Changes - ARCHIVED [Dataset]. https://data.cdc.gov/Public-Health-Surveillance/Weekly-COVID-19-County-Level-of-Community-Transmis/jgk8-6dpn
    Explore at:
    csv, tsv, json, application/rssxml, xml, application/rdfxmlAvailable download formats
    Dataset updated
    Oct 6, 2022
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Authors
    CDC COVID-19 Response
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    Reporting of Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. This dataset will receive a final update on June 1, 2023, to reconcile historical data through May 10, 2023, and will remain publicly available.

    This archived public use dataset contains historical case and percent positivity data updated weekly for all available counties and jurisdictions. Each week, the dataset was refreshed to capture any historical updates. Please note, percent positivity data may be incomplete for the most recent time period.

    Related data CDC provides the public with two active versions of COVID-19 county-level community transmission level data: this dataset with historical case and percent positivity data for each county from January 22, 2020 (Weekly Historical Changes dataset) and a dataset with the levels as originally posted (Weekly Originally Posted dataset) since October 20, 2022. Please navigate to the Weekly Originally Posted dataset for the Community Transmission Levels published weekly on Thursdays.

    Methods for calculating county level of community transmission indicator The County Level of Community Transmission indicator uses two metrics: (1) total new COVID-19 cases per 100,000 persons in the last 7 days and (2) percentage of positive SARS-CoV-2 diagnostic nucleic acid amplification tests (NAAT) in the last 7 days. For each of these metrics, CDC classifies transmission values as low, moderate, substantial, or high (below and here). If the values for each of these two metrics differ (e.g., one indicates moderate and the other low), then the higher of the two should be used for decision-making.

    CDC core metrics of and thresholds for community transmission levels of SARS-CoV-2 Total New Case Rate Metric: "New cases per 100,000 persons in the past 7 days" is calculated by adding the number of new cases in the county (or other administrative level) in the last 7 days divided by the population in the county (or other administrative level) and multiplying by 100,000. "New cases per 100,000 persons in the past 7 days" is considered to have transmission level of Low (0-9.99); Moderate (10.00-49.99); Substantial (50.00-99.99); and High (greater than or equal to 100.00).

    Test Percent Positivity Metric: "Percentage of positive NAAT in the past 7 days" is calculated by dividing the number of positive tests in the county (or other administrative level) during the last 7 days by the total number of tests resulted over the last 7 days. "Percentage of positive NAAT in the past 7 days" is considered to have transmission level of Low (less than 5.00); Moderate (5.00-7.99); Substantial (8.00-9.99); and High (greater than or equal to 10.00).

    The data in this dataset are considered provisional by CDC and are subject to change until the data are reconciled and verified with the state and territorial data providers.

    This dataset is created using CDC’s Policy on Public Health Research and Nonresearch Data Management and Access.

    Archived data CDC has archived two prior versions of these datasets. Both versions contain the same 7 data elements reflecting community transmission levels for all available counties and jurisdictions; however, the datasets updated daily. The archived datasets can be found here:

    Archived Originally Posted dataset

    Archived Historical Changes dataset

    Archived Data Notes:

    October 27, 2022: Due to a processing issue this dataset will not be posted this week. CDC is currently working to address the issue and will publish the data when able.

    November 10, 2022: As of 11/10/2022, this dataset will continue to incorporate historical updates made to case and percent positivity data; however, community transmission level will only be published in the corresponding Weekly COVID-19 County Level of Community Transmission as Originally Posted dataset (Weekly Originally Posted dataset).

    Note:

    October 20, 2022: Due to a data reporting error, the case rate for Philadelphia County, Pennsylvania is lower than expected in the COVID-19 Community Transmission Level data released on October 20, 2022. This could lead to the COVID-19 Community Transmission Level for Philadelphia County being underestimated; therefore, it should be interpreted with caution.

    November 3, 2022: Due to a reporting cadence issue, case rates for Missouri counties are calculated based on 11 days’ worth of case count data in the COVID-19 Community Transmission Level data released on November 3, 2022, instead of the customary 7 days’ worth of data. This could lead to the COVID-19 Community Transmission Levels metrics for Missouri counties being overestimated; therefore, they should be interpreted with caution.

    November 10, 2022: Due to a reporting cadence change, case rates for Alabama counties are calculated based on 13 days’ worth of case count data in the COVID-19 Community Transmission Level data released on November 10, 2022, instead of the customary 7 days’ worth of data. This could lead to the COVID-19 Community Transmission Levels metrics for Alabama counties being overestimated; therefore, they should be interpreted with caution.

    November 10, 2022: Per the request of the jurisdiction, cases among non-residents have been removed from all Hawaii county totals throughout the entire time series. Cumulative case counts reported by CDC will no longer match Hawaii’s COVID-19 Dashboard, which still includes non-resident cases. 

    November 10, 2022: In the COVID-19 Community Transmission Level data released on November 10, 2022, multiple municipalities in Puerto Rico are reporting higher than expected increases in case counts. CDC is working with territory officials to verify the data submitted. 

    December 1, 2022: Due to cadence changes over the Thanksgiving holiday, case rates for all Ohio counties are reported as 0 in the COVID-19 Community Transmission Level data released on December 1, 2022. Therefore, the COVID-19 Community Transmission Levels may be underestimated and should be interpreted with caution. 

    December 22, 2022: Due to an internal revision process, case rates for some Tennessee counties may appear higher than expected in the December 22, 2022, weekly release. Therefore, the COVID-19 Community Transmission Levels metrics for some Tennessee counties may be overestimated and should be interpreted with caution.

    December 22, 2022: Due to reporting of a backlog of historic COVID-19 cases, case rates for some Louisiana counties will appear higher than expected in the December 22, 2022, weekly release. Therefore, the COVID-19 Community Transmission Levels metrics for some Louisiana counties may be overestimated and should be interpreted with caution.

    December 29, 2022: Due to technical difficulties, county data from Alabama could not be incorporated via standard practices. As a result, case and death metrics will be reported as 0 in the December 29, 2022, weekly release. Therefore, the COVID-19 Community Transmission Levels metrics for Alabama counties will be underestimated and should be interpreted with caution.

    January 5, 2023: Due to a reporting cadence issue, case rates for all Alabama counties will be calculated based on 14 days’ worth of case count data in the COVID-19 Community Transmission Level information released on January 5, 2023, instead of the customary 7 days’ worth of case count data. Therefore, the weekly case rates will be overestimated, which could affect counties’ COVID-19 Community Transmission Level classification and should be interpreted with caution.

    January 5, 2023: Due to North Carolina’s holiday reporting cadence, aggregate case data will contain 14 days’ worth of data instead of the customary 7 days. As a result, case metrics will appear higher than expected in the January 5, 2023, weekly release. COVID-19 Community Transmission metrics may be overestimated and should be interpreted with caution.

    January 12, 2023: Due to data processing delays, Mississippi’s aggregate case data will be reported as 0. As a result, case metrics will appear lower than expected in the January 12, 2023, weekly release. COVID-19 Community Transmission metrics may be underestimated and should be interpreted with caution. 

    January 13, 2023: Aggregate case data released for Los Angeles County, California for the week of December 22nd, 2022, and December 29th, 2022, have been corrected for a data processing error.

    January 19, 2023: Due to a reporting cadence issue, Mississippi’s aggregate case data will be calculated based on 14 days’ worth of data instead of the customary 7 days in the January 19, 2023, weekly release. Therefore, COVID-19 Community Transmission metrics may be overestimated and should be interpreted with caution.

    January 26, 2023: Due to a reporting backlog of historic COVID-19 cases, case rates for two Michigan counties

  13. W

    CD140 - Population Usually Resident in the State (Number) by County of...

    • cloud.csiss.gmu.edu
    json-stat, px
    Updated Jun 20, 2019
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    Ireland (2019). CD140 - Population Usually Resident in the State (Number) by County of Birth, CensusYear, Sex and City of Enumeration [Dataset]. https://cloud.csiss.gmu.edu/uddi/dataset/ation-usually-resident-in-the-state-number-by-county-of-birth-censusyear-sex-and-city-of-enumer
    Explore at:
    px, json-statAvailable download formats
    Dataset updated
    Jun 20, 2019
    Dataset provided by
    Ireland
    License

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

    Description

    Population Usually Resident in the State (Number) by County of Birth, CensusYear, Sex and City of Enumeration

    View data using web pages

    Download .px file (Software required)

  14. o

    20 Richest Counties in Ohio

    • ohio-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). 20 Richest Counties in Ohio [Dataset]. https://www.ohio-demographics.com/counties_by_population
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    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.ohio-demographics.com/terms_and_conditionshttps://www.ohio-demographics.com/terms_and_conditions

    Area covered
    Ohio
    Description

    A dataset listing Ohio counties by population for 2024.

  15. d

    Number of Reported Malaria Cases by County— United States, 2016

    • catalog.data.gov
    • data.virginia.gov
    • +3more
    Updated Jun 28, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). Number of Reported Malaria Cases by County— United States, 2016 [Dataset]. https://catalog.data.gov/dataset/number-of-reported-malaria-cases-by-county-united-states-2016-81b56
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    Dataset updated
    Jun 28, 2025
    Dataset provided by
    Centers for Disease Control and Prevention
    Area covered
    United States
    Description

    This dataset contains deidentified data from the National Malaria Surveillance System on the number of malaria cases reported in the United States in 2016, by county. Only counties reporting five or more cases are included in this dataset.

  16. T

    Number of Private for All Industries in Forest County, WI

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Apr 27, 2020
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    TRADING ECONOMICS (2020). Number of Private for All Industries in Forest County, WI [Dataset]. https://tradingeconomics.com/united-states/number-of-private-establishments-for-all-industries-in-forest-county-wi-fed-data.html
    Explore at:
    csv, xml, json, excelAvailable download formats
    Dataset updated
    Apr 27, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Forest County, Wisconsin
    Description

    Number of Private for All Industries in Forest County, WI was 271.00000 Establishments in October of 2024, according to the United States Federal Reserve. Historically, Number of Private for All Industries in Forest County, WI reached a record high of 300.00000 in July of 2003 and a record low of 230.00000 in January of 1990. Trading Economics provides the current actual value, an historical data chart and related indicators for Number of Private for All Industries in Forest County, WI - last updated from the United States Federal Reserve on July of 2025.

  17. TIGER/Line Shapefile, 2022, Nation, U.S., County And Equivalent Entities

    • datasets.ai
    • catalog.data.gov
    23, 55, 57
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    U.S. Census Bureau, Department of Commerce, TIGER/Line Shapefile, 2022, Nation, U.S., County And Equivalent Entities [Dataset]. https://datasets.ai/datasets/tiger-line-shapefile-2022-nation-u-s-county-and-equivalent-entities
    Explore at:
    55, 23, 57Available download formats
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    U.S. Census Bureau, Department of Commerce
    Area covered
    United States
    Description

    The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. 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, 2022, as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

  18. F

    Number of Private Establishments for All Industries in Palm Beach County, FL...

    • fred.stlouisfed.org
    json
    Updated Jun 4, 2025
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    (2025). Number of Private Establishments for All Industries in Palm Beach County, FL [Dataset]. https://fred.stlouisfed.org/series/ENU1209920510
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 4, 2025
    License

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

    Area covered
    Palm Beach County, Florida
    Description

    Graph and download economic data for Number of Private Establishments for All Industries in Palm Beach County, FL (ENU1209920510) from Q1 1990 to Q4 2024 about Palm Beach County, FL; Miami; establishments; private industries; FL; private; industry; and USA.

  19. a

    Washington Counties (no water) / washco area

    • hub.arcgis.com
    • gis-kingcounty.opendata.arcgis.com
    Updated Sep 23, 2005
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    King County (2005). Washington Counties (no water) / washco area [Dataset]. https://hub.arcgis.com/datasets/d2be2d35055448afbb902a0f81a71033
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    Dataset updated
    Sep 23, 2005
    Dataset authored and provided by
    King County
    Area covered
    Description

    Political county boundaries for Washington state. Also as KINGCO for King County only.

  20. TIGER 2015 Counties

    • mapdirect-fdep.opendata.arcgis.com
    • hub.arcgis.com
    Updated Jan 1, 2015
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    Florida Department of Environmental Protection (2015). TIGER 2015 Counties [Dataset]. https://mapdirect-fdep.opendata.arcgis.com/datasets/tiger-2015-counties
    Explore at:
    Dataset updated
    Jan 1, 2015
    Dataset authored and provided by
    Florida Department of Environmental Protectionhttp://www.floridadep.gov/
    Area covered
    Description

    The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. 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 as of January 1, 2015, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS). Please contact GIS.Librarian@floridadep.gov for more information.

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Close
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(2024). Counties - United States of America [Dataset]. https://public.opendatasoft.com/explore/dataset/georef-united-states-of-america-county/

Counties - United States of America

Explore at:
11 scholarly articles cite this dataset (View in Google Scholar)
excel, json, geojson, csvAvailable download formats
Dataset updated
Jun 6, 2024
License

https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain

Area covered
United States
Description

This dataset is part of the Geographical repository maintained by Opendatasoft. This dataset contains data for counties and equivalent entities in United States of America. 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.Processors and tools are using this data. Enhancements Add ISO 3166-3 codes. Simplify geometries to provide better performance across the services. Add administrative hierarchy.

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