14 datasets found
  1. Population density in the U.S. 2023, by state

    • statista.com
    Updated Dec 3, 2024
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    Statista (2024). Population density in the U.S. 2023, by state [Dataset]. https://www.statista.com/statistics/183588/population-density-in-the-federal-states-of-the-us/
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    Dataset updated
    Dec 3, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, Washington, D.C. had the highest population density in the United States, with 11,130.69 people per square mile. As a whole, there were about 94.83 residents per square mile in the U.S., and Alaska was the state with the lowest population density, with 1.29 residents per square mile. The problem of population density Simply put, population density is the population of a country divided by the area of the country. While this can be an interesting measure of how many people live in a country and how large the country is, it does not account for the degree of urbanization, or the share of people who live in urban centers. For example, Russia is the largest country in the world and has a comparatively low population, so its population density is very low. However, much of the country is uninhabited, so cities in Russia are much more densely populated than the rest of the country. Urbanization in the United States While the United States is not very densely populated compared to other countries, its population density has increased significantly over the past few decades. The degree of urbanization has also increased, and well over half of the population lives in urban centers.

  2. Population density of the United States 2019

    • statista.com
    Updated Dec 7, 2024
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    Statista (2024). Population density of the United States 2019 [Dataset]. https://www.statista.com/statistics/183475/united-states-population-density/
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    Dataset updated
    Dec 7, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    This graph shows the population density of the United States of America from 1790 to 2019. In 2019, the population density was approximately 92.9 residents per square mile of land area. Population density in the United States Population density has been tracked for over two hundred years in the United States. Over the last two centuries, the number of people living in the United States per square mile has grown from 4.5 in 1790 to 87.4 in 2010. After examining the data in detail, it becomes clear that a major population increase started around 1870. Population density was roughly 11 at the time and has doubled in the last century. Since then, population density grew by about 16 percent each decade. Population density doubled in 1900, and grew in total by around 800 percent until 2010.

    The population density of the United States varies from state to state. The most densely populated state is New Jersey, with 1,208 people per square mile living there. Rhode Island is the second most densely populated state, with slightly over 1,000 inhabitants per square mile. A number of New England states follow at the top of the ranking, making the northeastern region of the United States the most densely populated region of the country.

    The least populated U.S. state is the vast territory of Alaska. Only 1.3 inhabitants per square mile reside in the largest state of the U.S.

    Compared to other countries around the world, the United States does not rank within the top 50, in terms of population density. Most of the leading countries and territories are city states. However, the U.S. is one of the most populous countries in the world, with a total population of over 327 million inhabitants, as of 2018.

  3. a

    ARC Population Forecasts series13

    • opendata.atlantaregional.com
    Updated Jun 10, 2015
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    Georgia Association of Regional Commissions (2015). ARC Population Forecasts series13 [Dataset]. https://opendata.atlantaregional.com/datasets/55778658bd3846eb8a4e93c3e4c327cd
    Explore at:
    Dataset updated
    Jun 10, 2015
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission from ARC's Regional Plan Update to show population forecasts by census tract for the Atlanta region.Attributes:GEOID10 = The entire Federal Information Processing Series (FIPS) code for this geography. FIPS codes were formerly known as Federal Information Processing Standards codes, until the National Institute of Standards and Technology (NIST) announced its decision in 2005 to remove geographic entity codes from its oversight. The Census Bureau continues to maintain and issue codes for geographic entities covered under FIPS oversight, albeit with a revised meaning for the FIPS acronym. Geographic entities covered under FIPS include states, counties, congressional districts, core based statistical areas, places, county subdivisions, subminor civil divisions, consolidated cities, and all types of American Indian, Alaska Native, and Native Hawaiian areas. FIPS codes are assigned alphabetically according to the name of the geographic entity and may change to maintain alphabetic sort when new entities are created or names change. FIPS codes for specific geographic entity types are usually unique within the next highest level of geographic entity with which a nesting relationship exists. For example, FIPS state, congressional district, and core based statistical area codes are unique within nation; FIPS county, place, county subdivision, and subminor civil division codes are unique within state. The codes for American Indian, Alaska Native, and Native Hawaiian areas also are unique within state; those areas in multiple states will have different codes for each state.NAME10 = Census tract numberPLNG_REGIO = Planning regionPercent_BA_or_Higher = Percentage of the population that has a bachelor's degree or higherMedian_household_income = Median household incomeSquare_Miles = Total area in square milesHouseholds, 2015 = Total number of households forecasted for 2015Population, 2015 = Total population forecated for 2015Households, 2020 = Total number of households forecasted for 2020Population, 2020 = Total population forecasted for 2020Households, 2025 = Total number of households forecasted for 2025Population, 2025 = Total population forecasted for 2025Households 2030 = Total number of households forecasted for 2030Population, 2030 = Total population forecasted for 2030Households, 2035 = Total number of households forecasted for 2035Population, 2035 = Total population forecasted for 2035Households, 2040 = Total number of households forecasted for 2040Population, 2040 = Total population forecasted for 2040Population Change, 2015-2040 = Forecasted population change between 2015 and 2040Household Change, 2015-2040 = Forecasted change in the number of households between 2015 and 2040Population Change per Square Mile, 2015-2040 = Forecasted population change per square mile between 2015 and 2040Population Change per Square Mile 2000-2010 = Actual change in population per square mile between 2000 and 2010Shape.STArea() = Total area in square feetSource: Atlanta Regional CommissionDate: 2015For additional information, please visit the Atlanta Regional Commission at www.atlantaregional.com

  4. a

    CENSUS 2020 PL94171 MONTANA RESERVATION

    • hub.arcgis.com
    • ceic-mtdoc.opendata.arcgis.com
    Updated Aug 23, 2021
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    Montana Department of Commerce (2021). CENSUS 2020 PL94171 MONTANA RESERVATION [Dataset]. https://hub.arcgis.com/datasets/4d78337ba485494a81a9aa99c621a6e0
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    Dataset updated
    Aug 23, 2021
    Dataset authored and provided by
    Montana Department of Commerce
    Area covered
    Description

    Population and Housing data for American Indian Reservations within the State of Montana was compiled from the PL 94-171 Redistricting Summary files released by the U.S. Census Bureau for the 2020 Decennial Census. This data set was created by the Montana Department of Commerce for use by the citizens of Montana and the general public. TIGER shapefiles were joined to the tabular summary file data to create this data set. A subset of variables from the release were selected for this dataset. A description of each variable and calculations are provided here.

    VINTAGE - Decennial Census vintage year - Calculation

    SUMLEV - Geography summary level - Calculation

    GEOID - Geography ID - Calculation

    NAME - Geography Name - Calculation

    AREALAND - Area of land in square meters - Calculation

    AREAWATR - Area of water in square meters - Calculation

    INTPTLAT - Geography point latitude - Calculation

    INTPTLON - Geography point longitude - Calculation

    POPTOT - Population Total - Calculation P0010001

    POPPCAP - Population per square mile - Calculation P0010001 / (AREALAND / 2589988.110336)

    POPWH - Population White alone - Calculation P0010003

    POPBL - Population Black alone - Calculation P0010004

    POPAI - Population American Indian or Alaska Native alone - Calculation P0010005

    POPAS - Population Asian alone - Calculation P0010006

    POPNH - Population Native Hawaiian or Pacific Islander alone - Calculation P0010007

    POPOT - Population Some other Race alone - Calculation P0010008

    POP2MO - Population 2 or more races - Calculation P0010009

    POPWHPCT - Population White alone percent - Calculation P0010003 / P0010001 * 100

    POPBLPCT - Population Black alone percent - Calculation P0010004 / P0010001 * 100

    POPAIPCT - Population American Indian or Alaska Native alone percent - Calculation P0010005 / P0010001 * 100

    POPASPCT - Population Asian alone percent - Calculation P0010006 / P0010001 * 100

    POPNHPCT - Population Native Hawaiian or Pacific Islander alone percent - Calculation P0010007 / P0010001 * 100

    POPOTPCT - Population Some other Race alone percent - Calculation P0010008 / P0010001 * 100

    POP2MOPCT - Population 2 or more races percent - Calculation P0010009 / P0010001 * 100

    POPWHC - Population White alone or in combination - Calculation P0010003+ P00100011+ P00100012+ P00100013+ P00100014+ P00100015+ P0010027+ P0010028+ P0010029+ P00100030+ P00100031+ P00100032+ P00100033+ P00100034+ P00100035+ P00100036+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100054+ P00100055+ P00100056+ P00100057+ P00100064+ P00100065+ P00100066+ P00100067+ P00100068+ P00100071

    POPBLC - Population Black alone or in combination - Calculation P0010004+ P00100011+ P00100016+ P00100017+ P00100018+ P00100019+ P0010027+ P0010028+ P0010029+ P00100030+ P00100037+ P00100038+ P00100039+ P00100040+ P00100041+ P00100042+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100058+ P00100059+ P00100060+ P00100061+ P00100064+ P00100065+ P00100066+ P00100067+ P00100069+ P00100071

    POPAIC - Population American Indian or Alaska Native alone or in combination - Calculation P0010005+ P00100012+ P00100016+ P0010020+ P0010021+ P0010022+ P0010027+ P00100031+ P00100032+ P00100033+ P00100037+ P00100038+ P00100039+ P00100043+ P00100044+ P00100045+ P00100048+ P00100049+ P00100050+ P00100054+ P00100055+ P00100056+ P00100058+ P00100059+ P00100060+ P00100062+ P00100064+ P00100065+ P00100066+ P00100068+ P00100069+ P00100071

    POPASC - Population Asian alone or in combination - Calculation P0010006+ P00100013+ P00100017+ P0010020+ P0010023+ P0010024+ P0010028+ P00100031+ P00100034+ P00100035+ P00100037+ P00100040+ P00100041+ P00100043+ P00100044+ P00100046+ P00100048+ P00100051+ P00100052+ P00100054+ P00100055+ P00100057+ P00100058+ P00100059+ P00100061+ P00100062+ P00100064+ P00100065+ P00100067+ P00100068+ P00100069+ P00100071

    POPNHC - Population Native Hawaiian or Pacific Islander alone or in combination - Calculation P0010007+ P00100014+ P00100018+ P0010021+ P0010023+ P0010025+ P0010029+ P00100032+ P00100034+ P00100036+ P00100038+ P00100040+ P00100042+ P00100043+ P00100045+ P00100046+ P00100049+ P00100051+ P00100053+ P00100054+ P00100056+ P00100057+ P00100058+ P00100060+ P00100061+ P00100062+ P00100064+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071

    POPOTC - Population Some Other Race alone or in combination - Calculation P0010008+ P00100015+ P00100019+ P0010022+ P0010024+ P0010025+ P00100030+ P00100033+ P00100035+ P00100036+ P00100039+ P00100041+ P00100042+ P00100044+ P00100045+ P00100046+ P00100050+ P00100052+ P00100053+ P00100055+ P00100056+ P00100057+ P00100059+ P00100060+ P00100061+ P00100062+ P00100065+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071

    POPWHCPCT - Population White alone or in combination percent - Calculation (P0010003+ P00100011+ P00100012+ P00100013+ P00100014+ P00100015+ P0010027+ P0010028+ P0010029+ P00100030+ P00100031+ P00100032+ P00100033+ P00100034+ P00100035+ P00100036+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100054+ P00100055+ P00100056+ P00100057+ P00100064+ P00100065+ P00100066+ P00100067+ P00100068+ P00100071)/ P0010001 * 100

    POPBLCPCT - Population Black alone or in combination percent - Calculation (P0010004+ P00100011+ P00100016+ P00100017+ P00100018+ P00100019+ P0010027+ P0010028+ P0010029+ P00100030+ P00100037+ P00100038+ P00100039+ P00100040+ P00100041+ P00100042+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100058+ P00100059+ P00100060+ P00100061+ P00100064+ P00100065+ P00100066+ P00100067+ P00100069+ P00100071)/ P0010001 * 100

    POPAICPCT - Population American Indian or Alaska Native alone or in combination percent - Calculation (P0010005+ P00100012+ P00100016+ P0010020+ P0010021+ P0010022+ P0010027+ P00100031+ P00100032+ P00100033+ P00100037+ P00100038+ P00100039+ P00100043+ P00100044+ P00100045+ P00100048+ P00100049+ P00100050+ P00100054+ P00100055+ P00100056+ P00100058+ P00100059+ P00100060+ P00100062+ P00100064+ P00100065+ P00100066+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPASCPCT - Population Asian alone or in combination percent - Calculation (P0010006+ P00100013+ P00100017+ P0010020+ P0010023+ P0010024+ P0010028+ P00100031+ P00100034+ P00100035+ P00100037+ P00100040+ P00100041+ P00100043+ P00100044+ P00100046+ P00100048+ P00100051+ P00100052+ P00100054+ P00100055+ P00100057+ P00100058+ P00100059+ P00100061+ P00100062+ P00100064+ P00100065+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPNHCPCT - Population Native Hawaiian or Pacific Islander alone or in combination percent - Calculation (P0010007+ P00100014+ P00100018+ P0010021+ P0010023+ P0010025+ P0010029+ P00100032+ P00100034+ P00100036+ P00100038+ P00100040+ P00100042+ P00100043+ P00100045+ P00100046+ P00100049+ P00100051+ P00100053+ P00100054+ P00100056+ P00100057+ P00100058+ P00100060+ P00100061+ P00100062+ P00100064+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPOTCPCT - Population Some Other Race alone or in combination percent - Calculation (P0010008+ P00100015+ P00100019+ P0010022+ P0010024+ P0010025+ P00100030+ P00100033+ P00100035+ P00100036+ P00100039+ P00100041+ P00100042+ P00100044+ P00100045+ P00100046+ P00100050+ P00100052+ P00100053+ P00100055+ P00100056+ P00100057+ P00100059+ P00100060+ P00100061+ P00100062+ P00100065+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPHSP - Population Hispanic - Calculation P0020002

    POPNHSP - Population Non-Hispanic - Calculation P0020003

    POPHSPPCT - Population Hispanic percent - Calculation P0020002 / P0010001 * 100

    POPNHSPPCT - Population Non-Hispanic percent - Calculation P0020003 / P0010001 * 100

    POP18OV - Population 18 years and over - Calculation P0030001

    POP18OVPCT - Population 18 years and over percent - Calculation P0030001 / P0010001 * 100

    HUTOT - Housing Units Total - Calculation H0010001

    HUOCC - Housing Units Occupied - Calculation H0010002

    HUVAC - Housing Units Vacant - Calculation H0010003

    HUOCCPCT - Housing Units Occupied percent - Calculation H0010002 / H0010001 * 100

    HUVACPCT - Housing Units Vacant percent - Calculation H0010003 / H0010001 * 100

    POPGQ - Population Group Quarters - Calculation P0050001

    POPGQIN - Population Group Quarters - Institutionalized - Calculation P0050002

    POPGQNI - Population Group Quarters - Non-Institutionalized - Calculation P0050007

    POPGQPCT - Population Group Quarters percent - Calculation P0050001 / P0010001 * 100

    POPGQINPCT - Population Group Quarters - Institutionalized percent - Calculation P0050002 / P0010001 * 100

    POPGQNIPCT - Population Group Quarters - Non-Institutionalized percent - Calculation P0050007 / P0010001 * 100

    POPTOT2010 - Population Total 2010 - Calculation

    POPCHG - Population Change from 2010 to 2020 - Calculation

    POPCHGPCT - Population Percent Change from 2010 to 2020 - Calculation

  5. a

    Children Under 5

    • opendata.atlantaregional.com
    Updated Jun 10, 2015
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    Georgia Association of Regional Commissions (2015). Children Under 5 [Dataset]. https://opendata.atlantaregional.com/datasets/GARC::children-under-5/about
    Explore at:
    Dataset updated
    Jun 10, 2015
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission from the United States Census Bureau's 2000 Decennial Census to show the count and percentage of children under the age of 5 by census tract within the Atlanta Region.Attributes:GEOID10 = The entire Federal Information Processing Series (FIPS) census tract code. FIPS codes were formerly known as Federal Information Processing Standards codes, until the National Institute of Standards and Technology (NIST) announced its decision in 2005 to remove geographic entity codes from its oversight. The Census Bureau continues to maintain and issue codes for geographic entities covered under FIPS oversight, albeit with a revised meaning for the FIPS acronym. Geographic entities covered under FIPS include states, counties, congressional districts, core based statistical areas, places, county subdivisions, subminor civil divisions, consolidated cities, and all types of American Indian, Alaska Native, and Native Hawaiian areas. FIPS codes are assigned alphabetically according to the name of the geographic entity and may change to maintain alphabetic sort when new entities are created or names change. FIPS codes for specific geographic entity types are usually unique within the next highest level of geographic entity with which a nesting relationship exists. For example, FIPS state, congressional district, and core based statistical area codes are unique within nation; FIPS county, place, county subdivision, and subminor civil division codes are unique within state. The codes for American Indian, Alaska Native, and Native Hawaiian areas also are unique within state; those areas in multiple states will have different codes for each state.NAME10 = Census tract numberPLNG_REGIO = Planning regionPercent_BA_or_Higher = Percentage of people who have a bachelor's degree or higherMedian_household_income = Median household incomeUnder_5_population_2010 = The population under 5 years of age in 2010Population Change per square mile 2000-2010 = Population Change per square mile 2000-2010 Percent Population under 5 in 2010 = The percentage of the population under 5 years of age in 2010Shape.STArea() = Total area in square feetSource: U.S. Census Bureau, Atlanta Regional CommissionDate: 2010For additional information, please visit the Atlanta Regional Commission at www.atlantaregional.com

  6. a

    CENSUS 2020 PL94171 MONTANA TRACT

    • hub.arcgis.com
    • ceic-mtdoc.opendata.arcgis.com
    Updated Aug 23, 2021
    + more versions
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    Montana Department of Commerce (2021). CENSUS 2020 PL94171 MONTANA TRACT [Dataset]. https://hub.arcgis.com/maps/mtdoc::census-2020-pl94171-montana-tract
    Explore at:
    Dataset updated
    Aug 23, 2021
    Dataset authored and provided by
    Montana Department of Commerce
    Area covered
    Description

    Population and Housing data for Census Tracts within the State of Montana was compiled from the PL 94-171 Redistricting Summary files released by the U.S. Census Bureau for the 2020 Decennial Census. This data set was created by the Montana Department of Commerce for use by the citizens of Montana and the general public. TIGER shapefiles were joined to the tabular summary file data to create this data set. A subset of variables from the release were selected for this dataset. A description of each variable and calculations are provided here.

    VINTAGE - Decennial Census vintage year - Calculation

    SUMLEV - Geography summary level - Calculation

    GEOID - Geography ID - Calculation

    NAME - Geography Name - Calculation

    AREALAND - Area of land in square meters - Calculation

    AREAWATR - Area of water in square meters - Calculation

    INTPTLAT - Geography point latitude - Calculation

    INTPTLON - Geography point longitude - Calculation

    POPTOT - Population Total - Calculation P0010001

    POPPCAP - Population per square mile - Calculation P0010001 / (AREALAND / 2589988.110336)

    POPWH - Population White alone - Calculation P0010003

    POPBL - Population Black alone - Calculation P0010004

    POPAI - Population American Indian or Alaska Native alone - Calculation P0010005

    POPAS - Population Asian alone - Calculation P0010006

    POPNH - Population Native Hawaiian or Pacific Islander alone - Calculation P0010007

    POPOT - Population Some other Race alone - Calculation P0010008

    POP2MO - Population 2 or more races - Calculation P0010009

    POPWHPCT - Population White alone percent - Calculation P0010003 / P0010001 * 100

    POPBLPCT - Population Black alone percent - Calculation P0010004 / P0010001 * 100

    POPAIPCT - Population American Indian or Alaska Native alone percent - Calculation P0010005 / P0010001 * 100

    POPASPCT - Population Asian alone percent - Calculation P0010006 / P0010001 * 100

    POPNHPCT - Population Native Hawaiian or Pacific Islander alone percent - Calculation P0010007 / P0010001 * 100

    POPOTPCT - Population Some other Race alone percent - Calculation P0010008 / P0010001 * 100

    POP2MOPCT - Population 2 or more races percent - Calculation P0010009 / P0010001 * 100

    POPWHC - Population White alone or in combination - Calculation P0010003+ P00100011+ P00100012+ P00100013+ P00100014+ P00100015+ P0010027+ P0010028+ P0010029+ P00100030+ P00100031+ P00100032+ P00100033+ P00100034+ P00100035+ P00100036+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100054+ P00100055+ P00100056+ P00100057+ P00100064+ P00100065+ P00100066+ P00100067+ P00100068+ P00100071

    POPBLC - Population Black alone or in combination - Calculation P0010004+ P00100011+ P00100016+ P00100017+ P00100018+ P00100019+ P0010027+ P0010028+ P0010029+ P00100030+ P00100037+ P00100038+ P00100039+ P00100040+ P00100041+ P00100042+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100058+ P00100059+ P00100060+ P00100061+ P00100064+ P00100065+ P00100066+ P00100067+ P00100069+ P00100071

    POPAIC - Population American Indian or Alaska Native alone or in combination - Calculation P0010005+ P00100012+ P00100016+ P0010020+ P0010021+ P0010022+ P0010027+ P00100031+ P00100032+ P00100033+ P00100037+ P00100038+ P00100039+ P00100043+ P00100044+ P00100045+ P00100048+ P00100049+ P00100050+ P00100054+ P00100055+ P00100056+ P00100058+ P00100059+ P00100060+ P00100062+ P00100064+ P00100065+ P00100066+ P00100068+ P00100069+ P00100071

    POPASC - Population Asian alone or in combination - Calculation P0010006+ P00100013+ P00100017+ P0010020+ P0010023+ P0010024+ P0010028+ P00100031+ P00100034+ P00100035+ P00100037+ P00100040+ P00100041+ P00100043+ P00100044+ P00100046+ P00100048+ P00100051+ P00100052+ P00100054+ P00100055+ P00100057+ P00100058+ P00100059+ P00100061+ P00100062+ P00100064+ P00100065+ P00100067+ P00100068+ P00100069+ P00100071

    POPNHC - Population Native Hawaiian or Pacific Islander alone or in combination - Calculation P0010007+ P00100014+ P00100018+ P0010021+ P0010023+ P0010025+ P0010029+ P00100032+ P00100034+ P00100036+ P00100038+ P00100040+ P00100042+ P00100043+ P00100045+ P00100046+ P00100049+ P00100051+ P00100053+ P00100054+ P00100056+ P00100057+ P00100058+ P00100060+ P00100061+ P00100062+ P00100064+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071

    POPOTC - Population Some Other Race alone or in combination - Calculation P0010008+ P00100015+ P00100019+ P0010022+ P0010024+ P0010025+ P00100030+ P00100033+ P00100035+ P00100036+ P00100039+ P00100041+ P00100042+ P00100044+ P00100045+ P00100046+ P00100050+ P00100052+ P00100053+ P00100055+ P00100056+ P00100057+ P00100059+ P00100060+ P00100061+ P00100062+ P00100065+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071

    POPWHCPCT - Population White alone or in combination percent - Calculation (P0010003+ P00100011+ P00100012+ P00100013+ P00100014+ P00100015+ P0010027+ P0010028+ P0010029+ P00100030+ P00100031+ P00100032+ P00100033+ P00100034+ P00100035+ P00100036+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100054+ P00100055+ P00100056+ P00100057+ P00100064+ P00100065+ P00100066+ P00100067+ P00100068+ P00100071)/ P0010001 * 100

    POPBLCPCT - Population Black alone or in combination percent - Calculation (P0010004+ P00100011+ P00100016+ P00100017+ P00100018+ P00100019+ P0010027+ P0010028+ P0010029+ P00100030+ P00100037+ P00100038+ P00100039+ P00100040+ P00100041+ P00100042+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100058+ P00100059+ P00100060+ P00100061+ P00100064+ P00100065+ P00100066+ P00100067+ P00100069+ P00100071)/ P0010001 * 100

    POPAICPCT - Population American Indian or Alaska Native alone or in combination percent - Calculation (P0010005+ P00100012+ P00100016+ P0010020+ P0010021+ P0010022+ P0010027+ P00100031+ P00100032+ P00100033+ P00100037+ P00100038+ P00100039+ P00100043+ P00100044+ P00100045+ P00100048+ P00100049+ P00100050+ P00100054+ P00100055+ P00100056+ P00100058+ P00100059+ P00100060+ P00100062+ P00100064+ P00100065+ P00100066+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPASCPCT - Population Asian alone or in combination percent - Calculation (P0010006+ P00100013+ P00100017+ P0010020+ P0010023+ P0010024+ P0010028+ P00100031+ P00100034+ P00100035+ P00100037+ P00100040+ P00100041+ P00100043+ P00100044+ P00100046+ P00100048+ P00100051+ P00100052+ P00100054+ P00100055+ P00100057+ P00100058+ P00100059+ P00100061+ P00100062+ P00100064+ P00100065+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPNHCPCT - Population Native Hawaiian or Pacific Islander alone or in combination percent - Calculation (P0010007+ P00100014+ P00100018+ P0010021+ P0010023+ P0010025+ P0010029+ P00100032+ P00100034+ P00100036+ P00100038+ P00100040+ P00100042+ P00100043+ P00100045+ P00100046+ P00100049+ P00100051+ P00100053+ P00100054+ P00100056+ P00100057+ P00100058+ P00100060+ P00100061+ P00100062+ P00100064+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPOTCPCT - Population Some Other Race alone or in combination percent - Calculation (P0010008+ P00100015+ P00100019+ P0010022+ P0010024+ P0010025+ P00100030+ P00100033+ P00100035+ P00100036+ P00100039+ P00100041+ P00100042+ P00100044+ P00100045+ P00100046+ P00100050+ P00100052+ P00100053+ P00100055+ P00100056+ P00100057+ P00100059+ P00100060+ P00100061+ P00100062+ P00100065+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPHSP - Population Hispanic - Calculation P0020002

    POPNHSP - Population Non-Hispanic - Calculation P0020003

    POPHSPPCT - Population Hispanic percent - Calculation P0020002 / P0010001 * 100

    POPNHSPPCT - Population Non-Hispanic percent - Calculation P0020003 / P0010001 * 100

    POP18OV - Population 18 years and over - Calculation P0030001

    POP18OVPCT - Population 18 years and over percent - Calculation P0030001 / P0010001 * 100

    HUTOT - Housing Units Total - Calculation H0010001

    HUOCC - Housing Units Occupied - Calculation H0010002

    HUVAC - Housing Units Vacant - Calculation H0010003

    HUOCCPCT - Housing Units Occupied percent - Calculation H0010002 / H0010001 * 100

    HUVACPCT - Housing Units Vacant percent - Calculation H0010003 / H0010001 * 100

    POPGQ - Population Group Quarters - Calculation P0050001

    POPGQIN - Population Group Quarters - Institutionalized - Calculation P0050002

    POPGQNI - Population Group Quarters - Non-Institutionalized - Calculation P0050007

    POPGQPCT - Population Group Quarters percent - Calculation P0050001 / P0010001 * 100

    POPGQINPCT - Population Group Quarters - Institutionalized percent - Calculation P0050002 / P0010001 * 100

    POPGQNIPCT - Population Group Quarters - Non-Institutionalized percent - Calculation P0050007 / P0010001 * 100

    POPTOT2010 - Population Total 2010 - Calculation

    POPCHG - Population Change from 2010 to 2020 - Calculation

    POPCHGPCT - Population Percent Change from 2010 to 2020 - Calculation

  7. a

    Census 2010 Blocks Georgia

    • opendata.atlantaregional.com
    Updated Oct 30, 2014
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    Georgia Association of Regional Commissions (2014). Census 2010 Blocks Georgia [Dataset]. https://opendata.atlantaregional.com/datasets/1cdf1cb3d551419299f7d1cc319bf2d3
    Explore at:
    Dataset updated
    Oct 30, 2014
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission using U.S. Census Bureau TIGER/Line files. The polygon features in Census_2010_Blocks_GA are subsets of Census_Blockgroups and Census_Tracts.Attributes:STATEFP10 = The Federal Information Processing Series (FIPS) state code. FIPS codes were formerly known as Federal Information Processing Standards codes, until the National Institute of Standards and Technology (NIST) announced its decision in 2005 to remove geographic entity codes from its oversight. The Census Bureau continues to maintain and issue codes for geographic entities covered under FIPS oversight, albeit with a revised meaning for the FIPS acronym. Geographic entities covered under FIPS include states, counties, congressional districts, core based statistical areas, places, county subdivisions, subminor civil divisions, consolidated cities, and all types of American Indian, Alaska Native, and Native Hawaiian areas. FIPS codes are assigned alphabetically according to the name of the geographic entity and may change to maintain alphabetic sort when new entities are created or names change. FIPS codes for specific geographic entity types are usually unique within the next highest level of geographic entity with which a nesting relationship exists. For example, FIPS state, congressional district, and core based statistical area codes are unique within nation; FIPS county, place, county subdivision, and subminor civil division codes are unique within state. The codes for American Indian, Alaska Native, and Native Hawaiian areas also are unique within state; those areas in multiple states will have different codes for each state.COUNTYFP10 = The Federal Information Processing Series (FIPS) county code. TRACTCE10 = Census Tract Codes and Numbers—Census tracts are identified by an up to four-digit integer number and may have an optional two-digit suffix; for example 1457.02 or 23. The census tract codes consist of six digits with an implied decimal between the fourth and fifth digit corresponding to the basic census tract number but with leading zeroes and trailing zeroes for census tracts without a suffix. The tract number examples above would have codes of 145702 and 002300, respectively.BLOCKCE10 = Census block number - Census blocks are numbered uniquely with a four-digit census block number from 0000 to 9999 within census tract, which nest within state and county. The first digit of the census block number identifies the block group. Block numbers beginning with a zero (in Block Group 0) are only associated with water-only areas.GEOID10 = A concatenation of STATEFP10, COUNTYFP10, TRACTCE10, and BLOCKCE10, which produces the entire FIPS code for this geography.NAME10 = Block nameMTFCC10 = MAF/TIGER feature class codeUR10 = Census urban/rural indicatorUACE10 = Census urbanized area codesFUNCSTAT10 = Functional statusALAND10 = Land area in square metersAWATER10 = Water area in square metersINTPTLAT10 = Latitude of the centroid (center of this geography)INTPLON10 = Longitude of the centroid (center of this geography)STFID = The entire FIPS code of this geographyCOUNTY_NM = County namePLNG_REGIO = Planning regionSUMLEV = Summary level of census geography (code)NAME = Block namePLACE = Census place codeSTATE = The state FIPS codeCOUNTY = The county FIPS codeTRACT = The tract FIPS codeBLOCK = The block FIPS codetotpop10 = Total populationoner_10 = One race populationwhite_or10 = White, one race populationbl_or10 = Black, one race populationaian_or10 = American Indian and Alaska Native, one race populationasia_or10 = Asian, one race populationnhpi_or10 = Native Hawaiian and Other Pacific Islander, one race populationsomoth_or1 = Some other, one race populationtwoplusr10 = Two-plus races populationtotpop101 = Total populationhisp_lat10 = Total Hispanic/Latino populationnonhisp10 = Total non-Hispanic/Latino populationnh_or10 = Non-Hispanic/Latino, one race populationnhw_or10 = Non-Hispanic/Latino White, one race populationnhbl_or10 = Non-Hispanic/Latino Black, one race populationnhai_or10 = Non-Hispanic/Latino American Indian and Alaskan Native, one race populationnhas_or10 = Non-Hispanic/Latino Asian, one race populationnhhp_or10 = Non-Hispanic/Latino Native Hawaiian and Other Pacific Islander, one race populationnhot_or10 = Non-Hispanic/Latino Other, one race populationnh_twor10 = Non-Hispanic/Latino, two or more races populationtothu10 = Total housing unitstotoccu_10 = Total occupied housing unitstotvach_10 = Total vacant housing unitsAcresLand = Land area in acresAcresWater = Water area in acresAcresTotal = Total area in acresSqMiLand = Land area in square milesDensPPSqMi = Density: Population per square mile of landShape.STArea() = Total area in square feetSource: U.S. Census Bureau, Atlanta Regional CommissionDate: 2010For additional information, please visit the Atlanta Regional Commission at www.atlantaregional.com

  8. Data from: Lost on the frontline, and lost in the data: COVID-19 deaths...

    • figshare.com
    zip
    Updated Jul 22, 2022
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    Loraine Escobedo (2022). Lost on the frontline, and lost in the data: COVID-19 deaths among Filipinx healthcare workers in the United States [Dataset]. http://doi.org/10.6084/m9.figshare.20353368.v1
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jul 22, 2022
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Loraine Escobedo
    License

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

    Area covered
    United States
    Description

    To estimate county of residence of Filipinx healthcare workers who died of COVID-19, we retrieved data from the Kanlungan website during the month of December 2020.22 In deciding who to include on the website, the AF3IRM team that established the Kanlungan website set two standards in data collection. First, the team found at least one source explicitly stating that the fallen healthcare worker was of Philippine ancestry; this was mostly media articles or obituaries sharing the life stories of the deceased. In a few cases, the confirmation came directly from the deceased healthcare worker's family member who submitted a tribute. Second, the team required a minimum of two sources to identify and announce fallen healthcare workers. We retrieved 86 US tributes from Kanlungan, but only 81 of them had information on county of residence. In total, 45 US counties with at least one reported tribute to a Filipinx healthcare worker who died of COVID-19 were identified for analysis and will hereafter be referred to as “Kanlungan counties.” Mortality data by county, race, and ethnicity came from the National Center for Health Statistics (NCHS).24 Updated weekly, this dataset is based on vital statistics data for use in conducting public health surveillance in near real time to provide provisional mortality estimates based on data received and processed by a specified cutoff date, before data are finalized and publicly released.25 We used the data released on December 30, 2020, which included provisional COVID-19 death counts from February 1, 2020 to December 26, 2020—during the height of the pandemic and prior to COVID-19 vaccines being available—for counties with at least 100 total COVID-19 deaths. During this time period, 501 counties (15.9% of the total 3,142 counties in all 50 states and Washington DC)26 met this criterion. Data on COVID-19 deaths were available for six major racial/ethnic groups: Non-Hispanic White, Non-Hispanic Black, Non-Hispanic Native Hawaiian or Other Pacific Islander, Non-Hispanic American Indian or Alaska Native, Non-Hispanic Asian (hereafter referred to as Asian American), and Hispanic. People with more than one race, and those with unknown race were included in the “Other” category. NCHS suppressed county-level data by race and ethnicity if death counts are less than 10. In total, 133 US counties reported COVID-19 mortality data for Asian Americans. These data were used to calculate the percentage of all COVID-19 decedents in the county who were Asian American. We used data from the 2018 American Community Survey (ACS) five-year estimates, downloaded from the Integrated Public Use Microdata Series (IPUMS) to create county-level population demographic variables.27 IPUMS is publicly available, and the database integrates samples using ACS data from 2000 to the present using a high degree of precision.27 We applied survey weights to calculate the following variables at the county-level: median age among Asian Americans, average income to poverty ratio among Asian Americans, the percentage of the county population that is Filipinx, and the percentage of healthcare workers in the county who are Filipinx. Healthcare workers encompassed all healthcare practitioners, technical occupations, and healthcare service occupations, including nurse practitioners, physicians, surgeons, dentists, physical therapists, home health aides, personal care aides, and other medical technicians and healthcare support workers. County-level data were available for 107 out of the 133 counties (80.5%) that had NCHS data on the distribution of COVID-19 deaths among Asian Americans, and 96 counties (72.2%) with Asian American healthcare workforce data. The ACS 2018 five-year estimates were also the source of county-level percentage of the Asian American population (alone or in combination) who are Filipinx.8 In addition, the ACS provided county-level population counts26 to calculate population density (people per 1,000 people per square mile), estimated by dividing the total population by the county area, then dividing by 1,000 people. The county area was calculated in ArcGIS 10.7.1 using the county boundary shapefile and projected to Albers equal area conic (for counties in the US contiguous states), Hawai’i Albers Equal Area Conic (for Hawai’i counties), and Alaska Albers Equal Area Conic (for Alaska counties).20

  9. a

    Race/Ethnicity (by Neighborhood Planning Unit) 2017

    • opendata.atlantaregional.com
    Updated Jun 21, 2019
    + more versions
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    Georgia Association of Regional Commissions (2019). Race/Ethnicity (by Neighborhood Planning Unit) 2017 [Dataset]. https://opendata.atlantaregional.com/datasets/b2e62b485b2346fab495136d574e5cec
    Explore at:
    Dataset updated
    Jun 21, 2019
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show population by race/ethnicity and change data by Neighborhood Planning Unit in the Atlanta region. The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website. Naming conventions: Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)Suffixes:NoneChange over two periods_eEstimate from most recent ACS_mMargin of Error from most recent ACS_00Decennial 2000 Attributes: SumLevelSummary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)GEOIDCensus tract Federal Information Processing Series (FIPS) code NAMEName of geographic unitPlanning_RegionPlanning region designation for ARC purposesAcresTotal area within the tract (in acres)SqMiTotal area within the tract (in square miles)CountyCounty identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)CountyNameCounty NameTotPop_e# Total population, 2017TotPop_m# Total population, 2017 (MOE)Hisp_e# Hispanic or Latino (of any race), 2017Hisp_m# Hispanic or Latino (of any race), 2017 (MOE)pHisp_e% Hispanic or Latino (of any race), 2017pHisp_m% Hispanic or Latino (of any race), 2017 (MOE)Not_Hisp_e# Not Hispanic or Latino, 2017Not_Hisp_m# Not Hispanic or Latino, 2017 (MOE)pNot_Hisp_e% Not Hispanic or Latino, 2017pNot_Hisp_m% Not Hispanic or Latino, 2017 (MOE)NHWhite_e# Not Hispanic, White alone, 2017NHWhite_m# Not Hispanic, White alone, 2017 (MOE)pNHWhite_e% Not Hispanic, White alone, 2017pNHWhite_m% Not Hispanic, White alone, 2017 (MOE)NHBlack_e# Not Hispanic, Black or African American alone, 2017NHBlack_m# Not Hispanic, Black or African American alone, 2017 (MOE)pNHBlack_e% Not Hispanic, Black or African American alone, 2017pNHBlack_m% Not Hispanic, Black or African American alone, 2017 (MOE)NH_AmInd_e# Not Hispanic, American Indian and Alaska Native alone, 2017NH_AmInd_m# Not Hispanic, American Indian and Alaska Native alone, 2017 (MOE)pNH_AmInd_e% Not Hispanic, American Indian and Alaska Native alone, 2017pNH_AmInd_m% Not Hispanic, American Indian and Alaska Native alone, 2017 (MOE)NH_Asian_e# Not Hispanic, Asian alone, 2017NH_Asian_m# Not Hispanic, Asian alone, 2017 (MOE)pNH_Asian_e% Not Hispanic, Asian alone, 2017pNH_Asian_m% Not Hispanic, Asian alone, 2017 (MOE)NH_PacIsl_e# Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017NH_PacIsl_m# Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017 (MOE)pNH_PacIsl_e% Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017pNH_PacIsl_m% Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017 (MOE)NH_OthRace_e# Not Hispanic, some other race alone, 2017NH_OthRace_m# Not Hispanic, some other race alone, 2017 (MOE)pNH_OthRace_e% Not Hispanic, some other race alone, 2017pNH_OthRace_m% Not Hispanic, some other race alone, 2017 (MOE)NH_TwoRace_e# Not Hispanic, two or more races, 2017NH_TwoRace_m# Not Hispanic, two or more races, 2017 (MOE)pNH_TwoRace_e% Not Hispanic, two or more races, 2017pNH_TwoRace_m% Not Hispanic, two or more races, 2017 (MOE)NH_AsianPI_e# Non-Hispanic Asian or Pacific Islander, 2017NH_AsianPI_m# Non-Hispanic Asian or Pacific Islander, 2017 (MOE)pNH_AsianPI_e% Non-Hispanic Asian or Pacific Islander, 2017pNH_AsianPI_m% Non-Hispanic Asian or Pacific Islander, 2017 (MOE)NH_Other_e# Non-Hispanic other (Native American, other one race, two or more races), 2017NH_Other_m# Non-Hispanic other (Native American, other one race, two or more races), 2017 (MOE)pNH_Other_e% Non-Hispanic other (Native American, other one race, two or more races), 2017pNH_Other_m% Non-Hispanic other (Native American, other one race, two or more races), 2017 (MOE)last_edited_dateLast date the feature was edited by ARC Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2013-2017 For additional information, please visit the Census ACS website.

  10. a

    Race/Ethnicity (by Strong, Prosperous, And Resilient Communities Challenge)...

    • opendata.atlantaregional.com
    Updated Jun 21, 2019
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    Georgia Association of Regional Commissions (2019). Race/Ethnicity (by Strong, Prosperous, And Resilient Communities Challenge) 2017 [Dataset]. https://opendata.atlantaregional.com/datasets/race-ethnicity-by-strong-prosperous-and-resilient-communities-challenge-2017/api
    Explore at:
    Dataset updated
    Jun 21, 2019
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show population by race/ethnicity and change data by Strong, Prosperous, And Resilient Communities Challenge in the Atlanta region. The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website. Naming conventions: Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)Suffixes:NoneChange over two periods_eEstimate from most recent ACS_mMargin of Error from most recent ACS_00Decennial 2000 Attributes: SumLevelSummary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)GEOIDCensus tract Federal Information Processing Series (FIPS) code NAMEName of geographic unitPlanning_RegionPlanning region designation for ARC purposesAcresTotal area within the tract (in acres)SqMiTotal area within the tract (in square miles)CountyCounty identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)CountyNameCounty NameTotPop_e# Total population, 2017TotPop_m# Total population, 2017 (MOE)Hisp_e# Hispanic or Latino (of any race), 2017Hisp_m# Hispanic or Latino (of any race), 2017 (MOE)pHisp_e% Hispanic or Latino (of any race), 2017pHisp_m% Hispanic or Latino (of any race), 2017 (MOE)Not_Hisp_e# Not Hispanic or Latino, 2017Not_Hisp_m# Not Hispanic or Latino, 2017 (MOE)pNot_Hisp_e% Not Hispanic or Latino, 2017pNot_Hisp_m% Not Hispanic or Latino, 2017 (MOE)NHWhite_e# Not Hispanic, White alone, 2017NHWhite_m# Not Hispanic, White alone, 2017 (MOE)pNHWhite_e% Not Hispanic, White alone, 2017pNHWhite_m% Not Hispanic, White alone, 2017 (MOE)NHBlack_e# Not Hispanic, Black or African American alone, 2017NHBlack_m# Not Hispanic, Black or African American alone, 2017 (MOE)pNHBlack_e% Not Hispanic, Black or African American alone, 2017pNHBlack_m% Not Hispanic, Black or African American alone, 2017 (MOE)NH_AmInd_e# Not Hispanic, American Indian and Alaska Native alone, 2017NH_AmInd_m# Not Hispanic, American Indian and Alaska Native alone, 2017 (MOE)pNH_AmInd_e% Not Hispanic, American Indian and Alaska Native alone, 2017pNH_AmInd_m% Not Hispanic, American Indian and Alaska Native alone, 2017 (MOE)NH_Asian_e# Not Hispanic, Asian alone, 2017NH_Asian_m# Not Hispanic, Asian alone, 2017 (MOE)pNH_Asian_e% Not Hispanic, Asian alone, 2017pNH_Asian_m% Not Hispanic, Asian alone, 2017 (MOE)NH_PacIsl_e# Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017NH_PacIsl_m# Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017 (MOE)pNH_PacIsl_e% Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017pNH_PacIsl_m% Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017 (MOE)NH_OthRace_e# Not Hispanic, some other race alone, 2017NH_OthRace_m# Not Hispanic, some other race alone, 2017 (MOE)pNH_OthRace_e% Not Hispanic, some other race alone, 2017pNH_OthRace_m% Not Hispanic, some other race alone, 2017 (MOE)NH_TwoRace_e# Not Hispanic, two or more races, 2017NH_TwoRace_m# Not Hispanic, two or more races, 2017 (MOE)pNH_TwoRace_e% Not Hispanic, two or more races, 2017pNH_TwoRace_m% Not Hispanic, two or more races, 2017 (MOE)NH_AsianPI_e# Non-Hispanic Asian or Pacific Islander, 2017NH_AsianPI_m# Non-Hispanic Asian or Pacific Islander, 2017 (MOE)pNH_AsianPI_e% Non-Hispanic Asian or Pacific Islander, 2017pNH_AsianPI_m% Non-Hispanic Asian or Pacific Islander, 2017 (MOE)NH_Other_e# Non-Hispanic other (Native American, other one race, two or more races), 2017NH_Other_m# Non-Hispanic other (Native American, other one race, two or more races), 2017 (MOE)pNH_Other_e% Non-Hispanic other (Native American, other one race, two or more races), 2017pNH_Other_m% Non-Hispanic other (Native American, other one race, two or more races), 2017 (MOE)last_edited_dateLast date the feature was edited by ARC Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2013-2017 For additional information, please visit the Census ACS website.

  11. a

    CENSUS 2020 PL94171 MONTANA STATE SENATE DISTRICT

    • hub.arcgis.com
    Updated Aug 23, 2021
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    Montana Department of Commerce (2021). CENSUS 2020 PL94171 MONTANA STATE SENATE DISTRICT [Dataset]. https://hub.arcgis.com/maps/mtdoc::census-2020-pl94171-montana-state-senate-district/about
    Explore at:
    Dataset updated
    Aug 23, 2021
    Dataset authored and provided by
    Montana Department of Commerce
    Area covered
    Description

    Population and Housing data for State Legislature Senate Districts within the State of Montana was compiled from the PL 94-171 Redistricting Summary files released by the U.S. Census Bureau for the 2020 Decennial Census.

    This data set was created by the Montana Department of Commerce for use by the citizens of Montana and the general public. TIGER shapefiles were joined to the tabular summary file data to create this data set. A subset of variables from the release were selected for this dataset. A description of each variable and calculations are provided here.

    VINTAGE - Decennial Census vintage year - Calculation

    SUMLEV - Geography summary level - Calculation

    GEOID - Geography ID - Calculation

    NAME - Geography Name - Calculation

    AREALAND - Area of land in square meters - Calculation

    AREAWATR - Area of water in square meters - Calculation

    INTPTLAT - Geography point latitude - Calculation

    INTPTLON - Geography point longitude - Calculation

    POPTOT - Population Total - Calculation P0010001

    POPPCAP - Population per square mile - Calculation P0010001 / (AREALAND / 2589988.110336)

    POPWH - Population White alone - Calculation P0010003

    POPBL - Population Black alone - Calculation P0010004

    POPAI - Population American Indian or Alaska Native alone - Calculation P0010005

    POPAS - Population Asian alone - Calculation P0010006

    POPNH - Population Native Hawaiian or Pacific Islander alone - Calculation P0010007

    POPOT - Population Some other Race alone - Calculation P0010008

    POP2MO - Population 2 or more races - Calculation P0010009

    POPWHPCT - Population White alone percent - Calculation P0010003 / P0010001 * 100

    POPBLPCT - Population Black alone percent - Calculation P0010004 / P0010001 * 100

    POPAIPCT - Population American Indian or Alaska Native alone percent - Calculation P0010005 / P0010001 * 100

    POPASPCT - Population Asian alone percent - Calculation P0010006 / P0010001 * 100

    POPNHPCT - Population Native Hawaiian or Pacific Islander alone percent - Calculation P0010007 / P0010001 * 100

    POPOTPCT - Population Some other Race alone percent - Calculation P0010008 / P0010001 * 100

    POP2MOPCT - Population 2 or more races percent - Calculation P0010009 / P0010001 * 100

    POPWHC - Population White alone or in combination - Calculation P0010003+ P00100011+ P00100012+ P00100013+ P00100014+ P00100015+ P0010027+ P0010028+ P0010029+ P00100030+ P00100031+ P00100032+ P00100033+ P00100034+ P00100035+ P00100036+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100054+ P00100055+ P00100056+ P00100057+ P00100064+ P00100065+ P00100066+ P00100067+ P00100068+ P00100071

    POPBLC - Population Black alone or in combination - Calculation P0010004+ P00100011+ P00100016+ P00100017+ P00100018+ P00100019+ P0010027+ P0010028+ P0010029+ P00100030+ P00100037+ P00100038+ P00100039+ P00100040+ P00100041+ P00100042+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100058+ P00100059+ P00100060+ P00100061+ P00100064+ P00100065+ P00100066+ P00100067+ P00100069+ P00100071

    POPAIC - Population American Indian or Alaska Native alone or in combination - Calculation P0010005+ P00100012+ P00100016+ P0010020+ P0010021+ P0010022+ P0010027+ P00100031+ P00100032+ P00100033+ P00100037+ P00100038+ P00100039+ P00100043+ P00100044+ P00100045+ P00100048+ P00100049+ P00100050+ P00100054+ P00100055+ P00100056+ P00100058+ P00100059+ P00100060+ P00100062+ P00100064+ P00100065+ P00100066+ P00100068+ P00100069+ P00100071

    POPASC - Population Asian alone or in combination - Calculation P0010006+ P00100013+ P00100017+ P0010020+ P0010023+ P0010024+ P0010028+ P00100031+ P00100034+ P00100035+ P00100037+ P00100040+ P00100041+ P00100043+ P00100044+ P00100046+ P00100048+ P00100051+ P00100052+ P00100054+ P00100055+ P00100057+ P00100058+ P00100059+ P00100061+ P00100062+ P00100064+ P00100065+ P00100067+ P00100068+ P00100069+ P00100071

    POPNHC - Population Native Hawaiian or Pacific Islander alone or in combination - Calculation P0010007+ P00100014+ P00100018+ P0010021+ P0010023+ P0010025+ P0010029+ P00100032+ P00100034+ P00100036+ P00100038+ P00100040+ P00100042+ P00100043+ P00100045+ P00100046+ P00100049+ P00100051+ P00100053+ P00100054+ P00100056+ P00100057+ P00100058+ P00100060+ P00100061+ P00100062+ P00100064+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071

    POPOTC - Population Some Other Race alone or in combination - Calculation P0010008+ P00100015+ P00100019+ P0010022+ P0010024+ P0010025+ P00100030+ P00100033+ P00100035+ P00100036+ P00100039+ P00100041+ P00100042+ P00100044+ P00100045+ P00100046+ P00100050+ P00100052+ P00100053+ P00100055+ P00100056+ P00100057+ P00100059+ P00100060+ P00100061+ P00100062+ P00100065+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071

    POPWHCPCT - Population White alone or in combination percent - Calculation (P0010003+ P00100011+ P00100012+ P00100013+ P00100014+ P00100015+ P0010027+ P0010028+ P0010029+ P00100030+ P00100031+ P00100032+ P00100033+ P00100034+ P00100035+ P00100036+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100054+ P00100055+ P00100056+ P00100057+ P00100064+ P00100065+ P00100066+ P00100067+ P00100068+ P00100071)/ P0010001 * 100

    POPBLCPCT - Population Black alone or in combination percent - Calculation (P0010004+ P00100011+ P00100016+ P00100017+ P00100018+ P00100019+ P0010027+ P0010028+ P0010029+ P00100030+ P00100037+ P00100038+ P00100039+ P00100040+ P00100041+ P00100042+ P00100048+ P00100049+ P00100050+ P00100051+ P00100052+ P00100053+ P00100058+ P00100059+ P00100060+ P00100061+ P00100064+ P00100065+ P00100066+ P00100067+ P00100069+ P00100071)/ P0010001 * 100

    POPAICPCT - Population American Indian or Alaska Native alone or in combination percent - Calculation (P0010005+ P00100012+ P00100016+ P0010020+ P0010021+ P0010022+ P0010027+ P00100031+ P00100032+ P00100033+ P00100037+ P00100038+ P00100039+ P00100043+ P00100044+ P00100045+ P00100048+ P00100049+ P00100050+ P00100054+ P00100055+ P00100056+ P00100058+ P00100059+ P00100060+ P00100062+ P00100064+ P00100065+ P00100066+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPASCPCT - Population Asian alone or in combination percent - Calculation (P0010006+ P00100013+ P00100017+ P0010020+ P0010023+ P0010024+ P0010028+ P00100031+ P00100034+ P00100035+ P00100037+ P00100040+ P00100041+ P00100043+ P00100044+ P00100046+ P00100048+ P00100051+ P00100052+ P00100054+ P00100055+ P00100057+ P00100058+ P00100059+ P00100061+ P00100062+ P00100064+ P00100065+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPNHCPCT - Population Native Hawaiian or Pacific Islander alone or in combination percent - Calculation (P0010007+ P00100014+ P00100018+ P0010021+ P0010023+ P0010025+ P0010029+ P00100032+ P00100034+ P00100036+ P00100038+ P00100040+ P00100042+ P00100043+ P00100045+ P00100046+ P00100049+ P00100051+ P00100053+ P00100054+ P00100056+ P00100057+ P00100058+ P00100060+ P00100061+ P00100062+ P00100064+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPOTCPCT - Population Some Other Race alone or in combination percent - Calculation (P0010008+ P00100015+ P00100019+ P0010022+ P0010024+ P0010025+ P00100030+ P00100033+ P00100035+ P00100036+ P00100039+ P00100041+ P00100042+ P00100044+ P00100045+ P00100046+ P00100050+ P00100052+ P00100053+ P00100055+ P00100056+ P00100057+ P00100059+ P00100060+ P00100061+ P00100062+ P00100065+ P00100066+ P00100067+ P00100068+ P00100069+ P00100071)/ P0010001 * 100

    POPHSP - Population Hispanic - Calculation P0020002

    POPNHSP - Population Non-Hispanic - Calculation P0020003

    POPHSPPCT - Population Hispanic percent - Calculation P0020002 / P0010001 * 100

    POPNHSPPCT - Population Non-Hispanic percent - Calculation P0020003 / P0010001 * 100

    POP18OV - Population 18 years and over - Calculation P0030001

    POP18OVPCT - Population 18 years and over percent - Calculation P0030001 / P0010001 * 100

    HUTOT - Housing Units Total - Calculation H0010001

    HUOCC - Housing Units Occupied - Calculation H0010002

    HUVAC - Housing Units Vacant - Calculation H0010003

    HUOCCPCT - Housing Units Occupied percent - Calculation H0010002 / H0010001 * 100

    HUVACPCT - Housing Units Vacant percent - Calculation H0010003 / H0010001 * 100

    POPGQ - Population Group Quarters - Calculation P0050001

    POPGQIN - Population Group Quarters - Institutionalized - Calculation P0050002

    POPGQNI - Population Group Quarters - Non-Institutionalized - Calculation P0050007

    POPGQPCT - Population Group Quarters percent - Calculation P0050001 / P0010001 * 100

    POPGQINPCT - Population Group Quarters - Institutionalized percent - Calculation P0050002 / P0010001 * 100

    POPGQNIPCT - Population Group Quarters - Non-Institutionalized percent - Calculation P0050007 / P0010001 * 100

    POPTOT2010 - Population Total 2010 - Calculation

    POPCHG - Population Change from 2010 to 2020 - Calculation

    POPCHGPCT - Population Percent Change from 2010 to 2020 - Calculation

  12. d

    Data from: The swans and geese of Alaska's arctic slope.

    • datadiscoverystudio.org
    • data.wu.ac.at
    Updated May 19, 2018
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    (2018). The swans and geese of Alaska's arctic slope. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/7a87310c369344b6b60fe9c747a391b1/html
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    Dataset updated
    May 19, 2018
    Description

    description: A mid-summer aerial search was made on the 23,000 square miles of waterfowl habitat on Alaska's Arctic slope. Observations included 159 whistling swan (Olor columbianus); 10,278 Canada geese (Branta canadensis); 20,981 black brant (Branta nigricans); 6,730 white-fronted geese (Anser albifrons); and 458 snow geese (Chen hyperborea). A fairly concentrated molting area for geese was found near Cape Ralkett. Expanded population estimates are given. Discussion includes: better census methods, the relation of these birds to areas of greater nesting concentration; possibility for banding and other studies; and the possibility of increasing abundance of snow geese. It is concluded that this large block of low density habitat could be representative of a vast Arctic area of low production that may be of considerable importance to the species involved.; abstract: A mid-summer aerial search was made on the 23,000 square miles of waterfowl habitat on Alaska's Arctic slope. Observations included 159 whistling swan (Olor columbianus); 10,278 Canada geese (Branta canadensis); 20,981 black brant (Branta nigricans); 6,730 white-fronted geese (Anser albifrons); and 458 snow geese (Chen hyperborea). A fairly concentrated molting area for geese was found near Cape Ralkett. Expanded population estimates are given. Discussion includes: better census methods, the relation of these birds to areas of greater nesting concentration; possibility for banding and other studies; and the possibility of increasing abundance of snow geese. It is concluded that this large block of low density habitat could be representative of a vast Arctic area of low production that may be of considerable importance to the species involved.

  13. a

    Race/Ethnicity (by Dekalb Sustainable Neighborhood Initiative) 2017

    • opendata.atlantaregional.com
    Updated Jun 21, 2019
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    Georgia Association of Regional Commissions (2019). Race/Ethnicity (by Dekalb Sustainable Neighborhood Initiative) 2017 [Dataset]. https://opendata.atlantaregional.com/maps/d60f9ebf597a44669f4e1e85ee8c118d
    Explore at:
    Dataset updated
    Jun 21, 2019
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show population by race/ethnicity and change data by Dekalb Sustainable Neighborhood Initiative in the Atlanta region. The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website. Naming conventions: Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)Suffixes:NoneChange over two periods_eEstimate from most recent ACS_mMargin of Error from most recent ACS_00Decennial 2000 Attributes: SumLevelSummary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)GEOIDCensus tract Federal Information Processing Series (FIPS) code NAMEName of geographic unitPlanning_RegionPlanning region designation for ARC purposesAcresTotal area within the tract (in acres)SqMiTotal area within the tract (in square miles)CountyCounty identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)CountyNameCounty NameTotPop_e# Total population, 2017TotPop_m# Total population, 2017 (MOE)Hisp_e# Hispanic or Latino (of any race), 2017Hisp_m# Hispanic or Latino (of any race), 2017 (MOE)pHisp_e% Hispanic or Latino (of any race), 2017pHisp_m% Hispanic or Latino (of any race), 2017 (MOE)Not_Hisp_e# Not Hispanic or Latino, 2017Not_Hisp_m# Not Hispanic or Latino, 2017 (MOE)pNot_Hisp_e% Not Hispanic or Latino, 2017pNot_Hisp_m% Not Hispanic or Latino, 2017 (MOE)NHWhite_e# Not Hispanic, White alone, 2017NHWhite_m# Not Hispanic, White alone, 2017 (MOE)pNHWhite_e% Not Hispanic, White alone, 2017pNHWhite_m% Not Hispanic, White alone, 2017 (MOE)NHBlack_e# Not Hispanic, Black or African American alone, 2017NHBlack_m# Not Hispanic, Black or African American alone, 2017 (MOE)pNHBlack_e% Not Hispanic, Black or African American alone, 2017pNHBlack_m% Not Hispanic, Black or African American alone, 2017 (MOE)NH_AmInd_e# Not Hispanic, American Indian and Alaska Native alone, 2017NH_AmInd_m# Not Hispanic, American Indian and Alaska Native alone, 2017 (MOE)pNH_AmInd_e% Not Hispanic, American Indian and Alaska Native alone, 2017pNH_AmInd_m% Not Hispanic, American Indian and Alaska Native alone, 2017 (MOE)NH_Asian_e# Not Hispanic, Asian alone, 2017NH_Asian_m# Not Hispanic, Asian alone, 2017 (MOE)pNH_Asian_e% Not Hispanic, Asian alone, 2017pNH_Asian_m% Not Hispanic, Asian alone, 2017 (MOE)NH_PacIsl_e# Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017NH_PacIsl_m# Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017 (MOE)pNH_PacIsl_e% Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017pNH_PacIsl_m% Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017 (MOE)NH_OthRace_e# Not Hispanic, some other race alone, 2017NH_OthRace_m# Not Hispanic, some other race alone, 2017 (MOE)pNH_OthRace_e% Not Hispanic, some other race alone, 2017pNH_OthRace_m% Not Hispanic, some other race alone, 2017 (MOE)NH_TwoRace_e# Not Hispanic, two or more races, 2017NH_TwoRace_m# Not Hispanic, two or more races, 2017 (MOE)pNH_TwoRace_e% Not Hispanic, two or more races, 2017pNH_TwoRace_m% Not Hispanic, two or more races, 2017 (MOE)NH_AsianPI_e# Non-Hispanic Asian or Pacific Islander, 2017NH_AsianPI_m# Non-Hispanic Asian or Pacific Islander, 2017 (MOE)pNH_AsianPI_e% Non-Hispanic Asian or Pacific Islander, 2017pNH_AsianPI_m% Non-Hispanic Asian or Pacific Islander, 2017 (MOE)NH_Other_e# Non-Hispanic other (Native American, other one race, two or more races), 2017NH_Other_m# Non-Hispanic other (Native American, other one race, two or more races), 2017 (MOE)pNH_Other_e% Non-Hispanic other (Native American, other one race, two or more races), 2017pNH_Other_m% Non-Hispanic other (Native American, other one race, two or more races), 2017 (MOE)last_edited_dateLast date the feature was edited by ARC Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2013-2017 For additional information, please visit the Census ACS website.

  14. a

    Race/Ethnicity (by Westside Future Fund) 2017

    • opendata.atlantaregional.com
    Updated Jun 21, 2019
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    Georgia Association of Regional Commissions (2019). Race/Ethnicity (by Westside Future Fund) 2017 [Dataset]. https://opendata.atlantaregional.com/datasets/race-ethnicity-by-westside-future-fund-2017/explore?showTable=true
    Explore at:
    Dataset updated
    Jun 21, 2019
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show population by race/ethnicity and change data by Westside Future Fund in the Atlanta region. The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website. Naming conventions: Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)Suffixes:NoneChange over two periods_eEstimate from most recent ACS_mMargin of Error from most recent ACS_00Decennial 2000 Attributes: SumLevelSummary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)GEOIDCensus tract Federal Information Processing Series (FIPS) code NAMEName of geographic unitPlanning_RegionPlanning region designation for ARC purposesAcresTotal area within the tract (in acres)SqMiTotal area within the tract (in square miles)CountyCounty identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)CountyNameCounty NameTotPop_e# Total population, 2017TotPop_m# Total population, 2017 (MOE)Hisp_e# Hispanic or Latino (of any race), 2017Hisp_m# Hispanic or Latino (of any race), 2017 (MOE)pHisp_e% Hispanic or Latino (of any race), 2017pHisp_m% Hispanic or Latino (of any race), 2017 (MOE)Not_Hisp_e# Not Hispanic or Latino, 2017Not_Hisp_m# Not Hispanic or Latino, 2017 (MOE)pNot_Hisp_e% Not Hispanic or Latino, 2017pNot_Hisp_m% Not Hispanic or Latino, 2017 (MOE)NHWhite_e# Not Hispanic, White alone, 2017NHWhite_m# Not Hispanic, White alone, 2017 (MOE)pNHWhite_e% Not Hispanic, White alone, 2017pNHWhite_m% Not Hispanic, White alone, 2017 (MOE)NHBlack_e# Not Hispanic, Black or African American alone, 2017NHBlack_m# Not Hispanic, Black or African American alone, 2017 (MOE)pNHBlack_e% Not Hispanic, Black or African American alone, 2017pNHBlack_m% Not Hispanic, Black or African American alone, 2017 (MOE)NH_AmInd_e# Not Hispanic, American Indian and Alaska Native alone, 2017NH_AmInd_m# Not Hispanic, American Indian and Alaska Native alone, 2017 (MOE)pNH_AmInd_e% Not Hispanic, American Indian and Alaska Native alone, 2017pNH_AmInd_m% Not Hispanic, American Indian and Alaska Native alone, 2017 (MOE)NH_Asian_e# Not Hispanic, Asian alone, 2017NH_Asian_m# Not Hispanic, Asian alone, 2017 (MOE)pNH_Asian_e% Not Hispanic, Asian alone, 2017pNH_Asian_m% Not Hispanic, Asian alone, 2017 (MOE)NH_PacIsl_e# Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017NH_PacIsl_m# Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017 (MOE)pNH_PacIsl_e% Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017pNH_PacIsl_m% Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017 (MOE)NH_OthRace_e# Not Hispanic, some other race alone, 2017NH_OthRace_m# Not Hispanic, some other race alone, 2017 (MOE)pNH_OthRace_e% Not Hispanic, some other race alone, 2017pNH_OthRace_m% Not Hispanic, some other race alone, 2017 (MOE)NH_TwoRace_e# Not Hispanic, two or more races, 2017NH_TwoRace_m# Not Hispanic, two or more races, 2017 (MOE)pNH_TwoRace_e% Not Hispanic, two or more races, 2017pNH_TwoRace_m% Not Hispanic, two or more races, 2017 (MOE)NH_AsianPI_e# Non-Hispanic Asian or Pacific Islander, 2017NH_AsianPI_m# Non-Hispanic Asian or Pacific Islander, 2017 (MOE)pNH_AsianPI_e% Non-Hispanic Asian or Pacific Islander, 2017pNH_AsianPI_m% Non-Hispanic Asian or Pacific Islander, 2017 (MOE)NH_Other_e# Non-Hispanic other (Native American, other one race, two or more races), 2017NH_Other_m# Non-Hispanic other (Native American, other one race, two or more races), 2017 (MOE)pNH_Other_e% Non-Hispanic other (Native American, other one race, two or more races), 2017pNH_Other_m% Non-Hispanic other (Native American, other one race, two or more races), 2017 (MOE)last_edited_dateLast date the feature was edited by ARC Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2013-2017 For additional information, please visit the Census ACS website.

  15. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Statista (2024). Population density in the U.S. 2023, by state [Dataset]. https://www.statista.com/statistics/183588/population-density-in-the-federal-states-of-the-us/
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Population density in the U.S. 2023, by state

Explore at:
29 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Dec 3, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2023
Area covered
United States
Description

In 2023, Washington, D.C. had the highest population density in the United States, with 11,130.69 people per square mile. As a whole, there were about 94.83 residents per square mile in the U.S., and Alaska was the state with the lowest population density, with 1.29 residents per square mile. The problem of population density Simply put, population density is the population of a country divided by the area of the country. While this can be an interesting measure of how many people live in a country and how large the country is, it does not account for the degree of urbanization, or the share of people who live in urban centers. For example, Russia is the largest country in the world and has a comparatively low population, so its population density is very low. However, much of the country is uninhabited, so cities in Russia are much more densely populated than the rest of the country. Urbanization in the United States While the United States is not very densely populated compared to other countries, its population density has increased significantly over the past few decades. The degree of urbanization has also increased, and well over half of the population lives in urban centers.

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