This statistic shows the 25 largest counties in the United States in 2022, by population. In 2022, about 9.72 million people were estimated to be living in Los Angeles County, California.

Additional information on urbanization in the United States

Urbanization is defined as the process by which cities grow or by which societies become more urban. Rural to urban migration in the United States, and around the world, is often undertaken in the search for employment or to enjoy greater access to services such as healthcare. The largest cities in the United States are steadily growing. Given their size, incremental increases yield considerable numerical gains as seen by New York increasing by 69,777 people in 2011, the most of any city. However in terms of percentage growth, smaller cities outside the main centers are growing the fastest, such as Georgetown city and Leander city in Texas.

Urbanization has increased slowly in the United States, rising from 80.77 percent of the population living in urban areas in 2010 to 82.66 percent in 2020. In 2018, the United States ranked 14th in a ranking of countries based on their degree of urbanization. Unlike fully urbanized countries such as Singapore and Hong Kong, the United States maintains a sizeable agricultural industry. Although technological developments have reduced demands for rural labor, labor in the industry and supporting services are still required.

A dataset listing Florida counties by population for 2024.

Monaco led the ranking for countries with the highest population density in 2024, with nearly 26,000 residents per square kilometer. The Special Administrative Region of Macao came in second, followed by Singapore. The world’s second smallest country Monaco is the world’s second-smallest country, with an area of about two square kilometers and a population of only around 40,000. It is a constitutional monarchy located by the Mediterranean Sea, and while Monaco is not part of the European Union, it does participate in some EU policies. The country is perhaps most famous for the Monte Carlo casino and for hosting the Monaco Grand Prix, the world's most prestigious Formula One race. The global population Globally, the population density per square kilometer is about 60 inhabitants, and Asia is the most densely populated region in the world. The global population is increasing rapidly, so population density is only expected to increase. In 1950, for example, the global population stood at about 2.54 billion people, and it reached over eight billion during 2023.

Urban and regional planners rely on Average Household Size as a foundational indicator for many of their models, calculations, and plans. Average household size (also known as "people per household") is a reflection of many dynamics at play, for example:Age of the population, as many older people tend to live in smaller households (one-person or two-person households)Housing prices in the area, proximity to colleges and universities, and how likely people are to live with roommatesFamily norms and traditions (e.g., multigenerational families are more common in some areas and with some population groups)This feature layer contains the Average Household Size and Population Density for states, counties, and tracts. Data from U.S. Census Bureau's 2014-2018 American Community Survey's 5-year estimates, Tables B25010 and B01001. Population Density was calculated based on the total population and area of land fields, which both came from the U.S. Census Bureau. See the field description for the formula used.This layer is symbolized to show the average household size. Population density, as well as average household size breakdown by housing tenure is presented in the pop-up. Click the Data tab -> Fields list to see all available attributes and their definitions.

This map shows population density of the United States. Areas in darker magenta have much higher population per square mile than areas in orange or yellow. Data is from the U.S. Census Bureau’s 2020 Census Demographic and Housing Characteristics. The map's layers contain total population counts by sex, age, and race groups for Nation, State, County, Census Tract, and Block Group in the United States and Puerto Rico. From the Census:"Population density allows for broad comparison of settlement intensity across geographic areas. In the U.S., population density is typically expressed as the number of people per square mile of land area. The U.S. value is calculated by dividing the total U.S. population (316 million in 2013) by the total U.S. land area (3.5 million square miles).When comparing population density values for different geographic areas, then, it is helpful to keep in mind that the values are most useful for small areas, such as neighborhoods. For larger areas (especially at the state or country scale), overall population density values are less likely to provide a meaningful measure of the density levels at which people actually live, but can be useful for comparing settlement intensity across geographies of similar scale." SourceAbout the dataYou can use this map as is and you can also modify it to use other attributes included in its layers. This map's layers contain total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, State, County, Census Tract, Block Group boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, State, County, Census Tract, Block GroupNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This map is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

This layer presents population density data by county for states bordering the U.S. Gulf, sourced from the U.S. Census Bureau’s 2020 Census Demographic and Housing Characteristics. Population density is displayed as the number of people per square kilometer.Broadly speaking, population density indicates how many people would inhabit one square kilometer if the population were evenly distributed across the area. However, population distribution is uneven. People tend to cluster in urban areas, while those in rural regions are spread out over a much more sparsely populated landscape.Population density is a crucial metric for understanding and managing human population dynamics and their effects on society and the environment. It helps assess various environmental challenges, including urban sprawl, pollution, habitat loss, and resource depletion. Coastal areas frequently experience high population density due to urbanization, influencing land use, housing, and infrastructure development. This density can also stimulate tourism and recreation, necessitating careful planning for facilities, transportation, and environmental protection. Additionally, coastal regions are more susceptible to natural disasters such as hurricanes and flooding, making population density data essential for developing effective evacuation plans and emergency services.Data: U.S. Census BureauDocumentation: U.S. Census BureauThis is a component of the Gulf Data Atlas (V2.0) for the Socioeconomic Conditions topic area.

The 1998 Dress Rehearsal was conducted as a prelude to the United States Census of Population and Housing, 2000, in the following locations: (1) Columbia, South Carolina, and surrounding areas, including the town of Irmo and the counties of Chester, Chesterfield, Darlington, Fairfield, Kershaw, Lancaster, Lee, Marlboro, Newberry, Richland, and Union, (2) Sacramento, California, and (3) Menominee County, Wisconsin, including the Menominee American Indian Reservation. This collection contains map files showing various levels of geography (in the form of Census Tract Outline Maps, Voting District/State Legislative District Outline Maps, and County Block Maps), TIGER/Line digital files, and Corner Point files for the Census 2000 Dress Rehearsal sites. The Corner Point data files contain the bounding latitude and longitude coordinates for each individual map sheet of the 1998 Dress Rehearsal Public Law (P.L.) 94-171 map products. These files include a sheet identifier, minimum and maximum longitude, minimum and maximum latitude, and the map scale (integer value) for each map sheet. The latitude and longitude coordinates are in decimal degrees and expressed as integer values with six implied decimal places. There is a separate Corner Point File for each of the three map types: County Block Map, Census Tract Outline Map, and Voting District/State Legislative District Outline Map. Each of the three map file types is provided in two formats: Portable Document Format (PDF), for viewing, and Hewlett-Packard Graphics Language (HP-GL) format, for plotting. The County Block Maps show the greatest detail and the most complete set of geographic information of all the maps. These large-scale maps depict the smallest geographic entities for which the Census Bureau presents data -- the census blocks -- by displaying the features that delineate them and the numbers that identify them. These maps show the boundaries, names, and codes for American Indian/Alaska Native areas, county subdivisions, places, census tracts, and, for this series, the geographic entities that the states delineated in Phase 2, Voting District Project, of the Redistricting Data Program. The HP-GL version of the County Block Maps is broken down into index maps and map sheets. The map sheets cover a small area, and the index maps are composed of multiple map sheets, showing the entire area. The intent of the County Block Map series is to provide a map for each county on the smallest possible number of map sheets at the maximum practical scale, dependent on the area size of the county and the density of the block pattern. The latter affects the display of block numbers and feature identifiers. The Census Tract Outline Maps show the boundaries and numbers of census tracts, and name the features underlying the boundaries. These maps also show the boundaries and names of counties, county subdivisions, and places. They identify census tracts in relation to governmental unit boundaries. The mapping unit is the county. These large-format maps are produced to support the P.L. 94-171 program and all other 1998 Dress Rehearsal data tabulations. The Voting District/State Legislative District Outline Maps show the boundaries and codes for voting districts as delineated by the states in Phase 2, Voting District Project, of the Redistricting Data Program. The features underlying the voting district boundaries are shown, as well as the names of these features. Additionally, for states that submit the information, these maps show the boundaries and codes for state legislative districts and their underlying features. These maps also show the boundaries of and names of American Indian/Alaska Native areas, counties, county subdivisions, and places. The scale of the district maps is optimized to keep the number of map sheets for each area to a minimum, but the scale and number of map sheets will vary by the area size of the county and the voting districts and state legislative districts delineated by the states. The Census 2000 Dress Rehearsal TIGER/Line Files consist of line segments representing physical features and governmental and statistical boundaries. The files contain information distributed over a series of record types for the spatial objects of a county. These TIGER/Line Files are an extract of selected geographic and cartographic information from the Census TIGER (Topological

This map shows the population density and total population in the United States in 2010. This is shown by state, county, tract, and block group. The color shows the population per square mile (population density), while the size of each feature shows the total population living there. This is a valuable way to represent population by understanding the quantity and density of the people living there. Areas with high population density are more tightly packed, while low population density means the population is more spread out.The map shows this pattern for states, counties, tracts, and block groups. There is increasing geographic detail as you zoom in, and only one geography is configured to show at any time. The data source is the US Census Bureau, and the vintage is 2010. The original service and data metadata can be found here.

This layer shows Population. This is shown by county boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.
This layer is symbolized to show the point by Population Density and size of the point by Total Population. The size of the symbol represents the total count of housing units. Population Density was calculated based on the total population and area of land fields, which both came from the U.S. Census Bureau. Formula used for Calculating the Pop Density (B01001_001E/GEO_LAND_AREA_SQ_KM). To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2015-2019ACS Table(s): B01001, B09020Data downloaded from: Census Bureau's API for American Community Survey Date of API call: February 10, 2021National Figures: data.census.gov The United States Census Bureau's American Community Survey (ACS): About the SurveyGeography & ACSTechnical Documentation News & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes.
All of these are rendered in this dataset as null (blank) values.

A dataset listing Ohio counties by population for 2024.

About this dataset

Context

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

Key observations

The largest age group in Ohio County, WV was for the group of age 60 to 64 years years with a population of 3,329 (7.94%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Ohio County, WV was the 80 to 84 years years with a population of 1,145 (2.73%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

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

Age groups:

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

VITAL SIGNS INDICATOR Population (LU1)

FULL MEASURE NAME Population estimates

LAST UPDATED October 2019

DESCRIPTION Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region.

DATA SOURCES U.S Census Bureau: Decennial Census No link available (1960-1990) http://factfinder.census.gov (2000-2010)

California Department of Finance: Population and Housing Estimates Table E-6: County Population Estimates (1961-1969) Table E-4: Population Estimates for Counties and State (1971-1989) Table E-8: Historical Population and Housing Estimates (2001-2018) Table E-5: Population and Housing Estimates (2011-2019) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

U.S. Census Bureau: Decennial Census - via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University Population Estimates (1970 - 2010) http://www.s4.brown.edu/us2010/index.htm

U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2011-2017) http://factfinder.census.gov

U.S. Census Bureau: Intercensal Estimates Estimates of the Intercensal Population of Counties (1970-1979) Intercensal Estimates of the Resident Population (1980-1989) Population Estimates (1990-1999) Annual Estimates of the Population (2000-2009) Annual Estimates of the Population (2010-2017) No link available (1970-1989) http://www.census.gov/popest/data/metro/totals/1990s/tables/MA-99-03b.txt http://www.census.gov/popest/data/historical/2000s/vintage_2009/metro.html https://www.census.gov/data/datasets/time-series/demo/popest/2010s-total-metro-and-micro-statistical-areas.html

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) All legal boundaries and names for Census geography (metropolitan statistical area, county, city, and tract) are as of January 1, 2010, released beginning November 30, 2010, by the U.S. Census Bureau. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of August 2019. For more information on PDA designation see http://gis.abag.ca.gov/website/PDAShowcase/.

Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970 -2010) and the American Community Survey (2008-2012 5-year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.

Population estimates for Bay Area PDAs are from the decennial Census (1970 - 2010) and the American Community Survey (2006-2010 5 year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Population estimates for PDAs are derived from Census population counts at the tract level for 1970-1990 and at the block group level for 2000-2017. Population from either tracts or block groups are allocated to a PDA using an area ratio. For example, if a quarter of a Census block group lies with in a PDA, a quarter of its population will be allocated to that PDA. Tract-to-PDA and block group-to-PDA area ratios are calculated using gross acres. Estimates of population density for PDAs use gross acres as the denominator.

Annual population estimates for metropolitan areas outside the Bay Area are from the Census and are benchmarked to each decennial Census. The annual estimates in the 1990s were not updated to match the 2000 benchmark.

The following is a list of cities and towns by geographical area: Big Three: San Jose, San Francisco, Oakland Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside Inland, Delta and Coastal: American Canyon, Antioch, Benicia, Brentwood, Calistoga, Clayton, Cloverdale, Concord, Cotati, Danville, Dixon, Dublin, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Lafayette, Livermore, Martinez, Moraga, Morgan Hill, Napa, Novato, Oakley, Orinda, Petaluma, Pittsburg, Pleasant Hill, Pleasanton, Rio Vista, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Sonoma, St. Helena, Suisun City, Vacaville, Walnut Creek, Windsor, Yountville Unincorporated: all unincorporated towns

About this dataset

Context

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

Key observations

The largest age group in Lake County, FL was for the group of age 65-69 years with a population of 28,218 (7.52%), according to the 2021 American Community Survey. At the same time, the smallest age group in Lake County, FL was the 85+ years with a population of 11,403 (3.04%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

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

Age groups:

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

A dataset listing New York counties by population for 2024.

Most of the United States (U.S.) population live together in a few densely populated areas. While this is a well known fact, visual explanations of this characteristic can be quite striking. These four maps illustrate in different ways where we live, and how we actually inhabit so little of our country's space.Map 1 shows the coastal shoreline counties of the U.S., which are the counties that are directly adjacent to an open ocean, a major estuary, or the Great Lakes. According to 2014 Census data, 39.1 percent of the U.S. population lived in those counties, often within miles of the coast.Map 2 highlights the largest and smallest counties in the U.S. Roughly fifty percent of the U.S. population lives in the country's 144 largest counties, while the roughly other 50 percent lives in 2,998 counties.Map 3 compares America's two largest counties (Los Angeles and Downtown Chicago) with the 14 smallest states.Map 4 compares the population of these two counties with 1,437 of the country's smallest counties. Nearly five percent of America's population lives in the counties covering downtown Los Angeles and downtown Chicago, which is the same proportion as those that live in the country's 1,437 smallest counties.Source: Ana Swanson, Washington Post Wonkblog. September 3, 2015

Link to landing page referenced by identifier. Service Protocol: Link to landing page referenced by identifier. Link Function: information-- dc:identifier.

A dataset listing Georgia counties by population for 2024.

About this dataset

Context

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

Key observations

The largest age group in Harris County, GA was for the group of age 55 to 59 years years with a population of 2,749 (7.74%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Harris County, GA was the 85 years and over years with a population of 486 (1.37%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

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

Age groups:

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

Each year, the Forecasting and Trends Office (FTO) publishes population estimates and future year projections. The population estimates can be used for a variety of planning studies including statewide and regional transportation plan updates, subarea and corridor studies, and funding allocations for various planning agencies.The 2020 population estimates reported are based on the US Census Bureau 2020 Decennial Census. The 2021 population estimates are based on the population estimates developed by the Bureau of Economic and Business Research (BEBR) at the University of Florida. BEBR uses the decennial census count for April 1, 2020, as the starting point for state-level projections. More information is available from BEBR here.This dataset contains boundaries for all 2010 Census Urban Clusters (UCs) in the State of Florida with 2020 census population and 2021 population estimates. All legal boundaries and names in this dataset are from the US Census Bureau’s TIGER/Line Files (2021).BEBR provides 2021 population estimates for counties in Florida. However, UC boundaries may not coincide with the jurisdictional boundaries of counties and UCs often spread into several counties. To estimate the population for an UC, first the ratio of the subject UC that is contained within a county (or sub-area) to the area of the entire county was determined. That ratio was multiplied by the estimated county population to obtain the population for that sub-area. The population for the entire UC is the sum of all sub-area populations estimated from the counties they are located within.For the 2010 Census, urban areas comprised a “densely settled core of census tracts and/or census blocks that meet minimum population density requirements, along with adjacent territory containing non-residential urban land uses as well as territory with low population density included to link outlying densely settled territory with the densely settled core.” In 2010, the US Census Bureau identified two types of urban areas—Urbanized Areas (UAs) and UCs. UCs have a population of at least 2,500 and less than 50,000 people. Note: Century, FL--AL Urban Cluster is located in two states: Florida (Escambia County) and Alabama (Escambia County). 2021 population of Escambia County, AL used for this estimation is from the US Census annual population estimates (2020-2021). All other Urban Clusters are located entirely within the state of Florida. Please see the Data Dictionary for more information on data fields. Data Sources:US Census Bureau 2020 Decennial CensusUS Census Bureau’s TIGER/Line Files (2021)Bureau of Economic and Business Research (BEBR) – Florida Estimates of Population 2021 Data Coverage: StatewideData Time Period: 2020 – 2021 Date of Publication: July 2022 Point of Contact:Dana Reiding, ManagerForecasting and Trends OfficeFlorida Department of TransportationDana.Reiding@dot.state.fl.us605 Suwannee Street, Tallahassee, Florida 32399850-414-4719

This dataset contains population densities of 15 study watersheds in Gwinnett County, Georgia from 2000 to 2020. Population densities were determined for 2000, 2010, and 2020 from the decadal U.S. Census and for 2012 and 2017 from the American Community Survey 5-year estimates of 2010-14 and 2015¬-19 block group data, respectively. Population density within each watershed was determined by clipping the census block group data by the watershed boundaries and area-weighting the block group population density data within each watershed. Census block group data is the smallest geographic unit for which the census provides data.