A dataset listing South Carolina counties by population for 2024.

U.S. Census Bureau QuickFacts statistics for South Carolina. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

About this dataset

Context

The dataset tabulates the Greenville County population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Greenville County across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Greenville County was 558,036, a 1.86% increase year-by-year from 2022. Previously, in 2022, Greenville County population was 547,845, an increase of 2.47% compared to a population of 534,648 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Greenville County increased by 176,889. In this period, the peak population was 558,036 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Greenville County is shown in this column.
• Year on Year Change: This column displays the change in Greenville County population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Greenville County Population by Year. You can refer the same here

Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Anderson County, SC (S1701ACS045007) from 2012 to 2023 about Anderson County, SC; Anderson; SC; percent; poverty; 5-year; population; and USA.

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

U.S. Census Bureau QuickFacts statistics for Edgefield County, South Carolina. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

Graph and download economic data for Resident Population in Charleston County, SC (SCCHAR9POP) from 1970 to 2024 about Charleston County, SC; Charleston; SC; residents; population; and USA.

About this dataset

Context

The dataset tabulates the population of Anderson County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Anderson County. The dataset can be utilized to understand the population distribution of Anderson County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Anderson County. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Anderson County.

Key observations

Largest age group (population): Male # 60-64 years (7,198) | Female # 60-64 years (7,760). 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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Anderson County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Anderson County is shown in the following column.
• Population (Female): The female population in the Anderson County is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Anderson County for each age group.

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 Anderson County Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Greenville County by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Greenville County across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 51.32% of total population being female. 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.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Greenville County is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Greenville 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 Greenville County Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Lancaster County population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Lancaster County across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Lancaster County was 108,215, a 3.33% increase year-by-year from 2022. Previously, in 2022, Lancaster County population was 104,724, an increase of 4.17% compared to a population of 100,529 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Lancaster County increased by 46,788. In this period, the peak population was 108,215 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Lancaster County is shown in this column.
• Year on Year Change: This column displays the change in Lancaster County population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Lancaster County Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Dorchester County population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Dorchester County across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Dorchester County was 169,833, a 2.28% increase year-by-year from 2022. Previously, in 2022, Dorchester County population was 166,050, an increase of 1.59% compared to a population of 163,452 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Dorchester County increased by 73,100. In this period, the peak population was 169,833 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Dorchester County is shown in this column.
• Year on Year Change: This column displays the change in Dorchester County population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Dorchester County Population by Year. You can refer the same here

Graph and download economic data for Population Estimate, Total, Hispanic or Latino, Some Other Race Alone (5-year estimate) in Marlboro County, SC (B03002018E045069) from 2009 to 2023 about Marlboro County, SC; SC; latino; hispanic; estimate; persons; 5-year; population; and USA.

Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Kershaw County, SC (S1701ACS045055) from 2012 to 2023 about Kershaw County, SC; Columbia; SC; percent; poverty; 5-year; population; and USA.

Graph and download economic data for Population Estimate, Total, Not Hispanic or Latino, Two or More Races, Two Races Excluding Some Other Race, and Three or More Races (5-year estimate) in Aiken County, SC (B03002011E045003) from 2009 to 2023 about Aiken County, SC; Augusta; SC; non-hispanic; estimate; persons; 5-year; population; and USA.

U.S. Census Bureau QuickFacts statistics for Sumter County, South Carolina. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

The American alligator (Alligator mississippiensis) is a species of ecological and economic importance in the southeastern United States. Within South Carolina, alligators are subject to private and public harvest programs, as well as nuisance removal. These management activities can have different impacts across alligator size classes that may not be apparent through widely-used monitoring techniques such as nightlight surveys. We synthesized multiple datasets within an integrated population model (IPM) to estimate size class-specific survival and abundance estimates, that would not be estimable through separate, non-integrated modeling frameworks. The IPM framework included a multistate mark-recapture-recovery model that used mark-recapture-recovery data from the Tom Yawkey Wildlife Center and growth transition probabilities that were estimated outside of the IPM framework. The IPM also included a state-space count model, which used nightlight survey counts of alligtaors from two survey routes: 1) Great Pee Dee and Waccamaw Rivers; and 2) South Santee Rivers. The IPM modeling framework also used mean clutch size data from the Tom Yawkey Wildlife Center and public and private harvest data within the state model. Lastly, we evaluated the effects of capture effort on capture probability, as well as the effects of water temperature and relative water level on count detection probability, and provide all covariate datasets. Our IPM framework determined that size class-specific survival rates were relatively high for all non-hatchling size classes, and abundance trends differed between the two nightlight survey sites.

Population 16 years and over Poverty Rate Statistics for 2023. This is part of a larger dataset covering poverty in York County, South Carolina by age, education, race, gender, work experience and more.

U.S. Census Bureau QuickFacts statistics for Richland County, South Carolina. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

Total household population Health Insurance Coverage Statistics for 2023. This is part of a larger dataset covering consumer health insurance coverage rates in Horry County, South Carolina by age, education, race, gender, work experience and more.

U.S. Census Bureau QuickFacts statistics for Hampton County, South Carolina. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.