Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Charleston by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Charleston. The dataset can be utilized to understand the population distribution of Charleston by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Charleston. 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 Charleston.
Key observations
Largest age group (population): Male # 30-34 years (7,315) | Female # 30-34 years (7,766). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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
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.
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/.
This dataset is a part of the main dataset for Charleston Population by Gender. You can refer the same here
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Resident Population in Charleston-North Charleston, SC (MSA) (CRLPOP) from 2000 to 2024 about Charleston, SC, residents, population, and USA.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Population Estimate, Total, Hispanic or Latino, Some Other Race Alone (5-year estimate) in Charleston County, SC (B03002018E045019) from 2009 to 2023 about Charleston County, SC; Charleston; SC; latino; hispanic; estimate; persons; 5-year; population; and USA.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
U.S. Census Bureau QuickFacts statistics for Charleston city, 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.
Comprehensive demographic and housing statistics for ZIP code 29405 in North Charleston, South Carolina.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Chart and table of population level and growth rate for the Charleston-North Charleston metro area from 1950 to 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the mean household income for each of the five quintiles in Charleston County, SC, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Charleston County median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
This list ranks the 24 cities in the Charleston County, SC by Multi-Racial Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
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.
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/.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Population 25 years and over Poverty Rate Statistics for 2023. This is part of a larger dataset covering poverty in North Charleston, South Carolina by age, education, race, gender, work experience and more.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Population 26 years and over Health Insurance Coverage Statistics for 2023. This is part of a larger dataset covering consumer health insurance coverage rates in Charleston, South Carolina by age, education, race, gender, work experience and more.
Based on SC Broadband Office (SCBBO) analysis of FCC Broadband Data Collection (fcc.gov), Jun. 30, 2023 (as of Mar. 19, 2024), submissions that were audited through the SC BEAD Challenge process which concluded on Jun. 30, 2024. The SC BEAD Challenge process relied upon FCC BSL Fabric Jun. 30, 2023, Version 3.2 (pub. Jul. 21, 2023). Satellite and mobile broadband services are excluded. Population and K-12 estimates are derived from residential unit level data based on the FCC BSL fabric. Broadband investment data based on SCBBO actual BSL contract data in the case of state-managed funds (when available) and best-available federal data in the case of FCC and US Department of Agriculture (USDA) managed investments. County-level investments are based upon data provided to the SCBBO. The SCBBO is neither responsible nor liable for damages or injuries caused by failure of performance, error, omission, inaccuracy, inaccessibility, incompleteness or any other errors of this information period or formatting on this slide. This data should be used for general reference purposes only. Additional broadband information regarding South Carolina may be found at www.scdigitaldrive.org. Submit comments or questions to broadband@ors.sc.gov
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Two or more races Poverty Rate Statistics for 2023. This is part of a larger dataset covering poverty in Charleston, South Carolina by age, education, race, gender, work experience and more.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 1991 to 2023 for North Charleston High School vs. South Carolina and Charleston 01 School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual black student percentage from 1991 to 2023 for A. C. Corcoran Elementary School vs. South Carolina and Charleston 01 School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual white student percentage from 1991 to 2023 for North Charleston High School vs. South Carolina and Charleston 01 School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
45 to 54 years Poverty Rate Statistics for 2023. This is part of a larger dataset covering poverty in Charleston County, South Carolina by age, education, race, gender, work experience and more.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual asian student percentage from 1990 to 2018 for North Charleston High School vs. South Carolina and Charleston 01 School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Hispanic Poverty Rate Statistics for 2023. This is part of a larger dataset covering poverty in North Charleston, South Carolina by age, education, race, gender, work experience and more.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual total revenue from 1990 to 2021 for Charleston 01 School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual math proficiency from 2011 to 2022 for North Charleston High School vs. South Carolina and Charleston 01 School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Charleston by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Charleston. The dataset can be utilized to understand the population distribution of Charleston by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Charleston. 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 Charleston.
Key observations
Largest age group (population): Male # 30-34 years (7,315) | Female # 30-34 years (7,766). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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
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.
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/.
This dataset is a part of the main dataset for Charleston Population by Gender. You can refer the same here