- What is the Population Rate of Change?
- What is the Population Density?
- What is the Land Area?
- What is the Percent who did not finish the 9th grade?
- What is the Total Administration Salaries?
- What is the Student Teacher Ratio?
- What is the Median Earnings?
- What is the Number of Employees?
- What is the Percent Without Health Insurance?
- What is the Access to Exercise Opportunities Rate?
The population count of South Carolina was 4,834,605 in 2016.
Demographics and Population Datasets Involving South Carolina
- API data.winnipeg.ca | Last Updated 2017-04-20T15:01:32.000Z
Population of visible minority groups living in neighbourhoods, neighbourhood clusters, wards, community areas, and custom areas including downtown and the entire city.
- API data.cityofnewyork.us | Last Updated 2017-09-28T16:04:18.000Z
Population details of selected Hispanic groups in New York City Boroughs
- API data.raleighnc.gov | Last Updated 2018-03-30T22:01:50.000Z
The businesses listed here are certified by the State of North Carolina and are registered vendors as part of the City of Raleigh's directory of Minority and Women-owned Business Enterprise (MWBE). The City's Business Assistance Coordinator manages the MWBE Assistance program Minority-Owned Business, maintains this Minority and Women-owned Business Directory, and solicits participation in construction contracts. Certified businesses in this directory are distributed to City departments for use on city projects.
- API data.vbgov.com | Last Updated 2017-10-12T13:51:45.000Z
This dataset provides demographic information from the American Community Survey about residents of Virginia Beach. This data was originally provided in the executive summary of the City of Virginia Beach’s Operating Budget.
- API bronx.lehman.cuny.edu | Last Updated 2013-06-10T03:17:53.000Z
Results from the 2010 Census regard ethnic makeup of Bronx census tracts. Source of this data came from the faculty of the Geography department at Lehman College
- API data.code4sa.org | Last Updated 2015-01-25T08:01:43.000Z
- API data.code4sa.org | Last Updated 2016-03-01T18:41:28.000Z
Disablities and demographics of people living in the Khayelitsha area at suburb level extracted from the Census 2011 dataset
- API data.code4sa.org | Last Updated 2015-02-11T18:04:51.000Z
- API data.code4sa.org | Last Updated 2015-01-25T08:30:23.000Z
- API data.pa.gov | Last Updated 2017-07-31T18:19:23.000Z
This data is pulled from the U.S. Census website. This data is for years Calendar Years 2009-2014. Product: SAHIE File Layout Overview Small Area Health Insurance Estimates Program - SAHIE Filenames: SAHIE Text and SAHIE CSV files 2009 – 2014 Source: Small Area Health Insurance Estimates Program, U.S. Census Bureau. Internet Release Date: May 2016 Description: Model‐based Small Area Health Insurance Estimates (SAHIE) for Counties and States File Layout and Definitions The Small Area Health Insurance Estimates (SAHIE) program was created to develop model-based estimates of health insurance coverage for counties and states. This program builds on the work of the Small Area Income and Poverty Estimates (SAIPE) program. SAHIE is only source of single-year health insurance coverage estimates for all U.S. counties. For 2008-2014, SAHIE publishes STATE and COUNTY estimates of population with and without health insurance coverage, along with measures of uncertainty, for the full cross-classification of: •5 age categories: 0-64, 18-64, 21-64, 40-64, and 50-64 •3 sex categories: both sexes, male, and female •6 income categories: all incomes, as well as income-to-poverty ratio (IPR) categories 0-138%, 0-200%, 0-250%, 0-400%, and 138-400% of the poverty threshold •4 races/ethnicities (for states only): all races/ethnicities, White not Hispanic, Black not Hispanic, and Hispanic (any race). In addition, estimates for age category 0-18 by the income categories listed above are published. Each year’s estimates are adjusted so that, before rounding, the county estimates sum to their respective state totals and for key demographics the state estimates sum to the national ACS numbers insured and uninsured. This program is partially funded by the Centers for Disease Control and Prevention's (CDC), National Breast and Cervical Cancer Early Detection ProgramLink to a non-federal Web site (NBCCEDP). The CDC have a congressional mandate to provide screening services for breast and cervical cancer to low-income, uninsured, and underserved women through the NBCCEDP. Most state NBCCEDP programs define low-income as 200 or 250 percent of the poverty threshold. Also included are IPR categories relevant to the Affordable Care Act (ACA). In 2014, the ACA will help families gain access to health care by allowing Medicaid to cover families with incomes less than or equal to 138 percent of the poverty line. Families with incomes above the level needed to qualify for Medicaid, but less than or equal to 400 percent of the poverty line can receive tax credits that will help them pay for health coverage in the new health insurance exchanges. We welcome your feedback as we continue to research and improve our estimation methods. The SAHIE program's age model methodology and estimates have undergone internal U.S. Census Bureau review as well as external review. See the SAHIE Methodological Review page for more details and a summary of the comments and our response. The SAHIE program models health insurance coverage by combining survey data from several sources, including: •The American Community Survey (ACS) •Demographic population estimates •Aggregated federal tax returns •Participation records for the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp program •County Business Patterns •Medicaid •Children's Health Insurance Program (CHIP) participation records •Census 2010 Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level.