- What is the Population Count?
- What is the Population Density?
- What is the Land Area?
- What is the Percent who did not finish the 9th grade?
- What is the Median Earnings?
- What is the Number of Employees?
- What is the Crime incident count?
- What is the Water Area?
- What is the High School Graduation Rate?
- What is the Median Female Earnings?
The population rate of change of Columbia, SC was 0.84% in 2018.
Demographics and Population Datasets Involving Columbia, SC
- API data.cambridgema.gov | Last Updated 2019-09-17T17:16:51.000Z
This data set provides demographic and journey to work characteristics of the Cambridge Labor Force by primary mode of their journey to work. Attributes include age, presence of children, racial and ethnic minority status, vehicles available, time leaving home, time spent traveling, and annual household income. The data set originates from a special tabulation of the American Community Survey - the 2012 - 2016 version of the Census Transportation Planning Products (CTPP). The Cambridge Labor Force consist of all persons who live in Cambridge who work or are actively seeking employment. For more information on Journey to Work data in Cambridge, please see the full 2015 report (https://www.cambridgema.gov/~/media/Files/CDD/FactsandMaps/profiles/moving_forward_20150930.ashx?la=en).
- API data.cambridgema.gov | Last Updated 2019-09-17T17:17:39.000Z
This data set provides demographic and journey to work characteristics of the Cambridge Workforce by primary mode of their journey to work. Attributes include age, presence of children, racial and ethnic minority status, vehicles available, time arriving at work, time spent traveling, and annual household income. The data set originates from a special tabulation of the American Community Survey - the 2012 - 2016 version of the Census Transportation Planning Products (CTPP). The Cambridge Workforce consist of all persons who work in Cambridge, regardless of home location. For more information on Journey to Work data in Cambridge, please see the full 2015 report: https://www.cambridgema.gov/~/media/Files/CDD/FactsandMaps/profiles/moving_forward_20150930.ashx?la=en).
- API data.lacounty.gov | Last Updated 2019-12-06T23:13:12.000Z
Emissions from passenger vehicles and trucks are estimated based on VMT by vehicle type. VMT for each jurisdiction is estimated using trip-based travel forecasting models developed by Southern California Association of Governments (SCAG). SCAG’s regional travel demand model analyzes transportation network and socioeconomic data such as population, household, and employment, to forecast daily vehicle trips for each traffic analysis zone (TAZ). Model outputs include: • Vehicle trips by type: including cars, light trucks, medium duty trucks, heavy duty trucks, and transit vehicles • Vehicle trip lengths by trip purpose • Vehicle trip origins and destinations Based on vehicle trips analysis, VMT calculations are performed for all cities within LA County (except for the City of Avalon), including unincorporated areas that are under direct County control. Using CARB Emissions Factors (EMFAC) model, CO2 and N2O emissions are estimated by multiplying emissions rates with vehicle activity data in all cities and unincorporated areas within the South Coast (SC) sub-area and the Mojave Desert (MD) sub-area. Sub-area emissions are then disaggregated based on speed bin by time of day and vehicle profile to estimate GHG emissions from into passenger vehicle and heavy duty trucks.
- API data.virginia.gov | Last Updated 2021-02-22T20:18:07.000Z
"ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) created Centers for Disease Control and Prevention Social Vulnerability Index (CDC SVI or simply SVI, hereafter) to help public health officials and emergency response planners identify and map the communities that will most likely need support before, during, and after a hazardous event. SVI indicates the relative vulnerability of every U.S. Census tract. Census tracts are subdivisions of counties for which the Census collects statistical data. SVI ranks the tracts on 15 social factors, including unemployment, minority status, and disability, and further groups them into four related themes. Thus, each tract receives a ranking for each Census variable and for each of the four themes, as well as an overall ranking." For more see https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/SVI_documentation_2018.html
Rate of Hospitalizations for Opioid Overdose per 100,000 Residents by Demographics CY 2016- 2017 Statewide Health Care Cost Containment Council (PHC4)data.pa.gov | Last Updated 2019-01-18T20:03:25.000Z
Rate of hospitalization for opioid overdose per 100,000 PA Residents categorized by principal diagnosis of heroin or opioid pain medication overdose by year and demographic. This analysis is restricted to Pennsylvania residents age 15 and older who were hospitalized in Pennsylvania general acute care hospitals. Disclaimer: PHC4’s database contains statewide hospital discharge data submitted to PHC4 by Pennsylvania hospitals. Every reasonable effort has been made to ensure the accuracy of the information obtained from the Uniform Claims and Billing Form (UB-82/92/04) data elements. Computer collection edits and validation edits provide opportunity to correct specific errors that may have occurred prior to, during or after submission of data. The ultimate responsibility for data accuracy lies with individual providers. PHC4 agents and staff make no representation, guarantee, or warranty, expressed or implied that the data received from the hospitals are error-free, or that the use of this data will prevent differences of opinion or disputes with those who use published reports or purchased data. PHC4 will bear no responsibility or liability for the results or consequences of its use.
- API data.kcmo.org | Last Updated 2019-11-25T23:04:22.000Z
DETAILED CHARACTERISTICS OF PEOPLE AND HOUSING FOR INDIVIDUAL 2010 CENSUS TRACT PORTIONS INSIDE OR OUTSIDE KCMO - Some demographic data are from the 2010 Census while other data are from the 2013-2017 American Community Survey (ACS). The ACS replaces what until 2000 was the Long Form of the census; both have been based on surveys of a partial sample of people. The ACS sample is so small that surveys from five years must be combined to be reliable. The 2013-2017 ACS is the most recent grouping of 5 years of data. ACS data have been proportioned to conform with 2010 Census total population and total households.
- API data.wa.gov | Last Updated 2019-05-16T19:13:48.000Z
The American Community Survey (ACS) is designed to estimate the characteristic distribution of populations* and estimated counts should only be used to calculate percentages. They do not represent the actual population counts or totals. Beginning in 2019, the Washington Student Achievement Council (WSAC) has measured educational attainment for the Roadmap Progress Report using one-year American Community Survey (ACS) data from the United States Census Bureau. These public microdata represents the most current data, but it is limited to areas with larger populations leading to some multi-county regions**. *The American Community Survey is not the official source of population counts. It is designed to show the characteristics of the nation's population and should not be used as actual population counts or housing totals for the nation, states or counties. The official population count — including population by age, sex, race and Hispanic origin — comes from the once-a-decade census, supplemented by annual population estimates (which do not typically contain educational attainment variables) from the following groups and surveys: -- Washington State Office of Financial Management (OFM): https://www.ofm.wa.gov/washington-data-research/population-demographics -- US Census Decennial Census: https://www.census.gov/programs-surveys/decennial-census.html and Population Estimates Program: https://www.census.gov/programs-surveys/popest.html **In prior years, WSAC used both the five-year and three-year (now discontinued) data. While the 5-year estimates provide a larger sample, they are not recommended for year to year trends and also are released later than the one-year files. Detailed information about the ACS at https://www.census.gov/programs-surveys/acs/guidance.html
- API data.kcmo.org | Last Updated 2019-11-25T22:48:59.000Z
BASIC CHARACTERISTICS OF PEOPLE AND HOUSING FOR INDIVIDUAL 2010 CENSUS TRACT PORTIONS INSIDE OR OUTSIDE KCMO - Some demographic data are from the 2010 Census while other data are from the 2013-2017 American Community Survey - ACS. The ACS replaces what until 2000 was the Long Form of the census; both have been based on surveys of a partial sample of people. The ACS sample is so small that surveys from five years must be combined to be reliable. The 2013-2017 ACS is the most recent grouping of 5 years of data. ACS data have been proportioned to conform with 2010 Census total population and total households.
- API data.bayareametro.gov | Last Updated 2020-12-09T01:58:17.000Z
This data set represents all tracts within the San Francisco Bay Region, and contains attributes for the eight Metropolitan Transportation Commission (MTC) Communities of Concern (CoC) tract-level variables for exploratory purposes. MTC 2018 Communities of Concern (tract geography) is based on eight ACS 2014-2018 (ACS 2018) tract-level variables: ● Minority (70% threshold) ● Low-Income (less than 200% of Fed. poverty level, 28% threshold) ● Level of English Proficiency (12% threshold) ● Seniors 75 Years and Over (8% threshold) ● Zero-Vehicle Households (15% threshold) ● Single Parent Households (18% threshold) ● People with a Disability (12% threshold) ● Rent-Burdened Households (14% threshold) If a tract exceeds both threshold values for Low-Income and Minority shares OR exceeds the threshold value for Low-Income AND also exceeds the threshold values for three or more variables, it is a CoC. Detailed documentation on the production of this feature set can be found at https://github.com/BayAreaMetro/Spatial-Analysis-Mapping-Projects/blob/master/Project-Documentation/Communities-of-Concern/README.md
- API data.austintexas.gov | Last Updated 2021-02-10T00:00:23.000Z
A new component of fair housing studies is an analysis of the opportunities residents are afforded in “racially or ethnically concentrated areas of poverty,” also called RCAPs or ECAPs. An RCAP or ECAP is a neighborhood with significant concentrations of extreme poverty and minority populations. HUD’s definition of an RCAP/ECAP is: • A Census tract that has a non‐white population of 50 percent or more AND a poverty rate of 40 percent or more; OR • A Census tract that has a non‐white population of 50 percent or more AND the poverty rate is three times the average tract poverty rate for the metro/micro area, whichever is lower. Why the 40 percent threshold? The RCAP/ECAP definition is not meant to suggest that a slightly‐lower‐than‐40 percent poverty rate is ideal or acceptable. The threshold was borne out of research that concluded a 40 percent poverty rate was the point at which a neighborhood became significantly socially and economically challenged. Conversely, research has shown that areas with up to 14 percent of poverty have no noticeable effect on community opportunity. (See Section II in City of Austin’s 2015 Analysis of Impediments to Fair Housing Choice: http://www.austintexas.gov/sites/default/files/files/NHCD/Reports_Publications/1Analysis_Impediments_for_web.pdf) This dataset provides socioeconomic data on protected classes from the 2008-2012 American Community Survey on census tracts in Austin’s city limits and designates which of those tracts are considered RCAPs or ECAPs based on these socioeconomic characteristics. A map of the census tracts designated as RCAPs or ECAPs is attached to this dataset and downloadable as a pdf (see below).