- 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 Student Teacher Ratio?
- What is the Median Earnings?
- What is the Mean Job Proximity Index?
- What is the Number of Employees?
- What is the Percent Without Health Insurance?
- What is the Mean Environmental Health Hazard Index?
The population rate of change of Inyo County, CA was -0.60% in 2018.
Demographics and Population Datasets Involving Inyo County, CA
- API data.sccgov.org | Last Updated 2023-12-09T01:03:43.000Z
The dataset provides information about the demographics and characteristics of deaths with COVID-19 by racial/ethnic groups among Santa Clara County residents. Source: California Reportable Disease Information Exchange. Data notes: The Other category for the race/ethnicity graph includes American Indian/Alaska Native and people who identify as multi-racial. This table is updated every Friday.
- API data.sccgov.org | Last Updated 2023-12-09T01:03:43.000Z
The dataset provides information about the demographics and characteristics of COVID-19 cases by racial/ethnic groups among Santa Clara County residents. Source: California Reportable Disease Information Exchange. Data notes: The Other category for the race/ethnicity graph includes American Indian/Alaska Native and people who identify as multi-racial. This table is updated every Thursday.
- API performance.smcgov.org | Last Updated 2016-08-31T20:40:07.000Z
Violent and property crime rates per 100,000 population for San Mateo County and the State of California. The total crimes used to calculate the rates for San Mateo County include data from: Sheriff's Department Unincorporated, Atherton, Belmont, Brisbane, Broadmoor, Burlingame, Colma, Daly City, East Palo Alto, Foster City, Half Moon Bay, Hillsborough, Menlo Park, Millbrae, Pacifica, Redwood City, San Bruno, San Carlos, San Mateo, South San Francisco, Bay Area DPR, BART, Union Pacific Railroad, and CA Highway Patrol.
- API healthstat.dph.sbcounty.gov | Last Updated 2019-03-13T19:07:43.000Z
Percent of People who Cannot Afford to Feed Themselves Sufficiently. U.S. Census Bureau, Current Population Survey, December Supplement (AKA USDA Food Security Supplement). Dissected by Year, Geographic Area, Age Category, and Race/Ethnicity.
- API data.virginia.gov | Last Updated 2023-05-22T14:49:26.000Z
"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
- API data.ct.gov | Last Updated 2023-08-02T14:53:12.000Z
NOTE: As of 4/15/2021, this dataset will no longer be updated and will be replaced by two new datasets: 1) "COVID-19 Vaccinations by Town" (https://data.ct.gov/Health-and-Human-Services/COVID-19-Vaccinations-by-Town/x7by-h8k4) and "COVID-19 Vaccinations by Town and Age Group" (https://data.ct.gov/Health-and-Human-Services/COVID-19-Vaccinations-by-Town-and-Age-Group/gngw-ukpw). A summary of COVID-19 vaccination coverage in Connecticut by town. Records without an address could not be included in town vaccine coverage estimates. Total population estimates are based on 2019 data. A person who has received one dose of any vaccine is considered to have received at least one dose. A person is considered fully vaccinated if they have received 2 doses of the Pfizer or Moderna vaccines or 1 dose of the Johnson & Johnson vaccine. The fully vaccinated are a subset of the number who have received at least one dose. The number with At Least One Dose and the number Fully Vaccinated add up to more than the total number of doses because people who received the Johnson & Johnson vaccine fit into both categories. SVI refers to the CDC's Social Vulnerability Index - a measure that combines 15 demographic variables to identify communities most vulnerable to negative health impacts from disasters and public health crises. Measures of social vulnerability include socioeconomic status, household composition, disability, race, ethnicity, language, and transportation limitations - among others. Towns with a "yes" in the "Has SVI tract >0.75" field are those that have at least one census tract that is in the top quartile of vulnerability (e.g., a high-need area). 34 towns in Connecticut have at least one census tract in the top quartile for vulnerability. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected.
NYSERDA Low- to Moderate-Income New York State Census Population Analysis Dataset: Average for 2013-2015data.ny.gov | Last Updated 2019-11-15T22:30:02.000Z
How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov. The Low- to Moderate-Income (LMI) New York State (NYS) Census Population Analysis dataset is resultant from the LMI market database designed by APPRISE as part of the NYSERDA LMI Market Characterization Study (https://www.nyserda.ny.gov/lmi-tool). All data are derived from the U.S. Census Bureau’s American Community Survey (ACS) 1-year Public Use Microdata Sample (PUMS) files for 2013, 2014, and 2015. Each row in the LMI dataset is an individual record for a household that responded to the survey and each column is a variable of interest for analyzing the low- to moderate-income population. The LMI dataset includes: county/county group, households with elderly, households with children, economic development region, income groups, percent of poverty level, low- to moderate-income groups, household type, non-elderly disabled indicator, race/ethnicity, linguistic isolation, housing unit type, owner-renter status, main heating fuel type, home energy payment method, housing vintage, LMI study region, LMI population segment, mortgage indicator, time in home, head of household education level, head of household age, and household weight. The LMI NYS Census Population Analysis dataset is intended for users who want to explore the underlying data that supports the LMI Analysis Tool. The majority of those interested in LMI statistics and generating custom charts should use the interactive LMI Analysis Tool at https://www.nyserda.ny.gov/lmi-tool. This underlying LMI dataset is intended for users with experience working with survey data files and producing weighted survey estimates using statistical software packages (such as SAS, SPSS, or Stata).
- API bronx.lehman.cuny.edu | Last Updated 2012-10-21T14:06:17.000Z
2010 Census Data on population, pop density, age and ethnicity per zip code
- API data.countyofnapa.org | Last Updated 2023-08-10T21:09:02.000Z
Report P-3: Population Projections Race/Ethnicity and Sex by Individual Years of Age, 2010 to 2060 California (2019 Baseline) Data Notes: "The California Department of Finance (DOF), Demographic Research Unit is responsible by statute for maintaining postcensal population projections which are calculated using the demographic balancing equation: Current Population = Previous Population + (Births - Deaths) +Net Migration This method calculates the population in the target year by starting with the population from the previous year, adding natural increase (births minus deaths) and net migration that occurred during the time period between the two years. The births, deaths, and migration anticipated during the time period are called the components of change. A cohort-component method traces people born in a given year throughout their lives. As each year passes, cohorts change due to the mortality and migration assumptions. Applying fertility assumptions to women of childbearing age forms new cohorts at age zero. These 2019 baseline projections incorporate the latest historical population, birth, death, and migration data available as of July 1, 2020. Historical trends from 1990 through 2020 for births, deaths, and migration are examined. County populations by age, sex, and race/ethnicity are projected to 2060. The county projections are then summed to obtain data for the state. " View the Methodology at: https://dof.ca.gov/Forecasting/Demographics/Projections/ Published by: Demographic Research Unit Department of Finance Website: www.dof.ca.gov/Forecasting/Demographics/Projections/ Phone: 916-323-4086 Suggested Citation California Department of Finance. Demographic Research Unit. Report P-3: Population Projections, California, 2010-2060 (Baseline 2019 Population Projections; Vintage 2020 Release). Sacramento: California. July 2021. Data dictionary: https://dof.ca.gov/wp-content/uploads/sites/352/Forecasting/Demographics/Documents/P3_Dictionary.txt
- API data.cdc.gov | Last Updated 2022-02-14T14:19:58.000Z
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. In addition to tract-level rankings, SVI 2018 also has corresponding rankings at the county level. Notes below that describe “tract” methods also refer to county methods.