The population count of North Dakota was 745,475 in 2017. The population count of Wyoming was 583,200 in 2017.
Demographics and Population Datasets Involving North Dakota or Wyoming
- API data.orcities.org | Last Updated 2017-01-09T17:17:43.000Z
Data from the American Communities Survey 2014. This data includes information on household income, city industries composition, and class of workers.
- API data.orcities.org | Last Updated 2017-01-19T17:03:58.000Z
This dataset focuses on housing statistics from the American Community Survey 2014.
- 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 data.ny.gov | Last Updated 2018-11-20T23:01:09.000Z
This dataset shows the population, civilian labor force, unemployed, and unemployment rate for people aged 16 years and older by race and ethnicity in New York State and its Labor Market Regions.
- API data.orcities.org | Last Updated 2017-01-06T16:41:02.000Z
Data from the American Community Survey 2014 on all LOC member cities. This dataset includes select information for education, health and transportation statistics.
- API data.sonomacounty.ca.gov | Last Updated 2019-05-23T08:32:59.000Z
Historical population data captured daily. Two figures are shown those in custody and those in outside custody but are still under the responsibility of Sonoma County Sheriff. Examples of outside custody include home confinement, state prison, hospital stays, weekend custody, and supervised by other agencies.
- API data.transportation.gov | Last Updated 2019-05-22T14:40:51.000Z
NOTICE: We would like to bring to your attention some errors in the metadata fields for Wyoming BSM deposited from 12/3/2018 – present, which we are working to fix. Please see full details in the <a href="http://usdot-its-cvpilot-public-data.s3.amazonaws.com/index.html" target="_blank">ITS DataHub data sandbox</a>. </n></n> This is a live running log of approximately one day's worth of sanitized Basic Safety Messages (BSM) from the Wyoming Connected Vehicle (CV) Pilot project. All sanitized BSMs from this project can be found on the public data sandbox here: http://usdot-its-cvpilot-public-data.s3.amazonaws.com/index.html. J2735 standard BSM elements are those that begin with coreData_ and partII_. Additional contextual information specific to the Wyoming CV Pilot to help analysis is included in metadata_ columns.
- API data.pa.gov | Last Updated 2019-04-01T15:15:07.000Z
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.
- API opendata.utah.gov | Last Updated 2019-04-19T06:16:01.000Z
Median Household Income All States 2000-2012
2011 National Household Survey (NHS) - Occupation by Census Tracts, Dissemination Areas, Wards and Urban Service Areasdata.strathcona.ca | Last Updated 2016-12-13T22:25:18.000Z
The data shows labour force frequency distribution by National Occupational Classification (NOC) and North American Industry Classification System (NAICS) in four different boundary types. The data was provided by Statistics Canada but it has been sectioned and transposed. The fields come from NHS profile reports of Statistics Canada and some information may not be available for all the boundaries. The fields have been arranged in the same order as NHS profile reports. To see a more complete description of the fields click on this link: http://www12.statcan.gc.ca/nhs-enm/2011/dp-pd/prof/details/Page.cfm?Lang=E&Geo1=CSD&Code1=4811052&Data=Count&SearchText=Strathcona%20County&SearchType=Begins&SearchPR=01&A1=All&B1=All&GeoLevel=PR&GeoCode=10#tabs1