The population rate of change of North Dakota was 2.20% in 2014.

Population

Population Change

Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API - Notes:

1. ODN datasets and APIs are subject to change and may differ in format from the original source data in order to provide a user-friendly experience on this site.

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Demographics and Population Datasets Involving North Dakota

  • API

    2010 Census/ACS Detailed Census Tract Data

    data.kcmo.org | Last Updated 2013-02-08T20:45:56.000Z

    detailed characteristics of people and housing for individual 2010 census tract portions inside or outside KCMO

  • API

    2010 Census/ACS Detailed Census Tract Data

    data.kcmo.org | Last Updated 2014-06-10T19:35:31.000Z

    detailed characteristics of people and housing for individual 2010 census tract portions inside or outside KCMO

  • API

    1980 Census Detailed Census Tract Data

    data.kcmo.org | Last Updated 2013-02-08T20:55:45.000Z

    detailed 1980 characteristics of people and housing for individual 2010 census tract portions inside or outside KCMO

  • API

    2000 Census Detailed Census Tract Data

    data.kcmo.org | Last Updated 2013-02-08T20:57:43.000Z

    detailed 2000 characteristics of people and housing for individual 2010 census tract portions inside or outside KCMO

  • API

    1990 Census Detailed Census Tract Data

    data.kcmo.org | Last Updated 2013-02-08T20:56:58.000Z

    detailed 1990 characteristics of people and housing for individual 2010 census tract portions inside or outside KCMO

  • API

    2009-2013 American Community Survey Detailed Census Tract Data

    data.kcmo.org | Last Updated 2015-09-08T16:00:10.000Z

    detailed characteristics of people and housing for individual 2010 census tract portions inside or outside KCMO

  • API

    26th Ave SW Greenway at SW Oregon St

    data.seattle.gov | Last Updated 2016-12-06T22:03:07.000Z

    The counters consist of two small tube sensors stretching across the street, which are attached to a small metal counting box made by Eco-Counter. The tubes only count people riding bikes. They are very accurate and designed to be used on greenways.

  • API

    Uninsured Population Census Data CY 2009-2014 Human Services

    data.pa.gov | Last Updated 2016-11-08T20:03:29.000Z

    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.

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    Certified Vendors - Office of Supplier Diversity

    data.delaware.gov | Last Updated 2016-10-13T14:39:02.000Z

    This data set is of certified businesses owned and controlled 51% or more by minorities, women, veterans, and individuals with disabilities. The data set is updated daily and is searchable and exportable at this link: http://directory.osd.gss.omb.delaware.gov/index.shtml. The Office of Supplier Diversity's mission is to assist the entire supplier diversity community of minority, women, veteran, service disabled veteran, and individuals with disabilities owned businesses as well as small businesses of a unique size in competing for the provision of commodities, services, and construction to State departments, agencies, authorities, school districts, higher education institutions and all businesses. The Office of Supplier Diversity sits within Government Support Services, a Division of the Office of Management and Budget.

  • API

    Durham Compass Data - by Census Blockgroups

    brigades.opendatanetwork.com | Last Updated 2015-02-21T02:49:07.000Z

    Most recent Demographic, % Racial, Unmaintained Properties Data, etc. See Data Key for descriptions: LIST: Total Population Population Density White/Caucasian Black/African American Asian Hispanic/Latino Other Race Median Age Race/Ethnic Diversity Youth Population Retirement-Age Population Land Use Diversity Median Household Income Per Capita Income Residential Building Permit Values Commercial Building Permit Values Supplemental Security Income Crimes Involving Property Crimes with a Violent Component Drug-Related Crimes Renter-Occupied Housing Rent 30% or More of Income Monthly Owners Costs 30% or More of Income Minimum housing code violations Unmaintained Property Violations Average Age of Residential Property Percent Commuting 30 Minutes or More Percent of Commuters Driving Alone Tree Canopy Impervious Area Automotive Code Violations Sidewalk-to-Roadway Ratio Commuting to Work by Bicycle Commuting to Work by Foot Households Within Walking Distance to Bus Stops Number of Daily Bus Arrivals Number of Nightly Bus Arrivals Working from Home Households Within Walking Distance to Banks Households Within Walking Distance to Full Service Grocers Households Within Walking Distance to Pharmacies