The population count of Wells County, ND was 4,055 in 2018.
Population
Population Change
Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API -
Demographics and Population Datasets Involving Wells County, ND
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Social Vulnerability Index for Virginia by Census Tract, 2018
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
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NYSERDA Low- to Moderate-Income New York State Census Population Analysis Dataset: Average for 2013-2015
data.ny.gov | Last Updated 2019-11-15T22:30:02.000ZHow 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).
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Social Vulnerability Index 2018 - United States, county
data.cdc.gov | Last Updated 2022-02-14T14:19:58.000ZATSDR’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.
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Social Vulnerability Index 2018 - United States, tract
data.cdc.gov | Last Updated 2022-02-14T14:22:44.000ZATSDR’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.
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City and Township Population Data
data.ramseycounty.us | Last Updated 2022-03-21T15:37:41.000ZSources: MN State Demographic Center and the Metropolitan Council. Released August 2020. The Minnesota State Demographic Center (our office) and the Metropolitan Council jointly produce population and household estimates for all years between the U.S. Census Bureau's decennial (10-year) counts. The Met Council produces the estimates for the seven counties of Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington, as well as all cities and townships within those counties. Our office produces the estimates for the other 80 Minnesota counties outside of the 7-county metro, as well as all cities and townships within those counties. Notes: New estimates are released annually in late July for the prior year. All data are dated to April 1. Persons per household is calculated by dividing the household population by the number of occupied households in any given geography. The household population does not equal the total population because some residents live in "group quarters" settings (such as college dormitories, nursing facilities, shelters, treatment centers, religious orders, military barracks, or correctional facilities), and thus are not living in households. Cities that cross county boundaries are segmented by each county's portion (labeled "part"), as well as appearing in total under "Multi-County City" in the "COUNTY NAME" column.
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2018 Social Vulnerability Index
data.brla.gov | Last Updated 2021-12-07T15:23:24.000ZThe 2018 Social Vulnerability Index indicates the relative vulnerability of every U.S. Census tract. Census tracts are subdivisions of counties in which the Census Bureau aggregates statistical data. The SVI ranks the tracts on 15 social factors, including unemployment, minority status, and disability, and further groups them into four related themes. Thus, every tract receives a ranking for each Census variable, each of the four themes, and an overall ranking.
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Virginia Social Vulnerability Index (SVI) (2018) by Census Tract (Datathon)
data.virginia.gov | Last Updated 2023-05-22T14:58:02.000ZSVI 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.
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Hospital Inpatient Discharges (SPARCS De-Identified): 2013
health.data.ny.gov | Last Updated 2019-09-13T19:04:24.000ZThe Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.
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2010 Census/ACS Basic Block Group Data
data.kcmo.org | Last Updated 2021-11-12T14:15:42.000Zbasic characteristics of people and housing for individual 2010 census block groups
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Vital Signs: Income (Median by Place of Residence) – by tract
data.bayareametro.gov | Last Updated 2019-08-13T16:18:03.000ZVITAL SIGNS INDICATOR Income (EC4) FULL MEASURE NAME Household income by place of residence LAST UPDATED May 2019 DESCRIPTION Income reflects the median earnings of individuals and households from employment, as well as the income distribution by quintile. Income data highlight how employees are being compensated for their work on an inflation-adjusted basis. DATA SOURCE U.S. Census Bureau: Decennial Census Count 4Pb (1970) Form STF3 (1980-1990) Form SF3a (2000) https://nhgis.org U.S. Census Bureau: American Community Survey Form B19013 (2006-2017; place of residence) http://api.census.gov Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1970-2017; specific to each metro area) http://data.bls.gov CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Income data reported in a given year reflects the income earned in the prior year (decennial Census) or in the prior 12 months (American Community Survey); note that this inconsistency has a minor effect on historical comparisons (for more information, go to: http://www.census.gov/acs/www/Downloads/methodology/ASA_nelson.pdf). American Community Survey 1-year data is used for larger geographies – metropolitan areas and counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Quintile income for 1970-2000 is imputed from Decennial Census data using methodology from the California Department of Finance (for more information, go to: http://www.dof.ca.gov/Forecasting/Demographics/Census_Data_Center_Network/documents/How_to_Recalculate_a_Median.pdf). Bay Area income is the population weighted average of county-level income. Income has been inflated using the Consumer Price Index specific to each metro area; however, some metro areas lack metro-specific CPI data back to 1970 and therefore adjusted data is unavailable for some historical data points. Note that current MSA boundaries were used for historical comparison by identifying counties included in today’s metro areas.