The population count of Kootenai County, ID was 145,046 in 2015. The population count of Spokane County, WA was 480,832 in 2015.
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 Spokane County, WA or Kootenai County, ID
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WAOFM - Census - Population and Housing, 2000 and 2010
data.wa.gov | Last Updated 2021-09-01T17:20:31.000ZPopulation and housing information extracted from decennial census Public Law 94-171 redistricting summary files for Washington state for years 2000 and 2010.
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Driver Licenses and ID Cards Transferred to Washington
data.wa.gov | Last Updated 2024-08-15T21:49:33.000ZThis data set shows monthly counts of new Washington State driver licenses and identification cards (ID) where customers presented licenses or IDs from other states or countries. The data is organized by Washington counties where the customers live. It shows where the previous driver licenses or ID cards were issued.
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Educational Attainment of Washington Population by Age, Race/Ethnicity/, and PUMA Region
data.wa.gov | Last Updated 2019-05-16T19:13:48.000ZThe 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
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Pierce County, WA -- COVID Risk Index Score
internal.open.piercecountywa.gov | Last Updated 2020-05-26T22:54:57.000ZPopulation over 60 (S0101), Women Who Had a Birth in the Past 12 Months (B13002), Below Poverty Level (B17015), No Health Insurance (B27001), Household Receiving SNAP Assistance (S2201), No Internet Access (B28002), Total Population (B01003) and Language at Home (C16001)
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American Community Survey 5 Year Estimates - Pierce County, WA
internal.open.piercecountywa.gov | Last Updated 2024-06-14T17:03:34.000ZPopulation over 60 (S0101), Women Who Had a Birth in the Past 12 Months (B13002), Below Poverty Level (B17015), No Health Insurance (B27001), Household Receiving SNAP Assistance (S2201), No Internet Access (B28002), Total Population (B01003) and Language at Home (C16001)
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Demographics For Unincorporated Areas In San Mateo County
datahub.smcgov.org | Last Updated 2018-10-25T21:45:46.000ZDemographics, including median income, total population, race, ethnicity, and age for unincorporated areas in San Mateo County. This data comes from the 2012 American Community Survey 5 year estimates DP03 and DP05 files. They Sky Londa area is located within two Census Tracts. The data for Sky Londa is the sum of both of those Census Tracts. Users of this data should take this into account when using data for Sky Londa.
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Driver License Transfers to Asotin County
data.wa.gov | Last Updated 2020-11-13T19:44:37.000ZThis dataset includes information about driver license transfers from other states and countries to Asotin County, Washington.
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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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Hospital Inpatient Discharges (SPARCS De-Identified): 2014
health.data.ny.gov | Last Updated 2019-09-13T16:31:56.000ZThe 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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Vital Signs: Displacement Risk - by tract
data.bayareametro.gov | Last Updated 2019-08-13T16:05:43.000ZVITAL SIGNS INDICATOR Displacement Risk (EQ3) FULL MEASURE NAME Share of lower-income households living in tracts at risk of displacement LAST UPDATED December 2018 DESCRIPTION Displacement risk refers to the share of lower-income households living in neighborhoods that have been losing lower-income residents over time, thus earning the designation “at risk”. While “at risk” households may not necessarily be displaced in the short-term or long-term, neighborhoods identified as being “at risk” signify pressure as reflected by the decline in lower-income households (who are presumed to relocate to other more affordable communities). The dataset includes metropolitan area, regional, county and census tract tables. DATA SOURCE U.S. Census Bureau: Decennial Census 1980-1990 Form STF3 https://nhgis.org U.S. Census Bureau: Decennial Census 2000 Form SF3a https://nhgis.org U.S. Census Bureau: Decennial Census 1980-2010 Longitudinal Tract Database http://www.s4.brown.edu/us2010/index.htm U.S. Census Bureau: American Community Survey 2010-2015 Form S1901 5-year rolling average http://factfinder2.census.gov U.S. Census Bureau: American Community Survey 2010-2017 Form B19013 5-year rolling average http://factfinder2.census.gov CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Aligning with the approach used for Plan Bay Area 2040, displacement risk is calculated by comparing the analysis year with the most recent year prior to identify census tracts that are losing lower-income households. Historical data is pulled from U.S. Census datasets and aligned with today’s census tract boundaries using crosswalk tables provided by LTDB. Tract data, as well as regional income data, are calculated using 5-year rolling averages for consistency – given that tract data is only available on a 5-year basis. Using household tables by income level, the number of households in each tract falling below the median are summed, which involves summing all brackets below the regional median and then summing a fractional share of the bracket that includes the regional median (assuming a simple linear distribution within that bracket). Once all tracts in a given county or metro area are synced to today’s boundaries, the analysis identifies census tracts of greater than 500 lower-income people (in the prior year) to filter out low-population areas. For those tracts, any net loss between the prior year and the analysis year results in that tract being flagged as being at risk of displacement, and all lower-income households in that tract are flagged. To calculate the share of households at risk, the number of lower-income households living in flagged tracts are summed and divided by the total number of lower-income households living in the larger geography (county or metro). Minor deviations on a year-to-year basis should be taken in context, given that data on the tract level often fluctuates and has a significant margin of error; changes on the county and regional level are more appropriate to consider on an annual basis instead.