The population count of Twin Falls Micro Area (ID) was 107,097 in 2018.

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.

2. To build your own apps using this data, see the ODN Dataset and API links.

3. If you use this derived data in an app, we ask that you provide a link somewhere in your applications to the Open Data Network with a citation that states: "Data for this application was provided by the Open Data Network" where "Open Data Network" links to http://opendatanetwork.com. Where an application has a region specific module, we ask that you add an additional line that states: "Data about REGIONX was provided by the Open Data Network." where REGIONX is an HREF with a name for a geographical region like "Seattle, WA" and the link points to this page URL, e.g. http://opendatanetwork.com/region/1600000US5363000/Seattle_WA

Demographics and Population Datasets Involving Twin Falls Micro Area (ID)

  • API

    2010 Census/ACS Basic Block Group Data

    data.kcmo.org | Last Updated 2021-11-12T14:15:42.000Z

    basic characteristics of people and housing for individual 2010 census block groups

  • API

    2010 Census/ACS Basic Block Group Data

    data.kcmo.org | Last Updated 2014-06-10T19:28:50.000Z

    basic characteristics of people and housing for individual 2010 census block groups

  • API

    2010 Census/ACS Basic Block Group Data

    data.kcmo.org | Last Updated 2019-04-19T18:51:48.000Z

    basic characteristics of people and housing for individual 2010 census block groups

  • API

    Vital Signs: Displacement Risk - by tract

    data.bayareametro.gov | Last Updated 2019-08-13T16:05:43.000Z

    VITAL 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.

  • API

    Point In Time Homeless Survey Data

    data.sonomacounty.ca.gov | Last Updated 2019-07-12T18:26:35.000Z

    The County of Sonoma conducts an annual homeless count for the entire county. The survey data is derived from a sample of about 600 homeless persons countywide per year. The resulting information is statistically reliable only for the county as a whole, not for individual locations. The exception is the City of Santa Rosa, where the sample taken within the city is large enough to be predictive of the overall homeless population in that city.

  • API

    City of Cincinnati, Ohio Resident Survey

    data.cincinnati-oh.gov | Last Updated 2022-09-15T14:21:32.000Z

    The Cincinnati Community Perceptions Survey was developed by the City's Office of Performance and Data Analytics and ETC Institute in the fall of 2021. This community engagement tool was designed to allow the City Administration to evaluate resident satisfaction with our services and measure that level of satisfaction against cities of similar size, location, and demographics. The survey design also allows the City to capture community priorities for investment in services over the next two years. The survey was administered during the winter of 2021 by mail to a random sample of households across the city, and was available to complete by mail or online. The goal of 1,200 completed surveys was exceeded, with a total of 1,408 residents completing the survey. The overall residents for the sample of 1,408 households have a precision of at least +/-2.6% at the 95% level of confidence, and are demographically representative of our city's population. This year's survey will set a baseline for Cincinnati to work from with the goal of better understanding where we are excelling in service delivery and where our local government could benefit from intentional improvement and resources. Find the link to the Survey landing page here: https://etcinstitute.com/directionfinder2-0/city-of-cincinnati-ohio/