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The population count of San Juan County, CO was 544 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 San Juan County, CO

  • API

    Demographics For Unincorporated Areas In San Mateo County

    datahub.smcgov.org | Last Updated 2018-10-25T21:45:46.000Z

    Demographics, 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.

  • API

    Social Vulnerability Index for Virginia by Census Tract, 2018

    data.virginia.gov | Last Updated 2022-11-09T20:24:29.000Z

    "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

  • 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

    Educational Attainment of Washington Population by Age, Race/Ethnicity/, and PUMA Region

    data.wa.gov | Last Updated 2019-05-16T19:13:48.000Z

    The 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

  • API

    2010 Census/ACS Detailed Block Group Data

    data.kcmo.org | Last Updated 2021-11-12T14:22:17.000Z

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

  • API

    equity_priority_communities_2020_acs2018

    data.bayareametro.gov | Last Updated 2023-03-19T07:18:29.000Z

    gis.plan.equity_priority_communities_2020_acs2018

  • API

    Travel Decision Survey 2019

    data.sfgov.org | Last Updated 2020-01-31T22:45:39.000Z

    **Please refer to the downloadable XLSX attachment (http://bit.ly/SFMTATravelSurvey2019) for the complete dataset, metadata, and instructions for use.** This workbook provides data and data dictionaries for the SFMTA 2019 Travel Decision Survey. On behalf of San Francisco Municipal Transportation Agency (SFMTA), Corey, Canapary & Galanis (CC&G) undertook a Mode Share Survey within the City and County of San Francisco as well as the eight surrounding Bay Area counties of Alameda, Contra Costa, San Mateo, Marin, Santa Clara, Napa, Sonoma and Solano. The primary goals of this study were to: • Assess percent mode share for travel in San Francisco for evaluation of the SFMTA Strategic Objective 2.2: Mode Share target of 80% sustainable travel by 2030. • Evaluate the above statement based on the following parameters: number of trips to, from, and within San Francisco by Bay Area residents. Trips by visitors to the Bay Area and for commercial purposes are not included. • Provide additional trip details, including trip purpose for each trip in the mode share question series. • Collect demographic data on the population of Bay Area residents who travel to, from, and within San Francisco. • Collect data on travel behavior and opinions that support other SFMTA strategy and project evaluation needs. The survey was conducted as a telephone study among 801 Bay Area residents aged 18 and older. Interviewing was conducted in English, Spanish, Mandarin, Cantonese, and Tagalog. Surveying was conducted via random digit dial (RDD) and cell phone sample. All survey datasets incorporate respondent weighting based on age and home location; utilize the “weight” field when appropriate in your analysis. The survey period for this survey is as follows: 2019: May - August 2019 The margin of error is related to sample size (n). For the total sample, the margin of error is 3.3% for a confidence level of 95%. When looking at subsets of the data, such as just the SF population, just the female population, or just the population of people who bicycle, the sample size decreases and the margin of error increases. Below is a guide of the margin of error for different samples sizes. Be cautious in making conclusions based off of small sample sizes. At the 95% confidence level is: • n = 801(Total Sample). Margin of error = +/- 3.3% • n = 400. Margin of error = +/- 4.85% • n = 100. Margin of error = +/- 9.80%

  • API

    Influenza (Flu)_Pneumonia

    internal-sandiegocounty.data.socrata.com | Last Updated 2022-06-29T22:06:31.000Z

    Basic Metadata Note: this is the combination of influenza (flu) and pneumonia combined as they often co-occur together. *Rates per 100,000 population. Age-adjusted rates per 100,000 2000 US standard population. **Blank Cells: Rates not calculated for fewer than 5 events. Rates not calculated in cases where zip code is unknown. ***API: Asian/Pacific Islander. ***AIAN: American Indian/Alaska Native. Prepared by: County of San Diego, Health & Human Services Agency, Public Health Services, Community Health Statistics Unit, 2019. Code Source: ICD-9CM - AHRQ HCUP CCS v2015. ICD-10CM - AHRQ HCUP CCS v2018. ICD-10 Mortality - California Department of Public Health, Group Cause of Death Codes 2013; NHCS ICD-10 2e-v1 2017. Data Guide, Dictionary, and Codebook: https://www.sandiegocounty.gov/content/dam/sdc/hhsa/programs/phs/CHS/Community%20Profiles/Public%20Health%20Services%20Codebook_Data%20Guide_Metadata_10.2.19.xlsx

  • 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.