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The population density of Ventura County, CA was 456 in 2015.

Population Density

Population Density is computed by dividing the total population by Land Area Per Square Mile.

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

Geographic and Population Datasets Involving Ventura County, CA

  • API

    San Mateo County And California Crime Rates 2000-2014

    performance.smcgov.org | Last Updated 2016-08-31T20:40:07.000Z

    Violent and property crime rates per 100,000 population for San Mateo County and the State of California. The total crimes used to calculate the rates for San Mateo County include data from: Sheriff's Department Unincorporated, Atherton, Belmont, Brisbane, Broadmoor, Burlingame, Colma, Daly City, East Palo Alto, Foster City, Half Moon Bay, Hillsborough, Menlo Park, Millbrae, Pacifica, Redwood City, San Bruno, San Carlos, San Mateo, South San Francisco, Bay Area DPR, BART, Union Pacific Railroad, and CA Highway Patrol.

  • API

    COVID-19 cases by city of residence

    data.sccgov.org | Last Updated 2024-10-26T00:04:33.000Z

    The dataset summarizes counts and rates of cumulative COVID-19 cases by cities in Santa Clara County. Source: California Reportable Disease Information Exchange This dataset is updated every Thursday.

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    Next Generation Simulation (NGSIM) Vehicle Trajectories and Supporting Data

    datahub.transportation.gov | Last Updated 2024-05-20T18:02:47.000Z

    Click “Export” on the right to download the vehicle trajectory data. The associated metadata and additional data can be downloaded below under "Attachments". Researchers for the Next Generation Simulation (NGSIM) program collected detailed vehicle trajectory data on southbound US 101 and Lankershim Boulevard in Los Angeles, CA, eastbound I-80 in Emeryville, CA and Peachtree Street in Atlanta, Georgia. Data was collected through a network of synchronized digital video cameras. NGVIDEO, a customized software application developed for the NGSIM program, transcribed the vehicle trajectory data from the video. This vehicle trajectory data provided the precise location of each vehicle within the study area every one-tenth of a second, resulting in detailed lane positions and locations relative to other vehicles. Click the "Show More" button below to find additional contextual data and metadata for this dataset. For site-specific NGSIM video file datasets, please see the following: - NGSIM I-80 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-I-80-Vide/2577-gpny - NGSIM US-101 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-US-101-Vi/4qzi-thur - NGSIM Lankershim Boulevard Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Lankershi/uv3e-y54k - NGSIM Peachtree Street Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Peachtree/mupt-aksf

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    Deer Tick Surveillance: Adults (Oct to Dec) excluding Powassan virus: Beginning 2008

    health.data.ny.gov | Last Updated 2024-05-01T18:05:44.000Z

    This dataset provides the results from collecting and testing adult deer ticks, also known as blacklegged ticks, or by their scientific name <i>Ixodes scapularis</i>. Collection and testing take place across New York State (excluding New York City) from October to December, when adult deer ticks are most commonly seen. Adult deer ticks are individually tested for different bacteria and parasites, which includes the bacteria responsible for Lyme disease. These data should simply be used to educate people that there is a risk of coming in contact with ticks and tick-borne diseases. These data only provide adult tick infections at a precise location and at one point in time. Both measures, tick population density and percentage, of ticks infected with the specified bacteria or parasite can vary greatly within a very small area and within a county. These data should not be used to broadly predict disease risk for a county. Further below on this page you can find links to tick prevention tips, a video on how to safely remove a tick, and more datasets with tick testing results. Interactive charts and maps provide an easier way to view the data.

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    WAOFM - Census - Population and Housing, 2000 and 2010

    data.wa.gov | Last Updated 2021-09-01T17:20:31.000Z

    Population 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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    Deer Tick Surveillance: Nymphs (May to Sept) excluding Powassan virus: Beginning 2008

    health.data.ny.gov | Last Updated 2024-05-01T18:07:53.000Z

    This dataset provides the results from collecting and testing nymph deer ticks, also known as blacklegged ticks, or by their scientific name <i>Ixodes scapularis</i>. Collection and testing take place across New York State (excluding New York City) from May to September, when nymph deer ticks are most commonly seen. Nymph deer ticks are individually tested for different bacteria and parasites, which includes the bacteria responsible for Lyme disease. These data should simply be used to educate people that there is a risk of coming in contact with ticks and tick-borne diseases. These data only provide nymph tick infections at a precise location and at one point in time. Both measures, tick population density and percentage, of ticks infected with the specified bacteria or parasite can vary greatly within a very small area and within a county. These data should not be used to broadly predict disease risk for a county. Further below on this page you can find links to tick prevention tips, a video on how to safely remove a tick, and more datasets with tick testing results. Interactive charts and maps provide an easier way to view the data.

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    COVID-19 cases by zip code of residence

    data.sccgov.org | Last Updated 2024-10-26T00:01:51.000Z

    The datset summarizes counts and rates of cumulative COVID-19 cases by zip codes in Santa Clara County. Source: California Reportable Disease Information Exchange. This dataset is updated every Thursday.

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    WAOFM - Census - Population Density by County by Decade, 1900 to 2020

    data.wa.gov | Last Updated 2023-07-06T16:48:57.000Z

    Washington state population density by county by decade 1900 to 2020.

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    Napa County and California Population Totals 2011-2020

    data.countyofnapa.org | Last Updated 2023-07-26T16:19:55.000Z

    Data Source: CA Department of Finance Data: Population estimates for January 1, 2011, through January 1, 2020. The population estimates benchmark for April 1, 2010 is also provided. Citation: State of California, Department of Finance, E-4 Population Estimates for Cities, Counties, and the State, 2011-2020, with 2010 Census Benchmark. Sacramento, California, May 2022. For detailed information on methodology and other data considerations, visit: https://dof.ca.gov/Forecasting/Demographics/Estimates/e-4-population-estimates-for-cities-counties-and-the-state-2011-2020-with-2010-census-benchmark-new/

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    Choose Maryland: Compare Counties - Demographics

    opendata.maryland.gov | Last Updated 2024-07-09T17:43:22.000Z

    Population profile - total, rate of change, age, and density.