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A Dot for Every Vote

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Why we love it

While many maps show the outcome of the 2016 US presidential election, this one illustrates how the votes were distributed across the country. We love how this map employs a unique approach in dot density mapping—each dot represents a single vote from the 130 million total votes. It is a dasymetric map, which means instead of dots filling collection areas uniformly, they are reallocated to more representative areas. In this case, the dots are constrained to areas where people live.

Why it works

Not every vote on this map is meant to be discernable. To ensure that votes don't obscure one another, each dot is transparent. This map works because, collectively, the dots coalesce into a meaningful picture of where there was uniform support. Intense blue indicates votes for Hillary Clinton, and intense red indicates votes for Donald Trump. Areas with mixed outcomes are comprised of dots that coalesce visually into varying shades of purple. 

Important steps

  • Generalize dataset, convert to polygons

    Find a dataset appropriate for reallocation. Here, the National Land Cover Database 30 m raster dataset is reclassified to 500 m resolution to generalize urban and rural areas. Convert the resulting raster to a feature class using the Raster to Polygon geoprocessing tool.
    National Land Cover Database
    Raster to Polygon geoprocessing tool

  • Working with datasets

    Intersect county polygons containing election data with land cover polygons to produce the election polygons.
    Intersect geoprocessing tool

  • Move election results to derived polygons

    Reallocate election totals for the two parties within intersected polygons, proportionally based on area but weighted to density as defined by the land cover dataset.
    Dasymetric reallocation

  • Create symbols for final polygons

    Symbolize resultant intersected polygons with dot density symbology using two symbol classes: transparent blue circles to show Democratic votes and transparent red circles to show Republican votes.
    Dot density symbology
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Requirements

  • Data and software

    Use an authoritative dataset of raw election results at the smallest collection area, like US counties. Use a companion dataset to extrapolate a reasonable estimation of where people actually live, like categories from the National Land Cover Database.
    ArcGIS Pro
    National Land Cover Database

  • Analysis

    Reallocating data into representative spatial units is complicated work. Finish with dot density symbology in ArcGIS Pro. Create new fields in the attribute table and use the field calculator to derive reallocated values for each polygon.
    Field calculation
    Reallocation example

  • Time

    Most time is spent intersecting data and reallocating values. This is dependent on the data and parameters you choose. It takes only a few moments to symbolize a larger number of points, as in this example, and share your web map to ArcGIS Online.
    Share a web map
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Tips and tricks

  • Do not imply precision

    Although the map looks precise, it is not showing the exact location of individual votes. It's simply a reallocation of dots randomly within the defined areas of where people live. To ensure this level of accuracy is not implied, limit how far the map can be zoomed in.
    Limit visible scales

  • Use transparent symbols

    To imply mixed voting patterns and ensure votes are not obscured, use substantially transparent symbols.
    Color in symbology
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Kenneth Field, map author

Map Author

Kenneth Field

Kenneth Field is a professional carto-nerd, amateur drummer, and snowboarder. He's also a high-quality, innovative, and sometimes a little crazy cartographer of modern maps.

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