Beer vs. Wine

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Why we love it

We love this map because it tells a clear, playful story: Where in the US do more people prefer beer, and where do they prefer wine. Using data on per capita sales, the map’s colors indicate preferences around the country. Areas where people spend more money on either beer or wine appear brighter. Places where people are not spending a lot on beer or wine, recede into the dark background. A simple legend uses icons and colors that coordinate with the map title.

Why it works

A traditional approach might be to make two maps that can be compared side by side. This map works by allowing two subjects to be compared in one map using what’s known as bivariate mapping. Color hues pay tribute to the subject of the map—amber for beer and purple for wine. Brightness levels convey an overall sense of sales volume. As a result, we can see regional variations and nuances that help us understand the sometimes fickle spending habits of US consumers.

See the story map

Important steps

  • Crunch the numbers

    The map uses raw per capita spending data that is calculated into relative proportions using ArcGIS Pro. These comparable ratios show an overwhelming national preference for beer. Yet, in areas where wine is preferred, it’s a heavy favorite.

  • Assign colors

    This map communicates regional preferences for beer or wine via a diverging color scheme. More extreme preferences (nearly two standard deviations from average) are given full saturation while areas of middling preference fade towards a neutral gray.
    About standard deviations

  • Brightness shows higher demand

    Beverage preference means more in areas of higher spending overall. A high proportional preference matters less when overall spending is quite low. Use per-capita spending to set transparency, so high-demand areas appear bright while low-demand areas visually recede.
    Attribute-driven symbology
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Requirements

  • Data

    The data comes courtesy of Esri Demographics, which provides local spending data on various products and services as sales per household or index. The author used these spending rates to add a new field and calculate the strength of preference for beer or wine.
    Esri Demographics data

  • Analysis

    Exploratory analysis led to maps of each beverage preference, and then a map of the combined rate of preference via a diverging color scheme. Key patterns are revealed by figuring out where spending deviates from the national norm.

  • Time

    It took a few minutes to precalculate additional fields comparing per capita beer and wine spending. About an hour was spent exploring thematic options to best represent the phenomenon. Another hour or so was devoted to working on the custom legend.
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Tips and tricks

  • Fun topic, fun legend

    At a glance, the legend should orient and engage the reader. Assembling fun and simple custom legends to key thematic data can unlock an author’s sense of creative ownership. Use or create simple clipart to represent a common understanding of the subject.
    Handcraft a legend

  • Make several maps

    This map started out as simple individual maps of extreme preference and a map of overall spending before it was merged into a bivariate map. Share that process with your audience by creating a story map leads them on a narrative through your mapping and discovery process.
    Create a story map

  • Map a rate, not a count

    Maps of polygons work better when their colors represent a rate, not a count. Mapping total dollar spending would really just be a map of total population in disguise. Per-capita spending is much more reflective of a place, and a fair comparison of the folks who live there.
    Mapping rates
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Map Author

John Nelson

I have way too much fun looking for ways to understand and visually present data, engage others, and write about it. Otherwise, I’m chasing around toddlers and wrangling chickens. Life is good.

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If you liked this map, check out these other Maps We Love that explore similar topics.

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