{"id":1954,"date":"2017-04-29T03:17:43","date_gmt":"2017-04-29T03:17:43","guid":{"rendered":"https:\/\/blogs.scu.edu\/dataviz\/?p=1954"},"modified":"2017-04-29T03:17:43","modified_gmt":"2017-04-29T03:17:43","slug":"beer-belly-of-the-usa","status":"publish","type":"post","link":"https:\/\/blogs.scu.edu\/dataviz\/2017\/04\/29\/beer-belly-of-the-usa\/","title":{"rendered":"Beer Belly of the USA!"},"content":{"rendered":"

The visualization below is part of an article-cum-experiment \u2013 \u201cWhere Bars Outnumber Grocery Stores\u201d authored by NATHAN YAU posted to a site \u2013 Data Underload.<\/p>\n

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DESCRIPTION:<\/u><\/strong><\/p>\n

Author built this map to verify a claim made in an older article claiming the central-western region of the country can be called the \u201cbeer belly of the country\u201d since the bars outnumber the grocery stores in and around that area.<\/p>\n

This map is made with a help of a two-category (number of bars and number of grocery stores) map picked up from the Google Places API. The nice thing about the Google Places API is that businesses are categorized and searchable. Pulling the count of bars or grocery stores in each area of the country is particularly easier. To build this visualization, for every 20 miles, the author searched within a 10-mile radius for bars and grocery stores and got the ratios.<\/p>\n

Basically, the more bars, the darker the brown and the more grocery stores, the darker the green. And as per the older claim, it can really be seen that high bar concentration in Wisconsin, whereas the rest of the country has significantly more grocery stores.<\/p>\n

Positives:<\/p>\n

The need for the visualization is clear \u2013 to find out where in the country bars are outnumbering the grocery stores and verify that central-western region of the country is really the \u201cbeer belly of the country\u201d.<\/p>\n

Data picked is accurate since it checks out when compared to that of the older article which made the initial claim. (comparison below)<\/p>\n

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The calculation done for pulling out ratio is also quite clear and sensible. The factors considered are very precise while plotting in the map giving it a great clarity.<\/p>\n

Negatives:<\/p>\n

Although the need for the visualization is clear, the interpretation of the visualization will change with the audience. The conclusion can vary from \u2013 \u201cpeople in the state with more bars must drink a lot\u201d to \u201cpeople just prefer bars over restaurants\u201d to \u201cbars serve food too\u201d or \u201cpeople in states with lesser bars just drink at home\u201d. Theses variations arise because of insufficient factors being taken into consideration for this analysis.<\/p>\n

First off, the definition of \u201cbeer belly\u201d is place where alcohol consumption is maximum, but there is no consideration of that in data collected. There are so many factors which ideally should be taken into consideration to call a place the beer belly, like:<\/p>\n