My Geographic Map of Florida COVID-19 Cases by ZIP Code

    For this week’s assignment, I was instructed to find a dataset and create a visual using Tableau. I selected the Florida COVID-19 Cases by ZIP Code (April 28, 2021) dataset from the University of South Florida Libraries’ Digital Heritage and Humanities Collection, originally downloaded from the Florida Department of Health ArcGIS Data Portal. Using this data, I wanted to examine how COVID-19 cases were distributed across Florida ZIP codes during the s
pring of 2021. After importing the dataset into Tableau, I generated this geographical map using a blue color scale, since it provided the clearest contrast.

    On the map, ZIP codes shaded in darker blue represent higher case counts, while lighter areas represent lower counts. Unsurprisingly, South Florida ZIP codes (especially in Miami-Dade and Broward counties) had the highest reported numbers. Central Florida areas around Orlando also showed clusters of elevated case counts. What stood out most was that some rural ZIP codes, while generally lighter, still had surprisingly high totals compared to neighboring areas. This suggests that while population density was a key driver, the spread was not limited to urban centers.

(Original map above) 

    When I first built the map, the gradient was skewed because a few ZIP codes had case counts as high as 16,000, while most others ranged only between 1,000 and 2,000. This caused most ZIPs to appear almost the same pale shade, which limited the insight viewers could gain. To address this, I adjusted the gradient scale so the maximum cutoff was closer to 5,000 cases. This rescaling reduced the influence of extreme outliers and allowed mid-range ZIP codes to display more meaningful variation. By doing this, I applied Gestalt principles of similarity and contrast—making differences among communities easier to see and interpret without distorting the overall picture of COVID-19 spread.

    To further improve this visualization, I would consider filtering the map to highlight only ZIP codes above a certain threshold. Additionally, normalizing the data by population (cases per 1,000 people) would make comparisons more meaningful and reduce bias toward heavily populated ZIP codes.

Data Source:
Florida COVID-19 Cases by Zip Code, April 28, 2021. Florida Department of Health via USF Libraries Digital Heritage and Humanities Collection.

 

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