Module 5 - Choropleth and Proportional Symbol Mapping

Figure 5 -  Map of European Wine Consumption

 For this project, the Albers projection was used because it preserves area accurately, which is essential for choropleth mapping. Since population density depends on the size of each region, an equal‑area projection prevents misleading distortions. Mapping population density instead of raw population counts also ensures the data is standardized and comparable across countries of different sizes.

A neutral tan color scheme was chosen to represent land, with darker shades showing higher population density. This palette is easy to interpret and avoids overwhelming the reader. Five classes were used to keep the map readable, and the data was classified using Natural Breaks because it best reflected the natural distribution of the dataset. Quantile classification was avoided because it would have grouped very different values together and misrepresented the data.

Wine consumption was displayed using red circles, which stand out clearly against the tan land and blue ocean. The data did not need normalization because population density was already calculated using area. SQL queries were used to filter and manipulate the dataset, allowing for cleaner data presentation and more precise symbol placement.

Graduated symbols were chosen over proportional symbols because they were more user‑friendly and communicated the ranges more clearly in the legend. Although proportional symbols are truest to the raw data, they made it harder to distinguish outliers like Vatican City and were less intuitive for readers. Flannery Compensation was not used; even if proportional symbols had been chosen, it would have exaggerated the Vatican outlier, caused symbol overlap in Europe’s dense geography, and made the legend harder to interpret.

Throughout the project, careful attention was given to cartographic design principles: selecting an appropriate color scheme, choosing a meaningful classification method, creating a clear and accurate legend, using effective thematic symbols, and compiling the final map in a way that communicates the data honestly and clearly. Including the projection information on the map reinforces that the spatial representation is accurate and that the data is being presented faithfully.