For these maps, the quantile classification method seemed to work the best, as it distributes a set of values into groups that contain an equal set of values, which works well here. I used a light to dark purple color scheme, with lighter colors showing lower values and darker colors showing higher values of population density. I like this color scheme as it shows the data clearly without being too bright and distracting. I used circular graduated symbols for the wine consumption data, and I felt that 5 classes here shows the data effectively. The symbols are a color that is easy to read and also allows the underlying population density map to be easily seen. I see that the countries with the most wine consumption tend to be in central and southern Europe and the countries with the least are in eastern Europe. The countries with the lowest population densities seem to be those with cold climates (Russia and the Nordic countries).
The gender per population maps were also created using the quantile classification scheme. This shows a high percentage of females in countries such as Russia and a high percentage of males in the Nordic countries and Iceland. Most other countries are relatively balanced. Looking at the two gender ratio maps side by side, one sees that one is nearly the inverse of the other, which makes sense, as these are percent per total population.
I enjoyed learning about choropleth maps as they are seen everywhere, and it was interesting to learn how they are used and misused. I also gained an appreciation for the use of graduated and proportional symbols on maps.
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