Mapping with Choropleth and Proportional/Graduated Symbology

 This week we focused on choropleth and proportional symbol mapping. For the final outcome of our map, we should have a clear presentation of European population density and wine consumption. We were tasked with reviewing the data that was provided to us on European population density (people per sq km) and wine consumption (liters per capita) paying attention to any outliers and viewing the map projection. Having a better understanding of our data will help us to make better choices on how to most accurately present the data. We spent some time exploring different color schemes for a choropleth map until we found the one that best represented our data before creating our map. The outcome of these exercises was to better familiarize ourselves with color schemes, creating schemes that worked well on the map and in the legend and most accurately displayed the data. To see the effect of using different methods and classifications. To also see how it can help your map and how it can hurt your map. Comparing the use of proportional and graduated symbols helped us to get a deeper understanding of the impact they have on the data visual. Another outcome was using SQL to make changes to the data, allowing for a cleaner clearer presentation.

The map I have created here I completed all of it in ArcGIS Pro. I chose to go with a multipart color scheme ranging from light cream to a dark green. I felt this scheme did an accurate job showing the different classes for the population density. I also used the color vision simulator tool to make sure that the color scheme would still accurately display the data for anyone with color blindness. I chose to create a point symbol to a thematic picture symbol by using the styles tool and adding a SVG file of clipart of a wine glass. I chose to go with the graduated method for displaying my picture symbology. When comparing the different methods I felt the graduate showed the most accurate display of the different sizes putting the data into 5 different classes that I could adjust. I used the convert labels to annotation tool to adjust the labeling of the countries. It was a long struggle for me to find the balance of size and placement of the labels with the symbology. I then finished my map in the layout tap adding all of my map elements and inset map. I played around with quite a few different map extents until I final found the one that was just right. So please enjoy finding out where the real wine drinkers are in Europe!