In this week's module, we learned the importance of cloropleth maps
and using appropriate proportional symbols. To make sure that we
comprehend the material, we applied what we learned by creating a
cloropleth map showing the wine consumption in Europe. We did the majority
of the data manipulation in ArcMap, such as, choosing a color scheme for
the map, used the SQL Query language to remove outliers in the dataset
of our map, and we applied a data classification method to help represent
our data. After exporting our map from ArcMap to AI, the finishing
touches were added. The touches that I added were labeling the
countries in Europe, adjusting the 'Wine Consumption' legend, and adding
a solid color background to the map.
The data classification scheme that I chose was
quantiles due to there being more color variation with the data being
presented. We are also observing the population of wine consumers in each
country so quantiles method is more suited for this type of map as well.The thematic color scheme I chose started with a light
tan color graduating to a dark brown. I chose this color scheme as to not
overwhelm the map reader with all of the symbol elements we will be adding to the
map thus allowing the map reader to easily look at the data on the map. Along with the color schemes, I
used the graduated method for my symbols to help present wine
consumption in each European country. The reason for me choosing this
method and not the proportional method is the
proportional method seems to overwhelm the map with huge symbols and one
could
not make out what country it resided on. With the graduated method, I’m
able to
select the size range of my symbols and it also allows me select how
many classes
I want to utilize to showcase my data.
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