This lab focused on the use of proportional symbol maps and bivariate symbol mapping. The first map below is a map of the populations of the largest cities in India. I used proportional symbols to represent different values of the population fields for each of these cities. 3 classes were used to symbolize this information, 5 classes is what I was originally working with but it turned out to be too busy and quite difficult to construct the legend properly with more than 3 symbols. To create the stacked legend here, I just inserted a normal legend then converted it to graphics. From here I ungrouped the elements then proceeded to piece them together into what you see in the map below. The colors were chosed intentionlally to assist in legibility of the map. The countries surrounding India, the water feature, and the land mass of India were all symbolized with unsaturated colors. The symbols were then done with an overly saturated red color and outlined with a light red/yellow to help the smaller symbols stand out easier.
Below is a nother proportionaly symbol map but there are two seperate fields, increase and decrease in jobs. The legend was pieced together to symbolized both of these fields. The difficult part was allowing all the symbols to be visibile, this was done by rearranging the drawing order and transparency to ensure all symbols could be seen.
In order to create the map below I took each of the variables data and set them up into a quantile classification system with 3 classes. From here I recorder the class breaks. Using select by attribute, I chose the grouping of the first class break, second, and third for each group giving them 1,2, or 3 as their names, then A, B, or C for the next group. From here I created a unique values symbology classification with the 9 possible outcomes and inserted the legend. I converted that legend to graphics and manually manipulated the legend into the bivariate legend you see below.
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