Making and Evaluating a Pie Chart

 The Creation of a Pie Chart

    This dataset from the American Kennel Club 2024 displays the percentages of popular dog breeds, for example, Labradors, French Bulldogs, and Poodles. A good choice to represent this kind of data is a pie chart, since we’re adding up percentages in five categories, totaling up to 100%. Making it easy to understand which breeds are more popular than others. Showing the comparison first in size, and then viewing the percentages either on the side of each slice or in the middle. An article titled “Story Telling with Data” elaborates on what data is considered good for this kind of chart, speaking about how each slice represents one component and all slices added together equal the whole, which, in my chart, can be applied.

    Looking at the pie chart above, the data could be used in another kind of chart. A bar chart allows the data to be understood more easily as well, but since it’s a percentage, it might not work the best. There’s also a donut chart, which would display the same sort of concept as the pie chart, but it won't display the main goal, which would be the data being compared to the total, to not compare exact numbers. What I learned so far from comparing pie charts to other types of charts is that bar charts show details better, while pie charts do a better job of showing proportions. Design choices like color and labels have an impact on how to understand a chart. Some design guidelines I learned from “Story Telling with Data” are that a pie chart shouldn’t have an overload of slices; a good amount would be a range of 5-7. Avoiding 3D pie charts is for the better since it’s hard to see properly and distorts the data. Also that legends aren't needed; just applying the percentages with what the percentages represent is the easiest and best option. 

Resources:

Story Telling with Data