One of the most common uses of charts is illustrating part-to-whole relationships, aka. \u201cdata composition.\u201d The Pie chart may be the most popular chart type for this purpose, but other chart types may be just as good (or much better, experts will argue).<\/p>\n
In this article, we will look at ways to effectively communicate parts-to-whole relationships effectively using pie, donut, sunburst, stacked bar\/column, stacked area, and treemap charts.<\/p>\n
Which chart to use is primarily driven by the nature of the data. As a rule of thumb, for simple datasets (six or fewer elements), a pie or donut chart works well. For more dense datasets, other charts are better to illustrate composition, such as stacked bar, column, or area charts. For nested (hierarchical) data sets, a sunburst and treemap might be right for the job.<\/p>\n
Let’s explore these chart types and see where we might want to pick chart type over another.<\/p>\n
The pie chart is the most popular way to visualize composition, thanks to its simple design. The ingredients or elements are presented as fractional parts of a whole. The chart below<\/a> shows the composition of gasses in the air we breathe.<\/p>\n