If comparing the totals for a categorical variable are important, then a different chart type like a standard bar chart or stacked bar chart will be better at performing the task. Since there aren’t any native elements for group totals in a grouped bar chart, it will take a lot of work on the reader’s part to estimate a total for any categorical level, primary or secondary. It is worth calling out the fact that the grouped bar chart is not well-equipped to compare totals across levels of individual categorical variables. Between-group comparisons are aided by choosing a consistent color and order for each secondary variable’s level to be plotted in each group. A number of bars are plotted in each group equal to the number of levels of the secondary categorical variable. For within-group comparisons, the primary categorical variable’s levels determine a location for a cluster of bars to be plotted. In order to facilitate these comparisons, bars in a grouped bar chart are plotted systematically. In the example above, a within-group comparison would focus on the bars for a single quarter, while a between-group comparison would focus on bars for a single representative across quarters. We’ll call comparisons of the first type “within-group” comparisons, and comparisons of the second type “between-group”. A grouped bar chart is used when you want to look at how the second category variable changes within each level of the first, or when you want to look at how the first category variable changes across levels of the second.
Where the grouped bar chart differs is its division of data points across two different categorical variables, not just one. Like a standard bar chart, the grouped bar chart is built for showing a distribution of data points or making comparisons across different categories of data. We can also check individual performances such as Mersey’s relatively stable performance across the year, or York’s major bump in Q4 after a slide from Q1 through Q3. We can see from the plot that Lincoln had the best performance in Q1 with Kent best in all remaining quarters. Colors and positions are consistent within each cluster: for example, we can see that Kent is always in blue and plotted first. One bar cluster is plotted for each quarter, and in each cluster, one bar for each representative. The grouped bar chart above compares new quarterly revenue for four sales representatives across a year. Bars are grouped by position for levels of one categorical variable, with color indicating the secondary category level within each group.
A grouped bar chart (aka clustered bar chart, multi-series bar chart) extends the bar chart, plotting numeric values for levels of two categorical variables instead of one.
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