We discuss how these findings can inform the better design of interactive stacked bar charts and visualization tools. However, for single-attribute comparisons, all chart types delivered similar performance. Participants perceived the inverting and diverging stacked bar charts as easier-to-use than the classical stacked bar chart for overall-attribute comparisons. The results also show that performing overall-attribute comparisons using the classical and diverging stacked bar charts required more time than performing single-attribute comparisons using these charts. The results of the study suggest that, for overall-attribute comparisons, the inverting stacked bar chart was the most effective with regards to the completion time. We measured the completion time, error rate, and perceived difficulty of the comparison tasks. Each chart type was used to visualize six attributes of data where half of the attributes have the characteristics of ‘lower better’ whereas the other half attributes are with ‘higher better.’ Thirty participants were asked to perform two types of comparison tasks: single-attribute and overall-attribute comparisons. To assess the efficacy of stacked bar charts in supporting attribute-comparison tasks, we conducted a user study to compare three types of stacked bar charts: classical, inverting, and diverging. Theyre a common data visualization because. Stacked Line charts are used with data which can be placed in an order, from low to high. A Stacked Bar Chart is a type of graph used to show the breakdown of categories into two or more subcategories. Stacked bar charts are a visualization method for presenting multiple attributes of data, and many visualization tools support these charts. This is done by stacking lines on top of each other.
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