Debating the Morality of Pie and Donut Charts vs. Bar Graphs: A Look at Their Pros and Cons
In the realm of data visualization, a common question arises: which chart type is most effective for presenting simple, categorical data? A recent study, while not directly comparing bar charts, pie charts, and donut charts using multiple metrics and pupillometry, sheds light on this issue based on well-established findings in cognitive psychology and data visualization.
Key Findings from Related Research
The study reveals that bar charts are typically superior for accurately interpreting and comparing categorical values. This is because viewers can easily compare the heights of bars, which are mapped to a common scale. In contrast, pie and donut charts can be less accurate for value comparison, especially when the differences between categories are small. The human visual system struggles to accurately compare areas and angles, which are used to represent proportions in these charts.
Cognitive load, referring to the amount of working memory used during task performance, is another critical factor. Bar charts generally impose lower cognitive load for simple categorical comparison tasks, since they rely on a straightforward and efficiently processed visual feature (bar height or length). On the other hand, pie and donut charts require the brain to process and compare angles or arcs, which is inherently more demanding and can increase extraneous cognitive load, especially for novices or when there are many categories.
Pupillometry, a reliable method for measuring cognitive load, was not extensively used in studies directly comparing these chart types. However, research in cognitive psychology and neuroscience confirms that more complex tasks result in higher cognitive load, as reflected in EEG and pupillometry measures.
In terms of flexibility and perceptual ease, bar charts are highly flexible and can accommodate many categories, facilitate comparisons, and allow for easy addition of confidence intervals or other information. Pie charts and donut charts, on the other hand, are less flexible for more than a few categories (typically recommended for 5 or fewer), and their perceptual effectiveness declines rapidly as the number of categories increases.
Summary Table
| Chart Type | Accuracy/Comparison | Cognitive Load | Flexibility | |--------------|--------------------|---------------|-------------| | Bar Chart | High | Low | High | | Pie Chart | Moderate–Low | Moderate–High | Low | | Donut Chart | Moderate–Low | Moderate–High | Low |
Key Takeaways
The study suggests that bar charts outperform pie and donut charts in terms of accuracy, lower cognitive load, and flexibility for simple, categorical data comparison. Pie and donut charts are less effective for value comparison and impose higher cognitive load, particularly for data with many categories or when precise comparisons are needed.
While there is no widely cited study using pupillometry that specifically compares these three chart types, pupillometry and cognitive neuroscience support the idea that more complex visual tasks increase cognitive load. However, further research using pupillometry to directly compare these chart types is warranted.
In conclusion, bar charts remain the preferred choice for displaying simple, categorical data due to their accuracy, lower cognitive load, and flexibility. When it comes to data visualization, keeping it simple and easy to understand often leads to the most effective communication of information.
Data-and-cloud-computing technology can be utilized for analyzing and storing vast amounts of data needed for educational resources, facilitating self-development through personalized learning paths and interactive simulations. In the field of education-and-self-development, bar charts, based on their high accuracy, low cognitive load, and flexibility, are strongly recommended for presenting simple categorical data like performance rankings and progress tracking.
