Data Visualization

Foundational research by William S. Cleveland and Robert McGill found in their paper "Graphical Perception and Graphical Methods for analyzing Scientific Data", Science, New Series, Vol. 229, No. 4716, pp 828-833, studied what graph types people are able to interpret with accuracy.  Their findings of what people were able to decode most accurately are ranked in the following list from easiest to most difficult to decode:

1. Position on a common scale e.g. scatter plot, line chart
2. Position on identical but nonaligned scales e.g. small multiples
3. Length e.g. bar charts
4. Direction e.g. line chart
5. Angle and slope (tie) e.g. pie charts
6. Area e.g. bubble graphs
7. Volume, density, and colour saturation (tie) e.g. heatmap
8. Curvature e.g. donut chart
9. Colour hue e.g. weather maps

Picking one of these can help you to select the chart that will work best for you. There are a number of resources you can use to pick the right chart:

• Chart Chooser: This site provides templates to make various charts using Excel and Powerpoint
• Data Visualization Catalogue: A useful guide for selecting a chart based on your analysis or communications needs.