Dos and Don’ts of Data Visualisation
Whether on purpose or not, a statistician can mislead an audience with a chart. This article explains some chart design principles and common mistakes novice data analysts make. Think about the statistical charts you have seen on billboards, in the news, and in research studies. Using these principles as a guide, would you classify any of those charts as misleading? Be sure to take note of the suggestions for successful dashboards.
Make charts easy to read
Do remove any visual clutter (increase data-ink ratio, Tufte's principle)
Perfection is achieved not when there is nothing more to add, but when there is nothing left to take away.
Antoine de Saint-Exupery
As shown in the example below, it is important to remove any visual clutter to let the content stand out.
- Remove the background
- Remove (or lighten) the grid
- Remove the % on the Y axis, if clarified on top
- Remove the title of the X axis, if not necessary
- Remove the legend if the bars can be labelled
- Remove the colours if not necessary
- Remove any graphical effect (shadow).
