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.
Choose your chart
Dual axis charts, pros and cons
There is a debate around dual axis charts. They are mainly used to highlight some relation in the trend of two data sets with different units of measure or to compare two data series with the same measure, but different magnitudes.
The advantage of these charts is that they illustrate a lot of information with limited space. The downside is that they are often not easy to read, and they could even lead to misleading interpretations.
Best practice:
- To avoid confusion, the data need to be clearly referable to their own axis with the help of colours and text.
- To avoid misleading interpretation, when using the same unit, the axes should be synchronised.
If you want to keep different scales to see the evolution in detail, you can opt for side-by-side charts and use annotations to highlight possible correlations between the two series.
If you want to keep both data series in one chart, you can create an indexed chart. An indexed chart that does not tell anything about absolute numbers but shows the relative change in data series over time.
Another alternative to the dual axis, is the connected scatterplot.