Did you know that all Formula 1 cars must incorporate a large plank of wood as one of their components?
A wooden board?
Yes effectively!
Formula 1 cars use a wooden board, the “sliding block” placed under the car. This ensures that the height of the car remains within the legal limits established during races. Additionally, the board serves as a critical safety feature, sacrificing road rub to protect the car’s essential components from potential damage upon contact with curbs. Importantly, its impact on performance is minimal. The skate is made from a wood and fiber composite material and is designed to wear at a constant rate.¹
Why do I mention this? This anecdote highlights that even a technologically advanced field like Formula 1 can effectively use a (theoretically) simple component . This parallel extends to the realm of data visualization. As I have stated on numerous occasions, Most data-driven insights can be skillfully communicated using three basic chart types: bar chart, line chart, and pie chart.
But what happens if these three types fail to capture the essence of the phenomenon we are trying to explain? Or what happens if we use several simple graphs instead of just one, but a little more complex one? Or, going back to our F1 example, did we just decide to replace the wood with carbon fiber and draw something sleeker? In this post, I will explore the alternatives available should such a scenario occur.
The goal is to provide an overview of alternative forms of data visualization. So, I’m going to talk about chart options beyond the traditional triumvirate of bar, line, and pie charts, which I consider the default for most cases anyway.
That said, I fully recognize the plethora of other display options available. I usually consider using them when the conventional trio doesn’t fit the bill. Here, I will present you with a selection of visualization forms that I find particularly valuable. I will also guide you through some…
