The one dataset, two charts, two opposite stories.
The introduced scale has a huge impact on how we digest and interpret the presented data. The linear scale represents natural numbers, which we can easily compare. The logarithmic scale is not intuitive for us. It’s a mathematical concept, which we can use when we want to describe multiplicative factors or when is a huge skewness towards large numbers. We need to use brainpower to understand it. What is more, we are so used to linear one that we can easily overlook that visual is depicted on a logarithmic scale. We should inform our audience that logarithmic is used… and make sure that they understand how to read it.
Because of COVID-19 huge amount of statistic are generated and published across the internet. Those statistics try to tell a story about COVID-19 phenomenon. Most of them focus on a number of confirmed cases and deaths. I notice two data visualisation’s trends regarding presenting data about this virus. The first one concentrates on the growth of a total number of confirmed cases and the second one on the pace of disease spreading.
Let’s feel the difference.
“PANIC chart” — I saw somewhere a good name of such a linear chart. I couldn’t more agree. Tell me, what feelings this chart evokes in you?
This is an exponential chart (another mathematical concept), which depict the growth of the phenomenon. Very rapid growth to be specific.
Below we can see the same data. However, embedded on a different scale. Please, look carefully. Each grid represents 10 to n power. Don’t you think that the below chart isn’t so scary?
What stories these two charts tell us?
Let’s base them on 18th of Mar and 4th of Apr. The Linear chart tells us that till 18th of Mar nothing spectacular happened. Totally opposite to the Logarithmic one, where we can see the fastest growth of confirmed cases. Between 18th and 4th on the Linear, we can see the huge growth. On the second one, the pace of growth decelerates. After 4th of April, the Linear continues to present the same pace of growth (steep hill), but on the Logarithmic, it’s plain to see that the curve flattens.