Data visualizations

Data-visualizations can be used for many purposes. But in general, they can help to get an overview of large data in many dimensions – and even over time, if they are animated. Like this example below, that shows the increase in the average, global temperature over the last 140 years.

The example below shows e how COVID-19 data can be displayed on an animated map istead of just in an ordinary graph. The example shows the development of confirmed COVID-19 cases per 100.000 inhabitants in the five Nordic contries in the period february to november 2020.

As I am rather new in the field of data-visualization, I try to improve my skills and knowledge – currently I am reading the book “Data visualisation” by Andy Kirk, which is very inspiring. He has a definition of the term as “the representation and presentation of data to fascilitate understanding”.

Below is another style, where the countries are represented by bars (that look like flags) instead. It shows the incidence (per 100.000 inhabitants) in six different age groups – also in the Nordic coutries. The period is week 1 to 46 in 2021.

And below two maps of the COVID-19 pandemic in Denmark (2020) – in the different municipalities. The one to the left shows the absolute numbers of confirmed COVID-19 cases – and the one to the rigth shows the normalized numbers (thus per inhabitant). On these maps, I have also added “heatmap” colors to make it even more clear.

At last, here is an animated map of the EU / EØS countries. Here, I have used color to indicate the change from the delta to the omicron variant of concern of coronavirus (blue to red), whereas the heigth of the countries indicate the incidence (thus infected in relation to inhabitants).

Data-visualizations do not need to be animated. Often a single image is more appropriate. Like this visualization of the proportion (percentages) of different age groups of the Danish population.