Viz 1: Global Debt, 2018
Viz 2: Global Government Debt by OECD country: 1995 - 2019
This grid chart displays global debt for the countries in the Organization for Cooperation and Economic Development (OECD). The years represented are 1995-2019, though not all countries contain information for all of those years.
Viz 3: Japan’s Rapidly Rising Gov’t Debt May Signal Trouble
Japan’s government debt-to- GDP ratio has nearly tripled since 1995 while most other countries remain fairly constant.
A comparison of the visualizations
The dataset used for these visualizations was downloaded from the Organization for Economic Cooperation and Development. It represents the general government debt for countries that are part of the OECD from 1995 to 2019. All three of these visualizations represent the same data in different ways. While none is necessarily better than the others, they each serve a different purpose. The first chart is a simple bar chart, good at representing data at a fixed point in order to compare various inputs. In this example, the chart shows the general government debt for the year 2018. This is a simple and easy way to see the differences by country for the year 2018.
The second visualization displays a series of separate sparkline charts, each of which represents a country’s debt from 1995 to 2019 as a line. This type of visualization is good for showing many different variables at once over a period of time. An alternative to this could be to represent the variables as lines on the same chart, though that risks getting messy and confusing very quickly if too many variables are involved.
The final visualization is 4D, as it includes the element of time. It is an animated scatterplot that demonstrates how each country’s debt has changed over time. I initially wanted to represent the dataset in a static chart by finding the difference between current global debt and 1995 global debt for each country and representing these numbers on a graph. However, I could not find a chart that would do this analysis for me, and the assignment instructions said to use the downloaded dataset, meaning I couldn’t do the calculations and add them as an additional column. But I found this animated scatterplot, which represents the change in a much more interesting way. The country of focus, Japan, is represented as a darker color in order to stand out. I didn’t really see a need to change the rest of the country colors because I think fading them was sufficient to de-emphasize them. I also purposefully kept the y-axis with a max of 240 because it adds a little drama when Japan is literally almost “off the chart,” which affirms the story being told. This type of chart is great for comparing a single variable to a group of variables, as is being done here, but might not work if each variable needs to be given equal attention.
Reference: https://data.oecd.org/gga/general-government-debt.htm