Flourish is a free, web-based data visualization tool with many pre-built templates that work to steer users toward implementing good design principles. Each of the visualizations below was made using Flourish and the OECD government debt data.
The grid of line charts below displays time series data of the debt-to-GDP ratio for each country included in the OECD data. The visualization consists of several subplots, each of which represents a unique country. Separating each country allows the viewer to more easily see trends for distinct countries, while the shared axes allow for these trends to be compared between countries.
Line charts are a classic method of displaying time series data as the lines. However, when there are many categories included in one plot, the line chart can become cluttered. As such, it is helpful to highlight specific data of interest. In this chart, I highlight the average debt-to-gdp ratio over time for all reported countries.
Whereas the plots above visualized the full dataset, this dot plot focuses on a subset of the data. This plot worked to convey the change in Debt-to-GDP ratio for individual countries between 2010 and 2019.
Like the dot plot above, the slope chart shows provides information for a subset of the data. While the plot looks similar to a line chart, the slope chart shows more general trends by only including data from certain years and connecting those years with slopes that represent the average total change in debt-to-GDP ratio in that time. The slope chart below shows the change in debt-to-GDP ratio over five year intervals and highlights the OECD average.
There are many ways to visualize data, each of which may be appropriate for depending on the type of data, the audience, and the main point of the visualization. At the same time, there are several common themes throughout the visualizations that help create clean, easy to read visualizations and unite the visualizations with a common theme. Similar colors are used in the visualizations to keep the theme consistent. Grey is used as a background color against which other information can be contrasted because its neutral nature helps other colors stand out. Red, a bright color with good contrast, is used to represent the debt-to-GDP data that the viewer should be focused on. Red is also a color associated with debt and loss of money (think ‘in the red’), so it is a logical color to use for visualizations about debt as viewers will likely already have a pre-existing association. For the dot-plot, a dark maroon and dark grey-blue were used to represent the two years as they fit with the color scheme and the relatively equal intensities of the colors encourage the viewer to consider the colors equally important.
Each of the visualizatoins also includes unique aspects that help them clearly convey certain aspects of the data. The bar chart provided by OECD is useful for visualizing the debt-to-GDP ratio for individual countries on a yearly basis. While the remaining visualizations each contain a time series component, this bar plot provides a snapshot of a period in time where the emphasis is on the countries (categories) and their debt-to-GDP ratio at a point in time rather than showing how debt-to-GDP ratio changes over time. This type of plot makes it easy to compare the ratio between countries because there are not as many points to consider as there are in the time series focused plots. The grid of line charts separates each country into its own subplot, so that the time series values for debt-to-GDP ratio are easier to distinguish for individual countries. This plot makes it easy to find a few countries of interest, and see how their debt-to-GDP ratio changes over time, but because the lines are in different subplots, it is more difficult to compare between countries. The next visualization consists of a simple line chart, which is a classic way of displaying time series data. However, the large number of countries included in the dataset can make the line chart look cluttered if they are all depcited in bright colors, so a highlight of the average debt-to-GDP ratio was placed on the chart with the ability to select specific countries of interest for comparison. Compared to the grid of line charts, it is more difficult to distingush the trends for individual countries over time, but it is far easier to compare between countries of interest, or in this case, compare countries of interest to the average.
Lastly, I included two additional visualizations that focus on subsets of the data. The dot plot shows the change in debt-to-GDP ratio between 2010 and 2019 for each country. While not presenting individual countries as distinctly as the grid of line charts, the dot plot does provide an easy interface for viewing trends for a specific country. Additionally, the dots help show change over time for the countries. Dot plots can become messy when including data for multiple dates, but when there are only two dates of interest, they share some advantages from the grid of line charts and the standard line chart in that they allow for easy comparison while also providing for distinguishability between countries. The slope chart represents a subset of the data similarly to the standard line chart, but rather than showing all the variation in the recorded data, the slope chart utilizes lines that represent the average rate of change between two time periods, which allows the chart to summarize trends over distinct time periods within the data. Slope charts provide for easy comparison between categories, but can become cluttered much like standard line charts. To address this, the OECD average was highlighted on the chart above to bring attention to the average trends in debt-to-GDP ratio among OECD countries for five year periods between 2009 and 2019.
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