Data Visualization 2

Includes Assignment Content

OCED Data

Beeswarm Plot (Raw Data)

AUSAUTBELCANCHECHLCOLCZEDEUDNKESPESTFINFRAGBRGRCHUNIRLISLISRITAJPNLTULUXLVAMEXNLDNORPOLPRTSVKSVNSWETURUSA199619982000200220042006200820102012201420162018

Explanation

The data visualization above display a beeswarm plot, which “distributes elements horizontally avoiding overlap between them and according to a selected dimension” (RAWGraphs). The data represented is “government debt by country for 1995 - 2018”, with each circle demonstrating the amount of debt (the bigger the circle the more debt the country holds). This data visualization is not effective. Therefore, I will present a secondary data visualization below that paints government debt in a comprehensible manner.

Area Graph (Raw Data- 2nd Data Visualization)

.996.998:02.002.004.006.008.010.012.014.016.018JPNGRCITABELCANUSAPRTFRAAUTHUNESPGBRDEUNLDSWEISRIRLFINDNKPOLSVKSVNAUSNORISLCHECZELTULVAMEXLUXCHLTURESTCOL

Explanation

Here is an Area Graph that provides effective data comparison. For each country there exists a linear line that represents area. Here the thickness of the line determines the amount of debt. For example, Ireland starts thin eventually increasing in weight where the latter half of the graph towards 2018, ultimately showing debt fluctuation. In terms of the logistics of the visualization:

  1. I copied the width (900) and Height (1500) from the beeswarm
  2. Implemented padding (10) to create some division between countries
  3. Centered value
  4. Used a monochromatic color scheme to avoid the “rainbow” effect and help visualize the countries with the most debt in darker colors and lightening it up as debt decreases. To distribute evenly, I divided the countries into seven groups based on the hierarchy of ascending debt making each group consist of five countries, altogether a total of 35 countries.
  5. Ordered the value in ascending fashion to convey the countries with the largest debt on top.

Overall, this was the only graph on Raw Data that convincingly conveyed debt, however, not error free since I was not able to fix the x-axis coding issue to display the appropriate year values.

Comparisons (Beeswarm vs Area)

There exist many variations on visually presenting data. Raw Data offers 21 different types of visualizations that range from dispersion to time series. For this particular assignment we had to work on a “Beeswarm plot” (a distribution graph) and an alternative choice, mine the “Area Graph” (classified as a time series).

In comparing both graphs they utilized shape/weight to articulate value. With the Beeswarm Plot, the circle’s size indicated debt, while the Area Graph line thickness was used to convey debt. Similarly, time is a key factor in both graphs. However, for my choice graph, I was not able to correct the time value like I did for the Beeswarm Plot, mainly due to my coding inexperience. In terms of color, the Beeswarm plot was left in black and white due to instruction, while with the Area Graph I “…used a monochromatic color scheme to avoid the “rainbow” effect and help visualize the countries with the most debt in darker colors and lightening it up as debt decreases. To distribute evenly, I divided the countries into five groups based on the hierarchy of ascending debt making each group consist of six countries, altogether a total of 35 countries.” With this dataset the best way to properly convey is utilizing a simple bar graph such as the OCED example. Since that was not an option, I ultimately went with the area graph because it resembles a bar graph but adds the feature of size/shape/weight into the equation to help reinforce the concept of debt: The bigger the debt, the bigger the line and vice versa. However, because of coding issues with the years, there exists error, due to the Area Graph dealing strictly with dates and not showing numeric values of the debt (which happens on the Beeswarm Plot).

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