Shivam

Telling Stories With Data - Assignment 2


Visualizing Government Debt


Part 1: Working with web-based visualization tools and data

General Government Debt for 2021

General government debt-to-GDP ratio measures the gross debt of the general government as a percentage of GDP.




Dataset Explanation 📝

  • The data for the general government debt for the various countries is open source and is collected from the Organization for Economic Co-operation and Development (OECD).
  • The general government debt-to-GDP ratio measures the gross debt of the general government in a country as a percentage of its GDP. This is a crucial indicator of the financial sustainability of the government.
  • The data is reported yearly for each country and ranges from 1995 to 2021. For some years, the government debt to GDP ratio was not reported for a few countries.
  • A few columns from the downloaded data were irrelevant, as they all were filled with the same values, top to bottom. Hence, these rows were not considered in the upcoming visualizations below.

Insights (very general) from the Visualization 📊

  • The above (guided) visualization shows a simple Bar Chart visualization depicting the government debt across various countries for the year 2021. It was built using OECD.
  • We learn that Japan's debt is way higher than that of other countries for 2021, followed by Greece and Italy. On the lower end, Estonia and Luxembourg have the most negligible debts.
  • The remaining countries are sorted based on increasing government debts from Estonia to Japan. OECD helped build an interactive bar chart wherein hovering over particular bars would highlight government debt (as a % of GDP) for that particular country.

Citations


Part 2: Working with Flourish

Visualization 1: Grid of Line Charts (Guided)

Government Debt across the Globe (1995 to 2021)

Japan (JPN) is going through tough times - Shows the highest increase in Government Debt



Insights from the Visualization 📊

  • The above (guided) visualization shows a Grid of Line Charts visualization depicting the government debt across various countries for the period 1995 to 2021. It was built as an initial step for using and getting to know Flourish.
  • The grid has multiple small line charts (one for each country). The lines depict the change in Debt to GDP ratio from 1995 to 2021 for every country.
  • Being small line charts with a lot of information, it is hard to interpret the exact message; however, on a general overview, I see Japan (JPN) is going through tough times. It shows the highest increase in Government Debt from 1995 to 2021 and has the highest government debts in the world for 2021.
  • Information from the line charts of other countries is quite less interpretable from the complexity of the graph. However, being an interactive visualization, one can hover over the lines to know the Government Debt to GDP ratio for a country for the desired year.

Citations


Visualization 2: Line Chart Race Visualization (Self-Designed)

Government Debt of Top Higher Studies Destinations for Indian Students (1995 to 2021)

USA faces the highest rise in Debt-to-GDP ratio among the top three study destinations


Choice of Visualization 📈

  • The grid of lines chart in Visualization 1 had a lot of things to convey in the small space. With a considerable number of countries and a small line chart for each one of them, it was challenging to compare the data for each country and extract the relevant information.
  • A line chart is helpful with such data, which has numerical values varying with time. However, the miniature versions of many line charts in Visualization 1 were not helpful. Hence, my first thought was to subset the data and focus on particular countries to convey the relevant information.
  • Being an international student in the USA, I decided to visualize government debts of the top higher study destinations (countries) for Indian students. Based on the ground reality of Indian students, I shortlisted to visualize the following countries: United States of America (USA), Canada, Australia, United Kingdom (UK), France, and Germany. It would help aspiring Indian students compare the government debts of the countries they are looking forward to for pursuing their higher education.
  • I had six countries and wanted to show how their government debts varied from 1995 to 2021. A simple static line chart with six lines (one for each country) would have been sufficient; however, upon exploration, I came across the Line Chart Race visualization, and it seemed perfect!
  • Contrary to showing the six static lines, the Line Chart Race visualization will form them dynamically, and it would be pleasing to the eyes of the audience. Additionally, it has the 'Ranks' tab to show how the six countries' rankings change over the years. Moreover, the 'Replay' button adds a cherry on the top :)
  • The interactive highlight option in the Line Chart Race visualization is also appealing. It helps highlight a line for a particular country to understand its trend better.

Choice of Color 🎨

  • Initially, I used the six default colors for the lines (one for each line). However, with the default color choice, the graph looked complex, and I could not get the message out. Thus, I decided to highlight the top three study destinations for Indian students - USA, Canada, and Australia, and hide the remaining three countries in the background (using the all-time favorite for such use cases - the gray!).
  • For USA, Canada, and Australia, I colored their lines with one of their national colors. Each of them had multiple national colors. Hence, I chose ones that would be distinct from the others and visually appealing (USA - Blue; Canada - Red; Australia - Gold).
  • The country names and government debts for the respective years were colored the same color as the six lines to display consistency.

Crafting for Clarity 💬

  • I expanded the abbreviated names of the six countries. However, the USA's long name did not fit well. Moreover, its abbreviated name was self-explanatory. Hence, I decided to keep the abbreviations (for countries) that are more famous and could be easily understood and expand the names for the rest.
  • The X-axis and Y-axis were intentionally not labeled as they were self-explanatory from the graph's title and would help avoid redundancy.

Insights from the Visualization 📊

  • Among the top three higher study destinations (USA, Canada, Australia) for Indian students, the USA faces the highest rise in government debts across the past years from 1995 to 2021.
  • Canada, Australia, and Germany have tried to maintain government debts over the past years.
  • The COVID-19 phase hit every country hard since there was a considerable spike in government debts for each country from 2019 to 2020. However, with recovery from COVID-19 since the start of vaccinations, each of these study destinations has seen a reduction in their government debts.
  • Upon minute observation, I find that from 1995 to 2021, the UK has seen the highest increase in government debts (among all six study destinations).

Citations


Part 3: Working with Tableau


Insights from the Visualization 📊

  • The above (guided) visualization shows the Highlight Tables visualization depicting the government debt across various countries for the period 1995 to 2021. It was built as an initial step for using and getting to know Tableau.
  • Since the locations were sorted based on descending average values of the debt-to- GDP ratio for 1995 to 2021, it was easier to identify that Japan, Greece, and Italy had more debt-to-GDP ratio than the other countries.
  • Moreover, color coding help understands the general trend of debt-to-GDP ratio across the various countries from 1995 to 2021.

Citations


Part 4: Comparing the above Visualizations

  • Bar Chart: With the bar chart, I could depict the debt-to-GDP ratio data for only 2021 for the respective countries. It was good, but I could not compare the trend for the debt-to-GDP ratio for the countries from 1995 to 2021. This was a major drawback.
  • Grid of Line Charts: On the contrary, the grid of line charts helps to compare the trend of the debt-to-GDP ratio for the countries from 1995 to 2021. But with so many countries and different line charts for each one of them, it brought in complexity and made it hard to grasp the message at first sight.
  • Highlight Tables: The Highlight Tables visualization was more detailed than the Bar Chart and the Grid of Line Charts. It used color coding and sorting to give out the message. Moreover, it had numbers on each cell to show the corresponding debt- to-GDP ratio. It was better than the Bar Chart and the Grid of Line Charts as it conveyed much more quickly. Such visualization can be helpful in cases where details for each data point are essential, along with conveying the general message.
  • Line Chart Race: The visualization of the Line Chart Race was adequate for the message it had to convey. It was simple, attractive, and pleasing to the eyes. The "race effect" in the lines and the "Ranks" tab helped easily understand the trend in the debt-to-GDP ratio across the years. The color choice was practical as well to further highlight the main message.

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