Assignment 2
Bar chart
2021: Top 5 Countries with the highest Government Debt-to-GDP ratio
🎨 Using the color gray to calm down the overall visual impression of the chart and allow the top 5 countries to stand out.
Line chart
1995-2021: Top 5 Countries with the highest Government Debt-to-GDP ratio
🎨 Using the color gray to shift the focus to the top 5 countries.
Part 2: Working with Flourish
Grid of line charts
🎨 A Grid of line charts allows us to visually compare several charts along a shared x and y axes.
📌 Takeaways:
- The General government debt-to-GDP ratio measures the gross debt of the general government as a percentage of GDP.
- The danger of default increases with the debt-to-GDP ratio, which might spark a financial panic in both local and global markets.
- Japan has the highest national debt in the world.
Custom Visualization
Circle packing chart
📌 Takeaways:
- Bigger circles depict higher debt-to-GDP ratios.
- We can infer that Japan and Greece continue to be at the center of the map during most years depicting the hight debt-to-GDP ratios.
🎨 Crafting for clarity
- The interactive chart shows an annual snapshot of the different countries, one year at a time. Thus, we can interpret how the positioning changed over time.
- In this manner, we can reduce eye travel compared to the grid of line charts.
🎨 Selecting chart types
- A circle packing chart allows us to visualize large datasets faster.
🎨 Color
- Drawback? I tried to adjust the color scale to match the size of the circles to make it faster to interpret. But Flourish doesn’t support color by value for this visualization type. This made me opt for a heatmap.
Heatmap
📌 Takeaways:
- We can infer that the OECD average has increased over time, especially in the past few years.
🎨 Color
- A heatmap allows us to visually compare categorical data faster with the help of color.
- The color scale is chosen keeping in mind that red is associated with negativity.
- In this case, darker colors symbolize the higher risk factor of countries not being able to pay the government debt.
🎨 Crafting for clarity
- If the reader is interested in a more precise value, we have pop-ups to display additional information.
- The general audience may not grasp Alpha-3 country codes quickly which is why I merged an additional data source from Kaggle to display the country names and improve readability.
🎨 Selecting chart types
- This map is static and less busy compared to the circle packing chart which can allow the user to explore trends at their own pace.
Comparing different methods of visualization
Bar chart
- Advantage: The bar chart is easier to grasp for the general audience since it is commonly used.
- Disadvantage: However it isn’t the best choice for representing trends over time.
Grid of line charts
- Advantage: We can visualize all the country trends over time.
- Disadvantage: Shared x and y axes increase eye travel and key information doesn’t stand out.
Heatmap (Custom visualization)
- Advantages:
- All the country trends over time can be displayed with minimal eye travel.
- The color scale aids the user to pick up on patterns faster.
- In this case, darker colors symbolize the higher risk factor of countries not being able to pay the government debt.
- The general audience may not grasp Alpha-3 country codes quickly which is why I merged an additional data source from Kaggle to display the country names and improve readability.
- Future improvement:
- I tried to sort the countries based on average debt-to-GDP ratio values over the years too.
- However, Flourish didn’t have an option to do so. Perhaps, a Python data visualization will support the vision I had.
Bonus: I’ve created a country heatmap visualization with Tableau which is much more easier to grasp for the user if they are well-versed with geography 😛
Data Source Acknowledgement
- OECD: This dataset provided the debt-to-GDP ratio for different countries from 1995-2021.
- Kaggle Dataset: This dataset helped me to map country names to the Alpha-3 country codes.
Part 3: Working with Tableau
Country Heatmap
Heatmap