The Reddit Is Beautiful subreddit has a monthly visualization challenge where you are given a dataset and challenged to visualize it – the June 2019 challenge was the World Happiness Rankings.
Approach
I used 2 tools to approach this challenge
- Python – a simple way to combine the 3 sheets that came part of the dataset
- Tableau – to visualize the newly combined data
Analysis
The best way to interact with the visualization is by heading over to Tableau Public and viewing the visualization story in Full Screen Mode.
2017 World Happiness Rankings
A filled world map with the world happiness rankings of 2017. As a added feature, I used the data from 2015 and 2016 to find which year the country was the happiest.
Most & Least Happiest Countries of 2017
Let’s take a look at the most and least happiest countries of 2017. In addition to the rankings, I also took the countries that improved the most and regressed the most as an indicator of happiness. To visualize this, I used a combination of maps (to show the countries on a map) and bar charts (to show the rank progression – plotting the change in rank from 2016 to 2017).
Happiness Rank Movement
To get a better picture of the happiness ranks, it was important to chart the happiness rank journey of the top 10 countries from the 2017 list. The color popularity for new cars visualization from sirvizalot is an excellent starting point for anyone who wants to learn how to leverage this type of visualization.
Happiness Scores
Now that the 2017 data has been visualized, it was important to see how the happiness values have shifted over the course of 2015 – 2017. The best way to do that was with a box and whiskers chart.
Conclusion
I really like the monthly challenges that the subreddit runs as it gives me a chance to work with a variety of tools and flex those data muscles outside the confines of the 9-5.