Introduction

After watching the Tableau Public training videos I was interested in finding a dataset to create a world map visualisation. I began researching data on the United Nations site UN data, however, none of the subjects captured my interested. Upon further research, I discovered the site Kaggle.

Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data. Kaggle provides data sets on a wide variety of subjects, from deaths in Games of Thrones to Hazardous Air Pollutants. I found a data set on World Happiness Report (2015-2017), score and rankings use data from the Gallup World Poll. The score is based answers from participants on the main life evaluation question asked in the poll. The participants rate various factors on a scale from zero to ten, ten being the best possible life and zero being the worst possible.

Visualisation Examples

For this data, I wanted to create visualisations focused on the larger trend over the individual score. I want the user to be able to see the distribution of happiness across all countries with one glance. Using a world map, heat map, or bubble cluster with colour divergence, the user would be able to see the distribution at a glance without having to scroll through a long list of each country and their corresponding happiness score.

Materials

Software:

• OpenRefine
• Tableau Public

Research resources used for this lab were:

• Kaggle (kaggle.com)
• Google
• United Nations (data.un.org)

Methods

1. Clean up data using OpenRefine
2. Import data to Tableau Public
   1. Preview of the data set will be created
   2. Make any modifications to dataset here
3. Open first worksheet
4. Drag and drop fields onto the canvas (white space) or drag and drop the fields onto the column or row dimensions on the top of the canvas
5. Format the visualisation by dragging and dropping fields onto the Marks box
   1. Colour
   2. Size
   3. Label
   4. Detail
   5. Tooltip
   6. Path
6. Create more visualisations by creating new sheets
7. Combine visualisations on dashboard
8. Publish to web
9. Share visualisations using embed link or URL link

Discussion and Results

I created five visualisations: world map, heat map, bar graph, line graph combined, and line graph individual. The world map, heat map, and bar graph display the average happiness score for each country over the span of three years (2015-2017). The line graphs display the individual happiness score for every country for each year available (2015-2017).

Line graph individual shows each country (alphabetical order). While this allows the user to see each line separately, it is a very wide visualisation and very difficult to compare the countries.

Line graph combined shows all the countries layered on top of each other. Despite the difficulty with differentiating individual lines, I prefer line graph combined to line graph individual. Line graph combined provides users with the overall trend at a glance with the option of seeing the individual score by clicking or hovering on the line. To increase readability and usability, I formatted line graph combined using colour divergence (red-green diverting) and size of the line (thinnest).

Formatting is very important to the usability and readability of a visualisation. I consistently formatted all visualisations with colour divergence (red-green diverting). With red representing the lowest score and green the highest score. On the heat map, some country names are only visible when the user hovers over the box due to the length (amount of characters) of the names. I intended to use ISO country codes as aliases to avoid this problem, however, country codes are not always known by users and sometimes not intuitive. For example, the ISO country code for Switzerland is CHE. This is a problem because many users may misinterpret “CHE” for another country such as Chile. Since Switzerland is the happiest country and therefore a focal point of the data, to avoid confusion I used full country names.

I created a dashboard using the world map and line graph combined. Combining these two visualisations allows the user to see the average and the discrete values of happiness for each country in one place. I set the funnel filter on the world map to allow the user the ability to isolate the corresponding country line in line graph combined. There the user will be able to see the happiness score from each year.

Future Directions

Researching other data sets limited the amount of time I was able to dedicate to the World Happiness data. The World Happiness Report was first released in 2012. I would like to continue working with this project by adding data from years 2012-2014. Also, I think it would be interesting to compare depression rates in these countries to see if there are any correlations.