Day 4 has arrived and we are all pretty tired. As usual, we had our presentations in the morning and then we were given our challenge. As the title suggest we were given data on the world happiness index and, the challenge is to find other indicators that may/may not indicate a correlation and visualise this. The only catch is, we have to use Power BI. This should be interesting.

Lessons from Day 3

Again, time-boxing. My goal was to try and finish it within the business day however, I was not able to achieve this however, I did finish a lot earlier than usual. Again, for Day-4 my goal will be to have everything finished by 5PM.

Data perp

Todays, data prep wasn’t very intense at all. As the happiness index data was already provided to us, and it was just a matter of time before we joined our data that we found to the index chart. I ended up looking at the expenditure per capita of countries and to see if there is a correlation. In other words, when there is a higher level of investment in healthcare, do people tend to be more happy. I will share a quick snapshot of the workflow:

  The top workflow is cleaning and reshaping the data the way I want it, and then joining them together. I also thought about grouping the countries by continents, and so I was able to get data for that and then join on the country name and code. Furthermore, I also wanted to know weather higher %GDP spend towards healthcare could be the reason why people are happier hence, that data was available and the same process was used to clean and join.

Power BI

Above is the landing page of my dashboard. Its split into just three sections:

  1. The first page simply ranks the countries (only by top 10) by happiness index and the highest expenditure, and you can drill through on each chart to get a more in depth-understanding of how the ranks have changed over time as well as the spending as well.
  2. Is the scatterplot which shows the relationship between the happiness index and average spend per capita. From what I am able to see there is a positive correlation between the average spend per capita, and happiness. Furthermore, the tooltips will also gives information on the average percentage contribution of GDP to healthcare per year as well. Since, countries with higher percentage have the luxury of being able to put away more for healthcare.

Today’s goal was about getting getting time-boxing correct. And I have achieved that. I managed to get everything I wanted and needed to get done in the allocated business day.

All there is left to do is present the dashboard, and get on with our final day of dashboard week.

The Data School
Author: The Data School