Intriguing Visualizations of Data from World Happiness Reports

A data science project, created by Dhruv Syngol, to visualize happiness data from a wide spectrum of countries

Date Created: June 24th, 2021

Curated by: Dhruv Syngol

The World Happiness Report is a publication of data collected by the Gallup World Poll. Data collected consists of a variety of six different statistics, from GDP per capita to freedom to corruption.

One statistic that the report collects is a Life Ladder Score. The life ladder score is based on the Cantril Ladder Score (on a scale of 10). A higher life ladder score indicates a better life while a lower score indicates a worse life.

Also, the GDP per capitas in the graphs are the natural log of the real GDP per capitas of the countries.

In my first data science project, I wanted to visualize the massive amounts of data collected from the World Happiness Reports over the years in order to present the data in a user-friendly and understandable format. I used the programming language R to achieve my goals.

First, I found two datasets (CSVs) on Kaggle that contained data from the World Happiness Report 2021 as well as data from the World Happiness Report over past years. From that point, I began analyzing, cleaning, and forming creative and eye-catching graphics to illustrate facinating trends in the data.

Visit my GitHub repository to see the code behind my works: https://github.com/dsy5/World-Happiness-Data-Analysis-and-Visualizations.git

Link to Source of Data: https://www.kaggle.com/ajaypalsinghlo/world-happiness-report-2021?select=world-happiness-report-2021.csv

Check out this website to learn more about the World Happiness Report: https://worldhappiness.report/

NOTE: The graphs are best viewed in landscape mode!

We can see that the regions of “North America and ANZ” and “Western Europe” dominate in mean life ladder scores, healthy life expectancy, and GDP per capita.

The regions of “Sub-Saharan Africa” and “South Asia” score low in the following statistics.

For the following graphs, move your cursor on a line in the interactive visualizations to see the year, life ladder score, and country name.

In this graph, we can see that Western European countries have higher life ladder scores than countries that comprise the Commonwealth of Independent States, South Asia, and Southeast Asia.

We see an upward trend in Life Ladder scores in the countries of the Commonwealth of Independent States; however, the trend is inverse for South Asia.

Southeast Asia and Western Europe seem to be stable in their Life Ladder scores over the 10 years.

In this graph, we can see an upward trend in GDP per capita in all regions highlighted in the graph.

Western European countries tend to have a higher GDP per capita.

Similar to the GDP per capita graph, there are upward trends in the regions highlighted for the healthy life expectancy at birth statistic.

Western European countries tend to have high, yet similar healthy life expectancy at birth statistics.

We can also see that countries like Nepal and Kazakhstan have made significant jumps in healthy life expectancy.

For the following graphs, move your cursor on a point in the interactive visualizations to GDP per capita, life ladder score year, region, and country name.

Double-click on a region in the legend to isolate specific points of that region on the graph. You can click on other regions to compare countries in different regions and their respective scores.

Double-click on the graph if you want to zoom out.

In the first graph, I wanted to create a scatter plot with the life ladder scores and GDP per capita on one graph. I plotted each country and filled each point by region.

In this graph, we can see that countries in Western Europe have high GDP per capitas and high life ladder scores (as seen in the top-right corner of the graph).

Countries in the bottom-left corner, including those from Sub-Saharan Africa and South Asia, have lower GDP per capitas and lower life ladder scores.

This graph can help contribute to a conclusion that countries in Western European, North America, as well as Australia and New Zealand, tend to have a better quality of life compared to other countries of the world.

The freedom and social support scores signify the extent to which each statistic impacted beneficial changes in life quality. I wanted to plot these scores for each country and fill each point by region.

Similar to the graph above, we can see that countries in Western Europe and North America and ANZ have more freedom to make life choices and have access to more social support.

Countries in the bottom-left corner have less freedom and social support.

Countries in regions like South Asia are plotted all around the graph and are not strictly clustered like countries in Southeast Asia and North America and ANZ.