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The term happiness has been defined as‘‘the experience of joy, contentment, or positive well-being, combined with a sense that one’s life is good, meaningful, and worth-while”(Lyunomirsky 2008).It is an universally accepted idea that everyone desires happiness. Traditionally, income, health, and family are closely related to happiness. However, there is limited research on how additional social factors, such as freedom, trust and openness of country impacts one’s level of happiness. Knowing the importance and impacts of these three factors can help policy makers revise and change policies to enhance the level of happiness of a country. The aim of this software is to detect the correlation between trust, freedom, openness and happiness, and how happiness and openness scores are distributed throughout the world, and how these three social factors effected the happiness score in different regions, especially in the 10 countries that have the highest and lowest happiness scores. The happiness datasets from Gallup World Poll for each country within a 3-year period (2015-2017) and openness dataset from the 2015 Global Open Data Index were used for analysis. In this study, the main tools used are Python and Python packages. The study results are useful to government officials in revising policies to enhance the level of happiness of a country. This software cleans the four datasets, merges them into one dataset, and visualizes the relationship and changes of trust, freedom, openness and happiness scores.
Happiness Score, Correlation Analysis, Data Mining, Python, Visualization
Happiness Score, Correlation Analysis, Data Mining, Python, Visualization
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