In this project we analyzed the World Happiness Report to gain insights into the factors affecting the happiness of countries around the world. We used Python and several data analysis libraries such as Seaborn Pandas Matplotlib Plotly Pyspark and Anaconda to clean analyze and visualize the data.
The happiness scores and rankings are calculated using data from the Gallup World Poll. The World Happiness Report dataset includes happiness scores and rankings for 156 countries, as well as several socio-economic, health, and environmental factors that are believed to contribute to happiness. We used this data to perform a detailed analysis and gain insights into the factors affecting happiness across different countries. The scores are derived from nationally representative samples spanning from 2015 to 2019, and Gallup weights are applied to ensure the estimates are representative. The subsequent columns following the happiness score indicate the degree to which six factors - economic production, social support, life expectancy, freedom, perception of corruption, and generosity - contribute to higher life evaluations in each country compared to Dystopia, a hypothetical nation with values equivalent to the world's lowest national averages for each of these factors. While these factors do not affect the total score reported for each country, they do shed light on why certain countries are ranked higher than others.
We analyzed the data using various statistical and data visualization techniques. We used Pandas to clean and manipulate the data, Seaborn and Matplotlib to create visualizations, and Plotly to create interactive maps. We also used Pyspark to process large datasets efficiently. We looked at factors such as GDP per capita, social support, life expectancy, freedom to make life choices, generosity, and perceptions of corruption to identify the key drivers of happiness across different countries. We visualized the data using various graphs and charts, including scatter plots, bar charts, and heatmaps.
Our analysis shows that the factors that contribute to happiness vary widely across different countries. For example, while social support and freedom to make life choices are important factors for overall happiness, perceptions of corruption have a greater impact on happiness in some countries than others. Overall, our analysis provides valuable insights into the complex and multifaceted nature of happiness and highlights the importance of considering a range of factors when studying happiness.