CIA-Country-Analysis-and-Clustering

This study conducts a comprehensive analysis of socioeconomic factors across countries worldwide, examining indicators such as population, area, density, migration, infant mortality, GDP per capita, literacy, phone usage, arable land, climate, birth and death rates, and economic sector distribution. It reveals significant variations in population density, infant mortality, and GDP per capita, showcasing diverse socio-economic landscapes. Moreover, it scrutinizes the geographical distribution of arable land and economic structures, highlighting the roles of agriculture, industry, and services in each country's development. The study offers a concise overview of crucial socio-economic indicators, providing insights into global demographic and economic dynamics. According to the testing results, K-means with PCA emerged as the superior clustering method, achieving a fair clustering with a silhouette score of 0.4904. Agglomerative clustering demonstrated better performance when clustering countries based on specific features, such as GDP per capita and phone usage, as indicated by the higher silhouette score of 0.6743.