From Data to Insight: Explaining Voting Behavior in the German and European Parliaments Using Shiny

This project investigates the voting patterns of members in the German Bundestag and the European Parliament through advanced data science techniques. By applying three different clustering algorithms to voting records and party affiliations sourced from various online platforms, the study aims to uncover voting blocs and informal alliances. The insights are visualized through a Shiny app intended for the general public, providing a user-friendly interface to explore these patterns. Additionally, the findings contribute to academic research by offering a deeper understanding of political alignment and behavior in legislative bodies.