This project focuses on applying network data analysis techniques to study passenger flight data. By utilizing graph theory, applied statistics, and data science, the project aims to gain insights into air transport networks' resilience, robustness, and efficiency. The dataset used consists of domestic flight data from various countries and years, and the analysis is conducted across different graph scales.
Graph Analysis at Different Scales:
- Perform graph analysis at three distinct scales:
- Macro-scale: Conduct statistical analysis on the network.
- Meso-scale: Analyze community structures within the network.
- Node-level: Assess centrality measures of individual nodes in the network.
- Evaluate and discuss the findings from the three graph analysis scales.
- Interpret the implications of the analysis in terms of real-world socioeconomic and engineering aspects of air transport networks.
The dataset, provided via the data folder, comprises domestic flight data from different countries and years.
The related notebook can be found here with all explanations regarding the analysis.