A Data Science Perspective on European Aviation: Measuring Scheduling Asymmetry Across Carrier Types

Structured aviation datasets increasingly enable empirical analysis of airline behavior at the route level.While prior research on European aviation has addressed pricing, network topology, and connectivity, the temporal dimension of route operation, specifically how flights are distributed across the days of the week, remains underexplored as a measurable feature.This research presents a data science framework for quantifying scheduling asymmetry in European air routes, applied to a publicly available dataset of 18,111 routes, which was reduced to 16,094 after preprocessing.A normalized scheduling asymmetry score is determined for routes from binary weekly availability vectors and compared across low-cost carriers (LCC) and full-service carriers (FSC) using exploratory analysis, descriptive statistics, and non-parametric hypothesis testing.Only 39.2% of LCC routes operate on all seven days, compared to 55.4% of FSC routes, and the difference in scheduling asymmetry between the two groups is statistically significant under a Mann-Whitney U test.LCC routes exhibit higher scheduling asymmetry and more limited weekly coverage than FSC routes.A strong negative Spearman correlation between asymmetry and weekly frequency further confirms that routes served on fewer days tend to be much more uneven.The analysis also identifies a price paradox in which routes operating fewer days per week carry higher median fares, consistent with market concentration effects.These findings are especially useful for airlines, airport management, tourism boards, and regulators seeking to optimize route planning and regional connectivity.