INTERNATIONAL AIR PASSENGER TRANSPORT: A COMPARATIVE DATA ANALYSIS FOR THE YEARS 2010, 2015 AND 2020

Abstract

International air passenger transport is a strategic element of global mobility, directly influenced by economic, social, and health factors, highlighting the need for comparative analyses capable of understanding its dynamics over time, especially in the face of disruptive events. This study aims to comparatively analyze the behavior of international air passenger transport in the years 2010, 2015, and 2020, identifying patterns of growth, contraction, and impacts resulting from external factors, with emphasis on the effects of the COVID-19 pandemic. To this end, a data science methodology based on the OSEMN process is applied, encompassing the stages of obtaining, cleaning, exploring, modeling, and interpreting data from publicly available databases, using statistical techniques and diagnostic analyses, such as drill-down. Thus, it is observed that, between 2010 and 2015, there was an average growth of approximately 22% in the volume of international passengers, driven by globalization and the expansion of air routes, especially in Europe and Asia. Conversely, in 2020, a contraction of over 60% was identified, associated with the restrictions imposed by the pandemic, in addition to the loss of historically observed seasonal patterns. This allows us to conclude that, although the sector shows a long-term expansion trend, it remains highly vulnerable to exogenous events, highlighting the importance of data science as a strategic tool to support decision-making in complex and dynamic scenarios.