A approach to cost analysis of shrimp fishery in Chubut through data science techniques

Abstract

This study analyzes the direct costs and production of shrimp fishing (Pleoticus muelleri) in the province of Chubut during the 2022 season, focusing on the operations of freezer-trawler vessels. Using real-world datasets provided by a local fishing company, a data analysis methodology was developed that included data structuring, cleaning, and integration of operational and unloading records, employing data science tools such as Python and Google Colab. Visualization techniques, exploratory analysis, and correlation metrics were applied to identify cost patterns, operational efficiency, and idle capacity. The results show a strong correlation between catch volumes and certain operating costs, as well as significant efficiency differences among vessels. The study also raises key questions regarding port logistics and operational planning. This methodological approach aims to provide analytical tools applicable to the productive and economic management of the fishing sector.