In this project, I focused on analyzing traffic accidents in the Autonomous City of Buenos Aires (CABA) from 2016 to 2022. The objective was to uncover patterns and trends, helping inform policy decisions to improve road safety.
Utilizing Python, SQL, and Power BI, I conducted an in-depth analysis that included ETL processes, exploratory data analysis (EDA), and the creation of key performance indicators (KPIs). The project highlighted temporal trends, geographic distributions, and the demographics most affected by accidents.
One of the project’s major findings was a noticeable increase in accidents up until 2019, followed by a decline during the pandemic years of 2020 and 2021. Moreover, the data revealed that motorcycles are disproportionately involved in severe accidents, particularly on avenues.
The final deliverable included a comprehensive dashboard with visualizations and a set of recommended KPIs aimed at reducing accident fatalities by 10% and motorcycle-related deaths by 7% over the next year. These insights are intended to guide public policy and safety initiatives, ensuring that efforts are focused where they are most needed.