TRAFFIC ACCIDENT DATA ANALYSIS

Abstract

Traffic accidents are a major public safety problem that cause loss of life, injuries, and property damage every year. The purpose of this project is to analyse traffic accident data in order to identify patterns, causes, and possible prevention methods. In this project, accident data is collected and analysed using data analysis techniques to understand how factors such as road conditions, weather, time of day, vehicle type, and driver behaviour contribute to accidents. The analysis is performed using the Python programming language with data analysis libraries such as Pandas, NumPy, and Matplotlib. These tools help in cleaning the dataset, processing information, and visualizing accident trends through graphs and charts. The results of this study help in identifying high-risk areas, peak accident times, and major factors responsible for accidents. This information can be useful for traffic authorities and government agencies to take preventive measures such as improving road safety rules, better traffic management, and public awareness programs. The main goal of this project is to use data analysis techniques to improve road safety and reduce the number of traffic accidents by making data-driven decisions