The Global Road Accident Analysis aims to explore and understand patterns, causes, and impacts of road accidents worldwide. By analyzing large datasets, the study highlights key factors like time of day, weather conditions, road types, vehicle involvement, and casualty rates. The goal is to uncover meaningful insights that can help in improving road safety policies, optimizing emergency response strategies, and ultimately reducing the number and severity of accidents globally. Through visualizations and statistical methods, this analysis provides a comprehensive view of accident trends across different regions and environments.

The Global Road Accident Analysis aims to explore and understand patterns, causes, and impacts of road accidents worldwide. By analyzing large datasets, the study highlights key factors like time of day, weather conditions, road types, vehicle involvement, and casualty rates. The goal is to uncover meaningful insights that can help in improving road safety policies, optimizing emergency response strategies, and ultimately reducing the number and severity of accidents globally. Through visualizations and statistical methods, this analysis provides a comprehensive view of accident trends across different regions and environments.

Learning excercise

This dataset works with different columns like car names, manufacturing year, fuel type, car age etc. Had cleaned the data and performed some different types of interpretation and visualization.

Extended tidyvrese code was added on the MP's tidyverse code after the average delay by day of the week

PS6

PML_M10

population analysis of indian states