Welcome to my submission for Task 5 of the Data Science Internship at Prodigy Infotech. In this task, I have Analyze the traffic accident data to identify patterns related to road condition, weather, and time of day.
The dataset used for this task is Traffic accident_dataset.This dataset contains information about traffic accidents, including driver and casualty demographics, vehicle types, accident causes, and severity of injuries. It includes features such as the time of day, day of the week, driver's age, educational level, driving experience, vehicle movement, and details of any casualties involved. The dataset can be used to analyze trends in traffic accidents, risk factors, and potential areas for safety improvements.
- Jupyter notebook
- Pandas
- Numpy
- Matplotlip & Seaborn for visualization
- scikit learn
- imbalanced.learn
During the Analysis, I performed the following steps:
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Data Cleaning: Checked for missing values, duplicates, and outliers in the dataset and handled them accordingly.
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Visualization: Created a Sub Plot, Count Plot, and many different types of charts, plots to Analyze traffic accident data to identify patterns related to road conditions, weather, and time of day.
This project demonstrates the power of data-driven insights in addressing real-world issues, such as road safety and accident prevention. By utilizing detailed traffic accident data, we can identify patterns and trends that help prioritize interventions, improve traffic regulations, and ultimately reduce the number of accidents and casualties on the road.
While the current analysis provides valuable insights, the potential for further research in this area is vast. With more comprehensive data and advanced analytical techniques, future projects can make even more significant contributions to traffic safety and public policy.
Thank you for reviewing my submission!
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