Python_Project

🚦 Traffic Accident Data Analysis using Python

This project is a data analysis and visualization task using a real-world traffic accidents dataset. It explores patterns, trends, and critical insights to help understand factors that lead to different types of accidents.

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📌 Project Overview

The goal of this project is to:

• Perform Exploratory Data Analysis (EDA) on traffic accident data
• Identify key factors that influence accident severity
• Visualize the impact of conditions like weather, lighting, and damage level
• Use statistical plots like KDE plots, bar charts, and correlation heatmaps

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📂 Dataset

File: traffic_accidents.csv

This dataset includes columns such as:

• Crash Severity
• Weather Condition
• Lighting Condition
• Damage Level
• Crash Type
• Speed Limit, etc.

(Use df.columns in code to list all columns.)

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⚙️ Tech Stack & Tools

• Python 3.x
• Pandas – for data cleaning and manipulation
• Matplotlib & Seaborn – for data visualization
• NumPy – numerical operations

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📊 Key Visualizations

• KDE plots to analyze distributions (e.g., crash severity)
• Bar plots to compare categories like damage levels
• Correlation matrix for numerical attributes

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🚀 How to Run

1. Clone the repository
2. Install dependencies:

   pip install pandas seaborn matplotlib numpy