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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.

📌 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

📂 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.)

⚙️ Tech Stack & Tools

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

📊 Key Visualizations

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

🚀 How to Run

  1. Clone the repository
  2. Install dependencies: 
    pip install pandas seaborn matplotlib numpy