🚗 Car Insurance Data Analysis

This project explores car insurance trends using Python and visual storytelling. It includes a comprehensive data analysis notebook, an illustrative classic car image, and a well-structured dataset.

📁 Project Structure

📦 car-insurance-analysis/

├── car.jpg # Classic car image used for visuals/branding

├── car_insurance.csv # Dataset with car insurance customer information

├── notebook.ipynb # Main Jupyter Notebook with EDA & modeling

└── README.md # Project overview and setup instructions

🔍 Overview

This project focuses on:

• Analyzing car insurance data to uncover key customer behaviors.
• Performing exploratory data analysis (EDA).
• Visualizing insights using matplotlib and seaborn.
• Investigating potential factors influencing insurance purchases.
• Optional modeling or predictive analysis.

The classic blue Volkswagen Beetle in car.jpg adds a vintage flair to our visual assets.

📊 Dataset

The dataset (car_insurance.csv) includes information like:

• Age, job, marital status
• Education level
• Car ownership and previous claims
• Policy purchase decision

🛠️ Tech Stack

• Python 3.x
• Jupyter Notebook
• Pandas
• Matplotlib
• Seaborn
• Scikit-learn (optional ML section)

🚀 Getting Started

1. Clone the repo:

git clone https://github.com/yourusername/car-insurance-analysis.git
cd car-insurance-analysis

2. Install dependencies:

pip install -r requirements.txt

3. Launch the notebook:

jupyter notebook notebook.ipynb

📃 License

MIT License. Feel free to fork and modify the project!

Feel free to drop a ⭐ if you like the project!