Car Sales Data Analysis

Exploratory data analysis on a car sales dataset covering 23,906 transactions across 2022–2023.

Note: This is a synthetic dataset used for EDA practice. Insights reflect data patterns, not real market data.

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Tools Used

• Python
• pandas
• matplotlib
• seaborn
• Jupyter Notebook

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What I Looked At

• Sales by car brand and model
• Most popular body styles
• Regional sales performance
• Dealer performance comparison
• Customer gender and income breakdown
• Car price distribution
• Sales trends over time

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Key Insights

• Chevrolet, Dodge, and Ford are the top 3 selling brands
• SUV and Hatchback are the most popular body styles (over 50% of all sales)
• Austin and Janesville are the highest-performing regions
• 78% of buyers are male — 1 in 5 customers is female
• Car prices range from 1,200 to 85,800 USD, with most sales under 34,000 USD

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How to Run

1. Clone the repo
2. Make sure car_sale_data.csv is in the same folder as the notebook
3. Run jupyter notebook and open Project_Week_1.ipynb

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Dataset

• 23,906 rows, 16 columns
• Covers January 2022 – December 2023