AmirhosseinHonardoust/Market-Basket-Analysis

Python project for Market Basket Analysis. Generates synthetic retail transactions, mines frequent itemsets using Apriori & FP-Growth, derives association rules, and outputs CSVs + visualizations. Portfolio-ready example demonstrating data science methods for uncovering product co-purchase patterns.

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Experimental

This helps retail analysts and marketers discover which products customers frequently buy together. You provide transaction data, and it outputs insights like 'customers who buy X are 5x more likely to also buy Y' through CSV reports and visualizations. This is ideal for understanding purchasing habits and informing product placement or promotional strategies.

Use this if you want to understand co-purchase patterns in your retail transaction data, even if you need to generate synthetic data for demonstration or learning purposes.

Not ideal if you need a real-time recommendation engine or a solution that directly integrates with a point-of-sale system.

retail-analytics market-research product-bundling sales-strategy customer-behavior
No Package No Dependents
Maintenance 6 / 25
Adoption 7 / 25
Maturity 15 / 25
Community 0 / 25

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39

Forks

Language

Python

License

MIT

Last pushed

Oct 16, 2025

Commits (30d)

0

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