AmirhosseinHonardoust/Coffee-Shop-Profit-Predictor
Predict the profitability of potential coffee shop locations using SQL and Python. Combines data engineering with feature-rich regression modeling, visual analytics, and business insights to support data-driven site selection and retail decision-making.
The workflow combines SQLite for feature engineering (demand adjustment, price-income interactions, competition-normalized metrics) with ElasticNet regression in scikit-learn, producing interpretable profit predictions alongside diagnostic visualizations. Outputs include model coefficients, residual analysis, and ranked feature importance to guide site-selection decisions by quantifying the impact of rent, local events, foot traffic, and competition dynamics on monthly profitability.
Stars
43
Forks
—
Language
Python
License
MIT
Category
Last pushed
Oct 23, 2025
Commits (30d)
0
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