🧁 Bakery Data Lab

A companion data science project to the bakery-manager CLI app. This lab explores real-world analytics, trends, and predictions using transaction and inventory data collected by the bakery system.

---

🧠 Project Goals

• Analyze bakery inventory and transactions with Python & pandas
• Visualize trends using matplotlib and seaborn
• Forecast inventory depletion and sales using basic ML
• Build interactive or exportable reports for the team

---

📦 Tech Stack

• Python 3 (via Anaconda)
• Jupyter Notebook / JupyterLab
• pandas, matplotlib, seaborn
• SQLite (using data from bakery-manager)

Optional:

• scikit-learn for regression or classification
• streamlit for interactive dashboards

---

📁 Project Structure

bakery-data-lab/
├── notebooks/
│   └── transactions_analysis.ipynb
├── data/
│   └── bakery.db  # or CSV exports from bakery-manager
├── scripts/
│   └── connect_sqlite.py
├── README.md
└── requirements.txt  (optional for pip)

---

🏁 Getting Started

1. Clone this repo
2. Open a Jupyter notebook:

jupyter notebook

3. Run transactions_analysis.ipynb to explore sales + expenses

You can also use:

jupyter lab

---

💡 Data Source

This lab uses data generated by the bakery-manager Rust application:

• Inventory (inventory table)
• Transactions (transactions table)
• Recipes and usage (optional in advanced stages)

You can export the SQLite file or write a Rust function to output CSVs for easier import.

---

📊 Example Questions We’ll Answer

• What are my top-selling items?
• Which ingredients are depleting the fastest?
• When should I reorder butter?
• What’s the rolling 7-day revenue?

---

📈 Next Steps

• Add more notebooks to the /notebooks folder
• Link with your bakery-manager project for real-time analysis
• Build a streamlit dashboard version

---

Made with ☕ + 🍞 by Sarah, data baker-in-training 🧁