RetailPulse 📊

RetailPulse is a Django-based analytics dashboard designed for retail managers to visualize sales trends, monitor inventory health, and forecast peak shopping hours. It leverages Pandas for data aggregation and Matplotlib for generating server-side visualizations.

🚀 Features

• Interactive Dashboard: A centralized view of key performance indicators (KPIs) like Total Revenue, Items Sold, and Top Selling Categories.
• Data Visualization:
  • Revenue by Category: Bar chart comparing performance across product categories.
  • Monthly Trend: Line chart tracking revenue growth over the last 12 months.
  • Peak Shopping Heatmap: A heatmap displaying sales density by "Day of Week" vs. "Hour of Day" to identify busy periods.
• Inventory Management: Real-time Low Stock Alerts that flag items falling below their reorder point.
• Data Export: Download detailed sales reports as CSV files for offline analysis.
• Automated Data Seeding: Includes a custom management command to populate the database with realistic dummy data for testing.

🛠️ Tech Stack

• Backend: Python 3, Django 5.0+
• Data Analysis: Pandas
• Visualization: Matplotlib (Agg backend)
• Frontend: HTML5, Bootstrap 5.3
• Database: SQLite (Default)

📦 Installation Guide

Follow these steps to set up the project locally.

1. Clone the Repository

git clone https://github.com/YourUsername/RetailPulse.git
cd RetailPulse

2. Create a Virtual Environment

It is recommended to use a virtual environment to manage dependencies.

# Windows
python -m venv venv
venv\Scripts\activate

# Mac/Linux
python3 -m venv venv
source venv/bin/activate

3. Install Dependencies

Install the required packages listed in requirements.txt.

pip install -r requirements.txt

4. Database Setup

Apply the migrations to set up the database schema.

python manage.py makemigrations
python manage.py migrate

🌱 Data Seeding

This project includes a custom command to generate realistic test data (50 products and 600+ sales records). You must run this command to see data on the dashboard.

python manage.py seed_data

Output: "Successfully created 50 products and 600 sales."

▶️ Running the Application

Start the local development server:

python manage.py runserver

Open your browser and navigate to: 👉 http://127.0.0.1:8000/

📂 Project Structure

RetailPulse/
├── manage.py                   # Django CLI utility
├── requirements.txt            # Project dependencies
├── db.sqlite3                  # Database file
│
├── RetailPulse/                # Project Configuration
│   ├── settings.py             # App registration & DB config
│   ├── urls.py                 # Main URL routing
│   └── wsgi.py
│
└── forecaster/                 # Main Application
    ├── admin.py                # Admin panel configuration
    ├── models.py               # Product & Sale database models
    ├── views.py                # Dashboard logic & Matplotlib plotting
    ├── urls.py                 # App-specific URLs
    ├── management/
    │   └── commands/
    │       └── seed_data.py    # Custom data population script
    └── templates/
        └── dashboard.html      # Frontend template

📸 Screenshots

Add screenshots of your dashboard here to showcase the KPI cards and charts.

🤝 Contributing

Contributions are welcome! Please follow these steps:

1. Fork the project.
2. Create your feature branch (git checkout -b feature/AmazingFeature).
3. Commit your changes (git commit -m 'Add some AmazingFeature').
4. Push to the branch (git push origin feature/AmazingFeature).
5. Open a Pull Request.

📄 License

This project is open-source and available under the MIT License.

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RetailPulse • Created by Dharm Patel