jairoskd/nala-grains-analytics

Automated PDF Business Intelligence Dashboard for Tanzania Grain Wholesalers # 📊 Nala Warehouse Operations & Financial Analytics Engine An end-to-end financial analytics and automated reporting pipeline built for **Nala Warehouse**. This engine processes raw transactional sales data, calculates core business metrics (Revenue, Net Profit, Overdue Receivables), evaluates inventory turnover risk, and compiles multi-page executive PDF dashboards and high-definition visual assets. Engineered by **Namba Data Analytics**. ## Overview This tool generates a weekly/monthly PDF report for Nala that includes: - **Revenue Trend**: 2-week moving average of weekly sales - **Profit by Customer Segment**: Bar chart ranking Retail Chains, Wholesale, Importers, Processors - **Discount Impact**: How discount rates affect net profit across segments - **Inventory Turnover**: Average storage days by commodity - Maize, Beans, Rice, Groundnuts - **Closing Remarks**: Actionable summary + risks - **Namba Insights Brand Footer**: Contact banner Goal: Help management make decisions in 5 minutes instead of digging through Excel. ## Project Structure nala/ ├── nala_analysis.py # Data processing & calculations ├── nala_charts.py # Chart generation with matplotlib ├── nala_dashboard.py # Main entry point - generates PDF ├── data/ │ └── nala_sales.csv # Raw sales data ├── charts/ │ ├── weekly_revenue_trend.png # Chart 1 │ ├── sales_profit_per_customer.png # Chart 2 │ ├── discount_rate_profit_correlation.png # Chart 3 │ └── average_storage_duration.png # Chart 4 ├── output/ │ └── nala_dashboard_report.pdf # Final PDF report ├── assets/ │ └── namba_insights.jpg # Namba Data Analytics logo └── README.md # Project documentation ## ⚡ Installation & Setup ### 1. Clone the Repository ```bash git clone github.com cd nala ### 2. Set Up Virtual Environment # On macOS/Linux python3 -m ven …