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| # Teachers Training in ICT & Digital Initiatives | |
| A live dashboard application for tracking and managing teacher attendance across ICT training programs in Punjab. | |
| **Live Demo:** https://nielitscert.onrender.com/ | |
| ## 🎯 Overview | |
| This application provides real-time analytics and visualization of teachers trained in ICT initiatives across 23 districts of Punjab. It features an interactive map, comprehensive statistics, and detailed attendance records. | |
| ## ✨ Features | |
| - **Interactive Punjab Map** - Visual representation of teacher distribution across districts | |
| - **Live Statistics** - Real-time count of trained teachers, districts, schools, and batches | |
| - **Batch Management** - Track attendance across 12 training batches (333 teachers) | |
| - **District Filtering** - Filter data by district and batch for detailed analysis | |
| - **Gender Demographics** - Visualize gender distribution among participants | |
| - **Designation Analytics** - Top designations among trained teachers | |
| - **Photo Gallery** - Browse training session photos by batch | |
| - **Data Export** - Export attendance records to CSV | |
| - **Responsive Design** - Works seamlessly on desktop and mobile devices | |
| ## 🛠️ Technology Stack | |
| - **Backend:** Flask 3.0.3, Python 3.x | |
| - **Frontend:** HTML5, CSS3, JavaScript (ES6+) | |
| - **Maps:** Leaflet.js with GeoJSON | |
| - **Charts:** Chart.js | |
| - **Data Parsing:** PapaParse (CSV) | |
| ## 📊 Dataset | |
| - **23 Districts** across Punjab | |
| - **12 Training Batches** (380 target, 333 trained) | |
| - **333 Teachers** from various schools and designations | |
| - Comprehensive metadata: UDISE codes, designations, dates, gender | |
| ## 📁 Project Structure | |
| ``` | |
| Teachers-training-in-ICT-Digital-Initiatives/ | |
| ├── app.py # Flask backend & APIs | |
| ├── requirements.txt # Python dependencies | |
| ├── static/ | |
| │ ├── present_data.csv # Teacher attendance records | |
| │ ├── punjab_districts.geojson # Map boundaries & geometry | |
| │ ├── script.js # Main JavaScript logic | |
| │ ├── scert_logo.png # SCERT logo | |
| │ └── edu_logo.png # NIELIT logo | |
| ├── templates/ | |
| │ ├── index.html # Main dashboard | |
| │ └── gallery.html # Photo gallery | |
| └── Photo_Gallery/ # Training session photos (by batch) | |
| ``` | |
| ## 🎨 Dashboard Features | |
| ### Statistics Panel | |
| - Total trained teachers count | |
| - Number of active batches | |
| - Districts covered | |
| - Schools represented | |
| ### Interactive Map | |
| - Color-coded districts by attendance | |
| - Click on a district to filter data | |
| - Hover tooltips showing exact counts | |
| - Zoom and pan controls | |
| ### Analytics Charts | |
| - District-wise headcount bar chart | |
| - Gender demographics pie chart | |
| - Top designations visualization | |
| - Target vs achieved progress | |
| ### Data Table | |
| - Detailed teacher records with search | |
| - Filter by district and batch | |
| - Export to CSV | |
| - Print-friendly format | |
| ### Photo Gallery | |
| - Carousel view of batch photos | |
| - Navigate with previous/next buttons | |
| - Keyboard navigation support (arrow keys) | |
| ## ⚙️ Configuration | |
| Edit `app.py` to customize: | |
| - `GITHUB_CSV_URL` - Remote CSV file URL | |
| - `BATCH_TARGETS` - Expected teachers per batch | |
| - `DISTRICT_MAPPING` - District name standardization | |
| ## 🔍 API Endpoints | |
| - `GET /` - Main dashboard | |
| - `GET /gallery` - Photo gallery page | |
| - `GET /api/dates` - List of batches | |
| - `GET /api/stats` - Statistics data | |
| - `GET /api/gallery` - Available photos | |
| - `GET /api/teachers/<district>` - Teachers by district | |
| ## 👥 Built By | |
| **WBL Department** | |
| National Institute of Electronics & Information Technology (NIELIT) Ropar | |
| Ministry of Electronics & IT, Government of India | |
| For more information: https://nielit.gov.in/ropar/ | |
| ## 📄 License | |
| All rights reserved © 2026 WBL Department, NIELIT Ropar | |
| --- | |
| **Last Updated:** April 2026 | |
| **Database:** 333 Teachers | 23 Districts | 12 Batches | |