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Dashboard Module

Overview

The dashboard module provides a unified interface for viewing and analyzing data from multiple sources within the ClimateBackend system. It features server-side filtering and data processing capabilities.

Features

Data Sources

  • AWS Stations Data

    • Station name
    • Rainfall measurements
    • Timestamp information

  • Daily Prediction Data

    • Station-wise predictions
    • 3-day rainfall forecasts
    • Prediction timestamps

  • Tweet Data

    • Tweet content
    • Sentiment analysis
    • Location information
    • Timestamp

  • Crowdsource Data

    • Location information
    • Water depth measurements
    • User feedback
    • Submission timestamps

Filtering Capabilities

  • Date range selection (2020-01-01 to 2030-12-31)
  • Data source selection
  • Server-side processing
  • Efficient data retrieval

Data Display

  • Fixed-height data containers (400px)
  • Scrollable content areas
  • Tabular data presentation
  • Empty state handling

Data Export

  • CSV download functionality
  • Source-specific data exports
  • Date range filtering for exports

Technical Implementation

Views

  • Server-side filtering and processing
  • Django template rendering
  • Efficient database queries
  • Data pagination (100 records per source)

Templates

  • Responsive grid layout
  • Bootstrap styling
  • Fixed-height containers
  • Dynamic source rendering

Security

  • Login required for access
  • Staff-only permissions
  • CSRF protection
  • Input validation

Usage

  1. Access the dashboard at /dashboard/
  2. Select desired date range
  3. Choose data sources to display
  4. Click "Apply Filters" to update
  5. Use download buttons for data export

Code Structure

dashboard/
├── templates/
│   └── dashboard/
│       └── index.html      # Main dashboard template
├── views.py               # View logic and data processing
├── urls.py               # URL routing
└── models.py             # Dashboard-specific models

Performance Considerations

  • Server-side filtering reduces client load
  • Fixed record limits prevent overloading
  • Efficient database queries
  • Minimal JavaScript usage

Future Enhancements

  • Real-time data updates
  • Advanced filtering options
  • Data visualization charts
  • Custom view configurations
  • Mobile responsiveness improvements