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Property Value
Language TeX
Stars 0
Forks 0
Watchers 0
Open Issues 0
License No License
Created 2025-11-30
Last Updated 2026-02-19
Last Push 2025-12-19
Contributors 1
Default Branch main
Visibility private

Datasets

This repository includes 15 dataset(s):

Dataset Format Size

| data | | 0.0 KB |

| .gitkeep | | 0.1 KB |

| datasets | | 0.0 KB |

| README.md | .md | 3.62 KB |

| agricultural_experiment.csv | .csv | 3.81 KB |

| clinical_trial.csv | .csv | 2.18 KB |

| drug_dosage_study.csv | .csv | 3.42 KB |

| education_intervention.csv | .csv | 0.6 KB |

| employee_satisfaction.csv | .csv | 3.41 KB |

| environmental_study.csv | .csv | 6.36 KB |

| manufacturing_quality.csv | .csv | 0.64 KB |

| marketing_campaigns.csv | .csv | 4.03 KB |

| medical_treatment.csv | .csv | 2.32 KB |

| reaction_time_study.csv | .csv | 2.99 KB |

| website_testing.csv | .csv | 71.91 KB |

Reproducibility

This repository includes reproducibility tools:

  • Python requirements.txt

Status

  • Issues: Enabled
  • Wiki: Disabled
  • Pages: Disabled

README

GitHub Organization Dashboard

Automated interactive dashboard for monitoring repository statistics in the Digital-AI-Finance organization. Features real-time data visualization with daily updates via GitHub Actions.

Features

  • Automated Data Collection: Daily updates via GitHub Actions
  • Interactive Visualizations: Powered by Plotly for rich, interactive charts
  • Comprehensive Metrics:
  • Repository activity timeline
  • Commit patterns and trends
  • Language distribution analysis
  • Repository maturity scoring
  • Research focus areas
  • Contributor analytics
  • Modern UI: Dark theme with GitHub-inspired design
  • Zero Maintenance: Fully automated pipeline with scheduled updates
  • GitHub Pages Deployment: Accessible via web browser

Quick Start

Local Development

  1. Clone the repository 

    git clone https://github.com/Digital-AI-Finance/dashboard.git
cd dashboard

  2. Install dependencies 

    pip install -r requirements.txt

  3. Set up GitHub token (optional but recommended) 

    # Windows PowerShell
$env:GITHUB_TOKEN="your_github_personal_access_token"

# Or create a .env file
echo "GITHUB_TOKEN=your_token_here" > .env

  4. Run the dashboard update 

    python run_update.py

  5. View the dashboard Open index.html in your browser

GitHub Token Setup

For higher API rate limits (5000 requests/hour vs 60), create a GitHub Personal Access Token:

  1. Go to GitHub Settings > Developer settings > Personal access tokens > Tokens (classic)
  2. Click "Generate new token (classic)"
  3. Select scopes: public_repo, read:org
  4. Copy the token
  5. Set as environment variable GITHUB_TOKEN

Configuration

Edit config.yml to customize:

# Organization to monitor
organization: "Digital-AI-Finance"

# Dashboard settings
dashboard:
  title: "Your Custom Title"
  update_frequency: "daily"

# Visualization toggles
charts:
  repository_activity:
    enabled: true
    days_history: 90  # Adjust time window

  technology_stack:
    enabled: true

  research_impact:
    enabled: true

  repository_maturity:
    enabled: true

# Color scheme
colors:
  background: "#0d1117"
  primary: "#58a6ff"
  # ... customize colors

GitHub Actions Automation

The dashboard automatically updates daily via GitHub Actions:

Setup

  1. Enable GitHub Pages
  2. Go to repository Settings > Pages
  3. Source: Deploy from a branch

  4. Branch: gh-pages / root

  5. Verify workflow permissions

  6. Go to Settings > Actions > General
  7. Workflow permissions: Read and write permissions

  8. Save

  9. Manual trigger (optional)

  10. Go to Actions tab
  11. Select "Update Dashboard" workflow
  12. Click "Run workflow"

Schedule

  • Automatic: Daily at midnight UTC
  • On push: When code changes are pushed
  • Manual: Via Actions tab

Project Structure

github-dashboard/
|-- .github/
|   `-- workflows/
|       `-- update-dashboard.yml    # GitHub Actions workflow
|
|-- data/
|   |-- repository_stats.json       # Fetched GitHub data (generated)
|   `-- cache/                      # API response cache (generated)
|
|-- fetch_github_data.py            # GitHub API data fetcher
|-- generate_dashboard.py           # Dashboard HTML generator
|-- run_update.py                   # Convenience script to run both
|
|-- config.yml                      # Configuration file
|-- requirements.txt                # Python dependencies
|-- .gitignore                      # Git ignore rules
|
|-- index.html                      # Generated dashboard (output)
`-- README.md                       # This file

Scripts Overview

fetch_github_data.py

Fetches comprehensive data from GitHub API: - Organization metadata - Repository details (commits, languages, contributors) - Activity metrics - Maturity scoring - Rate limit management

Usage: 

python fetch_github_data.py

generate_dashboard.py

Generates interactive HTML dashboard with Plotly charts: - Commit timeline - Language distribution - Repository statistics - Maturity gauges - Research focus areas - Contributor activity

Usage: 

python generate_dashboard.py

run_update.py

Runs complete update pipeline (fetch + generate):

Usage: 

python run_update.py

Visualizations

1. Commit Activity Timeline

Line chart showing commit activity across all repositories over the last 90 days.

2. Technology Stack Distribution

Pie chart displaying programming language usage across the organization.

3. Repository Statistics

Bar charts comparing commits, stars, and forks across repositories.

4. Repository Maturity Scores

Gauge charts showing maturity levels based on: - Commit activity (20%) - Documentation (20%) - Testing infrastructure (20%) - License presence (15%) - CI/CD setup (15%) - Community engagement (10%)

Maturity Stages: - Production: 80-100% - Beta: 60-79% - Alpha: 40-59% - Planning: 20-39% - Concept: 0-19%

5. Research Focus Areas

Bar chart of research topics extracted from repository descriptions.

6. Contributor Activity

Bar chart showing contributor counts per repository.

Customization

Modify Charts

Edit generate_dashboard.py to customize visualizations:

def create_custom_chart(self, data: Dict) -> str:
    # Your custom Plotly chart code
    fig = go.Figure(...)
    return fig.to_html(full_html=False, include_plotlyjs='cdn')

Add to generate_html() method: 

custom_chart = self.create_custom_chart(data)

Update HTML template to include: 

<div class="chart-section">
    <h2>Custom Chart Title</h2>
    {{ custom_chart|safe }}
</div>

Change Color Scheme

Edit config.yml colors section:

colors:
  background: "#your_color"
  primary: "#your_color"
  # ... etc

Adjust Data Collection

Modify fetch_github_data.py: - Change since_days parameter for longer/shorter history - Add additional API endpoints - Customize maturity scoring weights

Troubleshooting

Rate Limit Errors

Problem: API rate limit exceeded

Solution: - Set GITHUB_TOKEN environment variable - Reduce update frequency - Enable caching in config.yml

Missing Data

Problem: Charts show no data

Solution: - Verify data/repository_stats.json exists - Check GitHub token permissions - Run python fetch_github_data.py manually to see errors

GitHub Pages Not Updating

Problem: Dashboard not showing latest data

Solution: - Check Actions tab for workflow errors - Verify gh-pages branch exists - Ensure workflow has write permissions - Clear browser cache

Import Errors

Problem: Module not found errors

Solution: 

pip install -r requirements.txt --upgrade

Dependencies

  • requests (2.31.0+): GitHub API communication
  • plotly (5.18.0+): Interactive visualizations
  • pandas (2.1.0+): Data processing
  • pyyaml (6.0.1+): Configuration parsing
  • jinja2 (3.1.2+): HTML templating
  • python-dateutil (2.8.2+): Date handling

Development

Adding New Metrics

  1. Fetch data in fetch_github_data.py: 

    def get_new_metric(self, repo_name: str) -> Dict:
    url = f"{self.base_url}/repos/{self.org_name}/{repo_name}/endpoint"
    return self._make_request(url)

  2. Create visualization in generate_dashboard.py: 

    def create_new_metric_chart(self, data: Dict) -> str:
    # Chart logic
    return fig.to_html(full_html=False, include_plotlyjs='cdn')

  3. Add to dashboard in HTML template

Testing Locally

# Test data fetching
python fetch_github_data.py

# Test dashboard generation
python generate_dashboard.py

# Open in browser
start index.html

Performance

  • API Calls: Approximately 10-20 per repository
  • Rate Limits: 5000/hour with token, 60/hour without
  • Generation Time: 1-3 minutes for 4 repositories
  • Dashboard Size: Approximately 2-5 MB HTML file

Security

  • GitHub Token: Never commit tokens to repository
  • Use secrets: Store in GitHub Secrets for Actions
  • Environment variables: Use .env file for local development (git-ignored)

License

MIT License - see LICENSE file for details

Contributing

Contributions welcome! Please: 1. Fork the repository 2. Create feature branch 3. Make changes 4. Test thoroughly 5. Submit pull request

Support

For issues or questions: - Open an issue on GitHub - Check existing issues for solutions - Review GitHub Actions logs for errors

Roadmap

Future enhancements: - [ ] Historical trend tracking - [ ] Comparison with other organizations - [ ] Email notifications on significant changes - [ ] Custom metric definitions - [ ] Export to PDF/PNG - [ ] Mobile app view - [ ] Real-time updates via webhooks

Acknowledgments

  • Built with Plotly for interactive visualizations
  • Deployed via GitHub Pages
  • Automated with GitHub Actions
  • Inspired by modern tech dashboard designs

(c) Joerg Osterrieder 2025