Other Visualization Tools: Dashboards & Reports

Modern data visualization tools like Streamlit, Dash, and Bokeh make it easy to build interactive dashboards and reports. These tools are Python-based, open-source, and can be deployed to cloud services for sharing insights.

Streamlit

Streamlit is a fast way to build and share data apps. It uses simple Python scripts and is ideal for quick dashboards.

Demo Code: See streamlit_demo/app.py for a basic bar chart dashboard.

Cloud Deployment: Streamlit apps can be deployed to Streamlit Cloud or platforms like Heroku.

Dash

Dash (by Plotly) is a powerful framework for analytical web apps. It supports complex layouts and interactive components.

Demo Code: See dash_demo/app.py for a dashboard using Dash and Plotly.

Cloud Deployment: Dash apps can be deployed to Dash Enterprise or Heroku.

Bokeh

Bokeh creates interactive visualizations for web browsers. It is flexible and integrates with other web frameworks.

Demo Code: See bokeh_demo/app.py for a simple Bokeh dashboard.

Cloud Deployment: Bokeh apps can be deployed to Bokeh Server or cloud platforms.

Automation & Version Control

All demo code is organized in folders and can be versioned with Git or other VCS. For CI/CD, use GitHub Actions or similar tools to automate deployment to the cloud.

Example Automation (GitHub Actions)

# .github/workflows/deploy.yml
name: Deploy Dashboards
on: [push]
jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Set up Python
        uses: actions/setup-python@v4
        with:
          python-version: '3.9'
      - name: Install dependencies
        run: |
          pip install streamlit dash bokeh
      - name: Run Streamlit app
        run: streamlit run streamlit_demo/app.py &
      - name: Run Dash app
        run: python dash_demo/app.py &
      - name: Run Bokeh app
        run: python bokeh_demo/app.py &