Zachary Blackwood & Peter Vidos - Creating Interactive, Animated Reports in Streamlit with ipyvizzu

Interactive animated data visualization using ipyvizzu can be integrated with Streamlit apps to create engaging reports and dashboards

Streamlit’s core principles include embracing Python scripting and treating widgets as variables that can be reused throughout the app

Multiple chart types and transitions can be combined into animated stories to help explain relationships in data without requiring extra explanation

Charts can be made interactive using features like filtering, zooming, and clicking on elements to trigger animations or data updates

No installation required to get started - can use GitHub Codespaces to fork sample apps and start building immediately

Built-in caching in Streamlit helps optimize performance by preventing unnecessary reruns of expensive operations

Charts can be customized with different styles, colors, and animation settings through configuration options

Bidirectional integration allows charts to react to Streamlit controls and chart interactions to update other app elements

Easy deployment through Streamlit Community Cloud for sharing apps built with public GitHub repos

Components system allows packaging JavaScript libraries like ipyvizzu as reusable Streamlit widgets that maintain Python-native feel