How to combine Matplotlib, Plotly, Seaborn, & more in a single Python Dashboard! (Shiny for Python)

This is part 4 of our multi-part series on creating professional dashboards with Shiny for Python. In this video, we'll explore how to integrate popular Python visualization libraries like Matplotlib, Plotly, Seaborn, and Altair into your Shiny apps. This allows you to leverage your existing visualization skills and seamlessly include them in interactive dashboards. We'll cover:
- Integrating Matplotlib and Seaborn for detailed visualizations
- Utilizing Altair and Plotly for dynamic charts
- Implementing Folium for interactive maps
- Customizing data tables with additional filters and selection modes

By the end of this video, you'll have a rich and diverse set of visualizations in your Shiny dashboard, setting the stage for the final styling touches in the next video.

Video by @KeithGalli

Video Timeline!
0:00 - Video Overview & Recap of Previous Video Dashboards
1:38 - Getting Setup with the Code (cloning branch from GitHub)
10:15 - Create a Seaborn Heatmap Chart (Sales Volume by Hour of the Day)
14:59 - Creating Interactive Charts with Jupyter Widgets (Plotly, Altair, Bokeh, Pydeck, & More…) | render_widget decorator
28:49 - Additional Rendering Options, Final Touches and Next Steps

Stay tuned for part 5, where we'll focus on styling and finalizing our dashboard. If you enjoyed this video, give it a thumbs up and subscribe to the channel to stay updated!

All videos in the series: