Introduction to Interactive Visualization

While matplotlib creates static images, interactive visualization libraries let users explore data dynamically. This lesson introduces interactive concepts and previews popular tools.

When to Go Interactive

Interactive Libraries Overview

Matplotlib's Limited Interactivity

Preparing Data for Interactive Plots

Practice: Design an Interactive Visualization

Key Takeaways

• Static plots (matplotlib) are best for reports, publications, and presentations
• Interactive plots are ideal for dashboards, exploration, and large datasets
• Popular interactive libraries: Plotly, Bokeh, Altair, Holoviews
• Prepare data in dictionary/DataFrame format for interactive tools
• Pre-compute hover text and color mappings
• Start with matplotlib for design, then port to interactive library

In the next lesson, we'll look at Plotly syntax and examples.