← Back to Data Science

All Topics

Advertisement

Learn/Data Science/Python for Data Science

Interactive Visualization

Topic: Visualization

Advertisement

Interactive Plots

Interactive visualizations enable exploration.

Plotly

import plotly.express as px. px.scatter(df, x, y, color) creates interactive scatter.

Hover shows tooltips. Zoom, pan enabled. Export to HTML with fig.write_html().

Bokeh

Bokeh provides web-based interactive plots. output_notebook() for Jupyter. HoverTool for interactivity.

Altair

Altair uses declarative JSON specification. Chart(data).encode(x, y, color).interact() adds interactivity.

Key Takeaways

  1. Plotly creates interactive web visualizations
  2. Bokeh enables custom web interactions
  3. Altair provides declarative specification

Advertisement

Advertisement

Need More Practice?

Get personalized data science help from ChatWhole's AI-powered platform.

Get Expert Help →