Data Science and Machine Learning (Theory and Projects) A to Z - Matplotlib, Seaborn, and Bokeh for Data Visualization:

This video tutorial introduces Bokeh, a powerful library for creating interactive plots that open as HTML files in a web browser. It contrasts Bokeh with static plotting libraries like Seaborn and Matplotlib, highlighting its interactive features. The tutorial guides viewers through setting up Bokeh in Jupyter Notebook, creating basic plots, and exploring advanced interactive features. It also covers creating multiple plots, customizing them, and adding additional graphs, demonstrating Bokeh's flexibility and interactivity.

What types of plots can you create using bouquet, and how do they differ?

In what ways can you modify the appearance of a plot in bouquet?

Discuss the process of adding multiple plots to a single figure in bouquet.

What are the different markers available in bouquet for plotting?