Interactive Data Visualization with Bokeh

Learn about the fundamentals of the Bokeh library in this course, which will enable you to level up your Python data visualization skills by building interactive plots. You’ll see how to set up configuration tools, including the HoverTool, providing various opportunities for stakeholders to interact with your plots!

For this chapter, you’ll learn how to customize axes, create and enhance a legend, modify glyph settings, and apply Bokeh's custom themes!

Learn how to use various elements to communicate with stakeholders. You’ll produce grouped bar plots with categorical data, build multiple subplots, add annotations, and modify the text to make your Bokeh visualizations even more striking!

Discover Bokeh's widgets and how they enable users to modify Python visualizations! You’ll learn about Spinners, which allow viewers to change the size of glyphs. We’ll discuss Sliders, which can be used to change axis ranges. Lastly, we’ll introduce the Select widget, which will enable plot updates based on dropdown options.