Interactive Temporal Visualization

We have so far seen how to manipulate temporal data and create static plots. Now, we need a visualization that can be rendered at runtime based on events and information details – an interactive plot in which the events could be zoom, hover, change of axis, 3D rotations, and more. Information details could be changing the aggregation column from year to month or days.

Now we will explain how to plot using the Bokeh library. First, we will plot a simple plot. At the end, we will learn about callbacks and the sophisticated functionalities of Bokeh.

Bokeh Basics

Bokeh is an interactive visualization library. It is able to handle large amounts of data and streaming data as well. Apart from Python, Bokeh can be used with R, Scala, Lua, and other programming languages.

For a simple graph, many interactivity tools come built-in with Bokeh, for example, pan, box zoom, and wheel zoom. Since we will be visualizing our output in a Jupyter...