Plotting with Bokeh

One of the major design principles of HoloViews is that the declaration of data is completely independent from the plotting implementation. This means that the visualization of HoloViews data structures can be performed by different plotting backends. As part of the 1.4 release of HoloViews, a Bokeh backend was added in addition to the default matplotlib backend. Bokeh provides a powerful platform to generate interactive plots using HTML5 canvas and WebGL, and is ideally suited towards interactive exploration of data.

By combining the ease of generating interactive, high-dimensional visualizations with the interactive widgets and fast rendering provided by Bokeh, HoloViews becomes even more powerful.

This tutorial will cover some basic options on how to style and change various plot attributes and explore some of the more advanced features like interactive tools, linked axes, and brushing.

As usual, the first thing we do is initialize the HoloViews notebook extension, but we now specify the backend specifically.

In [1]:
import numpy as np
import pandas as pd
import holoviews as hv
In [2]:
hv.extension('bokeh')