Python’s Bokeh Library for Interactive Data Visualization
Introduction
In this tutorial, we’re going to learn how to use Bokeh library in Python. Most of you would have heard of matplotlib, numpy, seaborn, etc. as they are very popular python libraries for graphics and visualizations. What distinguishes Bokeh from these libraries is that it allows dynamic visualization, which is supported by modern browsers (because it renders graphics using JS and HTML), and hence can be used for web applications with a very high level of interactivity.
Bokeh is available in R and Scala language as well; however, its Python counterpart is more commonly used than others.
Installation
The easiest way to install Boken using Python is through pip package manager. If you have pip installed in your system, run the following command to download and install Bokeh:
$ pip install bokeh
Note: If you choose this method of installation, you need to have numpy installed in your system already
Another method to install Bokeh is through Anaconda distribution. Simply go to your terminal or command prompt and run this command:
$ conda install bokeh
After completing this step, run the following command to ensure that