Book Image

Hands-On Data Visualization with Bokeh

By : Kevin Jolly
Book Image

Hands-On Data Visualization with Bokeh

By: Kevin Jolly

Overview of this book

Adding a layer of interactivity to your plots and converting these plots into applications hold immense value in the field of data science. The standard approach to adding interactivity would be to use paid software such as Tableau, but the Bokeh package in Python offers users a way to create both interactive and visually aesthetic plots for free. This book gets you up to speed with Bokeh - a popular Python library for interactive data visualization. The book starts out by helping you understand how Bokeh works internally and how you can set up and install the package in your local machine. You then use a real world data set which uses stock data from Kaggle to create interactive and visually stunning plots. You will also learn how to leverage Bokeh using some advanced concepts such as plotting with spatial and geo data. Finally you will use all the concepts that you have learned in the previous chapters to create your very own Bokeh application from scratch. By the end of the book you will be able to create your very own Bokeh application. You will have gone through a step by step process that starts with understanding what Bokeh actually is and ends with building your very own Bokeh application filled with interactive and visually aesthetic plots.
Table of Contents (10 chapters)

The Bokeh Workflow – A Case Study

When it comes to building your very own Bokeh visualization from scratch, a good practice to develop is to never start with Bokeh. Instead, the ideal approach is to perform a little exploratory analysis on your data first, in order to visualize the application you can create using Bokeh that can deliver the most value to your users.

Such an approach, of first exploring your dataset, helps you formulate the ideal visualization that you might want to present to your audience.

In this chapter, you will learn the exact workflow that you need to follow, from when you get the data to the final visualization that you want to present.

Bokeh, like most data visualization tools, is best used in a workflow that follows a logical sequence of steps, which will allow you to deliver impactful insights to your audience. This workflow can be summarized...