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)

Using Annotations, Widgets, and Visual Attributes for Visual Enhancement

Now that you have learned how to create plots and layouts in Bokeh, it is time to enhance them visually and add a layer of interactivity using annotations, widgets, and visual attributes.

Annotations are used to add supplemental information to your plots, such as titles, legends, and color maps that provide information about what the plot is trying to convey to the person who views your plot.

Widgets offer interactivity through buttons, drop-down menus, sliders, and textboxes. These widgets allow the person viewing the plot to interact with the plot and make changes to the way he or she wants to view it.

Visual attributes provide a vast range of visual enhancements to the plot, such as colors and fills for the lines and text, and interactivity enhancements such as the hover tool to hover over and select...