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)

Presenting your results

The right visualization is not just limited to picking the right type of plot, such as scatter plots or bar charts. It extends to picking the right colors, shapes, markers, and features.

Some of the questions that you will want to ask yourself when choosing the right visualization are as follows:

  • Do I want to transmit a positive message to my readers? If yes, the colors green and blue are a great choice
  • Do I want to transmit an alarming/negative message, indicating some form of danger/decline to my readers? If yes, the color red works best
  • Do I want to show how two different segments/categories differ from each other? If yes, using contrasting colors such as red and blue works well

The tone of the insight and message that you want to convey is critical when it comes to creating the ideal visualization.