Data Visualization with Bokeh

In this hands-on lab, you will master your knowledge of Bokeh, a very popular Python library for dynamic data visualization. Here, you will build standalone plots, and add interactive tools and features, including dynamic legends and Hover inspectors.

Before starting this lab, you are strongly encouraged to take the following courses:

• Data Wrangling with Pandas.
• Data Visualisation with Python using Matplotlib.
• Interactive Data Visualization with Python using Bokeh

Your data visualization skills will be challenged, and by the end of this lab, you should have a deep understanding of how Bokeh practically works.

Learning Objectives

Upon completion of this lab you will be able to:

• Build a standard plot with Bokeh using a line glyph;
• Bring interactivity inside a bokeh plot with a dynamic legend;
• Create a Column Data Source;
• Enrich a bokeh plot with the Hover Inspector;
• Visualize categorical variables with a bar chart;
• Create a multi-index bar plot for categorical variables;
• Build a histogram with Bokeh.

Intended Audience

This lab is intended for:

• Those interested in performing data visualization with Python.
• Anyone involved in data science and engineering pipelines.

Prerequisites

You should possess:

• An intermediate understanding of Python.
• Basic knowledge of the following libraries: Pandas, Matplotlib, Numpy.

Updates

August 8th, 2024 - Resolved Jupyter Notebook issue