hands-on lab

Data Visualization with Bokeh

Up to 1h
Get guided in a real environmentPractice with a step-by-step scenario in a real, provisioned environment.
Learn and validateUse validations to check your solutions every step of the way.
See resultsTrack your knowledge and monitor your progress.


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:

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.


You should possess:

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

About the author

Learning paths

Andrea is a Data Scientist at Cloud Academy. He is passionate about statistical modeling and machine learning algorithms, especially for solving business tasks.

He holds a PhD in Statistics, and he has published in several peer-reviewed academic journals. He is also the author of the book Applied Machine Learning with Python.

Covered topics

Lab steps

Bokeh Basic Plotting