Data Visualisation with Python: Bokeh and Advanced Layouts

Learn how to use Bokeh in Python

On the first week of the course, you’ll explore the key functions of Bokeh and how it can be used to create interactive visualisations and dashboards.

You’ll weigh up the benefits of Bokeh compared to other data visualisation packages, and explore the concept of Glyphs within Python and how they can be customised.

Explore data plotting in Python

Once you’ve mastered the basics you’ll learn about plot layouts, advanced features of the layouts, and the application of advanced widgets on Bokeh.

By the end of week two, you’ll understand the basics of layouts, interactions, and annotations, as well as being able to connect sliders to plots by updating plots from selects and putting it all together.

Understand the phases of data exploration

In week three, you’ll engage in an end to end exploration of data analysis. You’ll explore the various phases of data exploration and learn more about data ethics and the role of responsible storytelling.

You’ll also have the chance to conduct extended data analysis and visualisation, bringing all your learning together.

On the final week of the course, you’ll look at data analytics as an emerging field, the role of DataOps and UX design, and new technologies that have the potential to enhance your prospects as a data professional.

Throughout the course, you’ll have the opportunity to engage in a variety of practical exercises and complete real-world tasks that will place you in the role of a data analyst for a boutique streaming service.

This course is designed for professionals who would like to grow their confidence in using Python to produce exploratory and explanatory visualisations and build dashboards to communicate insights.

• A professional working with data on a regular basis or has a fundamental understanding of data analytics but wants to become more employable or progress in their career.
• A business analyst or junior data analysts looking to further develop their data visualisation skills using Python.
• An individual with existing programming capabilities looking to enter the data analytics field.

If you want to explore this subject further, you may be interested in these courses from the same provider. They share the same subject and overall learning outcomes. Access them here:

• Data Visualisation with Python: Matplotlib and Visual Analysis
• Data Visualisation with Python: Seaborn and Scatter Plots

During this course we’ll be using Tableau Public and Excel. If you don’t have Excel, you might find this online version useful. We recommend you use a computer to access these elements.

• Introduction to Bokeh, basic plotting, and layouts
• Welcome to the course!
• Introduction to Bokeh
• Basic plotting with Bokeh
• Layouts, interactions and annotations
• Wrap-up
• Annotations and interactive visualisations
• Introduction
• Layouts, interactions, and annotations
• Building interactive visualisations
• Wrap-up
• An end-to-end exploration and analysis
• Introduction
• End-to-end data exploration and analysis
• Ethical concerns
• Wrap-up
• New ways of working and looking ahead
• Introduction
• New ways of working
• Next steps
• Wrap-up