Interactive Data Visualization in Python With Bokeh

Chris Bailey 26 Lessons 2h 7m
data-science data-viz intermediate

Bokeh prides itself on being a library for interactive data visualization. The graphics are rendered using HTML and JavaScript, and your visualizations are easy to share as an HTML page. You will create a number of visualizations based on a real-world dataset.

The goal of this course is to get you up and running with Bokeh.

You will learn how to:

Transform your data into visualizations
Customize and organize your visualizations
Add interactivity to your visualizations

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Welcome to Bokeh

9 Lessons ⋅ 31m

1. Intro and Bokeh Course Overview (03:49)

2. From Data to Visualization (02:48)

3. Setting Up Your Bokeh Environment (02:55)

4. Generating Your First Figure to a Static HTML File (03:15)

5. Generating Your First Figure to a Jupyter Notebook (01:59)

6. Getting Your Figure Ready for Data (04:46)

7. Drawing Data With Glyphs (04:16)

8. Multiple Glyphs and Adding a Legend (06:45)

9. Bokeh Course: Section 1 Review (01:21)

Working With Data and Layouts

8 Lessons ⋅ 38m

1. Bokeh Course: Section 2 Overview (01:09)

2. A Quick Aside About Data (03:59)

3. Using the ColumnDataSource Object (09:53)

4. Using GroupFilter and CDSView (04:22)

5. Multiple Visualizations Using Column Layout (07:59)

6. GridPilot Layout (05:23)

7. Tabbed Layout With Panels (04:10)

8. Bokeh Course: Section 2 Review (01:09)

Adding Interaction

9 Lessons ⋅ 57m

1. Bokeh Course: Section 3 Overview (01:08)

2. Configuring the Toolbar (03:19)

3. Selecting Data Points (10:45)

4. Adding Hover Actions (03:24)

5. Emphasizing With Hover Inspections (02:53)

6. Linking Axes (12:56)

7. Linking Selections (10:45)

8. Highlighting Data Using the Legend (08:14)

9. Bokeh Course: Recap and Review (03:59)

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About Chris Bailey

Chris is an avid Pythonista and creates video tutorials for Real Python. He is a programmer and data analyst. He creates music under the name Tripnet. Chris lives in Hawaii with his wife and two dogs.

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