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Intro and Bokeh Course Overview

This lesson introduces the Interactive Data Visualization in Python with Bokeh course and gives an overview of what you will learn in each of the three sections.


Course Slides (PDF)

846.7 KB

00:00 Hi, this is Chris Bailey from Real Python. I’ll be taking you through the course Interactive Data Visualization in Python With Bokeh. Bokeh prides itself on being a library for interactive data visualization.

00:13 Your visualizations are rendered using HTML and JavaScript, which makes it very useful for web-based applications and dashboards. You can create beautiful custom charts for your projects or reports.

00:25 So, what will you learn to do? You’ll learn to transform your data into visualizations, customize and organize those visualizations, and then add lots of interactivity.

00:34 Let me give you an overview of what the course is going to cover. It’s broken into three sections, the first part being Welcome to Bokeh, and then Working with Data and Layouts, and then Adding Interaction.

00:44 After this intro, I’ll walk you through taking your data through to a visualization and all the small steps that are involved in between. Next, you’ll talk briefly about setting up your Bokeh environment.

01:00 I’ll show you generating your first figure to a static HTML file

01:08 and how Bokeh generates the HTML and JavaScript automatically for you. Next, I’ll show you how you can use Bokeh to generate figures inside of a Jupyter Notebook.

01:25 Then I’ll show you how to get your figure ready for data, setting up plot heights and width, backgrounds, and setting up your x- and y-axes.

01:36 Then you’ll start to work with glyphs. These are the lines, circles, squares, and bars—all those elements that make up the graphical content for your visualizations.

01:47 Then you’ll create a visualization with multiple glyphs. That also includes a legend. And then a short review. In Section 2, after a quick overview, I’ll take you on a quick aside about data.

02:04 This is where you’ll use pandas to read in some CSV files. I’ll show you how to use the ColumnDataSource object, which is extremely useful inside of Bokeh.

02:18 Once you start using the ColumnDataSource object, you can also start to use GroupFilter and CDSView to isolate data right inside the scripts for your visualizations.

02:31 I’ll show you how to lay out multiple visualizations using a column layout or a row layout. Then I’ll show you gridplot layout and tabbed layouts, using panels.

02:47 Then, a short review of Section 2. In Section 3, after a quick overview, you’ll be able to choose all the different items you’d like to configure in your toolbar. Then I’ll show you how you can select data points using some of those tools.

03:06 You’ll learn how to add hover actions and to configure tooltips. Next, you’ll learn about emphasizing those hover inspections.

03:21 Then I’ll show you linking axes,

03:27 and then linking selections

03:33 and how you can highlight data using the legend, how you can hide data, or how you can mute it. And last, a Bokeh course recap and review. All right, enough introduction.

03:48 Time to dive in.

Christopher Jacoby on April 13, 2024

Please update this course for Bokeh 3.x.

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