Interactive Data Visualization with Python and Bokeh

A complete guide on creating beautiful plots and data dashboards on the browser using the Python Bokeh library.

Created byArdit Sulce | 600,000+ Students

Last updated 2/2026

English

What you'll learn

Build advanced data visualization web apps using the Python Bokeh library.
Create interactive modern web plots that represent your data impressively.
Create widgets that let users interact with your plots.
Learn all the available Bokeh styling features.
Integrate and visualize data from Pandas DataFrames.
Create dynamic graphs that plot real-time data.
Plot time-series data.
Integrate your data visualization apps with Flask apps.
Deploy the apps in live servers.
Learn how to troubleshoot Bokeh apps.

Course content

7 sections • 79 lectures • 6h 47m total length

Course Introduction0:32
Get to know about a few facts about the course.
Helpful Resources0:22
Installation0:09
Getting Help0:23
What is Bokeh2:51
A short introduction on what Bokeh library can do.
Bokeh and Bokeh Server
Creating Your First Bokeh Plot13:52
Learn to create your first web-based plot with Bokeh.
Exercise 1: Plotting triangles and circle glyphs0:09
Exercise 1: Solution0:25
Using Bokeh with Pandas4:51
Learn to feed your Bokeh charts with data from Pandas dataframes.
Exercise 2: Plotting Education Data0:12
Exercise 2: Solution0:16
Bug with the Show Method5:09
There's currently an issue with the show() method explained in this lecture.
Using the Bokeh Documentation4:12
Get the links to the official documentation and learn how to use the documentation.

Section Introduction3:03
Get to know with this section.
Note0:15
Creating an Initial Plot3:13
Let's create a basic plot first before adding styling to it in the next lectures.
Figure Background5:43
Learn how to customize the background style of a Bokeh chart.
List of Colors0:20
Here's a complete list of colors you can use with Bokeh charts.
Title3:10
Learn how to customize the title of a Bokeh chart.
List of Text Fonts0:08
Here is a list of text font styles you can use in Bokeh.
Axes: Custom Styling8:01
Learn how to customize the axes style of a Bokeh chart.
Axes: Custom Geometry8:14
Learn how to customize the axes geometry of a Bokeh chart.
Axes: Categorical Data2:50
Learn how to plot categorical data.
Grid2:23
Learn how to customize the grid of a Bokeh chart.
Tools5:26
Learn how to customize the tools of a Bokeh chart.
Glyphs9:34
Learn how to customize the plotted glyphs of a Bokeh chart.
Legend: Configuring4:46
Learn how to customize the structure of the legend.
Legend: Styling7:00
Learn how to customize the style of the legend.
Popup Windows4:47
Learn how to create pop up window messages.
Exercise 3: Summary of Section 30:28
Exercise 3: Solution2:29

Section Introduction1:51
Here's an introduction to this section.
ColumnDataSource16:36
Learn how to use the native data source object of a Bokeh chart.
Exercise 4: Plotting Elements of the Periodic Table0:38
Exercise 4: Solution0:35
Popup Windows with Custom HTML10:46
Learn how to extract values from a ColumnDataSource for displaying in a popup window.
Gridplots5:07
Learn how to create multiple plots in one webpage.
Exercise 5: Gridplots0:17
Exercise 5: Solution0:31
Annotations: Spans and Boxes8:26
Learn how to draw lines and boxes on top of your plot elements.
Exercise 6: Span Annotations0:20
Exercise 6: Solution0:52
Annotations: Labels and LabelSets10:29
Learn how to add annotated text to your graph and label your plot glyphs.
Exercise 7: Labels in Spans0:08
Exercise 7: Solution1:01

Section Introduction2:24
Here's an introduction to this section.
Widgets in Static Bokeh Graphs6:31
Learn how to create user widgets besides your charts.
Widgets in Interactive Bokeh Server Apps7:18
Learn how to create user widgets besides Bokeh server charts.
Select Widgets: Changing Labels Dynamically13:08
Learn how to create a Select widget that allows users to change glyph labels.
Exercise 8: Select Widgets - Drawing Spans Dynamically0:39
Exercise 8: Tips0:34
Exercise 8: Solution1:09
RadioButtonGroup Widgets: Changing Labels Dynamically9:02
Learn how to create a RadioButtonGroup widget that allows users to switch between different label sets.
Slider Widgets: Filtering Glyphs, Part 113:57
Learn how to create a slider that allows users to filter glyphs based on data. Part 1.
Slider Widgets: Filtering Glyphs, Part 25:25
Learn how to create a slider that allows users to filter glyphs based on data. Part 2.

Section Introduction0:43
Here's an introduction to this section.
Streaming Random Points and Lines14:48
Learn how to create a dynamic graph that streams points and lines in real time.
Streaming Financial Data - Designing the App4:36
Learn how to design a Bokeh web app that streams trading data.
Streaming Financial Data - Webscraping12:16
Learn how to scrape data from a trading website for feeding your real-time Bokeh web app.
Streaming Financial Data - Plotting7:38
Learn how to plot real-time trading data scraped from a website every five seconds.
Streaming Timeseries Data19:38
Learn how to stream data along a datetime axis.
User Interaction Between Real-Time Plots and Widgets14:40
Learn how create widgets that allow users to interact with a real-time Bokeh chart.
Example: Visualizing Spinning Planets0:54
Here's one more data visualization example of a mini solar system.

Introduction to Flask8:51
Get a quick introduction to the Flask web framework.
Embedding Static Bokeh Plots in Flask15:56
Learn how to embed Bokeh static plots into a Flask web application.
Embedding Bokeh Server Plots in Flask9:02
Lean how to embed Bokeh Server apps into Flask web apps.
Embedding Static Bokeh Plots in Django: Setting up a Django App6:11
You will be guided on how to create a sample Django web app where we can later embed Bokeh plots.
Embedding Static Bokeh Plots in Django: Embedding the Plot10:44
Learn how to embed a Bokeh HTML plot in an existing Django web app.

Deployment Options7:41
A summary of services where you can deploy your Bokeh apps.
Deploying Static Bokeh Plots5:07
Learn how to publish your HTML Bokeh plots on a website for free.
Deploying Interactive Bokeh Server Apps Embedded in Flask- Setting up the VPS11:32
Here is how to set up a VPS (Virtual Private Server) for deploying Bokeh Server apps embedded in Flask apps.
Deploying Interactive Bokeh Server Apps Embedded in Flask - Installing Software7:44
Preparing the VPS by installing required software such as NGINX server, Python libraries, etc.
Deploying Interactive Bokeh Server Apps Embedded in Flask - Configuration Files4:03
Creating configuration files that tell the server how to run the deployed app.
Deploying Interactive Bokeh Server Apps Embedded in Flask - Uploading Files7:47
Uploading the project files into the remote server with FileZIlla.
Deploying Interactive Bokeh Server Apps Embedded in Flask - Editing Server Files5:47
Modifying some of the uploaded files on the server.
Deploying Interactive Bokeh Server Apps Embedded in Flask - Starting the Service2:29
Restarting the web server and finally having the app online.
Deploying Interactive Bokeh Server Apps Embedded in Flask - Troubleshooting5:30
Here is how to troubleshoot your app if it's not working.
Deploying Interactive Bokeh Server Apps as Standalone0:44
Bonus Lecture0:17

Requirements

A working computer (Windows, Mac, or Linux)
Basic knowledge of Python

Description

If you love Python and want to impress your clients or your employer with impressive data visualization on the browser, Bokeh is the way to go. This course is a complete guide to mastering Bokeh, a Python library for building advanced and data dashboards containing beautiful interactive visualizations. The course will guide you step by step from plotting simple datasets to building rich and beautiful data visualization web apps that plot data in real-time and allow web users to interact and change the behavior of your plots via the internet from their browsers.

Whether you are a data analyst, data scientist, statistician, or any other specialist who deals with data regularly, this course is perfect for you. It will give you the skills to visualize data in a way that excites your audience and eventually sells your product or your idea much easier. All you need to have to learn Bokeh is some basic prior knowledge of Python.

The course also contains exercises to help you check your skills as you progress. You will be given access to various data samples and provided with additional examples to enforce your Bokeh skills. The course is estimated to take you around four weeks to complete assuming you devote 10-20 hours/week depending on your productivity skills.

Who this course is for:

Anyone involved in the data industry
Anyone who is already familiar with Python basics

Interactive Data Visualization with Python and Bokeh

What you'll learn

Explore related topics

Course content

Getting Started13 lectures • 33min

Customizing Bokeh Graphs18 lectures • 1hr 12min

Advanced Plotting14 lectures • 58min

Bokeh Server: Interactive Plotting with HTML Widgets10 lectures • 1hr

Bokeh Server: Streaming Real Time Data8 lectures • 1hr 15min

Embedding Bokeh Plots in Websites5 lectures • 51min

Deploying Bokeh Data Visualization Apps in Live Servers11 lectures • 59min

Requirements

Description

Who this course is for: