Data Visualization on the Browser with Python and Bokeh
4.4 (847 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
7,340 students enrolled

Data Visualization on the Browser with Python and Bokeh

A complete guide on creating beautiful plots and data dashboards on the browser using the Python Bokeh library.
Bestseller
4.4 (847 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
7,340 students enrolled
Created by Ardit Sulce
Last updated 11/2018
English
English
Current price: $65.99 Original price: $94.99 Discount: 31% off
5 hours left at this price!
30-Day Money-Back Guarantee
This course includes
  • 6.5 hours on-demand video
  • 25 articles
  • 7 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
Training 5 or more people?

Get your team access to 4,000+ top Udemy courses anytime, anywhere.

Try Udemy for Business
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.
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 which is a Python  library for building advanced and modern data visualization web applications. The course will guide you step by step starting 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 internet from their browsers. Bokeh is a brand new data science library that is gaining traction fast so it's smart to be ahead of the competition and pack the skills in your portfolio. 

Whether you are a data analyst, data scientist, statistician or any other specialist in the data industry this course is perfect for you as 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 will be provided with additional examples to enforce your Bokeh skills. The course is estimated to take you around four weeks to complete assuming you devote a 10-20 hour / week depending on your productivity skills. You also get daily instructor support in the student forum inside the course which guarantees your success.

Who this course is for:
  • Anyone involved in the data industry
  • Anyone who is already familiar with Python basics
Course content
Expand all 77 lectures 06:46:48
+ Getting Started
11 lectures 32:37

Get to know about a few facts about the course.

Course Introduction
00:32
Installation
00:09

A short introduction on what Bokeh library can do.

Preview 02:51
Bokeh and Bokeh Server
2 questions

Learn to create your first web-based plot with Bokeh.

Preview 13:52
Exercise 1: Plotting triangles and circle glyphs
00:09
Exercise 1: Solution
00:25

Learn to feed your Bokeh charts with data from Pandas dataframes.

Using Bokeh with Pandas
04:51
Exercise 2: Plotting Education Data
00:12
Exercise 2: Solution
00:14

There's currently an issue with the show() method explained in this lecture.

Bug with the Show Method
05:09

Get the links to the official documentation and learn how to use the documentation.

Using the Bokeh Documentation
04:12
+ Customizing Bokeh Graphs
18 lectures 01:11:52

Get to know with this section.

Section Introduction
03:03
Note
00:15

Let's create a basic plot first before adding styling to it in the next lectures.

Creating an Initial Plot
03:13

Learn how to customize the background style of a Bokeh chart.

Figure Background
05:43

Here's a complete list of colors you can use with Bokeh charts.

List of Colors
00:20

Learn how to customize the title of a Bokeh chart.

Title
03:10

Here is a list of text font styles you can use in Bokeh.

List of Text Fonts
00:08

Learn how to customize the axes style of a Bokeh chart.

Axes: Custom Styling
08:01

Learn how to customize the axes geometry of a Bokeh chart.

Axes: Custom Geometry
08:14

Learn how to plot categorical data.

Axes: Categorical Data
02:50

Learn how to customize the grid of a Bokeh chart.

Grid
02:23

Learn how to customize the tools of a Bokeh chart.

Tools
05:26

Learn how to customize the plotted glyphs of a Bokeh chart.

Glyphs
09:34

Learn how to customize the structure of the legend.

Legend: Configuring
04:46

Learn how to customize the style of the legend.

Preview 07:00

Learn how to create pop up window messages.

Popup Windows
04:47
Exercise 3: Summary of Section 3
00:28
Exercise 3: Solution
02:29
+ Advanced Plotting
14 lectures 57:39

Here's an introduction to this section.

Section Introduction
01:51

Learn how to use the native data source object of a Bokeh chart.

ColumnDataSource
16:36
Exercise 4: Plotting Elements of the Periodic Table
00:38
Exercise 4: Solution
00:35

Learn how to extract values from a ColumnDataSource for displaying in a popup window.

Popup Windows with Custom HTML
10:46

Learn how to create multiple plots in one webpage.

Gridplots
05:07
Exercise 5: Gridplots
00:17
Exercise 5: Solution
00:31

Learn how to draw lines and boxes on top of your plot elements.

Annotations: Spans and Boxes
08:26
Exercise 6: Span Annotations
00:20
Exercise 6: Solution
00:52

Learn how to add annotated text to your graph and label your plot glyphs.

Annotations: Labels and LabelSets
10:29
Exercise 7: Labels in Spans
00:08
Exercise 7: Solution
01:01
+ Bokeh Server: Interactive Plotting with HTML Widgets
10 lectures 01:00:08

Here's an introduction to this section.

Section Introduction
02:24

Learn how to create user widgets besides your charts.

Widgets in Static Bokeh Graphs
06:31

Learn how to create user widgets besides Bokeh server charts.

Preview 07:18

Learn how to create a Select widget that allows users to change glyph labels.

Select Widgets: Changing Labels Dynamically
13:08
Exercise 8: Select Widgets - Drawing Spans Dynamically
00:39
Exercise 8: Tips
00:34
Exercise 8: Solution
01:09

Learn how to create a RadioButtonGroup widget that allows users to switch between different label sets.

RadioButtonGroup Widgets: Changing Labels Dynamically
09:02

Learn how to create a slider that allows users to filter glyphs based on data. Part 1.

Slider Widgets: Filtering Glyphs, Part 1
13:57

Learn how to create a slider that allows users to filter glyphs based on data. Part 2.

Slider Widgets: Filtering Glyphs, Part 2
05:25
+ Bokeh Server: Streaming Real Time Data
8 lectures 01:15:13

Here's an introduction to this section.

Section Introduction
00:43

Learn how to create a dynamic graph that streams points and lines in real time.

Streaming Random Points and Lines
14:48

Learn how to design a Bokeh web app that streams trading data.

Streaming Financial Data - Designing the App
04:36

Learn how to scrape data from a trading website for feeding your real-time Bokeh web app.

Streaming Financial Data - Webscraping
12:16

Learn how to plot real-time trading data scraped from a website every five seconds.

Streaming Financial Data - Plotting
07:38

Learn how to stream data along a datetime axis.

Streaming Timeseries Data
19:38

Learn how create widgets that allow users to interact with a real-time Bokeh chart.

User Interaction Between Real-Time Plots and Widgets
14:40

Here's one more data visualization example of a mini solar system.

Example: Visualizing Spinning Planets
00:54
+ Embedding Bokeh Plots in Websites
5 lectures 50:44

Get a quick introduction to the Flask web framework.

Introduction to Flask
08:51

Learn how to embed Bokeh static plots into a Flask web application.

Embedding Static Bokeh Plots in Flask
15:56

Lean how to embed Bokeh Server apps into Flask web apps.

Embedding Bokeh Server Plots in Flask
09:02

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: Setting up a Django App
06:11

Learn how to embed a Bokeh HTML plot in an existing Django web app.

Embedding Static Bokeh Plots in Django: Embedding the Plot
10:44
+ Deploying Bokeh Data Visualization Apps in Live Servers
11 lectures 58:33

A summary of services where you can deploy your Bokeh apps.

Deployment Options
07:41

Learn how to publish your HTML Bokeh plots on a website for free.

Deploying Static Bokeh Plots
05:07

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- Setting up the VPS
11:32

Preparing the VPS by installing required software such as NGINX server, Python libraries, etc.

Deploying Interactive Bokeh Server Apps Embedded in Flask - Installing Software
07:44

Creating configuration files that tell the server how to run the deployed app.

Deploying Interactive Bokeh Server Apps Embedded in Flask - Configuration Files
04:03

Uploading the project files into the remote server with FileZIlla.

Deploying Interactive Bokeh Server Apps Embedded in Flask - Uploading Files
07:47

Modifying some of the uploaded files on the server.

Deploying Interactive Bokeh Server Apps Embedded in Flask - Editing Server Files
05:47

Restarting the web server and finally having the app online.

Deploying Interactive Bokeh Server Apps Embedded in Flask - Starting the Service
02:29

Here is how to troubleshoot your app if it's not working.

Deploying Interactive Bokeh Server Apps Embedded in Flask - Troubleshooting
05:30
Deploying Interactive Bokeh Server Apps as Standalone
00:44
Closing Lecture
00:09