Interactive Data Visualization with Python & Bokeh
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Interactive Data Visualization with Python & Bokeh

A complete guide to building interactive and beautiful data visualization web apps using the Python Bokeh library.
Bestselling
4.5 (207 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
2,194 students enrolled
Created by Ardit Sulce
Last updated 6/2017
English
Current price: $10 Original price: $95 Discount: 89% off
30-Day Money-Back Guarantee
Includes:
  • 7 hours on-demand video
  • 25 Articles
  • 5 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I 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.
View Curriculum
Requirements
  • A working computer (Windows, Mac, or Linux)
  • Basic knowledge of Python
Description

Course released on 10/27/2016

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 has seven hours of video content and it is packed with eight 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 is the target audience?
  • Anyone involved in the data industry
  • Anyone who is already familiar with Python basics
Curriculum For This Course
82 Lectures
07:17:08
+
Getting Started
8 Lectures 26:23

Get to know about a few facts about the course.

Course Introduction
00:33

A short introduction on what Bokeh library can do.

Preview 06:02

Bokeh and Bokeh Server
2 questions

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

Creating Your First Bokeh Plot
13:52

Exercise 1: Plotting triangles and circle glyphs
00:10

Exercise 1: Solution
00:26

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

Using Bokeh with Pandas
04:51

Exercise 2: Plotting Education Data
00:13

Exercise 2: Solution
00:14
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Diving Into Bokeh
9 Lectures 37:39

Get to know with this section.

Section Introduction
01:29

Get to know with how a Bokeh chart is structured.

Structure of a Bokeh Chart
08:55

Let's go through the structure of a chart one more time.

Recap - Bokeh Structure
00:02

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

Bug with the Show Method
05:09

Learn about the three different coding interface levels of Bokeh.

Bokeh Interfaces
03:47

Here are three chart examples, one for each of the three Bokeh interfaces.

Bokeh Interfaces - Examples
07:41

Here's a recap of interfaces.

Recap - Bokeh Interfaces
00:18

Learn how the source code of Bokeh is structured.

Structure of the Bokeh Source Code
06:06

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

Using the Bokeh Documentation
04:12
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Customizing Bokeh Graphs
17 Lectures 01:11:11

Get to know with this section.

Section Introduction
03:03

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
00:21

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
00:09

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
00:30

Exercise 3: Solution
02:01
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Advanced Plotting
14 Lectures 57:47

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 Periodic Table Elements
00:45

Exercise 4: Solution
00:36

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
00:36

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

Annotations: Spans and Boxes
08:26

Exercise 6: Span Annotations
00:21

Exercise 6: Solution
00:49

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
00:58
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Bokeh Server: Interactive Plots and Widgets
10 Lectures 01:00:18

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
00:40

Exercise 8: Tips
00:38

Exercise 8: Solution
01:15

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
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Bokeh Server: Streaming Real Time Data
8 Lectures 01:15:16

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
00:57
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Embedding Bokeh Apps in Websites
5 Lectures 50:31

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
08:49

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
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Deploying Data Visualization Apps in Live Servers
11 Lectures 58:34

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
00:45

Closing Lecture
00:09
About the Instructor
Ardit Sulce
4.4 Average rating
10,936 Reviews
85,284 Students
6 Courses
Python and GIS Expert, Founder of PythonHow.com

Ardit received his master's degree in Geospatial Technologies from the Institute of Geoinformatics at University of Muenster, Germany. He also holds a Bachelor's degree in Geodetic Engineering.

Ardit offers his expertise in Python development on Upwork where he has worked with companies such as the Swiss in-Terra,  Center for Conservation Geography, and Rapid Intelligence. He is the founder of PythonHow where he authors written tutorials about the Python programming language.