Building Interactive Data Visualizations with D3.js: Create engaging data-driven and interactive visualizations to display complex data using D3.js [Video]
3 hours and 24 minutes | Friday, September 11, 2015 | Video: AVC (.mp4) 1280x720 25fps | Audio: AAC 48KHz 2ch | 789 MB
Genre: eLearning | Language: English | With: Code Files
About This Video
Produce beautiful and impactful data visualizations for the Web
Create highly interactive scatterplots and geo graphic maps
Use data to tell a story with custom and novel methods of visualization
Incorporate interactivity to enable users to dynamically change visualizations
Table of Contents
BINDING DATA TO HTML ELEMENTS
ENTERING, UPDATING, AND EXITING WITH DATA AND SVG SHAPES
BUILDING OUR FIRST VISUALIZATION – A SCATTER-PLOT
BUILDING A GEOMAP
PUTTING IT ALL TOGETHER - GEO-SCATTER
What You Will Learn
Understand the importance of using visual elements to simplify and derive meaning from data
Use the Enter/Update/Exit design pattern effectively
Learn to create custom visualizations
Incorporate user input for dynamic visualization engines.
Introduce transitions and animations to highlight changes when data is updated
Discover different techniques for visually encoding information in graphics
Master interactions with public APIs to pull in data from external sources
This course starts with the very basics of frontend web development showing the challenges of incorporating dynamic graphics without using D3. Users learn to combine data with visual elements on the page to create informative visualizations. By the end of this section, viewers will be comfortable with using the D3 library to create their own custom concept of data-driven visualizations.
We’ll see how to use real datasets via APIs to create custom visualizations. By leveraging the interactive nature of web programming we’ll look at how to incorporate user input to add interactivity to our visualization. We’ll start with basic scatter plots and slowly build upon this foundation to create more complicated forms of dynamic data visualizations. Eventually we’ll end the video course by walking through the process of creating a completely novel form of visualization merging concepts of both a scatter plot and a geographic map.
Building Interactive Data Visualization with D3.js provides one with the foundation to continue on their journey of creating novel and highly impactful data visualizations.
Style and Approach
This course employs a practical, hands-on approach to driving your complex data using D3.js with examples and line-by-line explanation of the programmed solutions.
Alex Simoes is a co-founder of the data visualization company Datawheel. He is a graduate at the MIT Media Lab where he worked to develop data decision making tools using visual techniques to explore big datasets. As part of his Master's thesis he developed The Observatory of Economic Development (atlas.media.mit.edu), a website used to visualize world trade flows with 50 years’ worth of data from more than 200 countries and 2000 products. He is also responsible for the creation of DataViva.info, a collaborative planning tool for Brazilian economic data. Alex is focused on using and contributing to open source projects including D3plus (D3plus.org), an extension to the D3 library that allows for fast and easy creation of online data visualizations. He is focused on developing novel visualization techniques to aid decision-making in all fields.
Michael Westbay graduated from San Diego State University with a BS degree in computer science and a minor in Japanese studies. Upon graduation, he moved to Japan to work for a software company, mainly dealing with databases. After 15 years at that company, he started working independently, connecting databases and web technologies.
Most of what Michael has written has been about Japanese baseball. He started a blog (before blogs were common) in 1995. That eventually led to writing a column for a Japanese baseball magazine for a couple of years. He relied heavily on his own baseball database for the article.