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Building Interactive Data Visualizations with D3.js [Video]

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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

For this course you will require basic knowledge of HTML, CSS, and JavaScript. It is not a prerequisite to have formal training in programming. If you are interested in presenting your data with aesthetically appealing visualizations, this course is for you.

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

GETTING STARTED
BINDING DATA TO HTML ELEMENTS
USING SVG
ENTERING, UPDATING, AND EXITING WITH DATA AND SVG SHAPES
BUILDING OUR FIRST VISUALIZATION – A SCATTER-PLOT
ADDING INTERACTIVITY
ADDING TRANSITIONS
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
In Detail

D3.js is a JavaScript library that enables data to drive interactive graphical forms and makes complex data analysis easier. Nowadays, big data, data deluge, and analytics are all trending buzzwords, so how does D3.js make sense of all this data? Simply by using visualizations and defining rules for dynamic graphics engines, which allows users to gain rich insights from large and complex datasets.

Building Interactive Data Visualization with D3.js showcases the D3 JavaScript library built specifically for the use of driving visual elements with data. This video course will walk you through the basics of the library by showing its core components and methodologies. By following along with the examples in this video you’ll become proficient at creating dynamic visualizations driven by user interactivity.

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.

Authors

Alex Simoes

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

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.

He was an early adopter of Netscape Navigator 2.0's JavaScript, seeing the potential of dynamic pages early on. Unfortunately, his experience in dealing with IE 4 on a time card system in 1997 soured his opinion on JavaScript for a number of years. He then concentrated on server-side technologies and had a number of articles published in Japanese web and database periodicals.

As third-party JavaScript frameworks conquered the incompatibilities, Microsoft built their own version of ECMAScript. Michael slowly came back to the dynamic scripting scene. jQuery and its ecosystem of plugins won him back full time, but it doesn't compare to the power and elegance of D3.js. Crossfilter and dc.js look like the next step in his never-ending pursuit of knowledge. This is Michael's second video course about D3.js, following the success of his Rapid D3.js course (https://www.packtpub.com/web-development/rapid-d3js-video).

Building Interactive Data Visualizations with D3.js [Video]

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网友最新评论 (1)

  1. 利用D3.js绑定互动数据可视化:创建吸引人的数据驱动和互动的视觉作品,用以演示复杂的数据 通过学习本教程,你讲获取基本的HTML、CSS和JavaScript知识。这并非是正式编程的预备课程。如果你对通过漂亮的吸引人的可视化方式演示你的作品感兴趣,那么本教程适合你的学习。 主要内容:了解使用视觉元素从数据中简化和衍生有意义的成果的重要性;有效地使用Enter、Update、Exit设计模式;学习创建自定义视觉效果;将用户数据用于动态视觉引擎;介绍转换和动画以强调数据更新时的改变;发现使用图片演绎数据信息的不同技术;掌握使用公共API从外部数据源中导入数据。
    wilde(特殊组-翻译)1年前 (2015-10-08)