Data Visualization and D3.js

Overview

Learn the fundamentals of data visualization and practice communicating with data. This course covers how to apply design principles, human perception, color theory, and effective storytelling to data visualization. If you present data to others, aspire to be an analyst or data scientist, or if you’d like to become more technical with visualization tools, then you can grow your skills with this course.

The course does not cover exploratory approaches to discover insights about data. Instead, the course focuses on how to visually encode and present data to an audience once an insight has been found.

This course is part of the Data Analyst Nanodegree.

Syllabus

Visualization Fundamentals

Learn about the elements of great data visualization.,Meet data visualization experts, learn about data visualization in the context of data science.,Learn how to represent data values in visual form.

Building Blocks

Learn how to use the open standards of the web to create graphical elements.,Select elements on the page, add SVG elements, and how to style SVG elements.,Instructor Notes throughout this lesson are available if you have little or no experience with HTML and CSS.

Design Principles

Which chart type to use for a data set.,Colors to avoid when making graphics.,How to determine if a graphic is effective.

Dimple js

Create graphics using the Dimple JavaScript library.,Learn about this library as a gentle coding introduction before learning about D3.js.,Produce great graphics with minimal code and interactivity without any extra effort.

Narratives

Learn how to incorporate different narrative structures into your visualizations.,Learn about bias in the data visualization process and learn how to add context.

Animation and Interaction

Learn how to leverage animation and interaction to bring more data insights to your audience.,Learn how to create a bubble map for the World Cup data set.

Taught by

Ryan Orban and Jonathan Dinu

Reviews

2.6 rating, based on 5 Class Central reviews

Start your review of Data Visualization and D3.js

Gregory J Hamel ( Life Is Study) @greg

Udacity's Data Visualization and D3.js is one of two new intermediate data science courses Udacity released this month, the other being an introduction machine learning. This course consists of 4 lessons covering visualization and D3.js basics, desi…

Udacity's Data Visualization and D3.js is one of two new intermediate data science courses Udacity released this month, the other being an introduction machine learning. This course consists of 4 lessons covering visualization and D3.js basics, design principles and dimple.js, narrative structures and interaction/animation. Each lesson spends some time discussing general visualization design principles and considerations followed by technical information, which often invovles combing through D3.js code. Since D3.js is a Javascript library, it is useful to have some exposure to Javascript, HTML and CSS before taking this course.

Data Visualization with D3.js has the same polished and streamlined content structure as Udacity's other courses, with each lesson taking the form of a series of short videos interspersed with quizzes. The content focused on visualization design and principles is well done. On the other hand, the meat of the course--the sections focused on coding and creating visualizations--were not as engaging as I'd hoped. D3.js is a low level Javascript library, so it takes a lot of code to generate graphs and a lot of time to explain the code and learn what it is doing. Too many videos consist of talking students through large chunks of somewhat cryptic code without much interactivity and it takes too long to get to the point where you make visualizations. I didn't feel like I was really learning how to make visualization myself so much as understanding bits and pieces of the instructor's code. The course doesn't give students enough opportunity and direction for writing D3.js code themselves: lessons 3 and 4 don't have problem sets. I think it was probably a mistake to use D3.js for such a short course. It might have been better to use a higher level visualization package that gets students making their own visualizations faster with less code.

Data Visualization with D3.js is not a bad course and I could see other students liking more than I did, but after taking Udacity's excellent Exploratory Data Analysis course, it was a disappointment. In the EDA course, you jump in and start generating tons of plots in R and actually get to the point where you are reasonably comfortable using ggplot2 to make plots by the end. If are looking to learn D3.js specifically, this course could be a good starting point, but for learning data visualization in general, D3.js seemed to be more of a barrier to learning than an asset. I'd liken this course to an introductory programming course that uses C. Starting with a lower level language like C can be a bit painful and it takes longer to get to the point where you are doing interesting things--time you don't have in a 4 lesson course.

I give this course 3 out of 5 stars: Satisfactory.
Angel

This course is outdated, it uses v3 but d3 has v4 time ago, changing many things between these two versions.
Sonsoles López
Sergiy Matusevych
Cláudio Tereso