Hi Friends -
Welcome to the nineteenth issue of DashingD3js.com's Weekly Newsletter .
Onwards to this week's links...
D3.js Release 3.1
New / Updated Functionality in Geo, Selections, Scales and Data, Geometry and SMASH.
Data Visualization Reading and Videos
The Power of Visualization's "Aha!" Moments
Amanda Cox has been a graphics editor at the New York Times for eight years. Trained as a statistician, Cox develops visualizations across platforms, from simple print infographics to highly complex online interactive data tools. I spoke to Cox about the Times' approach to visualization and the power of "Aha!" moments.
How We Die - Information is Beautiful
How did humans die in the 20th century? And which were the worst killers? Information is Beautiful gathered and examined mortality data from around the world – from disease to murder to mudslides – then calculated and visualised what killed the most people.
Understanding the TopoJSON Data Format
In order to use this dataformat, it can be usefull to understand the structure of a TopoJSON file. That is why I will break it appart and analyse each element in the following. A more detailed description of the dataformat can be found here.
Illusions In Data Visualization
Data visualizations are effective ways for inputting information into a human’s brain, and as Visual Analytics Researcher at Tableau Software and Visual.ly advisor Robert Kosara says, visualizations are what makes our world real. But even when the people who created the visualization are being honest, we can’t always trust what our eyes are showing us.
4 Objectives For Your Data Visualizations
Andy Kirk, data visualization architect, wants you to understand this basic point about data visualization: While it's popular and relevant today, it's not new. What is, though, are the opportunities and challenges associated with it. Kirk proposes a methodology for doing just that, a workflow "to give you the most effective and efficient way to approach making sense of your data, find stories in the data, and present and convey those stories to others."
D3.js Reading and Videos
Visualizing k-means Clustering Using D3.js
Having learned a little about d3.js at a hackathon I attended, I decided to put it to good use. Below is an interactive implementation of the k-means clustering algorithm, as visualized using d3.js. Click to place points.
Mapping with D3.js Overview - Malcolm Maclean
Another string to the bow of d3.js is the addition of a set of powerful routines for handling geographical information. I am firmly of the belief that mapping in particular has an enormous potential for adding value to data sets. The following collection of examples gives a brief taste of what has been accomplished by combining geographic information and D3 thus far.
Clickme: Render JS / D3.js Visualizations Using R Objects
Visualizing NFL Draft History
This project attempts to visually show all the draft picks for a particular team from 1960 - 2012. The invidiual chart shows all the picks(players) grouped by year, color coded by round. This can be further filtered by a particular round or a particular position. The heatmap chart shows how individual positions drafted for compare to each other, as displayed by intensity of the color, over a given range of years. This can be filtered by a particular decade or any starting and ending years using the year slider. D3.js Source code Included.
Hope that you had a great past week and that next week is even better!
Wishing you the best,