Data Visualization and D3.js Newsletter Issue 93 Weekly Data Visualization and D3.js Newsletter

Hi Friends -

Welcome to issue 93 of the Weekly Newsletter

Onwards to this week's links...


  • Introducing R2D3
    R2D3 is a new package for R I’ve been working on...The package was built using an object orientated approach. The functions in the package come in two types. The first type take R objects, vectors and data.frames and convert them into json files. There are a number of these depending on the data structure required for the d3. The second type take the json file output wrap some JavaScript around them and create an html file containing the D3 visualisation.

Data Visualization Reading and Videos

  • When The News Calls For Raw Data
    Last Friday, the New York Times published a map visualizing the distribution of military surplus gear by US county...On Tuesday of this week, the team at the Upshot posted to GitHub the full dataset they used to make the map...
  • New Data Visualization Tool Helps You Fight The Man
    Aaron Kreider, in an effort to put those less privileged voters on equal footing, spent the last year developing Justice Map, a data visualization tool that he hopes will offer a solution... By layering Google Maps and U.S. Census data, he created millions of map “tiles” that users can analyze and annotate after searching for a location.
  • Talking With... Antonio Farach
    In this interview, we catch up with Antonio for a more in-depth look at the work being done at Times of Oman/Al Shabiba, the challenges behind creating a high amount of quality pieces in two completely different languages, and the state of print journalism in the Middle East region.
  • Improving Data Visualization: Where Do I Put All Those Annotations?
    Annotations are simply text that indicate a point on a time-series chart when a key event occurred. These key events help us understand the movement—up or down—in time-series data. Simple. What could possibly be complicated about that? Well, sometimes annotated time-series charts can hard or confusing to read, especially when a chart has many of them. Here are some ideas about how to make annotations more clear.

D3.js Reading and Videos

  • Who Speaks What On GitHub?
    These visualization were built for the GitHub Data Challenge 2014. The source can be found on GitHub. These three visualizations provide insight into the language skills of users on GitHub. The three distinct techniques are displayed below. Want to know more? Read more here on how I built this!
  • Responsive Data Visualization
    The final chapter of my book, D3.js in Action, is focused on explaining using the D3 data visualization library for mobile development...The concept of creating websites that are properly formatted for various screen sizes and interaction methods is known as Responsive Web Design. Applying the same perspective to data visualization can be thought of as Responsive Data Visualization...
  • A Simple Text-Based Clock Using D3js
    A simple text-based clock that can be used as a Mac OSX Dashboard Widget...Based on the very sleek QLOCKTWO wall clock by Biegert & Funk. The page uses code based on this blog post, and makes use of D3.js for manipulating the DOM etc. The above install directions are based on this blog post.
  • Angularjs Directives For C3.js Chart Library
    The goal for the Angularjs directive is to come up with some sort of DSL in the HTML language for creating charts with c3.js. I will go though the different aspects of creating a chart.
  • Building A Memory Transit Map
    I have always liked the aesthetic of a subway map. There’s something about the web of colorful lines connected by dots trying so desperately to bring order to chaotic systems such as the NYC Subway or the London Underground. As an experiment, I thought it would be fun to try to automatically generate a transportation map given some set of arbitrary data.

Hope that you had a great past week and that next week is even better!

Wishing you the best, 
Sebastian Gutierrez

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