Data Visualization and D3.js Newsletter Issue 88

DashingD3js.com Weekly Data Visualization and D3.js Newsletter

Hi Friends -


Welcome to issue 88 of the DashingD3js.com Weekly Newsletter


Onwards to this week's links...
 

Featured
 

  • A Compendium Of SVG Information
    A huge pile of information about SVG...Covering: How to Use SVG, SVG as an Icon System, SVG Shape Syntax, SVG Patterns, About viewport, viewBox, and preserveAspectRatio, SVG Gradients, SVG and Fragment Identifiers, SVG Strokes, SVG and Text, Animating SVG, SVG JavaScript Libraries, Organizing SVG, SVG Clipping, SVG Build Tools, Getting SVG to Use, SVG Demos, SVG Filters, Data URIs and SVG, SVG and CSS, Optimizing SVG, SVG Software, Accessible SVG, SVG Talks, SVG and JavaScript, SVG Browser Support, SVG Fallbacks, SVG Specs, and Misc...
  • Working With D3.js And Canvas: When And How
    We can create charts quickly when working with D3.js and standard DOM elements, but that comes with a key limitation: the number of nodes we can render is fairly small...Thankfully, using D3.js with canvas (or really any other renderer) isn’t that hard. While it requires working a bit outside of D3.js’s usual lifecycle metaphor, it can still provide you with a lot of power...
 

Data Visualization Reading and Videos
 

  • Six Principles Of Communicating Data: A Checklist
    In a section of the first chapter of Communicating Data with Tableau (O’Reilly, 2014) I lay out six principles of communicating data: 1) know your goal, 2) use the right data, 3) select suitable visualizations, 4) design for aesthetics, 5) choose an effective medium and channel, and 6) check the results....
  • Three Charts Are All I Need
    The last few years have seen an explosion in new ways of visualizing data. There are new classes, consultants, startups, and competitions...In everyday business intelligence (the “real world”), the focus isn’t on visualizing information, it’s on solving problems, and I’ve found that upwards of 95% of problems can be addressed using one of three visualizations...
  • Visualizing High-Dimensional Data In The Browser With SVD, T-SNE And Three.js
    Data visualization, by definition, involves making a two- or three-dimensional picture of data, so when the data being visualized inherently has many more dimensions than two or three, a big component of data visualization is dimensionality reduction...in this post, we show off a proof of concept for interactively visualizing this kind of data in a browser, in 3D...
  • How To Easily Check Visualizations For Accuracy
    It is difficult to tell if many visualizations have been created correctly...Not all visualizations are difficult to double check though. There are a few visualizations that can be checked against themselves. These visualizations are both the easiest way to lose a viewer’s trust (if you do them wrong), and a good tool to regain trust slowly (if you do them right)...
  • Data Stories #38: Visual Complexity With Manuel Lima
    We have Manuel Lima on the show!...He created Visual Complexity in 2005, an archive of network visualizations which became very popular. He is also the author of two great books: Visual Complexity and The Book of Trees. In the show we talk about archiving visualizations, how to write and publish visualization books and how the whole field had developed and where it is heading.
 

D3.js Reading and Videos
 

  • D3.geo: Putting D3 On The Map
    At the recent Maptime SF, “D3.geo: Putting D3 on the Map“, Ian Johnson, along with wonderful folks from Stamen and Mapbox, introduced us to the library and got us started making some maps with D3 and TopoJSON...Here’s what we learned...
  • Building The 2014 One D Scorecard With NiJeL: D3.js For D3
    Data Driven Detroit (D3) launched the 2014 One D Scorecard in May. Today, we’re writing to share more about our process for making this interactive data tool through a Q & A with NiJeL, a team of data scientists and developers that D3 collaborated with to build out the Scorecard. But first, a little context about the project...
  • NYT Bestsellers
    Using the New York Times API I gathered data for eight weeks' worth of trade fiction paperback bestsellers. From there I loaded the book images into a script that would determine the most common colors from the pixels of the book cover. These colors are used in a gradient to make each line identifiable...Built with D3...
  • Automatic Labeling V1
    This is the first version of a d3 plugin for automatic labeling. I called it labeling.Each overlapped label rotates until no more overlaps. If one label reach the last position there is three options...Example shows Automatic Labeling on a D3 Map...

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

Wishing you the best, 
Sebastian Gutierrez
@DashingD3js
www.dashingd3js.com

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