Data Visualization and D3.js Newsletter Issue 32 Weekly Data Visualization and D3.js Newsletter

Hi Friends -

Welcome to the thirty-second issue of's Weekly Newsletter

Onwards to this week's links...


  • Data-Driven Aesthetics
    Ten years ago, I was a statistician at Bell Laboratories. The idea that data might be the basis for creative work in the arts was new to me. But since then, I have collaborated with artists like Mr. Rubin, designers, even an experimental theater company.
  • Just Enough SVG
    Now that D3.js is in a stable state and has achieved near-ubiquity amongst data visualization people, gears shift to document: how selections work, via reimplementation, presentations, and so on. Most of this focuses on the ‘hard part’ of D3.js, which is the concept of the selection and data join. This is about what you might call an easier part, or an even-lower-level one: SVG.

Data Visualization Reading and Videos

  • GeoJSON on GitHub: Now What?
    So GitHub announced that you can now automatically view any GeoJSON (& TopoJSON) files that may be in a repository inside an interactive map driven by MapBox technology. This simple enhancement to GitHub is probably one of the most significant developments in the geospatial industry in years. I’ll explain a little later in this post. It’s also important to view this new capability as a great, but limited, first step. I’ll discuss that a little later as well.
  • Miriah Meyer (Microsoft Faculty Fellow and Visualization Expert) Interview
    Miriah Meyer received her Ph.D. in computer science from the University of Utah, then did a postdoctoral fellowship at Harvard University and was a visiting fellow at MIT and the Broad Institute. We talked with Miriah about visualization, collaboration, and her influences during her career as part of the Simply Statistics Interview Series.
  • Dynamic CRM Data Visualizations With Excel 2013 GeoFlow
    There are some great new features available in Excel 2013 that can take your Dynamics CRM data visualization onto a whole new level without the need to invest in new server infrastructure or build traditional OLAP cubes on your SQL Server.
  • Data Visualization's New Shine
    In the hunt for alpha, Wall Street firms look for the right data visualization technologies to make sense of petabytes of structured and unstructured data while maintaining regulatory compliance.
  • Visualizing Flight Paths with Python
    This is an example of plotting flight paths from the OpenFlights dataset with the gcmap Python package. The OpenFlights dataset contains three files, airports.dat, routes.dat, and airlines.dat. We are interested in the first two. We'll use airports.dat to get the coordinates of each airport, and routes to determine which airports are paired by a route.

D3.js Reading and Videos

  • Converting Shapefiles to TopoJSON And A GitHub Secret
    This blog post will show you how to convert shapefiles to TopoJSON. We'll convert the two shapefiles we created in my previous blog post, containing all counties and municipalities of Norway. GitHub recently added support for GeoJSON, but you'll get an interactive map with TopoJSON as well! Just use .topojson as the file extension.
  • Messing Around With D3.js And Hierarchical Data
    These days there are a lot of browser-oriented visualization toolkits, such d3.js or jit.js. They’re great and easy to use, but how much do they scale when used with medium-large or very large datasets?
  • Pathways – Filling Space
    Paths was born from work looking at space filling algorithms. It turned out to be a nice random pattern generator. Built with D3.js - Play around with the parameters and when satisfied export to a graphics program where you can adjust colours and line thickness.

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

Wishing you the best, 
Sebastian Gutierrez

Want to better understand this topic?
Check out these super-useful D3.js Screencast Videos (1 in 3 are free...)
=> D3 Screencasts Videos