Data Visualization and D3.js Newsletter Issue 190 Weekly Data Visualization and D3.js Newsletter

Hi Friends -

Welcome to issue 190 of the Weekly Newsletter.

Onwards to this week's links...


  • Birth Of Cities: Visualizing 6,000 Years Of Urbanisation
    Whether it is Rome, Sparta, ancient Babylon or Troy, or maybe even vast ancient cities buried beneath the jungles of Cambodia, the human instinct to coalesce into villages, towns and cities is phenomenal, and a new map captures 6,000 years of this...
  • D3.js v4.0.0 Released
    D3 is now modular, composed of many small libraries that you can also use independently. Each library has its own repo and release cycle for faster development. The modular approach also improves the process for custom bundles and plugins...There are a lot of improvements in 4.0: there were about as many commits in 4.0 as in all prior versions of D3. Some changes make D3 easier to learn and use, such as immutable selections. But there are lots of new features, too! These are covered in detail in the release notes; here are a few highlights...

Data Visualization Reading and Videos

  • Child Mortality Rates
    Child Mortality Rates have fallen by extraordinary rates in the last century. It is a testament to the power of science and the common good working to make medical breakthroughs...Roll over the visualization to explore individual countries and their decrease in child mortality...
  • Analyzing Swearing In Movies Part 1: Swears Per Minute
    In this short article I'd like to explain the process I took to create some simple D3.js visualizations based on the number of swears per minute in movies. I'm going to do some additional analysis on this, but for now I'd just like to so you some samples, and code fragments that explains the process I've used...
  • The ggthemr package – Theme and colour your ggplot figures
    The ggthemr package was developed by a friend of mine, Ciarán Tobin, who works with me at KillBiller and Edgetier. The package gives a quick and easy way to completely change the look and feel of your ggplot2 figures, as well as quickly create a theme based on your own, or your company’s, colour palette...In this post, we will quickly examine some of the built in theme variations included with ggplot2 in R, and then look at the colour schemes available using ggthemr.
  • Venn Diagrams: Read and Use Them the Right Way
    Venn diagrams seem like a straightforward way to show combinations. In their most basic form, you have two circles that each represent a thing or a group, and the overlap represents the combination of the two. Non-overlapping areas represent separation. The entire area of the diagram, including the space outside the circles, represents all possible values, groups, or populations...That’s about it. But mistakes happen, and they seem to be common enough that makes me think these Venn diagram things might need some explaining...

D3.js Reading and Videos

  • Changes in D3 4.0
    D3 4.0 is modular. Instead of one library, D3 is now many small libraries that are designed to work together. You can pick and choose which parts to use as you see fit. Each library is maintained in its own repository, allowing decentralized ownership and independent release cycles. The default bundle combines about thirty of these microlibraries...If you don’t care about modularity, you can mostly ignore this change and keep using the default bundle. However, there is one unavoidable consequence of adopting ES6 modules: every symbol in D3 4.0 now shares a flat namespace rather than the nested one of D3 3.x....
  • Examples Using Matrix Transforms In SVG
    This image shows examples of affine transforms using the matrix(a,b,c,d,dx,dy) function in SVG, where a, b, c and d are the elements of a square matrix which is used to skew, rotate and scale a coordinate system, and dx and dy are the elements of the translation vector...
  • Quilted Blocks In D3 v4
    An example of using D3 v4 for making quilted block designs (also called color weaving; see Albers et al. work on visual aggregation for more information)...The data is randomly generated from a normal distribution, with the color scale quantized around two standard deviations from the mean. Refresh the page to see different distributions of data...

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