Data Visualization and D3.js Newsletter Issue 201

DashingD3js.com Weekly Data Visualization and D3.js Newsletter

Hi Friends -


Welcome to issue 201 of the DashingD3js.com Weekly Newsletter.
 

Onwards to this week's links...
 

Featured
 

  • The Entire History of Kickstarter Projects, Broken Down by City
    Pretty much all existing attempts to map creative communities use census and jobs data. But creative efforts are often side-hustles. They’re garage/basement/cottage industries that will not appear in a census. A different approach: use Kickstarter data, which is one of the largest archives of creative projects, ever. They gave us access to 100,000 projects, which means we can characterize every major city by the types of projects it launches...
  • Improving D3 Path Animation
    D3 provides us with many of the basic building blocks needed to make charts in browsers while also making it extremely easy to animate them. One of the most common charts created with D3 is a line chart, often consisting of a series of SVG elements to visualize the data. In this post, I dissect how the animation of paths work in D3 and how they can be improved...
 

Data Visualization Reading and Videos
 

  • UpSet: Visualization of Intersecting Sets
    Understanding relationships between sets is an important analysis task that has received widespread attention in the visualization community. The major challenge in this context is the combinatorial explosion of the number of set intersections if the number of sets exceeds a trivial threshold. In this paper we introduce UpSet, a novel visualization technique for the quantitative analysis of sets, their intersections, and aggregates of intersections...
  • Maarten Lambrechts On The Underused Power Of Explorable Explanations & More
    Probably the most famous data journalist in Belgium, Maarten Lambrechts, has never attended a traditional journalism school. He graduated as a bio-engineer which gave him a sense of working with statistics and math. Later on he spent a few years in Latin America, where he started blogging and reading works of authors like Edward Tufte, paving his way to journalism. Back in Belgium, he started working for a monthly magazine as a website manager, and that is where he started experimenting with data visualizations. Few years later, these experiments became his full-time job in the Mediafin newsroom...
  • PolicyViz Podcast: Episode #56 - Andy Kirk
    I’m very excited to welcome Andy Kirk to the show. Andy–as I’m sure you know–runs the popular website Visualisingdata.com, where he writes about all things data visualization, teaches dataviz through his workshops, and does a popular roundup of the best dataviz on the web...In this episode, Andy and I talk about his data visualization design process, dataviz sins, new projects, and, of course, his new book, Data Visualization: A Handbook for Data Driven Design...
  • Data Visualisation in Hydrology
    As an introduction to the blog, this post will review data visualisation in hydrology and explore why it is so important...
 

D3.js Reading and Videos
 

  • Antibiotic Resistance Simulation
    Inspired by this Harvard antibiotics resistance study I wanted to build a simulation of evolution...In this simulation the cells each produce a number, determined by its "genes", which are two random numbers added together. As they reproduce, sometimes those genes mutate, and the cells produce a new number. When they mutate, they are assigned a different color in the visualization...The "petri dish" is divided into 9 sections, like in the Harvard study. In place of exponentially increasing amounts of antibiotics in each column, the survival criteria is whether the cell's number is divisible by an increasingly large number...
  • py-d3: D3 block magic for Jupyter notebook
    py-d3 is an IPython extension which adds D3 support to the Jupyter Notebook environment...D3 is a well-known and -loved JavaScript data visualization and document object manipulation library which makes it possible to express even extremely complex visual ideas simply using an intuitive grammar. Jupyter is a browser-hosted Python executable environment which provides an intuitive data science interface...These libraries are foundational cornerstones of web-based data visualization and web-based data science, respectively. Wouldn't it be great if we could them to work together? This module does just that...
  • Voronoi binning (animated)
    Group data points around the largest points. The recipe is as follows: 1) sort data points according to their sizes (here size = d[3]) 2) use top 10% points as Voronoi sites 3) bin all data points according to their Voronoi cell, using voronoi.find(). The binning is rendered by using the Voronoi sites's color...
  • Data Joins in D3.js
    Understanding D3's Joins is critical to understanding how D3 works. It is a core concept that is reflected in pretty much every piece of D3 code you'll ever encounter. This tutorial illustrates how the join process works...

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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