Data Visualization and D3.js Newsletter Issue 196

DashingD3js.com Weekly Data Visualization and D3.js Newsletter

Hi Friends -


Welcome to issue 196 of the DashingD3js.com Weekly Newsletter.
 

Onwards to this week's links...
 

Featured
 

  • FiveThirtyEight's Data Journalism Workflow With R
    FiveThirtyEight is a data journalism site that uses R extensively for charts, stories, and interactives...In this presentation, I'll walk through how cutting-edge, data-oriented newsrooms like FiveThirtyEight use R by profiling a series of already-published stories and projects. I'll explain our use of R for chart-making in sports and politics stories; for the data analysis behind economics and science feature pieces; and for production-worthy interactives...
  • Interactive Data Visualization of Geospatial Data using D3.js, DC.js, Leaflet.js and Python
    The goal of this tutorial is to introduce the steps for building an interactive visualization of geospatial data...To do this, we will use a dataset from a Kaggle competition to build a data visualization that shows the distribution of mobile phone users in China...We will cover a wide range of technologies in this tutorial: Pandas for cleaning the data, Flask for building the server, Javascript libraries d3.js, dc.js and crossfilter.js for building the charts and Leaflet.js for building the map...
 

Data Visualization Reading and Videos
 

  • Building A ggplot2 Step By Step
    The post below will step through the making of this plot using R and ggplot2 (the dev version from Github). Each code chunk and accompanying image adds a little bit to the plot on its way to the final plot; depicted here. Hopefully this can help or inspire someone to take their plot beyond the basics...
  • ProPublica Data Institute 2016
    ProPublica Data Institute 2016 - An intensive workshop on how to use data, design and code for journalism. From June 1st to 15th in New York City...Here are all of the materials we used to teach the 2016 ProPublica Data Institute: slides, exercises, links, and homework...
  • Useful Scraping Techniques
    A recent NPR project that collects structured data about gun sale listings from Armslist.com demonstrates several of my favorite tricks for writing simple, fast scrapers with Python...
  • The Snows Of California - An Analysis Of California Snowfall In The 21st Century
    Snow is vital to the environmental health of the western United States. Unlike rainfall, it doesn't come as one burst that's here and then quickly gone. Instead, it tends to accrue over the winter and slowly melt as the temperatures rise in the spring. The melt typically continues into the early summer, providing a steady, consistent level of water in mountain watersheds. This is particularly important for a state like California, which receives almost no summer rainfall...
 

D3.js Reading and Videos
 

  • Split An SVG Path Into Pieces
    This is an example of how to split an SVG path into an arbitrary number of pieces...1) Draw an initial path, 2) Determine how many pieces you want and what percentage of the full path each piece should account for. (Here we're using 20 pieces of random sizes.), 3) Get the location of each section's points along the overall path, and 4) Use those points to draw a new path for each section...
  • Unit Testing Visualizations
    When we build visualizations that display a small and predictable data set we can usually get away with Looks-Right-Testing (LRT? Anyone? Anyone?). Of course all visualizations have to “look right” but when we start dealing with larger, dynamic datasets, or use our visualizations as UI building blocks we need a way to declare our assumptions and safeguard against regression with unit testing...
  • d3-force-gravity
    Implement gravitational attraction (or force-field-like repulsion) using d3-force...

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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