We live in a world where speed is venerated, rewarded, and sought after. But certain things stubbornly resist attempts to speed them up. I cannot make the tomato plant in my garden grow faster no matter what affirmations I read her nor if I tell her that Sheryl Sandberg advises her to Lean In and flower already. Sure, water and rich soil can speed things up a little, but in a world that’s looking for exponential growth, the tomato plant is opting out of leaning in. Learning, similarly, resists acceleration. We have not arrived at the point where we can simply plug in a new module and know French, and the rate at which we learn is still determined by[…]

Data Visualization & Intro to Tableau, May 1, 2017 Getting Ready Software: If you haven’t already, download the free version of Tableau and install it on your computer. Data sets: Download the Global Superstore dataset. This is a .zip file. Create a folder on your desktop called Tableau, put the .zip file in there, and unzip it. You will see a file called Global_Superstore.xls. If that link doesn’t work for you, try downloading this: Global Superstore (.XLS). Unit 1: History & Intro to Data Visualization We will dive into the history of data visualization and the basics of matching your dataset to an effective visualization. Exercise 1: Starting With Paper If you were designing a data dashboard for your life, what would[…]

Which state college systems offer the best “bang for the buck” when it comes to a student’s chance of graduating, and the amount of debt they will graduate with? With more and more students taking more than four years to graduate, it’s an important question — a question that a scatterplot can shed light on. A scatterplot shows you individual entities across two dimensions. Here’s an example showing you the relationship between the life expectancy of its country’s citizens and its Gross Domestic Product per capita (GDP).  As you can see, countries with lower GDP tend to have lower life expectancies. Now let’s try it with a dataset of our own. First, we have to get a dataset. We’ll start[…]

ABSURDLY ILLUSTRATED TUTORIALS Mapping: The Absurdly Illustrated Guide To Your First Data-Driven TileMill Map Timelines/Tabletop.js: The Absurdly Illustrated Guide To Your First Data-Driven Timeline Data Tables/Tabletop.js: The Absurdly Illustrated Guide To Sortable, Searchable Online Data Tables Immersive Digital Storytelling The Absurdly Illustrated Guide To Immersive, Tablet-Friendly News Stories Comparing and Contrasting/Rawcharts/D3.js: The Absurdly Illustrated Guide To Making Scatterplots With Rawcharts and D3.js

Typically, a finished product — whether it’s a simple one or something as sophisticated as “Snow Fall,” the New York Times’ immersive multimedia piece on an avalanche — doesn’t give many indications about how it was made, or what challenges the developer faced in creating it.  An apparently simple site might have taken hours while you might guess that another site took weeks when it took only hours because there were many available open-source tools to start out with that did a lot of the heavy lifting. Looking at the finished product — or a tutorial like my Insanely Illustrated Guide To Your First Data-Driven TileMill Map — doesn’t really give you insight into whether something took a little effort[…]

[UPDATED! This tutorial is newly updated as of 1/28/17 with new geocoding instructions and now works again!]  TileMill is a free-to-download application for Windows and the Mac that will let you build beautiful, data driven maps.  If the bland sameness of Google maps is giving you ennui, TileMill might be a good alternative for you.   There are many beautiful stylesheets to make TileMill maps visually distinct, and you can control the colors, line widths, and much more about your map using Carto, a CSS-derived language.  Here’s a beautiful map of Montreal using a watercolor-like stylesheet:   What follows is a detailed, highly-illustrated guide to creating your first map in TileMill.  We will be using real data from the Rhode[…]

My name is Lisa Williams and I recently finished teaching a four week course for absolute beginners on data visualization — absolute beginners who happened to have day jobs in mission-driven nonprofits and local community foundations.    I found the experience, and the class’ participants energy and insight very inspiring.  When I finished, I thought, “I should write a book — so that anybody who wants to change the world can also change charts and graphs.” I wasn’t sure what to call it, until I attended a gathering of my students and peers.  One of them suggested that I call it “Data For Radicals.”  “Do you really have to be that radical to learn data visualization?” I asked?  “No, but[…]