How I'm Learning D3.js

Since I started learning D3.js as part of the 100 Days of Code project the number one question I’ve gotten is: how are you learning D3? I’ve had lots of people that want to know what learning resources I’m using, what my process is, and what I suggest for how to start on D3. I don’t think I’m any sort of expert, and I certainly don’t claim to have the ultimate learning process, but now that I’m halfway through the project I decided to share what I’ve learned.

Textures and geometric shapes (12 Months of aRt, July)

I love R and I love ggplot, but there’s always been one thing that’s really irked me: the real lack of support for complex fills, filters, or other graphics effects goodness. In R, there’s basically only support for perfectly rendered shapes and solid fills. If you want something like a gradient fill, blur, or texture, you’re left to your lonesome. I really felt the pain when I discovered the magic of SVG filters and then sadly realized I didn’t have all this awesomeness in R.

Artistic coding for the useR (12 Months of aRt, June)

This month marks the halfway point of my 12 Months of aRt project, and I want to take the opportunity to reflect on the experience so far and share what I’ve learned with you. This past week I was preparing my lightning talk for useR2019, where I’ll be talking about artistic coding in R, and it gave me a chance to realize how much I’ve learned from this project in such a short time.

Custom fonts and plot quality with ggplot on Windows

Graphics devices are weird, and operating systems are even weirder. If you are a Mac of Linux user, lucky you, you can go on your merry way! But if you’re a Windows user and you’ve ever screamed at your computer “Why the #&*$ wont my fonts work!?!?” or “Why are my plots so &#**ing pixelated!?!”, then read on. Note this is accurate as of May 2019. There is a lot of development happening on ggplot and graphics in R, courtesy of Thomas Lin Pederson and the rest of the ggplot team.

Making the Data Visualization Society Timeline

The Data Visualization Society recently held their inaugural challenge. My final submission was a switchback style timeline that visualized each member as a watercolor splotch. I made the base graphic in R, and applied stylings to the SVG using manual editing and Inkscape. I got several questions about how I made it, so here’s the story from concept to final design. Concept From first looking at the DVS challenge data, I knew I would make a timeline.