Randall Munroe of xkcd on Data Stories

Randall Munroe of xkcd was on the Data Stories podcast. He talks about his work, his process, and communicating complex ideas to a wide audience. It’s amazing how much of his process overlaps with visualizing data.

Worth the full listen.

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My chat with Data Stories

I talked with Moritz and Enrico on Data Stories, my favorite visualization podcast. They’ve been providing a healthy balance of practice and research since 2012.

I don’t dare listen to myself, but based on the show notes we talked about FlowingData over the years, some of the changes in visualization, and answered listener questions. You can listen here.

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C’est la vis, teaching kids how to visualize data

By adulthood, it’s expected that we can read charts to some degree. You’re supposed to know how visual encodings map to data and then interpret. I don’t remember actually learning how to do that though. Do you? C’est la vis is a research project and app that aims to help with that. The project, by Basak Alper from NASA JPL and Nathalie Riche from Microsoft Research, along with Fanny Chevalier, Jeremy Boy, and Metin Sezgin, aims to help kids learn how charts work and help teachers create a curriculum that’s useful.

Hear about their work on the latest Data Stories podcast. A lot of the lessons learned can cross over to teaching grown ups visualization too.

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Working with R at the New York Times

Amanda Cox

Amanda Cox from the New York Times was on the Data Stories podcast. You should listen. She talks about how she uses R, workflow at the New York Times, and some of her favorite projects.

I listened while picking up my son from daycare. I hope some of it seeps into his consciousness through osmosis.

One note. In the beginning Amanda talks a little bit about how she got started. She was a statistics graduate student getting tired of the theory side of things. Her program didn't look at a ton of data in the first year, which led her to the New York Times, a placed aimed at practicality.

However, no surprise, it varies a lot by program. For example, the UCLA and Berkeley statistics departments get you looking at data early on. I haven't taken a course in years and am far removed from academics, but I only imagine it's more true with the whole data science field evolving into a real thing.

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