An opportunity to teach, an opportunity to give back… If you’ve seen one of my data science education talks or attended one of my workshops in the last few years, you’ve probably heard me talk about the unvotes package in R. This package provides the voting history of countries in the United Nations General Assembly, along with information such as date, description, and topics for each vote. I love using data from this package in my teaching, especially on day one of class, because the data are rich while being accessible.

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Last week I attended the Toronto Workshop on Reproducibility where I had to the pleasure of giving one of the keynotes. When I was asked to give a keynote for this event on teaching, I had the idea of reflecting on almost 9 years of teaching with introductory statistics and data science through the lens of reproducibility. I would have said “teaching with R Markdown”, but looking back through my notes, this wasn’t true as the rmarkdown package has not been around for that long – turns out I started teaching with it when it was just knitr.

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#TheMoment tweets

On Sunday morning I came across a tweet by NPR’s Lulu Garcia-Navarro morning asking people when they knew things were going to be different due to COVID. Whenever I read replies to a tweet like this I’m always tempted to scrape all the replies and take a look at the data to see if anything interesting emerges.

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Data science tutorials with learnr and gradethis

This post was contributed by Lee Suddaby and Zeno Kujawa, second year students at the University of Edinburgh majoring in Mathematics and Data Science, respectively.

Over the university summer break, we (Zeno and Lee) were busy making preparations for moving more of our Introduction to Data Science course from being human-graded to computer-graded. We both took this course in the Fall of 2019, as part of our first-year studies at the University of Edinburgh, and this is where we first learned R.

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If you’ve ever been to an R workshop I gave, you probably heard me say “if the only thing you get out of this workshop is that RStudio projects are awesome and you should use them, this workshop was worth your time”. And I stand by this statement, they are awesome!1 But sometimes you just want a project-less RStudio! When, you ask? Imagine you have an RStudio project open where you’re writing course slides, or a blog post, or a package… And then imagine a student asks a coding question and you want to run their code quickly but don’t want to populate your environment with the objects that code creates.

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Shiny for JSM 2019

It took me all of 30 minutes from starting this mini-project to writing this post. This is not meant to be a brag, but instead an ode to reproducibility. Last year for JSM 2018 I made a Shiny app to browse the conference schedule. I personally found that app really useful, and I know a few others did as well. And I saved my code in a GitHub repo. Now that JSM 2019 is almost here, I thought I’d try my code again.

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Citizen Statistician

Learning to swim in the data deluge