Data Journalism in R Tutorials

Welcome to Data Journalism in R

Welcome to Data Journalism in R

print("Hello world")
## [1] "Hello world"

Now that we got that out of the way, welcome to a brand new Storybench vertical, Data Journalism in R! This space will be home to tutorials, links to interesting projects that use R, and all varieties of other data journalism and R-related miscellany.

As I’ll be your tour guide, I figure I should tell you a bit about myself. I’m a PhD Candidate in the English department here at Northeastern as well as a freelance journalist. I began learning R several years ago in the context of a Humanities Data Analysis course that I took with History professor Ben Schmidt. Since then, I’ve put my R wizardry skills to work on the Viral Texts Project, as well as on a number of other projects. You can check out some links on my website if you’re interested. You can also follow me on Twitter.

Of course, there are a number of tools and programming languages available for journalists who want to work with data, so it might be worth saying something about why we’re featuring R here. Let’s start with the question of pre-made tools versus learning to do some programming. While web-based tools have become increasinlgy sophisticated in recent years (you can check out a list that the NULab compiled here), I’ve found that with even a little bit of coding skills, you can go a lot further. This is the know-enough-to-be-dangerous model. And actually, I’ve found in the years I’ve been learning R, that is actually pretty fun–in a sometimes frustrating stay up way past midnight trying to solve this one litte problem kind of way.

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Anyway, that’s probably enough by way of introduction. Storybench has already published several posts related to working with R, and you can see some of those here. My first, non-introduction post is also live now and focuses on connecting RStudio to Twitter and scraping down some data. Check it out!

Photo credit: Flickr user Dwayne Bent

Jonathan D. Fitzgerald
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