The strength of R doesn’t lie in a single programming paradigm, it lies within the warm, welcoming and ecclectic community of useRs.
Like anyone who gets introduced to R, you start to look on the web for other like minded people. Upon doing so, you find a vibrant community with very knowledgeable and helpful people. Bob Rudis (@hrbrmstr) is one of those people, doling out R wisdom, visualization, typography, culinary and infosec goodness on the regular.
He inspired a lot of my more public forays into R with his short-lived 52Vis contest, and inspired me to start writing my first package after viewing his
hrbrmisc package of personal functions. Quick aside here: I think this is a good starting place for people to dip their toes into package writing. Make a personal package with your own custom themes, palettes, helper functions, etc. It helps you with your own work and is a low-risk introduction to the world of packages. It’s how my first public package on CRAN came about, a natural extension of palettes I was using into the public domain.
Yet, in my opinion one of the most valuable things Bob does is star an incredible amount of work on github. I have found out about a lot of great work, software, talks and R packages from reviewing what he stars.
Wait. This actually needs a phrase …. “hrbrgazing”…… “hrbrstars”…..“starbrgazing”….too many vowels… “strbrgzng”?
Bob Barker: Tell him what he’s won Johnny.
Johnny: “You’ve won the next topic for a blog post!”
Apologies to @hrbrmstr but I’m going to use some vowels and stick with “starbrgazing”. I wanted to draw a little more attention to starbrgazing and just how much you can discover by using the more social aspect of github, following people, a pile of IFTTT alerts and reviewing and testing out what they star.
First, a little look regarding hrbrmstr’s starring activity, and which sort of projects in specific languages catch his eye. Naturally, R is of prominent focus, but there is also significant activity in other languages that compliment R, such as C++, JS and html.
Yeah, that’s a pretty heavy amount of R, with an increasing trend in recent years. Lets just look at the R projects for now. What sort of R projects has he starred over time ?
No surprise that the bulk of R projects are packages, with a smattering of educational stuff, shiny applications and analysis driven projects. Now, how popular are the projects that he’s starring?
We can see that in the early days, there was a little activity and that was limited to starring very popular and impactful packages in the R ecosystem. If you look at activity past 2014, you start to see more star activity in the smaller, perhaps lesser known projects. This activity could also very well be due to the growing popularity of R and the flurry of development on github with all of the orgs and movements to support Open Science, Data literacy, data science, and coding in general. Let’s break this up a bit by some arbitrary binning of popularity by stars.