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The R community is awesome (and fast)

Recently I whined/whinged or generally complained about a few sharp edges in some powerful R systems.

In each case I was treated very politely, listened to, and actually got fixes back in a very short timeframe from volunteers. That is really great and probably one of the many reasons R is a great ecosystem.

Please read on for my list of n=3 interactions.

  1. While discussing plotting market data I ran into a corner-case with ggplot2. Even though I figured out how to work around it, it is now fixed by the ggplot2 team!
  2. I wrote an entire article denouncing a default setting of a single argument in the ranger random forest library. The ranger author himself replied with a fix that is very clever and mathematically well-founded (I suspect he had be researching this issue a while on his own).
  3. I complained about summary presentation fidelity in base R summary.default. You guessed it: the volunteers have generously fielded a patch!

Like any real-world system R represents a sequence of history and compromises. Only unused systems can be perfect without compromise. It is very evident how eager and able the volunteers who maintain it are to make sure R represents very good compromises.

I would like to offer a sincere appreciation and thank you from me to the R community. If this is what you can expect using R it is yet another strong argument for R.

And personal thanks to: Martin Maechler, Hadley Wickham, and Marvin N. Wright.

2 thoughts on “The R community is awesome (and fast)”

  1. Can’t agree more. The #rstats community on twitter has been incredibly helpful with any whining I might do. I don’t think once I’ve been asked to read the manual or google it, and instead, helpful insights into solutions they’ve found to common problems (working directory hell, for example).

    John, I also want to thank you and your colleague, Nina Zumel. It was a pleasant surprise to see your name up on R-Bloggers, just as I was reading your name somewhere else.

    I am working through the Practical Data Science book you authored and the first chapter alone was worth the purchase. I had been reading it through my local library and after a few pages in I decided I needed a physical copy for myself.

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