R InfernoPatrick Burns

R Inferno

by Patrick Burns · first published 2012

4mentions
2recommended by
4HN commenters
2011–2014first – last mentioned

50% recommend50% neutral

Why HN recommends it

Catalogs R's gotchas, traps and surprising behaviors, explaining why they happen rather than just listing them; recommended for working R programmers who want to avoid common pitfalls, not for beginners.

Summarised by Claude from recommending comments

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Mentions per year

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What Hacker News says

  • ltjohnson · Feb 22, 2011 · Recommends

    …documentation [2]. I haven't gone through these, so I can't say much about them, or promise that they are up-to-date. I suspect not, as R develops rapidly. The one reference I can recommend highly is "The R Inferno" by Patrick Burns [3]. This is not a starter guide, but something you read after one. It gives excellent advice on avoiding common pitfalls in R. [1] http://cran.r-project.org/manuals.html [2] http://cran.r-project.org/other-docs.html…

    on “No, shut up. What statistical programming languages can learn from Dropbox.” ↗
  • Permit · Apr 3, 2014 · Recommends

    …the difficulty with which one has applying operations to the rows of a dataframe. Other frustrations like naming conventions are apparently results of legacy code. I'd strongly recommend the book The R Inferno[1] by Patrick Burns. It eases you through the nine circles of R hell that most newcomers seem to endure.

    on “One Page R: A Survival Guide to Data Science with R” ↗
  • crowding · Dec 6, 2012 · Mentions

    …everthing available on CRAN to add to that. -- R is a smaller, yet more expressive language. To be fair, it has about the same density of WTF and non-orthogonality as Matlab (which see, Patrick Burns' "The R Inferno") but makes up for it by being much better at functional programming, and by having more of the Lisp nature in general (R is homoiconic; you can write R code that manipulates R code). If you want object-oriented…

    on “Try R — A new online course, for free” ↗
  • rainforest · Jan 24, 2014 · Mentions

    Patrick Burns' R inferno[1] enumerates a lot of R's eccentricities and workarounds for them. I think R gets a lot better once you switch to using the libraries Hadley maintains like plyr and ggplot. I still think proficiency…

    on “Why I'm Betting On Julia” ↗

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