Tidyverse Tutorial

October 17, 2016

(This article was first published on Michael Levy - Rstats, and kindly contributed to R-bloggers)

Last week, I gave an overview of bunch of tidyverse packages (tibble, dplyr, tidyr, ggplot, readr, purrr) to the Davis R-Users’ Group. Here is that talk (and since videos don’t display everywhere this blog is syndicated, here is the YouTube link).

I mention early in the talk that the github_markdown specification in the YAML header produces a conveniently GitHub-renderable markdown file – here that is if you’d like to follow along, or you can download the rendered R Notebook (nb.html) file, which itself includes the R Markdown file (Awesome! In the upper right of the html file, click “Code” -> “Download Rmd”).

One final note, on the speed of tidyverse functions. Some tidyverse functions really do offer a speed advantage over base R (e.g. read_csv and filter), but the map speed advantage I mention here over lapply seems to be an artifact of both being wrapped in a map2 call in a data_frame call. They are actually equally fast. In my mind, the benefit of the tidyverse is that it makes R easier to write and read, which makes it less bug-prone and more approachable for beginners. It does that without imposing a speed penalty, and in some cases provides a little acceleration as a bonus.

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