The Win-Vector public R packages now all have new pkgdown documentation sites! (And, a thank-you to Hadley Wickham for developing the pkgdown tool.) Please check them out (hint: vtreat is our favorite).
While going over some of the discussion related to my last post I came up with a really neat way to use wrapr::let() and rlang/tidyeval together. Please read on to see the situation and example.
From dplyr issue 2916. The following appears to work. suppressPackageStartupMessages(library("dplyr")) COL <- "homeworld" starwars %>% group_by(.data[[COL]]) %>% head(n=1) ## # A tibble: 1 x 14 ## # Groups: COL  ## name height mass hair_color skin_color eye_color birth_year ## <chr> <int> <dbl> <chr> <chr> <chr> <dbl> ## 1 Luke Skywalker […]
Introduction The development version CRAN version of our R helper function wrapr::let() has switched from string-based substitution to abstract syntax tree based substitution (AST based substitution, or language based substitution). I am looking for some feedback from wrapr::let() users already doing substantial work with wrapr::let(). If you are already using […]
In this article we will discuss composing standard-evaluation interfaces (SE: parametric, referentially transparent, or “looks only at values”) and composing non-standard-evaluation interfaces (NSE) in R. In R the package tidyeval/rlang is a tool for building domain specific languages intended to allow easier composition of NSE interfaces. To use it you […]
Saw this the other day: In defense of wrapr::let() (originally part of replyr, and still re-exported by that package) I would say: let() was deliberately designed for a single real-world use case: working with data when you don’t know the column names when you are writing the code (i.e., the […]
I have written about referential transparency before. In this article I would like to discuss “leaky abstractions” and why wrapr::let() supplies a useful (but leaky) abstraction for R programmers.
R is a very fluid language amenable to meta-programming, or alterations of the language itself. This has allowed the late user-driven introduction of a number of powerful features such as magrittr pipes, the foreach system, futures, data.table, and dplyr. Please read on for some small meta-programming effects we have been […]
In this screencast we demonstrate how to easily and effectively step-debug magrittr/dplyr pipelines in R using wrapr and replyr.
This article is on writing sweet R code using the wrapr package.