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 column names will come later … Continue reading In defense of wrapr::let()
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. Abstractions A common definition of an abstraction is (from the OSX dictionary): the process of considering something independently of its associations, attributes, or concrete accompaniments. In … Continue reading Why to use wrapr::let()
In this screencast we demonstrate how to easily and effectively step-debug magrittr/dplyr pipelines in R using wrapr and replyr. Some of the big issues in trying to debug magrittr/dplyr pipelines include: Pipelines being large expressions that are hard to line-step into. Visibility of intermediate results. Localizing operations (in time and code position) in the presence … Continue reading Step-Debugging magrittr/dplyr Pipelines in R with wrapr and replyr
This article is on writing sweet R code using the wrapr package. The problem Consider the following R puzzle. You are given: a data.frame, the name of a column that you wish to find missing values (NA) in, and the name of a column to land the result. For instance: d <- data.frame(x = c(1, … Continue reading wrapr: for sweet R code
Recently Dirk Eddelbuettel pointed out that our R function debugging wrappers would be more convenient if they were available in a low-dependency micro package dedicated to little else. Dirk is a very smart person, and like most R users we are deeply in his debt; so we (Nina Zumel and myself) listened and immediately moved … Continue reading Announcing the wrapr packge for R
