Step-Debugging magrittr/dplyr Pipelines in R with wrapr and replyr
In this screencast we demonstrate how to easily and effectively step-debug magrittr/dplyr pipelines in R using wrapr and replyr.
replyr: Get a Grip on Big Data in R
replyr is an R package that contains extensions, adaptions, and work-arounds to make remote R dplyr data sources (including big data systems such as Spark) behave more like local data. This allows the analyst to more easily develop and debug procedures that simultaneously work on a variety of data services […]
wrapr: for sweet R code
This article is on writing sweet R code using the wrapr package.
Announcing the wrapr packge for R
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 […]
My recent BARUG talk: Parametric Programming in R with replyr
I want to share an edited screencast of my rehearsal for my recent San Francisco Bay Area R Users Group talk:
Evolving R Tools and Practices
One of the distinctive features of the R platform is how explicit and user controllable everything is. This allows the style of use of R to evolve fairly rapidly. I will discuss this and end with some new notations, methods, and tools I am nominating for inclusion into your view […]
Upcoming Win-Vector LLC public speaking engagements
I am happy to announce a couple of exciting upcoming Win-Vector LLC public speaking engagements. BARUG Meetup Tuesday, Tuesday February 7, 2017 ~7:50pm, Intuit, Building 20, 2600 Marine Way, Mountain View, CA. Win-Vector LLC’s John Mount will be giving a “lightning talk” (15 minutes) on R calling conventions (standard versus […]
Does replyr::let work with data.table?
I’ve been asked if the adapter “let” from our R package replyr works with data.table. My answer is: it does work. I am not a data.table user so I am not the one to ask if data.table benefits a from a non-standard evaluation to standard evaluation adapter such as replyr::let.
Comparative examples using replyr::let
Consider the problem of “parametric programming” in R. That is: simply writing correct code before knowing some details, such as the names of the columns your procedure will have to be applied to in the future. Our latest version of replyr::let makes such programming easier. Archie’s Mechanics #2 (1954) copyright […]
A Simple Example of Using replyr::gapply
It’s a common situation to have data from multiple processes in a “long” data format, for example a table with columns measurement and process_that_produced_measurement. It’s also natural to split that data apart to analyze or transform it, per-process — and then to bring the results of that data processing together, […]