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Playing With Pipe Notations

Recently Hadley Wickham prescribed pronouncing the magrittr pipe as “then” and using right-assignment as follows: I am not sure if it is a good or bad idea. But let’s play with it a bit, and perhaps readers can submit their experience and opinions in the comments section.

Function Objects and Pipelines in R

Composing functions and sequencing operations are core programming concepts. Some notable realizations of sequencing or pipelining operations include: Unix’s |-pipe CMS Pipelines. F#‘s forward pipe operator |>. Haskel’s Data.Function & operator. The R magrittr forward pipe. Scikit-learn‘s sklearn.pipeline.Pipeline. The idea is: many important calculations can be considered as a sequence […]

Reusable Pipelines in R

Pipelines in R are popular, the most popular one being magrittr as used by dplyr. This note will discuss the advanced re-usable piping systems: rquery/rqdatatable operator trees and wrapr function object pipelines. In each case we have a set of objects designed to extract extra power from the wrapr dot-arrow […]

Sharing Modeling Pipelines in R

Reusable modeling pipelines are a practical idea that gets re-developed many times in many contexts. wrapr supplies a particularly powerful pipeline notation, and a pipe-stage re-use system (notes here). We will demonstrate this with the vtreat data preparation system.

coalesce with wrapr

coalesce is a classic useful SQL operator that picks the first non-NULL value in a sequence of values. We thought we would share a nice version of it for picking non-NA R with convenient operator infix notation wrapr::coalesce(). Here is a short example of it in action: library("wrapr") NA %?% […]

Piping into ggplot2

In our wrapr pipe RJournal article we used piping into ggplot2 layers/geoms/items as an example. Being able to use the same pipe operator for data processing steps and for ggplot2 layering is a question that comes up from time to time (for example: Why can’t ggplot2 use %>%?). In fact […]