When I started writing about methods for better "parametric programming" interfaces for dplyr for R dplyr users in December of 2016 I encountered three divisions in the audience: dplyr users who had such a need, and wanted such extensions. dplyr users who did not have such a need ("we always know ...

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). The package sites: cdata replyr seplyr sigr vtre...

For many R users the magrittr pipe is a popular way to arrange computation and famously part of the tidyverse. The tidyverse itself is a rapidly evolving centrally controlled package collection. The tidyverse authors publicly appear to be interested in re-basing the tidyverse in terms of their new rlang/tidyeval ...

In our latest installment of “R and big data” let’s again discuss the task of left joining many tables from a data warehouse using R and a system called "a join controller" (last discussed here). One of the great advantages to specifying complicated sequences of operations in data (rather ...

Introduction The development version of our R helper function wrapr::let() has switched from string-based substitution to abstract syntax tree based substitution (AST based subsitution, 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 ...

This note describes a useful replyr tool we call a "join controller" (and is part of our "R and Big Data" series, please see here for the introduction, and here for one our big data courses). When working on real world predictive modeling tasks in production, the ability to join ...

In our latest “R and big data” article we show how to manage intermediate results in non-trivial Apache Spark workflows using R, sparklyr, dplyr, and replyr. Handle management Many Sparklyr tasks involve creation of intermediate or temporary tables. This can be through dplyr::copy_to() and through dplyr::compute(). These ...

Let’s worry a bit about substitution in R. Substitution is very powerful, which means it can be both used and mis-used. However, that does not mean every use is unsafe or a mistake. From Advanced R : substitute: We can confirm the above code performs no substitution: a