Keywords: tidyeval, tidyverse, dplyr, quasiquotation, NSE
Webpages:
https://CRAN.R-project.org/package=dplyr,
https://github.com/hadley/rlang Evaluating code in the context of a dataset is one of R’s most useful feature. This idiom is used in base R functions like subset() and transform() and has been developed in tidyverse packages like dplyr and ggplot2 to design elegant grammars. The downside is that such interfaces are notoriously difficult to program with. It is not as easy as it should be to program with dplyr inside functions in order to reduce duplicated code involving dplyr pipelines. To solve these issues, RStudio has developed
tidyeval, a set of new language features that make it straightforward to program with these grammars. We present tidyeval in this talk with a focus on solving concrete problems with popular tidyverse packages like dplyr.
