The R Journal: article published in 2019, volume 11:2

Comparing namedCapture with other R packages for regular expressions
Toby Dylan Hocking , The R Journal (2019) 11:2, pages 328-346.

Abstract Regular expressions are powerful tools for manipulating non-tabular textual data. For many tasks (visualization, machine learning, etc), tables of numbers must be extracted from such data before processing by other R functions. We present the R package namedCapture, which facilitates such tasks by providing a new user-friendly syntax for defining regular expressions in R code. We begin by describing the history of regular expressions and their usage in R. We then describe the new features of the namedCapture package, and provide detailed comparisons with related R packages (rex, stringr, stringi, tidyr, rematch2, re2r).

Received: 2019-02-25; online 2019-12-27, supplementary material, (2.2 KiB)
CRAN packages: namedCapture, rex, stringr, stringi, tidyr, rematch2, re2r, microbenchmark
CRAN Task Views implied by cited CRAN packages: NaturalLanguageProcessing

This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2019-050,
  author = {Toby Dylan Hocking},
  title = {{Comparing namedCapture with other R packages for regular
          expressions}},
  year = {2019},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2019-050},
  url = {https://doi.org/10.32614/RJ-2019-050},
  pages = {328--346},
  volume = {11},
  number = {2}
}