The R Journal: accepted article

This article will be copy edited and may be changed before publication.

Comparing namedCapture with other R packages for regular expressions PDF download
Toby Dylan Hocking

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

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

  author = {Toby Dylan Hocking},
  title = {{Comparing namedCapture with other R packages for regular
  year = {2019},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2019-050},
  url = {}