Comparing namedCapture with other R packages for regular expressions

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


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).

Original languageEnglish (US)
Pages (from-to)328-346
Number of pages19
JournalR Journal
Issue number2
StatePublished - Dec 1 2019
Externally publishedYes

ASJC Scopus subject areas

  • Statistics and Probability
  • Numerical Analysis
  • Statistics, Probability and Uncertainty


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