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).
Supplementary materials are available in addition to this article. It can be downloaded at RJ-2019-050.zip
namedCapture, rex, stringr, stringi, tidyr, rematch2, re2r, microbenchmark
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For attribution, please cite this work as
Hocking, "The R Journal: Comparing namedCapture with other R packages for regular expressions", The R Journal, 2019
BibTeX citation
@article{RJ-2019-050,
author = {Hocking, Toby Dylan},
title = {The R Journal: Comparing namedCapture with other R packages for regular expressions},
journal = {The R Journal},
year = {2019},
note = {https://doi.org/10.32614/RJ-2019-050},
doi = {10.32614/RJ-2019-050},
volume = {11},
issue = {2},
issn = {2073-4859},
pages = {328-346}
}