NOTE: This is a toy package created for expository purposes, for the second edition of R Packages. It is not meant to actually be useful. If you want a package for factor handling, please see stringr, stringi, rex, and rematch2.
The goal of regexcite is to make regular expressions more exciting! It provides convenience functions to make some common tasks with string manipulation and regular expressions a bit easier.
You can install the development version of regexcite from GitHub with:
# install.packages("devtools")
devtools::install_github("JH-Stat/fdahutch2")
#> Using GitHub PAT from the git credential store.
#> Downloading GitHub repo JH-Stat/fdahutch2@HEAD
#> Error in utils::download.file(url, path, method = method, quiet = quiet, :
#> cannot open URL 'https://api.github.com/repos/JH-Stat/fdahutch2/tarball/HEAD'
A fairly common task when dealing with strings is the need to split a
single string into many parts. This is what base::strplit()
and
stringr::str_split()
do.
(x <- "alfa,bravo,charlie,delta")
#> [1] "alfa,bravo,charlie,delta"
strsplit(x, split = ",")
#> [[1]]
#> [1] "alfa" "bravo" "charlie" "delta"
stringr::str_split(x, pattern = ",")
#> [[1]]
#> [1] "alfa" "bravo" "charlie" "delta"
Notice how the return value is a list of length one, where the first element holds the character vector of parts. Often the shape of this output is inconvenient, i.e. we want the un-listed version.
That’s exactly what fdahutch2::str_split_one()
does.
library(fdahutch2)
str_split_one(x, pattern = ",")
#> [1] "alfa" "bravo" "charlie" "delta"
Use str_split_one()
when the input is known to be a single string. For
safety, it will error if its input has length greater than one.
str_split_one()
is built on stringr::str_split()
, so you can use its
n
argument and stringr’s general interface for describing the
pattern
to be matched.
str_split_one(x, pattern = ",", n = 2)
#> [1] "alfa" "bravo,charlie,delta"
y <- "192.168.0.1"
str_split_one(y, pattern = stringr::fixed("."))
#> [1] "192" "168" "0" "1"
This is a basic example which shows you how to solve a common problem:
library(fdahutch2)
## basic example code
What is special about using README.Rmd
instead of just README.md
?
You can include R chunks like so:
summary(cars)
#> speed dist
#> Min. : 4.0 Min. : 2.00
#> 1st Qu.:12.0 1st Qu.: 26.00
#> Median :15.0 Median : 36.00
#> Mean :15.4 Mean : 42.98
#> 3rd Qu.:19.0 3rd Qu.: 56.00
#> Max. :25.0 Max. :120.00
You’ll still need to render README.Rmd
regularly, to keep README.md
up-to-date. devtools::build_readme()
is handy for this.
You can also embed plots, for example:
In that case, don’t forget to commit and push the resulting figure files, so they display on GitHub and CRAN.