course
/
r4ds
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

stringr 1.5.0 now on CRAN (#1169)

This commit is contained in:
Hadley Wickham 2022-12-05 06:55:03 +13:00 committed by GitHub
parent bf474ecffc
commit bff64c83eb
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 7 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

3
DESCRIPTION
View File

@ -30,7 +30,7 @@ Imports:
readxl,
repurrrsive,
slider,
stringr,
stringr (>= 1.5.0),
tidymodels,
tidyverse,
tidyr,
@ -46,7 +46,6 @@ Suggests:
Remotes:
tidyverse/dplyr,
tidyverse/dbplyr,
tidyverse/stringr,
tidyverse/tidyr,
tidyverse/purrr,
jennybc/repurrrsive

4
regexps.qmd
View File

@ -23,8 +23,8 @@ We'll finish up with a survey of other places in the tidyverse and base R where
### Prerequisites
::: callout-important
This chapter relies on features only found in stringr 1.5.0 and tidyr 1.3.0 which are still in development.
If you want to live life on the edge, you can get the dev versions with `devtools::install_github(c("tidyverse/stringr", "tidyverse/tidyr"))`.
This chapter relies on features only found in tidyr 1.3.0 which are still in development.
If you want to live life on the edge, you can get the dev versions with `devtools::install_github("tidyverse/tidyr")`.
:::
In this chapter, we'll use regular expression functions from stringr and tidyr, both core members of the tidyverse, as well as data from the babynames package.

8
strings.qmd
View File

@ -14,15 +14,16 @@ Now it's time to dive into them, learning what makes strings tick, and mastering
We'll begin with the details of creating strings and character vectors.
You'll then dive into creating strings from data, then the opposite; extracting strings from data.
We'll then discuss tools that work with individual letters. The chapter finishes off with functions that work with individual letters and a brief discussion of where your expectations from English might steer you wrong when working with other languages.
We'll then discuss tools that work with individual letters.
The chapter finishes off with functions that work with individual letters and a brief discussion of where your expectations from English might steer you wrong when working with other languages.
We'll keep working with strings in the next chapter, where you'll learn more about the power of regular expressions.
### Prerequisites
::: callout-important
This chapter relies on features only found in stringr 1.5.0 and tidyr 1.3.0 which are still in development.
If you want to live life on the edge you can get the dev versions with `devtools::install_github(c("tidyverse/stringr", "tidyverse/tidyr"))`.
This chapter relies on features only found in tidyr 1.3.0 which are still in development.
If you want to live life on the edge, you can get the dev versions with `devtools::install_github("tidyverse/tidyr")`.
:::
In this chapter, we'll use functions from the stringr package which is part of the core tidyverse.
@ -661,4 +662,3 @@ This also comes up when sorting strings with `dplyr::arrange()` which is why it
In this chapter you've learned about some of the power of the stringr package: you learned how to create, combine, and extract strings, and about some of the challenges you might face with non-English strings.
Now it's time to learn one of the most important and powerful tools for working withr strings: regular expressions.
Regular expressions are very concise, but very expressive, language for describing patterns within strings, and are the topic of the next chapter.