similar to: stringr 0.6

Strings are not glamorous, high-profile components of R, but they do play a big role in many data cleaning and preparations tasks. R provides a solid set of string operations, but because they have grown organically over time, they can be inconsistent and a little hard to learn. Additionally, they lag behind the string operations in other programming languages, so that some things that are easy to

Strings are not glamorous, high-profile components of R, but they do play a big role in many data cleaning and preparations tasks. R provides a solid set of string operations, but because they have grown organically over time, they can be inconsistent and a little hard to learn. Additionally, they lag behind the string operations in other programming languages, so that some things that are easy to

# stringr Strings are not glamorous, high-profile components of R, but they do play a big role in many data cleaning and preparations tasks. R provides a solid set of string operations, but because they have grown organically over time, they can be inconsistent and a little hard to learn. Additionally, they lag behind the string operations in other programming languages, so that some things that

# stringr Strings are not glamorous, high-profile components of R, but they do play a big role in many data cleaning and preparations tasks. R provides a solid set of string operations, but because they have grown organically over time, they can be inconsistent and a little hard to learn. Additionally, they lag behind the string operations in other programming languages, so that some things that

Changing the default behavior of regmatches would break its use with gregexpr, where the number of matches per input element faries, so a zero-length character vector makes more sense than NA_character_. > x <- c("John Doe", "e e cummings", "Juan de la Madrid") > m <- gregexpr("[A-Z]", x) > regmatches(x,m) [[1]] [1] "J"

if you want "to extract regex matches into a new column in a data.frame" then there are some package functions which do exactly that. three examples are namedCapture::df_match_variable, rematch2::bind_re_match, and tidyr::extract. For a more detailed discussion see my R journal submission (under review) about regular expression packages,

A very common use case for regmatches is to extract regex matches into a new column in a data.frame (or data.table, etc.) or otherwise use the extracted strings alongside the input. However, the default behavior is to drop empty matches, which results in mismatches in column length if reassignment is done without subsetting. For consistency with other R functions and compatibility with this use

Thank you, I am aware that there are packages that can accomplish this. I mentioned stringr::str_extract as a function that does not drop empty matches. I think that the behavior of regmatches(..., regexpr(...))?in base R should permit an option to prevent dropping of empty matches both for sake of consistency with the rest of the language (missing data does not yield a dropped index in other

Just started thinking about this. The name of regmatches() suggests that it will only extract the matches but not return anything for the non-matches. We might need another function that returns a value for non-matches. Perhaps the value should be the empty string for non-matches and NA for matches to NA. The rationale is that we delegate to regexpr() (at least conceptually), and it returns a

I'd be happy to entertain patches or at least more specific suggestions to improve strextract() and strcapture(). I hadn't exported strextract(), because I wasn't quite sure how it should behave. This feedback should be helpful. Thanks, Michael On Thu, Aug 29, 2019 at 2:20 PM Cyclic Group Z_1 via R-devel <r-devel at r-project.org> wrote: > > Thank you, I am aware that

Dear Raju I agree to Dirk that this is not really the best place for these matters, but as I got curious, I checked and found you should use test_package() and not test_dir(), as the latter does not load unexported functions of the package (such as check_string()) that may occur in the tests. For packaging of r-cran-stringr, it is probably most efficient to file a bug report there because of

I figured it out, at least enough to get rgeos's gSimplify function to work, which was my original goal; the stringr problem was with 0.2, however I got stringr 0.5 to install by changing the minimum version in DESCRIPTION from R2.11 to R 2.10. ... Thanks for the help! ############# # This is how I got rgeos to install in R GUI on my Intel Mac OS X 10.4: ############# # stringr

I am trying to learn how to run the unit tests in the stringr package and have the following questions. 1) The r-cran-stringr package does not suggest/depend on the r-cran-testthat package . Would it make sense to add such a thing since after all the tests in /usr/lib/R/site-library/stringr/tests rely on testthat package? 2) I am getting the following error when trying to run the unit tests %

Hola, Una forma de hacerlo es así... Pensando en que el separador de cada palabra es el "." y que la provincia es la cuarta palabra. > cad.ena <- c( + 'm.1.p.Álava' + ,'m.1.p.Albacete' + ,'m.2.p.Alicante' + ,'m.1.p.Almería' + ,'m.3.p.Asturias' + ,'m.1.p.Ávila' + ,'m.1.p.Badajoz' + ,'m.1.p.Baleares (Illes)' +

Hi Group, I have a question on Stringr package I have a table like this X Y ab su - di ac pi - tu ad tu - tu I want output like this X Y ab su ab di ac pi ac tu ad tu ad tu I am wondering if this operation can be done using stringr package (only) ? [[alternative HTML version deleted]]

# Roxygen2 The premise of `roxygen2` is simple: describe your functions in comments next to where their definitions and `roxygen2` will process your source code and comments to produce R compatible Rd files. Here's a simple example from the `stringr` package: ? ? #' The length of a string (in characters).? ? #'? ? #' @param string input character vector? ? #' @return numeric

# Roxygen2 The premise of `roxygen2` is simple: describe your functions in comments next to where their definitions and `roxygen2` will process your source code and comments to produce R compatible Rd files. Here's a simple example from the `stringr` package: ? ? #' The length of a string (in characters).? ? #'? ? #' @param string input character vector? ? #' @return numeric

Hola a todos. Soy un poco torpe manejando cadenas de texto, así que os pido ayuda. Tengo un vector de texto de este tipo datos$tipo [1] m.1.p.Álava m.1.p.Albacete [3] m.2.p.Alicante m.1.p.Almería [5] m.3.p.Asturias m.1.p.Ávila [7] m.1.p.Badajoz m.1.p.Baleares (Illes) [9] m.1.p.Barcelona m.1.p.Burgos [11] m.1.p.Cáceres m.1.p.Cádiz Y quiero extraer el

Thank you! I greatly appreciate your consideration, though of course it is up to you. I think many people switch to stringr/stringi simply because functions in those packages have some consistent design choices, for example, they do not drop empty/missing matches, which facilitates array-based programming. For example, in the cases where one needs to make a new column in a data.frame (data.table,

# testthat Testing your code is normally painful and boring. `testthat` tries to make testing as fun as possible, so that you get a visceral satisfaction from writing tests. Testing should be fun, not a drag, so you do it all the time. To make that happen, `testthat`: * Provides functions that make it easy to describe what you expect a function to do, including catching errors, warnings and