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like

Pattern Matching with Keyboard Shortcut


Description

Convenient wrapper around grepl() to match a pattern: x %like% pattern. It always returns a logical vector and is always case-insensitive (use x %like_case% pattern for case-sensitive matching). Also, pattern can be as long as x to compare items of each index in both vectors, or they both can have the same length to iterate over all cases.

Usage

like(x, pattern, ignore.case = TRUE)

x %like% pattern

x %like_case% pattern

Arguments

x

a character vector where matches are sought, or an object which can be coerced by as.character() to a character vector.

pattern

a character string containing a regular expression (or character string for fixed = TRUE) to be matched in the given character vector. Coerced by as.character() to a character string if possible. If a character vector of length 2 or more is supplied, the first element is used with a warning.

ignore.case

if FALSE, the pattern matching is case sensitive and if TRUE, case is ignored during matching.

Details

The %like% function:

  • Is case-insensitive (use %like_case% for case-sensitive matching)

  • Supports multiple patterns

  • Checks if pattern is a regular expression and sets fixed = TRUE if not, to greatly improve speed

  • Always uses compatibility with Perl

Using RStudio? The text %like% can also be directly inserted in your code from the Addins menu and can have its own Keyboard Shortcut like Ctrl+Shift+L or Cmd+Shift+L (see Tools > Modify Keyboard Shortcuts...).

Value

A logical vector

Stable Lifecycle


The lifecycle of this function is stable. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.

If the unlying code needs breaking changes, they will occur gradually. For example, a argument will be deprecated and first continue to work, but will emit an message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.

Read more on Our Website!

On our website https://msberends.github.io/AMR/ you can find a comprehensive tutorial about how to conduct AMR data analysis, the complete documentation of all functions and an example analysis using WHONET data. As we would like to better understand the backgrounds and needs of our users, please participate in our survey!

Source

See Also

Examples

# simple test
a <- "This is a test"
b <- "TEST"
a %like% b
#> TRUE
b %like% a
#> FALSE

# also supports multiple patterns
a <- c("Test case", "Something different", "Yet another thing")
b <- c(     "case",           "diff",      "yet")
a %like% b
#> TRUE TRUE TRUE
a[1] %like% b
#> TRUE FALSE FALSE
a %like% b[1]
#> TRUE FALSE FALSE

# get isolates whose name start with 'Ent' or 'ent'

if (require("dplyr")) {
  example_isolates %>%
    filter(mo_name(mo) %like% "^ent")
}

AMR

Antimicrobial Resistance Data Analysis

v1.6.0
GPL-2 | file LICENSE
Authors
Matthijs S. Berends [aut, cre] (<https://orcid.org/0000-0001-7620-1800>), Christian F. Luz [aut, ctb] (<https://orcid.org/0000-0001-5809-5995>), Alexander W. Friedrich [aut, ths] (<https://orcid.org/0000-0003-4881-038X>), Bhanu N. M. Sinha [aut, ths] (<https://orcid.org/0000-0003-1634-0010>), Casper J. Albers [aut, ths] (<https://orcid.org/0000-0002-9213-6743>), Corinna Glasner [aut, ths] (<https://orcid.org/0000-0003-1241-1328>), Judith M. Fonville [ctb], Erwin E. A. Hassing [ctb], Eric H. L. C. M. Hazenberg [ctb], Gwen Knight [ctb], Annick Lenglet [ctb], Bart C. Meijer [ctb], Sofia Ny [ctb], Rogier P. Schade [ctb], Dennis Souverein [ctb], Anthony Underwood [ctb]
Initial release
2021-03-14

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