Vectorised Pattern Matching with Keyboard Shortcut

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 %unlike% pattern

x %like_case% pattern

x %unlike_case% pattern

Source

Idea from the like function from the data.table package, although altered as explained in Details.

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 vector containing regular expressions (or a character string for fixed = TRUE) to be matched in the given character vector. Coerced by as.character() to a character string if possible.
ignore.case: if FALSE, the pattern matching is case sensitive and if TRUE, case is ignored during matching.

Value

A logical vector

Details

These like() and %like%/%unlike% functions:

Are case-insensitive (use %like_case%/%unlike_case% for case-sensitive matching)
Support multiple patterns
Check if pattern is a valid regular expression and sets fixed = TRUE if not, to greatly improve speed (vectorised over pattern)
Always use compatibility with Perl unless fixed = TRUE, to greatly improve speed

Using RStudio? The %like%/%unlike% functions can also be directly inserted in your code from the Addins menu and can have its own keyboard shortcut like Shift+Ctrl+L or Shift+Cmd+L (see menu Tools > Modify Keyboard Shortcuts...). If you keep pressing your shortcut, the inserted text will be iterated over %like% -> %unlike% -> %like_case% -> %unlike_case%.

Examples

a <- "This is a test"
b <- "TEST"
a %like% b
#> [1] FALSE
b %like% a
#> [1] FALSE

# also supports multiple patterns
a <- c("Test case", "Something different", "Yet another thing")
b <- c("case", "diff", "yet")
a %like% b
#> Warning: argument 'pattern' has length > 1 and only the first element will be used
#> [1]  TRUE FALSE FALSE
a %unlike% b
#> [1] FALSE FALSE FALSE

a[1] %like% b
#> Warning: argument 'pattern' has length > 1 and only the first element will be used
#> [1] TRUE
a %like% b[1]
#> [1]  TRUE FALSE FALSE

# \donttest{
# get isolates whose name start with 'Entero' (case-insensitive)
example_isolates[which(mo_name() %like% "^entero"), ]
#> ℹ Using column 'mo' as input for mo_name()
#> # A tibble: 0 × 46
#> # … with 46 variables: date <date>, patient <chr>, age <dbl>, gender <chr>,
#> #   ward <chr>, mo <mo>, PEN <sir>, OXA <sir>, FLC <sir>, AMX <sir>, AMC <sir>,
#> #   AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, CXM <sir>, FOX <sir>,
#> #   CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, TOB <sir>, AMK <sir>,
#> #   KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, FOS <sir>, LNZ <sir>,
#> #   CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, TCY <sir>, TGC <sir>,
#> #   DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, IPM <sir>, MEM <sir>, …

if (require("dplyr")) {
  example_isolates %>%
    filter(mo_name() %like% "^ent")
}
#> ℹ Using column 'mo' as input for mo_name()
#> # A tibble: 0 × 46
#> # … with 46 variables: date <date>, patient <chr>, age <dbl>, gender <chr>,
#> #   ward <chr>, mo <mo>, PEN <sir>, OXA <sir>, FLC <sir>, AMX <sir>, AMC <sir>,
#> #   AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, CXM <sir>, FOX <sir>,
#> #   CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, TOB <sir>, AMK <sir>,
#> #   KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, FOS <sir>, LNZ <sir>,
#> #   CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, TCY <sir>, TGC <sir>,
#> #   DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, IPM <sir>, MEM <sir>, …
# }