Pattern Matching

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

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. Long vectors are supported.
pattern	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. Missing values are allowed except for regexpr and gregexpr.
ignore.case	if FALSE, the pattern matching is case sensitive and if TRUE, case is ignored during matching.

Source

Idea from the like function from the data.table package, but made it case insensitive at default and let it support multiple patterns. Also, if the regex fails the first time, it tries again with perl = TRUE.

Value

A logical vector

Details

Using RStudio? This function can also be inserted from the Addins menu and can have its own Keyboard Shortcut like Ctrl+Shift+L or Cmd+Shift+L (see Tools > Modify Keyboard Shortcuts...).

Read more on our website!

On our website https://msberends.gitlab.io/AMR you can find a tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

grep

Examples

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

# also supports multiple patterns, length must be equal to x
a <- c("Test case", "Something different", "Yet another thing")
b <- c("case", "diff", "yet")
a %like% b
#> TRUE TRUE TRUE

# get frequencies of bacteria whose name start with 'Ent' or 'ent'
library(dplyr)
example_isolates %>%
  left_join_microorganisms() %>%
  filter(genus %like% '^ent') %>%
  freq(genus, species)