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Obtain matching indices corresponding to patterns

patterns.Rd

patterns returns the elements of cols that match the regular expression patterns, which must be supported by grep.

From v1.9.6, melt.data.table has an enhanced functionality in which measure.vars argument can accept a list of column names and melt them into separate columns. See the Efficient reshaping using data.tables vignette linked below to learn more.

Usage

patterns(
  ..., cols=character(0),
  ignore.case=FALSE, perl=FALSE,
  fixed=FALSE, useBytes=FALSE)

Arguments

...

A set of regular expression patterns.

cols

A character vector of names to which each pattern is matched.

ignore.case, perl, fixed, useBytes

Passed to grep.

See also

melt, https://github.com/Rdatatable/data.table/wiki/Getting-started

Examples

DT = data.table(x1 = 1:5, x2 = 6:10, y1 = letters[1:5], y2 = letters[6:10])
# melt all columns that begin with 'x' & 'y', respectively, into separate columns
melt(DT, measure.vars = patterns("^x", "^y", cols=names(DT)))
#>     variable value1 value2
#>       <fctr>  <int> <char>
#>  1:        1      1      a
#>  2:        1      2      b
#>  3:        1      3      c
#>  4:        1      4      d
#>  5:        1      5      e
#>  6:        2      6      f
#>  7:        2      7      g
#>  8:        2      8      h
#>  9:        2      9      i
#> 10:        2     10      j
# when used with melt, 'cols' is implicitly assumed to be names of input
# data.table, if not provided.
melt(DT, measure.vars = patterns("^x", "^y"))
#>     variable value1 value2
#>       <fctr>  <int> <char>
#>  1:        1      1      a
#>  2:        1      2      b
#>  3:        1      3      c
#>  4:        1      4      d
#>  5:        1      5      e
#>  6:        2      6      f
#>  7:        2      7      g
#>  8:        2      8      h
#>  9:        2      9      i
#> 10:        2     10      j