patterns.Rdpatterns returns the matching indices in the argument cols
corresponding to the regular expression patterns provided. The patterns 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.
patterns(..., cols=character(0))
| ... | A set of regular expression patterns. |
|---|---|
| cols | A character vector of names to which each pattern is matched. |
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 #> 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 #> 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