data.table (version 1.14.6)

transform.data.table: Data table utilities

Description

Utilities for data.table transformation.

transform by group is particularly slow. Please use := by group instead.

within, transform and other similar functions in data.table are not just provided for users who expect them to work, but for non-data.table-aware packages to retain keys, for example. Hopefully the (much) faster and more convenient data.table syntax will be used in time. See examples.

Usage

# S3 method for data.table
transform(`_data`, ...)
# S3 method for data.table
within(data, expr, ...)

Value

The modified value of a copy of data.

Arguments

data, _data

data.table to be transformed.

...

for transform, Further arguments of the form tag=value. Ignored for within.

expr

expression to be evaluated within the data.table.

Details

within is like with, but modifications (columns changed, added, or removed) are updated in the returned data.table.

Note that transform will keep the key of the data.table provided the targets of the transform (i.e. the columns that appear in ...) are not in the key of the data.table. within also retains the key provided the key columns are not touched.

See Also

transform, within and :=

Examples

DT <- data.table(a=rep(1:3, each=2), b=1:6)

DT2 <- transform(DT, c = a^2)
DT[, c:=a^2]
identical(DT,DT2)

DT2 <- within(DT, {
  b <- rev(b)
  c <- a*2
  rm(a)
})
DT[,`:=`(b = rev(b),
         c = a*2,
         a = NULL)]
identical(DT,DT2)

DT$d = ave(DT$b, DT$c, FUN=max)               # copies entire DT, even if it is 10GB in RAM
DT = DT[, transform(.SD, d=max(b)), by="c"]   # same, but even worse as .SD is copied for each group
DT[, d:=max(b), by="c"]                       # same result, but much faster, shorter and scales

# Multiple update by group. Convenient, fast, scales and easy to read.
DT[, `:=`(minb = min(b),
          meanb = mean(b),
          bplusd = sum(b+d)),  by=c%/%5]
DT