dt_separate: Separate columns with data.table

In TysonStanley/tidyfast: Fast Tidying of Data

Separate columns with data.table

Description

Separates a column of data into others, by splitting based a separator or regular expression

Usage

dt_separate(
  dt_,
  col,
  into,
  sep = ".",
  remove = TRUE,
  fill = NA,
  fixed = TRUE,
  immutable = TRUE,
  dev = FALSE,
  ...
)

Arguments

dt_	the data table (or if not a data.table then it is coerced with as.data.table)
col	the column to separate
into	the names of the new columns created from splitting col.
sep	the regular expression stating how col should be separated. Default is ..
remove	should col be removed in the returned data table? Default is TRUE
fill	if empty, fill is inserted. Default is NA.
fixed	logical. If TRUE match split exactly, otherwise use regular expressions. Has priority over perl.
immutable	If TRUE, .dt is treated as immutable (it will not be modified in place). Alternatively, you can set immutable = FALSE to modify the input object.
dev	If TRUE, the function can be used within other functions. It bypasses the usual non-standard evaluation. Default is FALSE.
...	arguments passed to data.table::tstrplit()

Value

A data.table with a column split into multiple columns.

Examples

library(data.table)
d <- data.table(
  x = c("A.B", "A", "B", "B.A"),
  y = 1:4
)

# defaults
dt_separate(d, x, c("c1", "c2"))

# can keep the original column with `remove = FALSE`
dt_separate(d, x, c("c1", "c2"), remove = FALSE)

# need to assign when `immutable = TRUE`
separated <- dt_separate(d, x, c("c1", "c2"), immutable = TRUE)
separated

# don't need to assign when `immutable = FALSE` (default)
dt_separate(d, x, c("c1", "c2"), immutable = FALSE)
d

TysonStanley/tidyfast documentation built on April 10, 2024, 9:20 a.m.