dtplyr (version 1.3.1)

mutate.dtplyr_step: Create and modify columns

Description

This is a method for the dplyr mutate() generic. It is translated to the j argument of [.data.table, using := to modify "in place". If .before or .after is provided, the new columns are relocated with a call to data.table::setcolorder().

Usage

# S3 method for dtplyr_step
mutate(
  .data,
  ...,
  .by = NULL,
  .keep = c("all", "used", "unused", "none"),
  .before = NULL,
  .after = NULL
)

Arguments

.data

A lazy_dt().

...

<data-masking> Name-value pairs. The name gives the name of the column in the output.

The value can be:

• A vector of length 1, which will be recycled to the correct length.

• A vector the same length as the current group (or the whole data frame if ungrouped).

• NULL, to remove the column.

• A data frame or tibble, to create multiple columns in the output.

.by

<tidy-select> Optionally, a selection of columns to group by for just this operation, functioning as an alternative to group_by(). For details and examples, see ?dplyr_by.

.keep

Control which columns from .data are retained in the output. Grouping columns and columns created by ... are always kept.

• "all" retains all columns from .data. This is the default.

• "used" retains only the columns used in ... to create new columns. This is useful for checking your work, as it displays inputs and outputs side-by-side.

• "unused" retains only the columns not used in ... to create new columns. This is useful if you generate new columns, but no longer need the columns used to generate them.

• "none" doesn't retain any extra columns from .data. Only the grouping variables and columns created by ... are kept.

Note: With dtplyr .keep will only work with column names passed as symbols, and won't work with other workflows (e.g. eval(parse(text = "x + 1")))

.before, .after

<tidy-select> Optionally, control where new columns should appear (the default is to add to the right hand side). See relocate() for more details.

Examples

library(dplyr, warn.conflicts = FALSE)

dt <- lazy_dt(data.frame(x = 1:5, y = 5:1))
dt %>%
  mutate(a = (x + y) / 2, b = sqrt(x^2 + y^2))

# It uses a more sophisticated translation when newly created variables
# are used in the same expression
dt %>%
  mutate(x1 = x + 1, x2 = x1 + 1)