mutate_sd: Mutate subset of data

In asardaes/table.express: Build 'data.table' Expressions with Data Manipulation Verbs

Mutate subset of data

Description

Like mutate-table.express but possibly recycling calls.

Usage

mutate_sd(.data, .SDcols, .how = identity, ...)

## S3 method for class 'ExprBuilder'
mutate_sd(
  .data,
  .SDcols,
  .how = identity,
  ...,
  .pairwise = TRUE,
  .prefix,
  .suffix,
  .parse = getOption("table.express.parse", FALSE),
  .chain = getOption("table.express.chain", TRUE)
)

## S3 method for class 'EagerExprBuilder'
mutate_sd(.data, ..., .parent_env = rlang::caller_env())

## S3 method for class 'data.table'
mutate_sd(.data, ...)

Arguments

.data	An instance of ExprBuilder.
.SDcols	See data.table::data.table and the details here.
.how	The function(s) or function call(s) that will perform the transformation. If many, a list should be used, either with list() or .(). If the list is named, the names will be used for the new columns' names. Lambdas specified as formulas are supported.
...	Possibly more arguments for all functions/calls in .how.
.pairwise	If FALSE, each function in .how is applied to each column in .SDcols (like a cartesian product).
.prefix, .suffix	Only relevant when .how is a function: add a prefix or suffix to the new column's name. If neither is missing, .prefix has preference.
.parse	Logical. Whether to apply rlang::parse_expr() to obtain the expressions.
.chain	Logical. Should a new frame be automatically chained to the expression if the clause being set already exists?
.parent_env	See end_expr()

Details

This function works similar to transmute_sd() but keeps all columns and can modify by reference, like mutate-table.express. It can serve like dplyr's scoped mutation variants depending on what's given to .SDcols.

Additionally, .SDcols supports:

• tidyselect::select_helpers

• A predicate using the .COL pronoun that should return a single logical when .COL is replaced by a column of the data.

• A formula using . or .x instead of the aforementioned .COL.

The caveat is that the expression is evaluated eagerly, i.e. with the currently captured data.table. Consider using chain() to explicitly capture intermediate results as actual data.tables.

To see more examples, check the vignette, or the table.express-package entry.

Examples

data("mtcars")

data.table::as.data.table(mtcars) %>%
    start_expr %>%
    mutate_sd(c("mpg", "cyl"), ~ .x * 2)

asardaes/table.express documentation built on April 16, 2023, 3:47 p.m.