mutate_vars: Conditional update of columns in data.table

In hope-data-science/tidyfst: Tidy Verbs for Fast Data Manipulation

Conditional update of columns in data.table

Description

Update or add columns when the given condition is met.

mutate_when integrates mutate and case_when in dplyr and make a new tidy verb for data.table. mutate_vars is a super function to do updates in specific columns according to conditions.

Usage

mutate_when(.data, when, ..., by)

mutate_vars(.data, .cols = NULL, .func, ..., by)

Arguments

.data	data.frame
when	An object which can be coerced to logical mode
...	Name-value pairs of expressions for mutate_when. Additional parameters to be passed to parameter '.func' in mutate_vars.
by	(Optional) Mutate by what group?
.cols	Any types that can be accepted by select_dt.
.func	Function to be run within each column, should return a value or vectors with same length.

Value

data.table

See Also

select_dt, case_when

Examples

iris[3:8,]
iris[3:8,] %>%
  mutate_when(Petal.Width == .2,
              one = 1,Sepal.Length=2)

iris %>% mutate_vars("Pe",scale)
iris %>% mutate_vars(is.numeric,scale)
iris %>% mutate_vars(-is.factor,scale)
iris %>% mutate_vars(1:2,scale)
iris %>% mutate_vars(.func = as.character)

hope-data-science/tidyfst documentation built on Sept. 23, 2024, 8:05 p.m.