Conditional update of columns in data.table
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.
mutate_when(.data, when, ..., by) mutate_vars(.data, .cols = NULL, .func, ..., by)
.data |
data.frame |
when |
An object which can be coerced to logical mode |
... |
Name-value pairs of expressions for |
by |
(Optional) Mutate by what group? |
.cols |
Any types that can be accepted by |
.func |
Function to be run within each column, should return a value or vectors with same length. |
data.table
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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.