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.frame
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.
(Optional) Mutate by what group?
Any types that can be accepted by select_dt.
Function to be run within each column, should return a value or vectors with same length.
data.table
iris[3:8,]
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 3 4.7 3.2 1.3 0.2 setosa
#> 4 4.6 3.1 1.5 0.2 setosa
#> 5 5.0 3.6 1.4 0.2 setosa
#> 6 5.4 3.9 1.7 0.4 setosa
#> 7 4.6 3.4 1.4 0.3 setosa
#> 8 5.0 3.4 1.5 0.2 setosa
iris[3:8,] %>%
mutate_when(Petal.Width == .2,
one = 1,Sepal.Length=2)
#> Index: <Petal.Width>
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species one
#> <num> <num> <num> <num> <fctr> <num>
#> 1: 2.0 3.2 1.3 0.2 setosa 1
#> 2: 2.0 3.1 1.5 0.2 setosa 1
#> 3: 2.0 3.6 1.4 0.2 setosa 1
#> 4: 5.4 3.9 1.7 0.4 setosa NA
#> 5: 4.6 3.4 1.4 0.3 setosa NA
#> 6: 2.0 3.4 1.5 0.2 setosa 1
iris %>% mutate_vars("Pe",scale)
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> <num> <num> <num> <num> <fctr>
#> 1: 5.1 3.5 -1.3357516 -1.3110521 setosa
#> 2: 4.9 3.0 -1.3357516 -1.3110521 setosa
#> 3: 4.7 3.2 -1.3923993 -1.3110521 setosa
#> 4: 4.6 3.1 -1.2791040 -1.3110521 setosa
#> 5: 5.0 3.6 -1.3357516 -1.3110521 setosa
#> ---
#> 146: 6.7 3.0 0.8168591 1.4439941 virginica
#> 147: 6.3 2.5 0.7035638 0.9192234 virginica
#> 148: 6.5 3.0 0.8168591 1.0504160 virginica
#> 149: 6.2 3.4 0.9301544 1.4439941 virginica
#> 150: 5.9 3.0 0.7602115 0.7880307 virginica
iris %>% mutate_vars(is.numeric,scale)
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> <num> <num> <num> <num> <fctr>
#> 1: -0.89767388 1.01560199 -1.3357516 -1.3110521 setosa
#> 2: -1.13920048 -0.13153881 -1.3357516 -1.3110521 setosa
#> 3: -1.38072709 0.32731751 -1.3923993 -1.3110521 setosa
#> 4: -1.50149039 0.09788935 -1.2791040 -1.3110521 setosa
#> 5: -1.01843718 1.24503015 -1.3357516 -1.3110521 setosa
#> ---
#> 146: 1.03453895 -0.13153881 0.8168591 1.4439941 virginica
#> 147: 0.55148575 -1.27867961 0.7035638 0.9192234 virginica
#> 148: 0.79301235 -0.13153881 0.8168591 1.0504160 virginica
#> 149: 0.43072244 0.78617383 0.9301544 1.4439941 virginica
#> 150: 0.06843254 -0.13153881 0.7602115 0.7880307 virginica
iris %>% mutate_vars(-is.factor,scale)
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> <num> <num> <num> <num> <fctr>
#> 1: -0.89767388 1.01560199 -1.3357516 -1.3110521 setosa
#> 2: -1.13920048 -0.13153881 -1.3357516 -1.3110521 setosa
#> 3: -1.38072709 0.32731751 -1.3923993 -1.3110521 setosa
#> 4: -1.50149039 0.09788935 -1.2791040 -1.3110521 setosa
#> 5: -1.01843718 1.24503015 -1.3357516 -1.3110521 setosa
#> ---
#> 146: 1.03453895 -0.13153881 0.8168591 1.4439941 virginica
#> 147: 0.55148575 -1.27867961 0.7035638 0.9192234 virginica
#> 148: 0.79301235 -0.13153881 0.8168591 1.0504160 virginica
#> 149: 0.43072244 0.78617383 0.9301544 1.4439941 virginica
#> 150: 0.06843254 -0.13153881 0.7602115 0.7880307 virginica
iris %>% mutate_vars(1:2,scale)
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> <num> <num> <num> <num> <fctr>
#> 1: -0.89767388 1.01560199 1.4 0.2 setosa
#> 2: -1.13920048 -0.13153881 1.4 0.2 setosa
#> 3: -1.38072709 0.32731751 1.3 0.2 setosa
#> 4: -1.50149039 0.09788935 1.5 0.2 setosa
#> 5: -1.01843718 1.24503015 1.4 0.2 setosa
#> ---
#> 146: 1.03453895 -0.13153881 5.2 2.3 virginica
#> 147: 0.55148575 -1.27867961 5.0 1.9 virginica
#> 148: 0.79301235 -0.13153881 5.2 2.0 virginica
#> 149: 0.43072244 0.78617383 5.4 2.3 virginica
#> 150: 0.06843254 -0.13153881 5.1 1.8 virginica
iris %>% mutate_vars(.func = as.character)
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> <char> <char> <char> <char> <char>
#> 1: 5.1 3.5 1.4 0.2 setosa
#> 2: 4.9 3 1.4 0.2 setosa
#> 3: 4.7 3.2 1.3 0.2 setosa
#> 4: 4.6 3.1 1.5 0.2 setosa
#> 5: 5 3.6 1.4 0.2 setosa
#> ---
#> 146: 6.7 3 5.2 2.3 virginica
#> 147: 6.3 2.5 5 1.9 virginica
#> 148: 6.5 3 5.2 2 virginica
#> 149: 6.2 3.4 5.4 2.3 virginica
#> 150: 5.9 3 5.1 1.8 virginica