I feel like there should be a very simple way to do this, but I can't figure this out. I want to use across with a list of variables and tidyselect helpers in a large dataset, but I'll use iris as an example.
Before the dplyr 1.0 update, I could successfully use scoped verbs like this:
VARS <- vars(Sepal.Length, starts_with("Petal"))
iris %>%
mutate_at(VARS, as.character)
I thought iris %>% mutate(across(!!!VARS, as.character)) would work but I get an error. I know the update supersedes vars, but I'm not able to save the variables with list or c.
Please help! Looking for an elegant tidyverse solution.
There are many options for you to choose.
library(dplyr)
VARS1 <- quote(c(Sepal.Length, starts_with("Petal")))
VARS2 <- expr(c(Sepal.Length, starts_with("Petal")))
VARS3 <- quo(c(Sepal.Length, starts_with("Petal")))
Output
> iris %>% mutate(across(!!VARS1, as.character)) %>% str()
'data.frame': 150 obs. of 5 variables:
$ Sepal.Length: chr "5.1" "4.9" "4.7" "4.6" ...
$ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
$ Petal.Length: chr "1.4" "1.4" "1.3" "1.5" ...
$ Petal.Width : chr "0.2" "0.2" "0.2" "0.2" ...
$ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
> iris %>% mutate(across(!!VARS2, as.character)) %>% str()
'data.frame': 150 obs. of 5 variables:
$ Sepal.Length: chr "5.1" "4.9" "4.7" "4.6" ...
$ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
$ Petal.Length: chr "1.4" "1.4" "1.3" "1.5" ...
$ Petal.Width : chr "0.2" "0.2" "0.2" "0.2" ...
$ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
> iris %>% mutate(across(!!VARS3, as.character)) %>% str()
'data.frame': 150 obs. of 5 variables:
$ Sepal.Length: chr "5.1" "4.9" "4.7" "4.6" ...
$ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
$ Petal.Length: chr "1.4" "1.4" "1.3" "1.5" ...
$ Petal.Width : chr "0.2" "0.2" "0.2" "0.2" ...
$ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...