R - Assign class using mutate

Question

I am using the openxlsx package to create excel files. To format a column as US dollars, the examples say to set the class to 'currency':

class(df$Currency) <- 'currency'

However, I would like to apply this to many columns as once and repeat once for currency, once for percentage etc. That is my ultimate goal however I get there - here is what I've tried so far.

First the working example:

df <- data.frame(sales = c(10, 20, 30, 40, 50), returns = c(-5, -10, -20, 0, 0))
class(df$sales) <- 'currency'
class(df$sales)
[1] "currency"

Now using dplyr and mutate Attempt 1:

df %>% 
mutate_all(`class<-`(., 'currency'))
Error: Can't create call to non-callable object

Attempt 2:

df <- df %>% 
`class<-`(., 'currency') 
df
$sales
[1] 10 20 30 40 50
attr(,"class")
[1] "currency"

That gets much much closer to what I wanted but the output is a list and as.data.frame and as.tbl both complain there is no method for class 'currency'.

When I used the class(df$sales) <- 'currency' I was able to just change the class within the existing dataframe.

I have a feeling this is a good chance to learn more about classes (I reviewed the Advanced R section on classes but couldn't make the connection to my problem)

Answer 1

To echo @Frank's comment above:

as.currency <- function(x) {class(x) <- "currency"; x}

iris %>%   
  mutate_all(funs(as.currency(.))) %>% 
  glimpse()

Observations: 150
Variables: 5
$ Sepal.Length <S3: currency> 5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4.9, 5.4, 4.8, 4.8, 4.3, 5.8, 5.7, 5.4, 5.1, 5.7, 5.1, ...
$ Sepal.Width  <S3: currency> 3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1, 3.7, 3.4, 3.0, 3.0, 4.0, 4.4, 3.9, 3.5, 3.8, 3.8, ...
$ Petal.Length <S3: currency> 1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5, 1.5, 1.6, 1.4, 1.1, 1.2, 1.5, 1.3, 1.4, 1.7, 1.5, ...
$ Petal.Width  <S3: currency> 0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.1, 0.2, 0.2, 0.1, 0.1, 0.2, 0.4, 0.4, 0.3, 0.3, 0.3, ...
$ Species      <S3: currency> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1...