dplyr mutate rowwise max of range of columns

I can use the following to return the maximum of 2 columns

newiris<-iris %>%
 rowwise() %>%
 mutate(mak=max(Sepal.Width,Petal.Length))

What I want to do is find that maximum across a range of columns so I don't have to name each one like this

newiris<-iris %>%
 rowwise() %>%
 mutate(mak=max(Sepal.Width:Petal.Length))

Any ideas?

Instead of rowwise(), this can be done with pmax

iris %>%
      mutate(mak=pmax(Sepal.Width,Petal.Length, Petal.Width))

May be we can use interp from library(lazyeval) if we want to reference the column names stored in a vector.

library(lazyeval)
nm1 <- names(iris)[2:4]
iris %>% 
     mutate_(mak= interp(~pmax(v1), v1= as.name(nm1)))

With rlang and quasiquotation we have another dplyr option. First, get the row names that we want to compute the parallel max for:

iris_cols <- iris %>% select(Sepal.Length:Petal.Width) %>% names()

Then we can use !!! and rlang::syms to compute the parallel max for every row of those columns:

iris %>%
  mutate(mak=pmax(!!!rlang::syms(iris_cols)))

• rlang::syms takes a string input (the column names), and turns it into a symbol
• !!! unquotes and splices its argument, here the column names

Which gives:

    Sepal.Length Sepal.Width Petal.Length Petal.Width    Species mak
1            5.1         3.5          1.4         0.2     setosa 5.1
2            4.9         3.0          1.4         0.2     setosa 4.9
3            4.7         3.2          1.3         0.2     setosa 4.7
4            4.6         3.1          1.5         0.2     setosa 4.6
5            5.0         3.6          1.4         0.2     setosa 5.0

h/t: https://stackoverflow.com/a/47773379/1036500