在 dplyr 总结中使用变量列名

Question

I found this question already asked but without proper answer. R using variable column names in summarise function in dplyr

I want to calculate the difference between two column means, but the column name should be provided by variables... So far I found only the function as.name to provide column names as text, but this somehow doesn't work here...

With fix column names it works.

x <- c('a','b')
df <- group_by(data.frame(a=c(1,2,3,4), b=c(2,3,4,5), c=c(1,1,2,2)), c)
df %>% summarise(mean(a) - mean(b))

With variable columns, it doesn't work

df %>% summarise(mean(x[1]) - mean(x[2]))
df %>% summarise(mean(as.name(x[1])) - mean(as.name(x[2])))

Since this was asked already 3 years ago and dplyr is under good development, I am wondering if there is an answer to this now.

Answer 1

You can use base::get :

df %>% summarise(mean(get(x[1])) - mean(get(x[2])))

# # A tibble: 2 x 2
#        c `mean(a) - mean(b)`
#    <dbl>               <dbl>
# 1     1                  -1
# 2     2                  -1

get will search in current environment by default.

As the error message says, mean expects a logical or numeric object, as.name returns a name:

class(as.name("a")) # [1] "name"

You could evaluate your name, that would work as well :

df %>% summarise(mean(eval(as.name(x[1]))) - mean(eval(as.name(x[2]))))
# # A tibble: 2 x 2
#       c `mean(eval(as.name(x[1]))) - mean(eval(as.name(x[2])))`
#   <dbl>                                                   <dbl>
# 1     1                                                      -1
# 2     2                                                      -1

Answer 2

This is not a direct answer to your question but maybe could be useful for other people reading your post: It could be easier to use variable columns directly, like

df %>% summarise(someName = mean(.[[1]]) - mean(.[[2]]))
############ which is the same as ############
df %>% summarise(someName = mean(.[,1,drop=T]) - mean(.[,2,drop=T]))

Note that drop=T is because when using just single square bracket the result preserves the class (in this case class( . ) = data.frame) and this isn't what we want (columns must be given in vector form to the summarise function)