dplyr - inputting columns to rowwise() with column index instead of column name

Question

I've found an excellent solution to a problem I'm having where I want to create a new column that computes the mean of all the cells in the corresponding row here:

https://stackoverflow.com/a/33438918/12744116

The data is admittedly not tidy, but the solution, which I've copied below, gets the job done:

data %>% 
    rowwise() %>% 
    mutate(c=mean(c(a,b)))

#      id     a     b     c
#   (dbl) (dbl) (dbl) (dbl)
# 1   101     1     2   1.5
# 2   102     2     2   2.0
# 3   103     3     2   2.5

However, unlike this simpler example, I have far too many columns to name. I'm wondering if there's any way of quickly referring to the columns using slicing notation (ie, instead of c(a, b), something like 2:3) or some other way of referring to the columns via their index.

I've found something similar on another Stack Overflow thread here , but the solution has its own problems since we're listing all the column indices instead of the column names. I have way too many columns for me to list them all for each calculation.

Any solutions?

EDIT: I figured one out myself, but I feel like it's too inelegant and I believe I'm maybe extracting the entire column for every row, which is obviously going to be a slower solution than expected:

data %>%
  mutate(id = row_number()) %>%
  rowwise() %>%
  mutate(avg = mean(c(.[id, 2:4], recursive=TRUE)))

Any solutions that are faster?

Answer 1

You can do:

df %>%
 mutate(c = rowMeans(select(., 2:3)))

   id a b   c
1 101 1 2 1.5
2 102 2 2 2.0
3 103 3 2 2.5

Or:

df %>%
 mutate(c = rowMeans(select(., 2:length(.))))

Answer 2

For me using rowMeans seems straightforward without involving tidyverse functions.

data$c <- rowMeans(data[2:3])

however, if you prefer tidyverse solution we can take a bit of help from purrr map functions.

library(dplyr)
library(purrr)

For only two columns

data %>% mutate(c = map2_dbl(a, b, ~mean(c(.x, .y))))

For many columns

data %>%  mutate(c = pmap_dbl(select(., a:b), ~mean(c(...))))