tidyr::unite across column patterns

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I have a dataset that looks something like this

site <- c("A", "B", "C", "D", "E")
D01_1 <- c(1, 0, 0, 0, 1)
D01_2 <- c(1, 1, 0, 1, 1)
D02_1 <- c(1, 0, 1, 0, 1)
D02_2 <- c(0, 1, 0, 0, 1)
D03_1 <- c(1, 1, 0, 0, 0)
D03_2 <- c(0, 1, 0, 0, 1)
df <- data.frame(site, D01_1, D01_2, D02_1, D02_2, D03_1, D03_2)

I am trying to unite the D0x_1 and D0x_2 columns so that the values in the columns are separated by a slash. I can do this with the following code and it works just fine:

library(dplyr)
library(tidyr)

df.unite <- df %>%
  unite(D01, D01_1, D01_2, sep = "/", remove = TRUE) %>%
  unite(D02, D02_1, D02_2, sep = "/", remove = TRUE) %>%
  unite(D03, D03_1, D03_2, sep = "/", remove = TRUE)

...but the problem is that it requires me to type out each unite pair multiple times and it is unwieldy across the large number of columns in my dataset. Is there a way in dplyr to unite across similarly patterned column names and then loop across the columns? unite_each doesn't seem to exist.

tidyr dplyr r
3 Answers

You can use an easy base R approach, too:

cols <- split(names(df)[-1], sub("_\\d+", "", names(df)[-1]))

cbind(df[1], sapply(names(cols), function(col) {
  do.call(paste, c(df[cols[[col]]], sep = "/"))
}))
#  site D01 D02 D03
#1    A 1/1 1/0 1/0
#2    B 0/1 0/1 1/1
#3    C 0/0 1/0 0/0
#4    D 0/1 0/0 0/0
#5    E 1/1 1/1 0/1
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