tidyverse pivot_longer several sets of columns, but avoid intermediate mutate_wider steps [duplicate]

Answer 1

Following @Ronak Shah's suggestion, I'm pasting my code here in case my column names are less structured. I'm building up this code on the dat data I specified in my initial post.

names(dat) <- c("id", "Q4", "Q5", "Q8r1", "Q8r2")

spec <- data.frame(.name  = names(dat)[-1],
                   .value = c("Q4Q5", "Q4Q5", "Q8", "Q8"),
                   brand  = rep(c("pepsi", "cola"), 2),
                   stringsAsFactors = FALSE)

dat_long <- pivot_longer_spec(dat, spec)

This gives essentially the same result as for the data with my structured names, just that the names are different now.

Again, I'm not entirely sure how generalizable this approach is, but it worked in my case.

Answer 2

You can use :

tidyr::pivot_longer(dat, cols = -id, 
                   names_to = c('.value', 'brand'), 
                   names_sep = "_")


#  id    brand  Q1r1  Q1r2
#  <chr> <chr> <dbl> <dbl>
#1 A     pepsi     1     1
#2 A     cola      0     0
#3 B     pepsi     0     1
#4 B     cola      0     1
#5 C     pepsi     1     1
#6 C     cola      1     1

Answer 3

We can use gather/spread

library(tidyr)
library(dplyr)
dat %>%
    gather(brand, value, -id) %>%
    separate(brand, into = c('name', 'brand')) %>% 
    spread(name, value)
#  id brand Q1r1 Q1r2
#1  A  cola    0    0
#2  A pepsi    1    1
#3  B  cola    0    1
#4  B pepsi    0    1
#5  C  cola    1    1
#6  C pepsi    1    1