Pivot_longer() with multiple new columns-CodePudding

I have a question about tidyr::pivot_longer().

Lets say I start with an imaginary dataframe. Imagine people were asked two Questions about two Genres. SQ1_2 would be the second question about the first genre.

set.seed(1234)
genres <- c("Crime", "Horror", "Love", "Sci-Fi", NA)
wide <- data.frame(
  ID = 1:10,
  Genre_1 = sample(genres, 10, replace = TRUE),
  Genre_2 = sample(genres, 10, replace = TRUE),
  SQ1_1 = sample(1:5, 10, replace = TRUE),
  SQ1_2 = sample(1:5, 10, replace = TRUE),
  SQ2_1 = sample(1:5, 10, replace = TRUE),
  SQ2_2 = sample(1:5, 10, replace = TRUE)
)

ID	Genre_1	Genre_2	SQ1_1	SQ1_2	SQ2_1	SQ2_2
1	Sci-Fi	Sci-Fi	3	5	2	2
2	Horror	Sci-Fi	4	1	3	5

I strive to achieve an end result like this:

ID	time	Genre	SQ1	SQ2
1	Genre_1	Sci-Fi	3	5
1	Genre_2	Sci-Fi	2	2
2	Genre_1	Horror	4	1
2	Genre_2	Sci-Fi	3	5

I used to do this task the following way:

long1 <- wide |> tidyr::pivot_longer(col = starts_with("Genre"),
                              names_to = "time",
                              values_to = "genre")
long2 <- wide |> tidyr::pivot_longer(col = c(SQ1_1, SQ2_1),
                              names_to = "time",
                              values_to = "SQ1")
long3 <- wide |> tidyr::pivot_longer(col = c(SQ1_2, SQ2_2),
                              names_to = "time",
                              values_to = "SQ2")
long <- long1 |> 
  dplyr::select(ID, time:genre) |>
  dplyr::mutate(SQ1 = long2$SQ1,
         SQ2 = long3$SQ2)

I was just curious if there is any way to create multiple new columns from different variables with one call of pivot_longer() (or any other function for that matter).

Any help is much appreciated! :)

CodePudding user response：

You need to make the naming rule consistent for those columns you want to pivot into longer format:

The j-th genre = Genre_j
The i-th question about the j-th genre = SQi_j

Then stack Genre, SQ1, SQ2 respectively:

library(dplyr)
library(tidyr)

wide %>%
  rename_with(~ sub('(\\d)_(\\d)', '\\2_\\1', .x), starts_with('SQ')) %>%
  pivot_longer(-1,
               names_to = c(".value", "Time"),
               names_sep = '_')

# # A tibble: 20 × 5
#       ID Time  Genre    SQ1   SQ2
#    <int> <chr> <chr>  <int> <int>
#  1     1 1     Sci-Fi     3     5
#  2     1 2     Sci-Fi     2     2
#  3     2 1     Horror     4     1
#  4     2 2     Sci-Fi     3     5