If statements for a multiple columns in R-CodePudding

data <- data.frame(id=c(1,2,3,4,5,6,7),
                  q1=c(3,4,5,2,1,2,4),
                   q2=c(3,4,4,5,4,3,2),
                   q3=c(2,3,2,3,1,2,3),
                   q4=c(3,4,4,4,4,5,5))

For these q1-q4 I would like to write a statement where it says if q1 = 1 then generate a q1_1 =1 ; if q1=2 then generate q1_2 = 2;if q1=3 then generate q1_3=3; if q1=4 then generate q1_4=4, and if q5=5 then generate q1_5=5 for all of the questions in this dataset. I know I would have to do some sort of loop and then maybe an if statement, but I am just not really familiar with loops at all.

The OUTPUT i am hoping to get looks like (but with more columns for all the questions)


  id q1 q2 q3 q4 q1_1 q1_2 q1_3 q1_4 q1_5
1  1  3  3  2  3   NA   NA    3   NA   NA
2  2  4  4  3  4   NA   NA   NA    4   NA
3  3  5  4  2  4   NA   NA   NA   NA    5
4  4  2  5  3  4   NA    2   NA   NA   NA
5  5  1  4  1  4    1   NA   NA   NA   NA
6  6  2  3  2  5   NA    2   NA   NA   NA
7  7  4  2  3  5    4   NA   NA    4   NA

Any help is appreciated, thank you!

CodePudding user response：

No loop necessary. Go long, then go wide, then join the original data.

library(tidyverse)

data <- tibble(id=c(1,2,3,4,5,6,7),
                  q1=c(3,4,5,2,1,2,4),
                   q2=c(3,4,4,5,4,3,2),
                   q3=c(2,3,2,3,1,2,3),
                   q4=c(3,4,4,4,4,5,5))

data |>
  pivot_longer(-id) |>
  mutate(name = paste(name, value, sep = "_")) |>
  pivot_wider() |>
  (\(d) left_join(data, d, by = "id"))()
#> # A tibble: 7 x 20
#>      id    q1    q2    q3    q4  q1_3  q2_3  q3_2  q4_3  q1_4  q2_4  q3_3  q4_4
#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1     1     3     3     2     3     3     3     2     3    NA    NA    NA    NA
#> 2     2     4     4     3     4    NA    NA    NA    NA     4     4     3     4
#> 3     3     5     4     2     4    NA    NA     2    NA    NA     4    NA     4
#> 4     4     2     5     3     4    NA    NA    NA    NA    NA    NA     3     4
#> 5     5     1     4     1     4    NA    NA    NA    NA    NA     4    NA     4
#> 6     6     2     3     2     5    NA     3     2    NA    NA    NA    NA    NA
#> 7     7     4     2     3     5    NA    NA    NA    NA     4    NA     3    NA
#> # ... with 7 more variables: q1_5 <dbl>, q1_2 <dbl>, q2_5 <dbl>, q1_1 <dbl>,
#> #   q3_1 <dbl>, q4_5 <dbl>, q2_2 <dbl>