How to transform table from one row per ID to one row per ID per column?

Question

I have the following table:

Table <- data.frame(ID=c(1,2),A=c("TRUE","FALSE"), B=c("1","2"))

ID	A	B
1	"TRUE"	"1"
2	"FALSE"	"2"

I want to transform it into the following table:

Table_transformed <- data.frame(ID=c(1,2,1,2),COLUMN=c("A","A","B","B"), VALUE=c("TRUE","FALSE","1","2"))

ID	COLUMN	VALUE
1	A	"TRUE"
2	A	"FALSE"
1	B	"1"
2	B	"2"

How to do this?

I have not found a way to do this yet without using non-generalized for-loops etc.

score 0 · Answer 1 · answered Jun 27 '23 at 10:35

A tidyverse solution:

df1 <- data.frame(ID=c(1,2),A=c("TRUE","FALSE"), B=c("1","2"))

library(tidyr)
library(dplyr)

df1 |> 
pivot_longer(-ID, names_to = "Column", values_to = "VALUE") |> 
arrange(Column)  

#> # A tibble: 4 × 3
#>      ID Column VALUE
#>   <dbl> <chr>  <chr>
#> 1     1 A      TRUE 
#> 2     2 A      FALSE
#> 3     1 B      1    
#> 4     2 B      2

^{Created on 2023-06-27 with reprex v2.0.2}

How to transform table from one row per ID to one row per ID per column?

1 Answers1