I have 12 columns with info for 12 tests, each test has three different scores (bl, ind, dup) and I have five test categories/types matches('fluen|acur|dlp|outc|nota'). I'm trying to pivot longer them into five columns 'fluen', dlp, 'acur' , 'ouct', 'nota' which will contain the test score/value for each test and a categorical column called type containing the tests names as factors (bl, ind, dup) avoiding hard-coding.
- data:
head(my_data)
ID blfluen indfluen dupfluen blacur indacur dupacur bldlp inddlp dupdlp blnota indnota dupnota
1 p1 77.58 97.37 102.10 5.33 5.05 5.15 69.33 52.42 60.20 7 6.0 6.0
2 p2 93.63 81.56 97.84 5.82 2.29 7.54 50.09 57.93 56.79 9 7.5 8.0
- desired output:
ID fluen dlp acur outc nota type
part1 bl
part1 ind
part1 dup
part2 bl
part2 ind
part2 dup
so on...
Question: how can I achieve the desired output with
pivot_longer()? I'm sure there's a way to do this at once avoiding hard-coding. I've seen similar questions, but the thing that caught me was the patterns names, I didn't know how to group then into a single regex, for ex... Thanks in advance!reproducible data:
> dput(head(my_data))
structure(list(ID = c("p1", "p2", "p3", "p4", "p5", "p6"), blfluen = c(77.58,
93.63, 96, 59.74, 107.83, 90), indfluen = c(97.37, 81.56, 103.94,
82.1, 100.31, 90.47), dupfluen = c(102.1, 97.84, 113.04, 93.87,
96.36, 94.13), blacur = c(5.33, 5.82, 4.46, 8.97, 6.76, 3.33),
indacur = c(5.05, 2.29, 2.43, 7.69, 8.41, 11.57), dupacur = c(5.15,
7.54, 1.53, 7.21, 3.77, 7.69), bldlp = c(69.33, 50.09, 55.71,
59.74, 60.6, 65.55), inddlp = c(52.42, 57.93, 55.77, 61.02,
54.57, 66.31), dupdlp = c(60.2, 56.79, 46.15, 63.29, 65.28,
56.26), blnota = c(7, 9, 8, 4, 9, 7), indnota = c(6, 7.5,
8, 5, 9, 7), dupnota = c(6, 8, 9, 6, 8.5, 7.5)), row.names = c(NA,
6L), class = "data.frame")
CodePudding user response：
Using the names_pattern argument and the special .value you could do:
library(tidyr)
my_data |>
pivot_longer(-ID, names_to = c("type", ".value"), names_pattern = "^(bl|ind|dup)(.*)$")
#> # A tibble: 18 × 6
#> ID type fluen acur dlp nota
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 p1 bl 77.6 5.33 69.3 7
#> 2 p1 ind 97.4 5.05 52.4 6
#> 3 p1 dup 102. 5.15 60.2 6
#> 4 p2 bl 93.6 5.82 50.1 9
#> 5 p2 ind 81.6 2.29 57.9 7.5
#> 6 p2 dup 97.8 7.54 56.8 8
#> 7 p3 bl 96 4.46 55.7 8
#> 8 p3 ind 104. 2.43 55.8 8
#> 9 p3 dup 113. 1.53 46.2 9
#> 10 p4 bl 59.7 8.97 59.7 4
#> 11 p4 ind 82.1 7.69 61.0 5
#> 12 p4 dup 93.9 7.21 63.3 6
#> 13 p5 bl 108. 6.76 60.6 9
#> 14 p5 ind 100. 8.41 54.6 9
#> 15 p5 dup 96.4 3.77 65.3 8.5
#> 16 p6 bl 90 3.33 65.6 7
#> 17 p6 ind 90.5 11.6 66.3 7
#> 18 p6 dup 94.1 7.69 56.3 7.5