I'm writing a function to pivot a data table to long format. For the cols = argument, the name of the first column will always be the same, but the final column (and number of columns) will change. Is there a way to grab the "rest" of the columns without naming them or by their indexes?
Say I have this sample data:
data <- structure(list(Site = c("A", "B"), Group = c("1", "2"), grip = c("S",
"H"), height = c("S", "T"), width = c("W", "N"), QA = c("Y",
"N")), class = "data.frame", row.names = c(NA, -2L))
That looks like this:
Site Group grip height width QA
1 A 1 S S W Y
2 B 2 H T N N
And sometimes the dataset will have more columns. Say I want to get columns grip:QA, without naming QA, or giving its index number. I tried the following:
data %>%
pivot_longer(cols = grip:everything(),
names_to = "Name",
values_to = "value")
But I get the warning Warning message: In x:y : numerical expression has 6 elements: only the first used, and it doesn't pivot the way I want it to. Is what I'm trying to achieve possible?
You could use last_col:
library(tidyr)
data %>%
pivot_longer(
cols = grip:last_col(),
names_to = "Name",
values_to = "value"
)
#> # A tibble: 8 × 4
#> Site Group Name value
#> <chr> <chr> <chr> <chr>
#> 1 A 1 grip S
#> 2 A 1 height S
#> 3 A 1 width W
#> 4 A 1 QA Y
#> 5 B 2 grip H
#> 6 B 2 height T
#> 7 B 2 width N
#> 8 B 2 QA N
Or as another option exclude the columns you don't want to include when pivoting using ! or -:
data %>%
pivot_longer(
cols = !c(Site, Group),
names_to = "Name",
values_to = "value"
)
#> # A tibble: 8 × 4
#> Site Group Name value
#> <chr> <chr> <chr> <chr>
#> 1 A 1 grip S
#> 2 A 1 height S
#> 3 A 1 width W
#> 4 A 1 QA Y
#> 5 B 2 grip H
#> 6 B 2 height T
#> 7 B 2 width N
#> 8 B 2 QA N