I have a data frame like this. The name of the second column is stored in a variable (supposed to be dynamic, fed into a function); the names of the first and the last ones are constant.
sel_col<-"w" #fed into a function previously
df <- tibble(id = 1:6, w = 10:15, x = 20:25)
df
#> # A tibble: 6 × 5
#> id w x
#> <int> <int> <int>
#> 1 1 10 20
#> 2 2 11 21
#> 3 3 12 22
#> 4 4 13 23
#> # ℹ 2 more rows
I also have variables with the sum of the values in columns.
sel_col_tot = sum(df[[sel_col]])
x_tot = sum(df$x)
Now, I need to add columns with the difference between the total value and the column value to yield this:
#> id w x sel_out x_out
#> <int> <int> <int> <int> <int>
#> 1 1 10 20 65 115
#> 2 2 11 21 64 114
#> 3 3 12 22 63 115
#> 4 4 13 23 62 116
And I need to do this using the column name coded in the variable. I tried to use mutate and {{}} or .[[]] syntaxis for it to use the var-coded column name. Like this:
... %>%
mutate(sel_out = sel_col_tot-.[[sel_tot]],
x_out = x_tot-x)
However, every time, it calculates the list of differences in all the rows and returns this error:
Error in `mutate()`:
ℹ In argument: `sel_out = sel_col_tot-.[[sel_tot]]`.
ℹ In row 1.
Caused by error:
! `sel_out` must be size 1, not 6.
How could I fix this and get the difference by row?
Thank you in advance for your help!
One option to access columns provided as a character string would be to use the .data pronoun:
library(dplyr, warn = FALSE)
sel_col <- "w"
df <- tibble(id = 1:6, w = 10:15, x = 20:25)
df |>
mutate(
sel_out = sum(.data[[sel_col]]) - .data[[sel_col]],
x_out = sum(x) - x
)
#> # A tibble: 6 × 5
#> id w x sel_out x_out
#> <int> <int> <int> <int> <int>
#> 1 1 10 20 65 115
#> 2 2 11 21 64 114
#> 3 3 12 22 63 113
#> 4 4 13 23 62 112
#> 5 5 14 24 61 111
#> 6 6 15 25 60 110