I have a function that takes in two arguments (columns). The function changes the value of one column (x) based on what the value in another column is (y).
fun <- function(x, y) {
x = coalesce(case_when(y %in% c("hello", "hi") ~ '1',
y == "thanks" ~ '2'), x)
}
However, this needs to be done over many column pairs, why I want to make it a function.
Is this the right way of doing it:
df %>% mutate(across(c(col1, col3), c(col2, col4), fun))
from
col1 col2 col3 col4
1 1
2 4
5 "hello" 5 "hello"
3
4 4
5 "hi" 5 "thanks"
5 "thanks"
5 "goodbye" 5 "hello"
To
col1 col2 col3 col4
1 1
2 4
1 "hello" 1 "hello"
3
4 4
1 "hi" 2 "thanks"
2 "thanks"
5 "goodbye" 1 "hello"
If it is pairwise, then we may need map2 which returns a list of vectors which can be assigned to new columns to the existing column of dataset (not clear from the code)
library(purrr)
library(dplyr)
fun <- function(data, x, y) {
coalesce(case_when(data[[y]] %in% c("hello", "hi") ~ 1,
data[[y]] == "thanks" ~ 2), data[[x]])
}
df[c("col1", "col3")] <- map2( c("col1", "col3"),
c("col2", "col4"), ~ fun(df, .x, .y))
-output
> df
col1 col2 col3 col4
1 1 <NA> 1 <NA>
2 2 <NA> 4 <NA>
3 1 hello 1 hello
4 3 <NA> NA <NA>
5 4 <NA> 4 <NA>
6 1 hi 2 thanks
7 2 thanks NA <NA>
8 5 goodbye 1 hello
df <- structure(list(col1 = c(1L, 2L, 5L, 3L, 4L, 5L, 5L, 5L), col2 = c(NA,
NA, "hello", NA, NA, "hi", "thanks", "goodbye"), col3 = c(1L,
4L, 5L, NA, 4L, 5L, NA, 5L), col4 = c(NA, NA, "hello", NA, NA,
"thanks", NA, "hello")), class = "data.frame", row.names = c(NA,
-8L))