Loop through columns and split fields automatically to new column - r

Question

I have been comparing two data frames in R using a package called daff and this is the final table I get:
dput(df)
structure(list(v1 = c("Silva->Silva/Mark", "Brandon->Brandon/Livo", "Mango->Mango or Apple"),
v2 = c("James->James=Jacy","NA->Na/Jane", "Egg->Egg and Orange")),
class = "data.frame", row.names = c(NA, -3L))
The rows fields have ->(arrow) to mean the data was modified in that cell from previous data frame column to current dataframe value. Now from here I had to separate the columns with ->(arrow) separator so that I can have an old column and new changed column. This means I added a suffix_old and _New to new columns. I used this code and see the output:
setDT(df)
df1<- lapply(names(df), function(x) {
mDT <- df[, tstrsplit(get(x), " *-> *")]
if (ncol(mDT) == 2L) setnames(mDT, paste0(x, c("_Old", "_New")))
}) %>% as.data.table()
OUTPUT
dput(df)
structure(list(v1_Old = c("Silva", "Brandon", "Mango"),
v1_New = c("Silva/Mark", "Brandon/Livo", "Mango or Apple"),
v2_Old = c("James","NA", "Egg"),
v2_New = c("James=Jacy","Na/Jane", "Egg and Orange")),
class = "data.frame", row.names = c(NA, -3L))
Now my next step is to compare every two columns which have _old and _new suffix to identify what was modified then split and store in new column called diff_v1 and diff_v2. This I did using this code (Realise I have to do this manually by creating different spliting code lines, this is tedious with over 20 separated columns):
df$diff_v1<- mapply(function(x, y) paste(setdiff(y, x), collapse = '| '), strsplit(df$v1_old, '\\||, | | -| \\+'), strsplit(df$v1_Name_new, '\\||, | | -| \\+'))
df$diff_v2<- mapply(function(x, y) paste(setdiff(y, x), collapse = '| '), strsplit(df$v2_old, '\\||, | | -| \\+'), strsplit(df$v2_new, '\\||, | | -| \\+'))
OUTPUT
dput(df)
structure(list(v1_Old = c("Silva", "Brandon", "Mango"),
v1_New = c("Silva/Mark", "Brandon/Livo", "Mango or Apple"),
diff_v1 = c("/Mark", "/Livo", "or Apple"),
v2_Old = c("James","NA", "Egg"),
v2_New = c("James=Jacy","Na/Jane", "Egg and Orange"),
diff_v2 = c("=Jacy","/Jane", "and Orange")),
class = "data.frame", row.names = c(NA, -3L))
My question is can I be able to loop through columns with _old and _new and create new column called diff_v1 and diff_v2 respectively without running code line by line since. I have multiple columns and they keep changing depending on dataframes I am comparing . Wanted to know How I can use code to automatically identify columns with _Old and _New suffix and split then create that new column after the two but should happen on each pair of columns.
Currently I have to go to the data frame, check columns with old and new then manually change in the code that is splitting and creating diff column

Answer 1

We could identify "Old" and "New" columns based on their name using grep. We can use str_remove which is vectorized over string and pattern to remove part of "Old" col which is present in "New" col to create new columns.
old_cols <- grep("Old$", names(df), value = TRUE)
new_cols <- grep("New$", names(df), value = TRUE)
df[sub("New$", "diff", new_cols)] <- Map(stringr::str_remove,
df[new_cols], df[old_cols])
To get the names in order, we can do
df <- df[order(sub("_.*", "", names(df)))]
df
# v1_Old v1_New v1_diff v2_Old v2_New v2_diff
#1 Silva Silva/Mark /Mark James James=Jacy =Jacy
#2 Brandon Brandon/Livo /Livo NA Na/Jane Na/Jane
#3 Mango Mango or Apple or Apple Egg Egg and Orange and Orange
Using tidyverse, we can do
library(tidyverse)
df %>%
bind_cols(map2(df %>% select(ends_with("New")),
df %>% select(ends_with("Old")), stringr::str_remove))