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Searching matching rows in different columns

I am looking for a function that can find matches in between the columns and output if it finds a matching row outputs "has matches" else "no matches"

for example

df = data.frame(id=c("good","bad","ugly","dirty","clean","frenzy"),di=c(1,2,"good","dirty",4,"ugly"))

> df
      id    di
1   good     1
2    bad     2
3   ugly  good
4  dirty dirty
5  clean     4
6 frenzy  ugly

I want to check di column has matches or not in id column such that

 > df
          id    di  match
    1   good     1  no matches
    2    bad     2  no matches
    3   ugly  good  has matches
    4  dirty dirty  has matches
    5  clean     4  no matches
    6 frenzy  ugly  has matches

This kind of approach what I am looking for

match_func <- function(x,y){

  }

df%>%
  do(match_func(.$id,.$di))

Thanks in advance!

Using base R and without if/else statement, you can compute match column with:

df$match <- c("no matches", "has matches")[(df$di %in% df$id) + 1]
df
#      id    di       match
#1   good     1  no matches
#2    bad     2  no matches
#3   ugly  good has matches
#4  dirty dirty has matches
#5  clean     4  no matches
#6 frenzy  ugly has matches

Just use %in% with ifelse

df %>% 
   mutate(match = ifelse(di %in% id, "has matches", "no matches"))

Or case_when

df %>% 
   mutate(match = case_when(di %in% id ~ "has matches",
                                   TRUE ~ "no matches"))

This can be directly wrapped in a function. Assuming that we are passing unquoted names, then convert it to quosure with enquo and then evaluate within the mutate by !!

f1  <- function(dat, col1, col2) {
    col1 = enquo(col1)
    col2 = enquo(col2)
    dat %>%
        mutate(match = case_when(!! (col1) %in% !!(col2) ~ "has matches", 
                 TRUE ~ "no matches"))
}
f1(df, di, id)
#      id    di       match
#1   good     1  no matches
#2    bad     2  no matches
#3   ugly  good has matches
#4  dirty dirty has matches
#5  clean     4  no matches
#6 frenzy  ugly has matches

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