Creating new column that flags row based on conditions

Question

I'm trying to filter this dataframe called df

structure(list(ï..ID = structure(c(2L, 1L, 4L, 6L, 3L, 7L, 5L, 
8L), .Label = c("Jay ", "Jim", "Jim ", "John ", "Mike ", "Peter", 
"Peter ", "Tom"), class = "factor"), Target1 = structure(c(8L, 
4L, 6L, 5L, 2L, 1L, 3L, 7L), .Label = c("Andreas", "Cheyne", 
"Frank", "John", "Mickey", "Raj", "Sarah", "Timothy"), class = "factor"), 
    Target2 = structure(c(4L, 3L, 1L, 5L, 2L, 1L, 1L, 1L), .Label = c("", 
    "Jake", "Peter", "Timothy ", "Tommy "), class = "factor"), 
    Parter1 = structure(c(3L, 2L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("", 
    "Mike ", "Timothy"), class = "factor"), Parter2 = structure(c(1L, 
    2L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("", "Peter"), class = "factor")), class = "data.frame", row.names = c(NA, 
-8L))

I'm trying to filter the dataframe such that if the names that appear in this vector x

x=c("Raj", "Timothy")

appears more than 2 times in columns 2-5 the row will have a variable for a brand new column called flag where flag =1 if the name appears more than 2 times and flag=0 if the name does not appear more than 2 times.

Answer 1

In Base R, we could use apply with MARGIN = 1 (row-wise)

df$flag <- as.integer(apply(df, 1, function(row) sum(row %in% x)) > 2)

df
#  ï..ID Target1 Target2 Parter1 Parter2 flag
#1   Jim Timothy Timothy Timothy            1
#2   Jay    John   Peter    Mike   Peter    0
#3  John     Raj                            0
#4 Peter  Mickey   Tommy                    0
#5   Jim  Cheyne    Jake                    0
#6 Peter Andreas                            0
#7  Mike   Frank                            0
#8   Tom   Sarah                            0

---

apply converts dataframe to matrix and can be slow some time. You can avoid apply call using sapply with same logic

df$flag <- as.integer(sapply(1:nrow(df), function(i) sum(df[i, ] %in% x)) > 2)

And another way to write it

df$flag <- as.integer(colSums(sapply(1:nrow(df), function(i) df[i, ] %in% x)) > 2)

PS - You had some white-spaces in the names, I had to first run

df[] <- lapply(df, trimws)

to remove them.