Populate a new column if a value is found in any column

Question

I want to check every row in data frame. I need to check all columns in that row to see if it contains a 1, if it does I want to populate another column that summarizes if any

Answer 1

Using:

dat$imputed <- c('no','yes')[1 + (rowSums(dat == 1) > 0)]

gives:

> dat
  A B C imputed
1 0 0 0      no
2 0 1 1     yes
3 1 0 0     yes
4 0 0 0      no

What this does:

• rowSums(dat == 1) > 0 creates a logical vector indicating whether a row contains a 1
• Adding 1 to that gives an integer vector
• Which in turn can be used to create the appropriate vector of yes and no values.

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Used data:

dat <- structure(list(A = c(0L, 0L, 1L, 0L), B = c(0L, 1L, 0L, 0L), C = c(0L, 1L, 0L, 0L)),
                 .Names = c("A", "B", "C"), class = "data.frame", row.names = c(NA, -4L))

Answer 2

A dplyr way would be

a1 %>% mutate(imputed_data = ifelse(rowSums(. == 1) != 0, "yes", "no"))

Answer 3

One of many solutions:

a1 = data.frame(A = c(0,0,1,0), B = c(0,1,0,0), C = c(0,1,0,0))

a1$imputed = apply(a1, 1, function(x) ifelse(any(x == 1), 'yes', 'no'))

  A B C imputed
1 0 0 0      no
2 0 1 1     yes
3 1 0 0     yes
4 0 0 0      no