function - Nested `ifelse` statements in R -

i have data in following format , trying create new variable includes total number of deaths each observation, "present" indicates ongoing event:

    birth1  death1  birth2  death2  birth3  death3  birth4  death4  birth5  death5  birth6  death6   1 1990    present                                        2 1984    1986    1986    present                                3 1985    1988    1988    present                                4 1987    1991    1991    1994    1996    present                        5 1987    1989    1989    present                              

i tried data$num.deaths <- ifelse(data$death1=="present", 0, 1) doesn't @ observations have more 1 death event. tried nested ifelse got same result. can point me fast , efficient way of doing this?

extract columns represent deaths giving deaths , in each row add number of elements not na, not empty strings , not equal "present". no packages used.

deaths <- data[grep("death", names(data))] rowsums(!is.na(deaths) & deaths != "" & deaths != "present") ## b c d  ## 0 1 1 2  

an alternative last line of code gives same result check each cell of each row having numeric , add successes in each row -- apply turns rows columns use colsums that.

colsums(apply(deaths, 1, grepl, pattern = "\\d")) 

note: it's best show output of dput(data) in question unambiguously , reproducibly convey input. without there small differences between have , answers assume purposes of reproducibility used input (which corresponds original input data , sample output shown in question before revised):

data <-  structure(list(birth1 = c(1990l, 1984l, 1985l, 1987l), death1 = c("present",  "1986", "1988", "1991"), birth2 = c(na, 1986l, 1988l, 1991l),      death2 = c("", "present", "present", "1994"), birth3 = c(na,      na, na, 1996l), death3 = c("", "", "", "present")), .names = c("birth1",  "death1", "birth2", "death2", "birth3", "death3"),  class = "data.frame", row.names = c("a", "b", "c", "d")) 

it looks this:

> data   birth1  death1 birth2  death2 birth3  death3   1990 present     na             na         b   1984    1986   1986 present     na         c   1985    1988   1988 present     na         d   1987    1991   1991    1994   1996 present