Counting the Position of the First 0 in Each Row - r

Question

I have a dataset that looks like this:
set.seed(999)
col1 = sample.int(10, 10)
col2 = sample.int(10, 10)
col3 = sample.int(10, 10)
col4 = sample.int(10, 10)
col5 = sample.int(10, 10)
col_data = data.frame(col1, col2, col3, col4, col5)
col1 col2 col3 col4 col5
1 4 8 3 9 8
2 7 5 9 7 10
3 1 7 7 8 2
4 6 6 5 5 4
5 8 10 8 3 7
6 2 3 1 2 6
7 5 9 2 1 1
8 10 2 4 4 3
9 9 1 10 6 9
10 3 4 6 10 5
I would like to create new columns in this dataset that :
Find out the position (i.e. column number) for the first "9" in each row
Find out the position (i.e. column number) for the first "7" in each row
Find out the position (i.e. column number) for the first "1" in each row
Find out the position (i.e. column number) for the first "10" in each row
Find out the position (i.e. column number) for the first "4" in each row
I thought this might be easier to do if the data was a matrix, and then convert it back to a data frame:
col_d = as.matrix(col_data)
first_4 = apply(col_d == 9, 1, which.max)
first_7 = apply(col_d == 7, 1, which.max)
first_1 = apply(col_d == 1, 1, which.max)
first_10 = apply(col_d == 10, 1, which.max)
first_4 = apply(col_d == 4, 1, which.max)
final = cbind(col_data, first_4, first_7, first_1, first_10, first_4)
But this does not appear to be working:
col1 col2 col3 col4 col5 first_4 first_7 first_1 first_10 first_4
1 4 8 3 9 8 1 1 1 1 1
2 7 5 9 7 10 1 1 1 5 1
3 1 7 7 8 2 1 2 1 1 1
4 6 6 5 5 4 5 1 1 1 5
5 8 10 8 3 7 1 5 1 2 1
6 2 3 1 2 6 1 1 3 1 1
7 5 9 2 1 1 1 1 4 1 1
8 10 2 4 4 3 3 1 1 1 3
9 9 1 10 6 9 1 1 2 3 1
10 3 4 6 10 5 2 1 1 4 2
For example: In the first row, there is no 10 - but the value of "first_10" is 1
Is there a way to resolve this error?
Thank you!

Answer 1

How about
apply(col_data == 7, 1, function(x) {ifelse(sum(x)==0, NA, which.max(x))})
[1] NA 1 2 NA 5 NA NA NA NA NA
apply(col_data == 10, 1, function(x) {ifelse(sum(x)==0, NA, which.max(x))})
[1] NA 5 NA NA 2 NA NA 1 3 4
You may change NA whatever you want, that it means there is no that number(i.e 7 or 10)
get second one
apply(col_data == 7, 1, function(x) {ifelse(sum(x)==0, NA, which(x)[2])})
get last one
apply(col_data == 7, 1, function(x) {ifelse(sum(x)==0, NA, dplyr::last(which(x)))})

Answer 2

Use max.col:
nr <- c(9, 7, 1, 10, 4)
nr <- setNames(nr, paste0("first_", nr))
cbind(col_data, sapply(nr, function(x) {
. <- col_data == x
tt <- max.col(., "first")
is.na(tt) <- tt == 1 & !.[,1]
tt
}))
# col1 col2 col3 col4 col5 first_9 first_7 first_1 first_10 first_4
#1 4 8 3 9 8 4 NA NA NA 1
#2 7 5 9 7 10 3 1 NA 5 NA
#3 1 7 7 8 2 NA 2 1 NA NA
#4 6 6 5 5 4 NA NA NA NA 5
#5 8 10 8 3 7 NA 5 NA 2 NA
#6 2 3 1 2 6 NA NA 3 NA NA
#7 5 9 2 1 1 2 NA 4 NA NA
#8 10 2 4 4 3 NA NA NA 1 3
#9 9 1 10 6 9 1 NA 2 3 NA
#10 3 4 6 10 5 NA NA NA 4 2
For the last:
nr <- c(9, 7, 1, 10, 4)
nr <- setNames(nr, paste0("last_", nr))
cbind(col_data, sapply(nr, function(x) {
. <- col_data == x
tt <- max.col(., "last")
is.na(tt) <- rowSums(.) == 0
tt
}))
# col1 col2 col3 col4 col5 last_9 last_7 last_1 last_10 last_4
#1 4 8 3 9 8 4 NA NA NA 1
#2 7 5 9 7 10 3 4 NA 5 NA
#3 1 7 7 8 2 NA 3 1 NA NA
#4 6 6 5 5 4 NA NA NA NA 5
#5 8 10 8 3 7 NA 5 NA 2 NA
#6 2 3 1 2 6 NA NA 3 NA NA
#7 5 9 2 1 1 2 NA 5 NA NA
#8 10 2 4 4 3 NA NA NA 1 4
#9 9 1 10 6 9 5 NA 2 3 NA
#10 3 4 6 10 5 NA NA NA 4 2
And for the second match:
nr <- c(9, 7, 1, 10, 4)
nr <- setNames(nr, paste0("2nd_", nr))
cbind(col_data, sapply(nr, function(x) {
. <- which(col_data == x, TRUE)
. <- tapply(.[,2], .[,1], `[`, 2)
replace(rep(NA_integer_, nrow(col_data)), as.integer(names(.)), .)
}))
# col1 col2 col3 col4 col5 2nd_9 2nd_7 2nd_1 2nd_10 2nd_4
#1 4 8 3 9 8 NA NA NA NA NA
#2 7 5 9 7 10 NA 4 NA NA NA
#3 1 7 7 8 2 NA 3 NA NA NA
#4 6 6 5 5 4 NA NA NA NA NA
#5 8 10 8 3 7 NA NA NA NA NA
#6 2 3 1 2 6 NA NA NA NA NA
#7 5 9 2 1 1 NA NA 5 NA NA
#8 10 2 4 4 3 NA NA NA NA 4
#9 9 1 10 6 9 5 NA NA NA NA
#10 3 4 6 10 5 NA NA NA NA NA
Or using apply on one column.
#First
apply(col_data == 9, 1, function(x) if(any(x)) which.max(x) else NA)
# [1] 4 3 NA NA NA NA 2 NA 1 NA
#Last
apply(col_data == 9, 1, function(x) if(any(x)) tail(which(x), 1) else NA)
# [1] 4 3 NA NA NA NA 2 NA 5 NA
#Second
apply(col_data == 9, 1, function(x) if(any(x)) which(x)[2] else NA)
# [1] NA NA NA NA NA NA NA NA 5 NA