Repeating loop and adding columns in R - r

Question

I am trying to build an R code that will take my loop and run it 20 times. Each time I would like to add a column to the existing data frame. Here I tried it by adding the code 3 times, but I feel like there must be an easier way to automate this. I am very grateful for any help.
My original data file (called "igel") contains two columns ("Year" and "Grid") and 1096 rows. With the loop I pick a random number from the column "Grid" and check whether it has been picked before. If so it adds 0 to a new column if not it adds 1.
Here the code:
a <- data.frame(matrix(ncol = 2, nrow = 0))
x <- c("number", "count")
colnames(a) <- x
for (i in 1:1096) {
num_i <- sample(igel$Grid, 1)
count_i <- c(if (num_i %in% a$number == TRUE) {0} else {1})
a<-a %>% add_row(number = num_i, count = count_i)
}
b <- data.frame(matrix(ncol = 2, nrow = 0))
x <- c("number", "count")
colnames(b) <- x
for (i in 1:1096) {
num_i <- sample(igel$Grid, 1)
count_i <- c(if (num_i %in% b$number == TRUE) {0} else {1})
b<-b %>% add_row(number = num_i, count = count_i)
}
c <- data.frame(matrix(ncol = 2, nrow = 0))
x <- c("number", "count")
colnames(c) <- x
for (i in 1:1096) {
num_i <- sample(igel$Grid, 1)
count_i <- c(if (num_i %in% c$number == TRUE) {0} else {1})
c<-c %>% add_row(number = num_i, count = count_i)
}
df.total<- cbind(a$count,b$count, c$count)

Answer 1

Consider sapply and even its wrapper, replicate and calculate number and count separately in vector calculations instead of growing object in loop by row.
# RUNS 3 SAMPLES OF igel$Grid 1,096 TIMES (ADJUST 3 TO ANY POSITIVE INT LIKE 20)
grid_number <- data.frame(replicate(3, replicate(1096, sample(igel$Grid, 1))))
# RUNS ACROSS 3 COLUMNS TO CHECK CURRENT ROW VALUE IS INCLUDED FOR ALL VALUES BEFORE ROW
grid_count <- sapply(grid_number, function(col)
sapply(seq_along(col), function(i)
ifelse(col[i] %in% col[1:(i-1)], 0, 1)
)
)
While above does not exactly reproduce your output, df.total (a matrix and not data frame), due to the random sampling within iterations, the two maintain similar structure:
dim(df.total)
# [1] 1096 3
dim(grid_count)
# [1] 1096 3

Answer 2

Try to avoid iterating through rows. It is rarely necessary, if ever. Here is one approach (replace n with 1096 and elem with igel$Grid):
n = 20
elem = 1:5
df.total = list()
for (i in 1:5) {
a = data.frame(number = sample(elem, n, replace=TRUE))
a$count = as.numeric(duplicated(a$number))
df.total[[i]] = a
}
df.total = as.data.frame(df.total)
df.total
## number count number.1 count.1 number.2 count.2 number.3 count.3 number.4 count.4
## 1 4 0 2 0 5 0 4 0 1 0
## 2 3 0 5 0 3 0 4 1 3 0
## 3 5 0 3 0 4 0 2 0 4 0
## 4 5 1 1 0 2 0 5 0 3 1
## 5 2 0 4 0 2 1 5 1 5 0
## 6 4 1 2 1 2 1 5 1 5 1
## 7 5 1 1 1 3 1 2 1 4 1
## 8 5 1 2 1 5 1 5 1 4 1
## 9 2 1 1 1 1 0 1 0 1 1
## 10 3 1 1 1 5 1 4 1 1 1
## 11 5 1 3 1 1 1 3 0 5 1
## 12 2 1 1 1 2 1 5 1 1 1
## 13 3 1 5 1 4 1 5 1 4 1
## 14 1 0 4 1 2 1 4 1 1 1
## 15 4 1 4 1 2 1 5 1 1 1
## 16 4 1 2 1 5 1 2 1 5 1
## 17 3 1 1 1 1 1 3 1 2 0
## 18 2 1 2 1 2 1 2 1 2 1
## 19 2 1 3 1 1 1 2 1 1 1
## 20 1 1 3 1 2 1 1 1 3 1