Create column conditioning the behavior of rows in the dataset - r

Question

I would like to do something very specific. I have a vast set of data, which, in summary, looks more or less like this, with values 0, 1 and 2:
I need to create a situation variable so that it contains the value 0, 1 and 2.
The value 0 for cases that contain only 0's and 1's in the entire line.
The value 1 for the case where the value 2 appears, but at some point 1 appears before it.
The value 2 for the case where the value 2 appears, but at some point 0 appears before it.
So it's something close to:
structure(list(X1 = c(1, 1, 1, 1, 1, 1, 1, 1, 0, 1), X2 = c(1,
1, 1, 1, 0, 0, 0, 0, 0, 2), X3 = c(0, 1, 1, 1, 1, 0, 0, 1, 0,
0), X4 = c(0, 1, 1, 0, 1, 1, 0, 0, 0, 0), X5 = c(2, 1, 1, 0,
2, 1, 1, 0, 0, 0), X6 = c(2, 1, 1, 0, 2, 1, 1, 0, 0, 0), X7 = c(2,
1, 1, 1, 2, 1, 1, 2, 0, 0), X8 = c(0, 1, 1, 1, 2, 1, 2, 2, 2,
0)), class = "data.frame", row.names = c(NA, 10L))

Answer 1

I wrote a score function and applied it over all the rows of your dataframe.
score <- function(x) {
a <- which(x == 2)
ifelse(length(a) > 0, ifelse(a[1] >=2, 2 - x[a[1] - 1], 1), 0)
}
df <- structure(list(X1 = c(1, 1, 1, 1, 1, 1, 1, 1, 0, 1),
X2 = c(1, 1, 1, 1, 0, 0, 0, 0, 0, 2),
X3 = c(0, 1, 1, 1, 1, 0, 0, 1, 0, 0),
X4 = c(0, 1, 1, 0, 1, 1, 0, 0, 0, 0),
X5 = c(2, 1, 1, 0, 2, 1, 1, 0, 0, 0),
X6 = c(2, 1, 1, 0, 2, 1, 1, 0, 0, 0),
X7 = c(2, 1, 1, 1, 2, 1, 1, 2, 0, 0),
X8 = c(0, 1, 1, 1, 2, 1, 2, 2, 2, 0)),
class = "data.frame", row.names = c(NA, 10L))
df$situation <- sapply(1:nrow(df), function(i) score(as.numeric(df[i,])))
df

Answer 2

Here's a tidyverse approach.
I'll first concatenate all columns together, then use grepl() to look for 12 or 02.
library(tidyverse)
df %>% rowwise() %>%
mutate(concat = paste(c_across(everything()), collapse = "")) %>%
ungroup() %>%
mutate(situation = case_when(
!grepl(2, concat) ~ 0,
grepl("12", concat) ~ 1,
grepl("02", concat) ~ 2
)) %>%
select(-concat)
Output
# A tibble: 10 x 9
X1 X2 X3 X4 X5 X6 X7 X8 situation
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 1 1 0 0 2 2 2 0 2
2 1 1 1 1 1 1 1 1 0
3 1 1 1 1 1 1 1 1 0
4 1 1 1 0 0 0 1 1 0
5 1 0 1 1 2 2 2 2 1
6 1 0 0 1 1 1 1 1 0
7 1 0 0 0 1 1 1 2 1
8 1 0 1 0 0 0 2 2 2
9 0 0 0 0 0 0 0 2 2
10 1 2 0 0 0 0 0 0 1
Note that this solution assumes that:
2 will not appear in the first column
1 or 2 in the situation is defined by the number immediately before 2 in your dataset
There will not be a case of 12 and 02 happening in the same row