R: codify a variable based on preavious observation and by other variable - r

Question

considering the following data:
Var1 Var2 Target
A 0 no
A 250 no
A 0 si
A 0 si
B 0 no
B 0 no
B 0 no
B 250 no
C 0 no
C 250 no
C 0 si
C 250 no
and look at the variable called Target. I need to reproduce it with the same values.
The condition to obtain "si" or "no" is the following:
for the same level of Var1 (e.g A) if Var2=250 and the nexts are =0 then Target=si
I made this code:
df$Target <- NA
for(i in unique(df$Var1)){
subset.data.frame(df, Var1==i)
for(n in 1: length(df$Var1))
df$Target <-
ifelse(df$Var2[n]==250 && df$Var2[n+1]==0 && df$Var1[n+1]==df$Var1[n], "si", "no"))
But I get Target=si only if the next Var2=0.
Instead, as described in the dataset above, all observations with Var2=0 after a 250 have to be Target=si.
Could you help me to solve the problem, please?
Thank you,
Andrea

Answer 1

Solution
library(dplyr)
df %>%
group_by(Var1) %>%
mutate(Target = ifelse(cumsum(lag(Var2, default=0) == 250) > 0
& Var2 == 0, 'si', 'no'))
Result
# A tibble: 12 x 3
# Groups: Var1 [3]
Var1 Var2 Target
<fctr> <int> <chr>
1 A 0 no
2 A 250 no
3 A 0 si
4 A 0 si
5 B 0 no
6 B 0 no
7 B 0 no
8 B 250 no
9 C 0 no
10 C 250 no
11 C 0 si
12 C 250 no
Explanation
We use dplyr to group df by the levels of Var1, then for each group cumsum(lag(Var2, default=0) == 250) > 0 tells us for every row in that group if any previous observations of Var2 within that group were 250 and Var2 == 0 tells us if the current observation of Var2 is 0. If both of those conditions are TRUE, we code Target as "si", otherwise we code it as "no"
Data
The data I started with for df are
structure(list(Var1 = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 3L, 3L, 3L, 3L), .Label = c("A", "B", "C"), class = "factor"),
Var2 = c(0L, 250L, 0L, 0L, 0L, 0L, 0L, 250L, 0L, 250L, 0L,
250L)), .Names = c("Var1", "Var2"), row.names = c(NA, -12L
), class = "data.frame")
Comparison to akrun's Solution
The output of arkun's solution is below so you can determine which approach is more appropriate for your problem.
# A tibble: 12 x 3
# Groups: Var1 [3]
Var1 Var2 Target
<fctr> <int> <chr>
1 A 0 si
2 A 250 no
3 A 0 no
4 A 0 no
5 B 0 no
6 B 0 no
7 B 0 si
8 B 250 no
9 C 0 si
10 C 250 no
11 C 0 si
12 C 250 no

Answer 2

We can use dplyr
library(dplyr)
df1 %>%
group_by(Var1) %>%
mutate(Target = replace(Target, Var2==0 & lead(Var2, default = Var2[n()])==250, 'si'))