I have a dataset with many different social media creators (creator_id). They posted many times (posting_count) and the posts are classified as ad if ad = 1. Now I always want to classify the 3 previous postings before ad = 1 as 1. Basically the "goal_variable" is what I want to get. A solution without a loop would be cool!!
creator_id <-c("aaa","aaa","aaa","aaa","aaa","aaa","aaa","aaa","bbb","bbb","bbb","bbb","bbb","bbb","bbb","bbb","bbb")
posting_count <- c(143,144,145,146,147,148,149,150,90,91,92,93,94,95,96,97,98)
ad <- c(0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,1)
goal_variable <- c(0,0,0,1,1,1,0,0,0,0,0,1,1,1,1,1,0)
df <- cbind(creator_id, posting_count, ad, goal_variable)
Here's a programmatical way using map. Basically, for each row, checking whether the current row is between 3 and 1 positions before the closest ad == 1.
library(purrr)
library(dplyr)
df %>%
group_by(creator_id) %>%
mutate(goal_variable = map_int(row_number(), ~ any((.x - which(ad == 1)) %in% -3:-1)))
output
# A tibble: 17 × 4
# Groups: creator_id [2]
creator_id posting_count ad goal_variable
<chr> <dbl> <dbl> <int>
1 aaa 143 0 0
2 aaa 144 0 0
3 aaa 145 0 0
4 aaa 146 0 1
5 aaa 147 0 1
6 aaa 148 0 1
7 aaa 149 1 0
8 aaa 150 0 0
9 bbb 90 0 0
10 bbb 91 0 0
11 bbb 92 0 0
12 bbb 93 0 1
13 bbb 94 0 1
14 bbb 95 0 1
15 bbb 96 1 1
16 bbb 97 0 1
17 bbb 98 1 0