I am doing my best to learn R, and this is my first post on this forum.
I currently have a data frame with a populated vector "x" and an unpopulated vector "counter" as follows:
x <- c(NA,1,0,0,0,0,1,1,1,1,0,1)
df <- data.frame("x" = x, "counter" = 0)
x counter
1 NA 0
2 1 0
3 0 0
4 0 0
5 0 0
6 0 0
7 1 0
8 1 0
9 1 0
10 1 0
11 0 0
12 1 0
I am having a surprisingly difficult time trying to write code that will simply populate counter so that counter sums the cumulative, sequential 1s in x, but reverts back to zero when x is zero. Accordingly, I would like counter to calculate as follows per the above example:
x counter
1 NA NA
2 1 1
3 0 0
4 0 0
5 0 0
6 0 0
7 1 1
8 1 2
9 1 3
10 1 4
11 0 0
12 1 1
I have tried using lag() and ifelse(), both with and without for loops, but seem to be getting further and further away from a workable solution (while lag got me close, the figures were not calculating as expected....my ifelse and for loops eventually ended up with length 1 vectors of NA_real_, NA or 1). I have also considered cumsum - but not sure how to frame the range to just the 1s - and have searched and reviewed similar posts, for example How to add value to previous row if condition is met; however, I still cannot figure out what I would expect to be a very simple task.
Admittedly, I am at a low point in my early R learning curve and greatly appreciate any help and constructive feedback anyone from the community can provide. Thank you.
You can use :
library(dplyr)
df %>%
group_by(x1 = cumsum(replace(x, is.na(x), 0) == 0)) %>%
mutate(counter = (row_number() - 1) * x) %>%
ungroup %>%
select(-x1)
# x counter
# <dbl> <dbl>
# 1 NA NA
# 2 1 1
# 3 0 0
# 4 0 0
# 5 0 0
# 6 0 0
# 7 1 1
# 8 1 2
# 9 1 3
#10 1 4
#11 0 0
#12 1 1
Explaining the steps -
x1), replace NA in x with 0 and increment the group value by 1 (using cumsum) whenever x = 0.x. This multiplication is necessary because it will help to keep counter as 0 where x = 0 and counter as NA where x is NA.