I'm working right now at Forex project and I found a problem on my way. I'm trying to find when was the last time when current value was this high or this low.
At the beginning I was trying to do that this way:
length(c(1:10)) - max(which(c(1:10) <= 6))
i.e. if we consider vector c(1:10,6) the output of the function above would be 4. Which would mean that 6 is the highest value since 4 intervals.
So my goal now was to implement above function into dplyr::mutate method. That's where things got out of hand... With the runner function from runner package I was able to create tibble with values and their lags:
# A tibble: 11 x 2
value `runner(value, lag = 1)`
<dbl> <list>
1 9 <dbl [0]>
2 7 <dbl [1]>
3 4 <dbl [2]>
4 1 <dbl [3]>
5 5 <dbl [4]>
6 2 <dbl [5]>
7 5 <dbl [6]>
8 4 <dbl [7]>
9 1 <dbl [8]>
10 6 <dbl [9]>
11 6 <dbl [10]>
But then no matter what I have tried I can't relate value number at current list to a runner column. I was trying things like purrr:map or sapply but is still would refer to whole column. I also trying to implement dplyr::rowWise but it didn't help me either.
I feel like I am going around the solution and that it can clearly be done easily. If there is some magic package that would help me to solve my issue quickly I would be more than thankful for help. But I would still like to know if there is a way to relate in that kind of situation to the current row value instead of whole column.
I was also trying to close this into one tidy user made function so that would be another plus if you could point me in that direction.
I have found the solution thanks to the @allan-cameron 's answer:
last_below <- function(x) {
sapply(
seq(x),
function(i) {
(i - tail(which(x[0:(i-1)] <= x[i]),1))[1]
}
)
}
By calling:
a %>%
mutate(b = last_below(value))
I get the output:
# A tibble: 11 x 2
value b
<dbl> <int>
1 9 NA
2 7 NA
3 4 NA
4 1 NA
5 5 1
6 2 2
7 5 1
8 4 2
9 1 5
10 6 1
11 6 1