I am trying to make bins based on a specific time interval and I want the bins to restart counting when the trial number changes. Here is sample data:
structure(list(Trial_Nr = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 2L, 2L), seconds = c(1, 1.25, 1.5, 1.75, 2, 2.25, 2.5, 2.75,
3, 3.25, 3.5, 3.75)), .Names = c("Trial_Nr", "seconds"), class = "data.frame", row.names = c(NA,
-12L))
Here is what the dataset looks like:
Trial_Nr seconds
1 1 1.00
2 1 1.25
3 1 1.50
4 1 1.75
5 1 2.00
6 1 2.25
7 2 2.50
8 2 2.75
9 2 3.00
10 2 3.25
11 2 3.50
12 2 3.75
My goal is to make .50 second bins within each trial number with the bins starting over at the start of a new trial. Just FYI: the real dataset has many more data points and the seconds column is not in equal intervals. This is my goal:
Trial_Nr seconds bin
1 1 1.00 1
2 1 1.25 1
3 1 1.50 2
4 1 1.75 2
5 1 2.00 3
6 1 2.25 3
7 2 2.50 1
8 2 2.75 1
9 2 3.00 2
10 2 3.25 2
11 2 3.50 3
12 2 3.75 3
I have tried the cut function and was able to cut by intervals, but I couldn't figure out how to account for the trial number. Thank you for all your help!
A simply tapply would do it:
myData$bin <- unlist(tapply(myData$seconds, myData$Trial_Nr, function(x) (x-min(x)) %/% 0.5 + 1))
> myData
Trial_Nr seconds bin
1 1 1.00 1
2 1 1.25 1
3 1 1.50 2
4 1 1.75 2
5 1 2.00 3
6 1 2.25 3
7 2 2.50 1
8 2 2.75 1
9 2 3.00 2
10 2 3.25 2
11 2 3.50 3
12 2 3.75 3
EDIT:
In case the trial_Nr is not ordered, tapply might mess up the order. Then you can simply do this step by step with split:
dat <- split(myData, myData$Trial_Nr)
dat <- lapply(dat, function(x) {x$bin <- (x$seconds-min(x$seconds)) %/% 0.5 + 1; x})
dat <- unsplit(dat, myData$Trial_Nr)