Calculate mean after last time of specific column specification - r

Question

example.df <- data.frame(GY = sample(300:600, 200, replace = T), sacc
= rep("f", each = 100), trial.number = rep(1:2,
each = 100), stringsAsFactors = F)
example.df$sacc[50:70] <- "s"
example.df$sacc[164:170] <- "s"
I have data looking similar to this. I would like to calculate the mean of GY after the last appearance of "s" for all the rest of the values of GY where sacc is f. In this example I could ofcourse just average on index number 71:100, however in the real data this isn't the case.
What I tried after the comment of Ronak (thanks!):
library(dplyr)
example.df %>%
group_by(trial.number) %>%
summarise(mean_tr = mean(GY[(max(which(sacc == "s")) + 1) : n()]))
%>%
data.frame()
I cant get it to work. Can someone help me out ? My original data.frame is 70k rows, an consists of a lot of variables. class = data.frame.

Answer 1

Update
As we need to do this by group, we can split it on trial.number and then apply the same operation to each group.
sapply(split(example.df, example.df$trial.number), function(x)
mean(x$GY[(max(which(x$sacc == "s")) + 1) : nrow(x)]))
# 1 2
#446.2333 471.7000
The same using dplyr could be achieved by
library(dplyr)
example.df %>%
group_by(trial.number) %>%
summarise(mean_tr = mean(GY[(max(which(sacc == "s")) + 1) : n()])) %>%
data.frame()
# trial.number mean_tr
#1 1 446.2333
#2 2 471.7000
Confirming again,
mean(example.df$GY[71:100])
#[1] 446.2333
mean(example.df$GY[171:200])
#[1] 471.7
Original Answer
We could do
mean(example.df$GY[(max(which(example.df$sacc == "s")) + 1) : nrow(example.df)])
#[1] 443.6667
Here, we first get all the indices where sacc is "s" then take max of it to get last occurrence. We get the mean of GY values from that index to end of the dataframe (nrow(example.df)).
To confirm,
mean(example.df$GY[71:100])
#[1] 443.6667