How to create a complex running calculation on an R data table - r

Question

I want to create a running calculation that includes logic to restart the running sum when the value is negative. Initially I have a data table or frame like below :
df <- data.frame(value1 = c(0,0,10,0,1,0,2,0)
, value2 = c(5,1,2,6,8,3,7,2))
value1 value2
0 5
0 1
10 2
0 6
1 8
0 3
2 7
0 2
I would like to take the cumulative sum of value2 subtracted by value1. However, if the new value is less than 0, then start the running calculation over.
i.e. end up with
value1 value2 newvalue
0 5 5
0 1 6
10 2 2
0 6 8
1 8 15
0 3 18
2 7 23
0 2 25
I tried multiple attempts with data.table and dplyr packages with no luck.
EDIT: Updated df to match the actual table shown.

Answer 1

I am sure there are other simpler ways to do this by tweaking cumsum or other such functions, but I came up with this basic loop to produce the desired output. Hope it helps !!
> df
GroupID value1 value2
1 1 0 5
2 1 0 1
3 1 10 2
4 2 0 6
5 2 1 8
6 3 0 3
7 3 2 7
8 3 0 2
for(i in 1:nrow(df)) {
if(i == 1) {
df$newvalue[i] <- df$value2[i]
} else {
df$newvalue[i] <- (df$newvalue[i-1] + df$value2[i]) - df$value1[i]
if(df$newvalue[i] < 0 | df$GroupID[i] != df$GroupID[i-1]) {
df$newvalue[i] <- df$value2[i]
}
}
}
> df
GroupID value1 value2 newvalue
1 1 0 5 5
2 1 0 1 6
3 1 10 2 2
4 2 0 6 6
5 2 1 8 13
6 3 0 3 3
7 3 2 7 8
8 3 0 2 10

Answer 2

I believe that explicitly looping through the data frame is the only solution for calculating this type of conditional cumulative sum. Sagar's solution was very helpful to me (I up-voted but do not have enough reputation points for it to count).
In my experience, new value needs to be initialized prior to starting the loop in order to work properly. Below is how I would approach this:
df$newvalue <- df$value2
for(i in 2:nrow(df)) {
if(df$GroupID[i] == df$GroupID[i-1]) {
df$newvalue[i] <- max(df$newvalue[i-1] + df$value2[i]) - df$value1[i], df$value2[i])
}
}