# [R] How do I do a conditional sum which only looks between certain date criteria

arun smartpink111 at yahoo.com
Fri Jun 6 05:09:29 CEST 2014

```Hi,
The expected output is confusing.
2013-01-01, x, 2
2013-01-02, x, 1
2013-01-03, x, 0
2013-01-04, x, 0
2013-01-05, x, 3
2013-01-06, x, 1
2013-01-01, y, 1
2013-01-02, y, 1
2013-01-03, y, 0
2013-01-04, y, 5
2013-01-05, y, 6

##Assuming that the data is ordered by date and no gaps in date
res1 <- unsplit(lapply(split(dat1, dat1\$user), function(x) {
indx <- (seq(nrow(x)) - 1)%/%3
x\$cum_items_bought_3_days <- ave(x\$items_bought, indx, FUN = cumsum)
x
}), dat1\$user)

##expected output
res2 <- unsplit(lapply(split(dat1, dat1\$user), function(x) {
indx <- (seq(nrow(x)) - 1)%/%3
x\$cum_items_bought_3_days <- ave(x\$items_bought, indx, FUN = cumsum)
indx2 <- seq(0, length(indx), by = 4)
x[indx2, 4] <- x[indx2, 4] + indx[indx2]
x
}), dat1\$user)

A.K.

Say I have data that looks like
date, user, items_bought
2013-01-01, x, 2
2013-01-02, x, 1
2013-01-03, x, 0
2013-01-04, x, 0
2013-01-05, x, 3
2013-01-06, x, 1
2013-01-01, y, 1
2013-01-02, y, 1
2013-01-03, y, 0
2013-01-04, y, 5
2013-01-05, y, 6
2013-01-06, y, 1

to get the cumulative sum per user per data point I was doing
data.frame(cum_items_bought=unlist(tapply(as.numeric(data\$items_bought), data\$user, FUN = cumsum)))

output from this looks like
date, user, items_bought
2013-01-01, x, 2
2013-01-02, x, 3
2013-01-03, x, 3
2013-01-04, x, 3
2013-01-05, x, 6
2013-01-06, x, 7
2013-01-01, y, 1
2013-01-02, y, 2
2013-01-03, y, 2
2013-01-04, y, 7
2013-01-05, y, 13
2013-01-06, y, 14

However I want to restrict my sum to only add up those that happened within 3 days of each row (relative to the user). i.e. the output needs to look like this:
date, user, cum_items_bought_3_days
2013-01-01, x, 2
2013-01-02, x, 3
2013-01-03, x, 3
2013-01-04, x, 1
2013-01-05, x, 3
2013-01-06, x, 4
2013-01-01, y, 1
2013-01-02, y, 2
2013-01-03, y, 2
2013-01-04, y, 6
2013-01-05, y, 11
2013-01-06, y, 12

```