R previous week total [duplicate] - r

Question

This question already has an answer here:
Aggregate by week in R
(1 answer)
Closed 7 years ago.
I have Date (column B) and Total (column A) variables - how can I create a new variable in R that sums the previous seven days' worth of Totals?
In Excel, I have the following formula:
=SUMIFS($A:$A,$B:$B, ">="&$B20-7,$B:$B,"<"&$B20)
and I just don't know how to convert this to work in R. Suggestions?

Answer 1

This will do it too, advanced, but short - essentially a one-liner.
# Initialze some data
date <- seq(as.Date("2001-01-01"),as.Date("2001-01-31"),"days")
tot <- trunc(rnorm(31,100,20))
df <- data.frame(date,tot)
# Now compute week sum by summing a subsetted df for each date
df$wktot <- sapply(df$date,function(x)sum(df[difftime(df$date,x,,"days") %in% 0:-6,]$tot))
Changed the variable names to match the posed problem.
It also handles the data in any order and multiple entries per day.
Edited to add comments and make it fit in a window.

Answer 2

If there is one total per day, this function may help:
rollSums <- function(totals, roll) {
res <- c()
for(i in 1:(length(totals)-roll)) {
res <- c(res, sum(totals[0:(roll-1)+i]))
}
res
}
df1
Total Date
1 3 2015-01-01
2 8 2015-01-01
3 4 2015-01-02
4 7 2015-01-03
5 6 2015-01-04
6 1 2015-01-04
7 10 2015-01-05
8 9 2015-01-06
9 2 2015-01-07
10 5 2015-01-08
rollSums(df1$Total, 3)
[1] 15 19 17 14 17 20 21
rollSums(df1$Total, 4)
[1] 22 25 18 24 26 22
It will take two arguments, the vector with the totals and how many days you'd like in each sum.
Data
dput(df1)
structure(list(Total = c(3L, 8L, 4L, 7L, 6L, 1L, 10L, 9L, 2L,
5L), Date = structure(c(16436, 16436, 16437, 16438, 16439, 16439,
16440, 16441, 16442, 16443), class = "Date")), .Names = c("Total",
"Date"), row.names = c(NA, -10L), class = "data.frame")
Update
In case you run into a situation with multiple values on the same day, here's a solution. Surprisingly, #MikeWise has a one-liner that can do all of this. See other answer.
grouped.roll <- function(DF, Values, Group, roll) {
totals <- eval(substitute(with(DF, tapply(Values, Group, sum))))
newsums <- rollSums(totals, roll)
data.frame(Group=names(totals), Sums=c(rep(NA, roll), newsums))
}
It uses the rollSums that I used earlier. It will spit out NAs until the desired day grouping begins. That may be the only advantage over the other answer. But they could easily edit that in, I'm sure. Just providing more options for reference.
grouped.roll(df1, Total, Date, 3)
Group Sums
1 2015-01-01 NA
2 2015-01-02 NA
3 2015-01-03 NA
4 2015-01-04 22
5 2015-01-05 18
6 2015-01-06 24
7 2015-01-07 26
8 2015-01-08 21