sum - R previous week total -

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• aggregate week in r 1 answer

i have date (column b) , total (column a) variables - how can create new variable in r sums previous 7 days' worth of totals?

in excel, have following formula:

=sumifs($a:$a,$b:$b, ">="&$b20-7,$b:$b,"<"&$b20)

and don't know how convert work in r. suggestions?

if there 1 total per day, 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 take 2 arguments, vector totals , how many days you'd 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 run situation multiple values on same day, here's solution. surprisingly, @mikewise has one-liner can 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 rollsums used earlier. spit out nas until desired day grouping begins. may advantage on other answer. edit in, i'm sure. providing more options 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