Rolling sums for groups with uneven time gaps

Question

Here\'s the tweak to my previously posted question. Here\'s my data:

set.seed(3737)
DF2 = data.frame(user_id = c(rep(27, 7), rep(11, 7)),
            date = as.D         


        

Answer 1

Here is another idea with findInterval to minimize comparisons and operations. First define a function to accomodate the basic part ignoring the grouping. The following function computes the cumulative sum, and subtracts the cumulative sum at each position from the one at its respective past date:

ff = function(date, value, minus)
{
    cs = cumsum(value)  
    i = findInterval(date - minus, date, left.open = TRUE) 
    w = which(as.logical(i))
    i[w] = cs[i[w]]
    cs - i
}

And apply it by group:

do.call(rbind, 
        lapply(split(DF2, DF2$user_id), 
               function(x) data.frame(x, 
                         minus7 = ff(x$date, x$value, 7), 
                         minus14 = ff(x$date, x$value, 14))))
#      user_id       date value minus7 minus14
#11.8       11 2016-01-01   6.8    6.8     6.8
#11.9       11 2016-01-03  21.3   28.1    28.1
#11.10      11 2016-01-05  19.8   47.9    47.9
#11.11      11 2016-01-07  22.0   69.9    69.9
#11.12      11 2016-01-10  19.4   82.5    89.3
#11.13      11 2016-01-14  17.5   58.9   106.8
#11.14      11 2016-01-16  19.3   56.2   119.3
#27.1       27 2016-01-01  15.0   15.0    15.0
#27.2       27 2016-01-03  22.4   37.4    37.4
#27.3       27 2016-01-05  13.3   50.7    50.7
#27.4       27 2016-01-07  21.9   72.6    72.6
#27.5       27 2016-01-10  20.6   78.2    93.2
#27.6       27 2016-01-14  18.6   61.1   111.8
#27.7       27 2016-01-16  16.4   55.6   113.2

The above apply-by-group operation can, of course, be replaced by any method prefereable.