Subtract previous year's from value from each grouped row in data frame

Question

I am trying to calculated the lagged difference (or actual increase) for data that has been inadvertently aggregated. Each successive year in the data includes values from t

Answer 1

Kind of hackish but keeping in place your wonderful Reduce you could add mock rows to your df for year 0:

mockRows <- data.frame(id = 1:5, value = 0, year = 0)
(df <- rbind(df, mockRows))
(df <- df[order(df$id, df$year), ])

(diffs <- lapply(split(df, df$id), function(x){diff(x$value)}))
(df <- df[df$year != 0,])

(df$actual <- Reduce(c, diffs)) # flatten the list of lists
df[order(as.numeric(rownames(df))),]

This is the output:

   id value year actual
1   1    21    3      5
2   2    26    3     16
3   3    26    3     14
4   4    26    3     10
5   5    29    3     14
6   1    16    2     10
7   2    10    2      5
8   3    12    2     10
9   4    16    2      7
10  5    15    2     13
11  1     6    1      6
12  2     5    1      5
13  3     2    1      2
14  4     9    1      9
15  5     2    1      2