With data frame:
df <- data.frame(id = rep(1:3, each = 5)
, hour = rep(1:5, 3)
, value = sample(1:15))
I want to add a cumulative sum column that matches the id
:
df
id hour value csum
1 1 1 7 7
2 1 2 9 16
3 1 3 15 31
4 1 4 11 42
5 1 5 14 56
6 2 1 10 10
7 2 2 2 12
8 2 3 5 17
9 2 4 6 23
10 2 5 4 27
11 3 1 1 1
12 3 2 13 14
13 3 3 8 22
14 3 4 3 25
15 3 5 12 37
How can I do this efficiently? Thanks!
df$csum <- ave(df$value, df$id, FUN=cumsum)
ave
is the "go-to" function if you want a by-group vector of equal length to an existing vector and it can be computed from those sub vectors alone. If you need by-group processing based on multiple "parallel" values, the base strategy is do.call(rbind, by(dfrm, grp, FUN))
.