I have the same question as this post, but I want to use dplyr
:
With an R dataframe, eg:
df <- data.frame(id = rep(1:3, each = 5)
, hour = rep(1:5, 3)
, value = sample(1:15))
how do I add a cumulative sum column that matches the id?
Without dplyr
the accepted solution of the previous post is:
df$csum <- ave(df$value, df$id, FUN=cumsum)
Like this?
df <- data.frame(id = rep(1:3, each = 5),
hour = rep(1:5, 3),
value = sample(1:15))
mutate(group_by(df,id), cumsum=cumsum(value))
Or if you use the dplyr
's piping operator:
df %>% group_by(id) %>% mutate(cumsum = cumsum(value))
Result in both cases:
Source: local data frame [15 x 4]
Groups: id
id hour value cumsum
1 1 1 4 4
2 1 2 14 18
3 1 3 8 26
4 1 4 2 28
5 1 5 3 31
6 2 1 10 10
7 2 2 7 17
8 2 3 5 22
9 2 4 12 34
10 2 5 9 43
11 3 1 6 6
12 3 2 15 21
13 3 3 1 22
14 3 4 13 35
15 3 5 11 46