I have a very basic question as I am relatively new to R. I was wondering how to add a value in a particular column to the previous one for each cross-sectional unit in my data separately. My data looks like this:
firm date value
A 1 10
A 2 15
A 3 20
A 4 0
B 1 0
B 2 1
B 3 5
B 4 10
C 1 3
C 2 2
C 3 10
C 4 1
D 1 7
D 2 3
D 3 6
D 4 9
And I want to achieve the data below. So I want to sum values for each cross-sectional unit incrementally.
firm date value cumulative value
A 1 10 10
A 2 15 25
A 3 20 45
A 4 0 45
B 1 0 0
B 2 1 1
B 3 5 6
B 4 10 16
C 1 3 3
C 2 2 5
C 3 10 15
C 4 1 16
D 1 7 7
D 2 3 10
D 3 6 16
D 4 9 25
Below is a reproducible example code. I tried lag() but couldn't figure out how to repeat it for each firm.
firm <- c("A","A","A","A","B","B","B","B","C","C","C", "C","D","D","D","D")
date <- c("1","2","3","4","1","2","3","4","1","2","3","4", "1", "2", "3", "4")
value <- c(10, 15, 20, 0, 0, 1, 5, 10, 3, 2, 10, 1, 7, 3, 6, 9)
data <- data.frame(firm = firm, date = date, value = value)
Does this work:
library(dplyr)
df %>% group_by(firm) %>% mutate(cumulative_value = cumsum(value))
# A tibble: 16 x 4
# Groups: firm [4]
firm date value cumulative_value
<chr> <int> <int> <int>
1 A 1 10 10
2 A 2 15 25
3 A 3 20 45
4 A 4 0 45
5 B 1 0 0
6 B 2 1 1
7 B 3 5 6
8 B 4 10 16
9 C 1 3 3
10 C 2 2 5
11 C 3 10 15
12 C 4 1 16
13 D 1 7 7
14 D 2 3 10
15 D 3 6 16
16 D 4 9 25