how to cumulatively add values in one vector in R

Question

I have a data set that looks like this

id  name    year    job    job2
1   Jane    1980    Worker  0
1   Jane    1981    Manager 1
1   Jane    1982    Manager 1
1   Jane    1983    Manager 1
1   Jane    1984    Manager 1
1   Jane    1985    Manager 1
1   Jane    1986    Boss    0
1   Jane    1987    Boss    0
2   Bob     1985    Worker  0
2   Bob     1986    Worker  0
2   Bob     1987    Manager 1
2   Bob     1988    Boss    0
2   Bob     1989    Boss    0
2   Bob     1990    Boss    0
2   Bob     1991    Boss    0
2   Bob     1992    Boss    0

Here, job2 denotes a dummy variable indicating whether a person was a Manager during that year or not. I want to do two things to this data set: first, I only want to preserve the row when the person became Boss for the first time. Second, I would like to see cumulative years a person worked as a Manager and store this information in the variable cumu_job2. Thus I would like to have:

id  name    year    job    job2 cumu_job2
1   Jane    1980    Worker  0   0
1   Jane    1981    Manager 1   1
1   Jane    1982    Manager 1   2
1   Jane    1983    Manager 1   3
1   Jane    1984    Manager 1   4
1   Jane    1985    Manager 1   5
1   Jane    1986    Boss    0   0
2   Bob     1985    Worker  0   0
2   Bob     1986    Worker  0   0
2   Bob     1987    Manager 1   1
2   Bob     1988    Boss    0   0

I have changed my examples and included the Worker position because this reflects more what I want to do with the original data set. The answers in this thread only works when there are only Managers and Boss in the data set - so any suggestions for making this work would be great. I'll be very much grateful!!

Answer 1

Here is the succinct dplyr solution for the same problem.

NOTE: Make sure that stringsAsFactors = FALSE while reading in the data.

library(dplyr)
dat %>%
  group_by(name, job) %>%
  filter(job != "Boss" | year == min(year)) %>%
  mutate(cumu_job2 = cumsum(job2))

Output:

   id name year     job job2 cumu_job2
1   1 Jane 1980  Worker    0         0
2   1 Jane 1981 Manager    1         1
3   1 Jane 1982 Manager    1         2
4   1 Jane 1983 Manager    1         3
5   1 Jane 1984 Manager    1         4
6   1 Jane 1985 Manager    1         5
7   1 Jane 1986    Boss    0         0
8   2  Bob 1985  Worker    0         0
9   2  Bob 1986  Worker    0         0
10  2  Bob 1987 Manager    1         1
11  2  Bob 1988    Boss    0         0

Explanation

1. Take the dataset
2. Group by name and job
3. Filter each group based on condition
4. Add cumu_job2 column.