Say you have a list which tells you what is y at x. You intend to manipulate y based on certain condition of x.

For example, given

# here x = year, y = some value
(some_list <- list(
    "year1" = 60,
    "year2" = 70,
    "year3" = 75,
    "year4" = 80,
    "year5" = 100
))
## $year1
## [1] 60
## 
## $year2
## [1] 70
## 
## $year3
## [1] 75
## 
## $year4
## [1] 80
## 
## $year5
## [1] 100

What is the cumulative sum of y at year 1, 3, 5?

In R, it seems natural to do it in a data frame.

library(dplyr)

# first convert to data frame
df <- unlist(some_list) %>% as.data.frame()

# assign a column name
names(df) <- "y"

# calc cumulative sum
df %>% mutate(cum_y = cumsum(y))
##     y cum_y
## 1  60    60
## 2  70   130
## 3  75   205
## 4  80   285
## 5 100   385

There is another convenient way to complete the same job.

# what we have
some_list
## $year1
## [1] 60
## 
## $year2
## [1] 70
## 
## $year3
## [1] 75
## 
## $year4
## [1] 80
## 
## $year5
## [1] 100
# what we want
cum_x <- c(1, 3, 5)

library(purrr)

# essentially a double loop
map(cum_x, function(x) {
    # here 'map' extracts the component from list (x[1], x[2], ...)
    # and reduce using function 'sum'
    reduce(map(1:x, ~ some_list[[.x]]), sum)
})
## [[1]]
## [1] 60
## 
## [[2]]
## [1] 205
## 
## [[3]]
## [1] 385