Computes the prior-to (i.e., the cumulative sum prior to but not including the current value) or the reverse (i.e., the number that large or larger) cumulative sum of a vector. Also works for 1-dimensional tables, matrices, and data.frames, though it is best used with vectors.
Note
An NA in the vector causes all returned values at and after the first NA for pcumsum and at and before the last NA for rcumsum to be NA. See the examples.
Author
Derek H. Ogle, DerekOgle51@gmail.com
Examples
## Simple example
cbind(vals=1:10,
cum=cumsum(1:10),
pcum=pcumsum(1:10),
rcum=rcumsum(1:10))
#> vals cum pcum rcum
#> [1,] 1 1 0 55
#> [2,] 2 3 1 54
#> [3,] 3 6 3 52
#> [4,] 4 10 6 49
#> [5,] 5 15 10 45
#> [6,] 6 21 15 40
#> [7,] 7 28 21 34
#> [8,] 8 36 28 27
#> [9,] 9 45 36 19
#> [10,] 10 55 45 10
## Example with NA
vals <- c(1,2,NA,3)
cbind(vals,
cum=cumsum(vals),
pcum=pcumsum(vals),
rcum=rcumsum(vals))
#> vals cum pcum rcum
#> [1,] 1 1 0 NA
#> [2,] 2 3 1 NA
#> [3,] NA NA NA NA
#> [4,] 3 NA NA 3
## Example with NA
vals <- c(1,2,NA,3,NA,4)
cbind(vals,
cum=cumsum(vals),
pcum=pcumsum(vals),
rcum=rcumsum(vals))
#> vals cum pcum rcum
#> [1,] 1 1 0 NA
#> [2,] 2 3 1 NA
#> [3,] NA NA NA NA
#> [4,] 3 NA NA NA
#> [5,] NA NA NA NA
#> [6,] 4 NA NA 4
## Example with a matrix
mat <- matrix(c(1,2,3,4,5),nrow=1)
cumsum(mat)
#> [1] 1 3 6 10 15
pcumsum(mat)
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0 1 3 6 10
rcumsum(mat)
#> [1] 15 14 12 9 5
## Example with a table (must be 1-d)
df <- sample(1:10,100,replace=TRUE)
tbl <- table(df)
cumsum(tbl)
#> 1 2 3 4 5 6 7 8 9 10
#> 10 21 30 43 54 66 75 90 93 100
pcumsum(tbl)
#> df
#> 1 2 3 4 5 6 7 8 9 10
#> 0 10 21 30 43 54 66 75 90 93
rcumsum(tbl)
#> 1 2 3 4 5 6 7 8 9 10
#> 100 90 79 70 57 46 34 25 10 7
## Example with a data.frame (must be 1-d)
df <- sample(1:10,100,replace=TRUE)
tbl <- as.data.frame(table(df))[,-1]
cumsum(tbl)
#> [1] 11 23 41 50 59 71 77 84 95 100
pcumsum(tbl)
#> [1] 0 11 23 41 50 59 71 77 84 95
rcumsum(tbl)
#> [1] 100 89 77 59 50 41 29 23 16 5