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
#> 12 23 34 43 51 59 65 78 87 100
pcumsum(tbl)
#> df
#> 1 2 3 4 5 6 7 8 9 10
#> 0 12 23 34 43 51 59 65 78 87
rcumsum(tbl)
#> 1 2 3 4 5 6 7 8 9 10
#> 100 88 77 66 57 49 41 35 22 13
## 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] 4 17 26 38 47 54 73 82 93 100
pcumsum(tbl)
#> [1] 0 4 17 26 38 47 54 73 82 93
rcumsum(tbl)
#> [1] 100 96 83 74 62 53 46 27 18 7