| rowsum {base} | R Documentation |
Compute sums across rows of a matrix-like object for each level of a grouping
variable. rowsum is generic, with methods for matrices and data
frames.
rowsum(x, group, reorder = TRUE, ...)
x |
a matrix, data frame or vector of numeric data. Missing values are allowed. |
group |
a vector giving the grouping, with one element per row of
x. Missing values will be treated as another group and a
warning will be given |
reorder |
if TRUE, then the result will be in order of
sort(unique(group)), if FALSE, it will be in the order
that rows were encountered. |
... |
other arguments for future methods |
The default is to reorder the rows to agree with tapply as in
the example below. Reordering should not add noticeably to the time
except when there are very many distinct values of group and
x has few columns.
The original function was written by Terry Therneau, but this is a new implementation using hashing that is much faster for large matrices.
To add all the rows of a matrix (ie, a single group) use
rowSums, which should be even faster.
a matrix or data frame containing the sums. There will be one row per
unique value of group.
x <- matrix(runif(100), ncol=5) group <- sample(1:8, 20, TRUE) xsum <- rowsum(x, group) ## Slower versions xsum2 <- tapply(x, list(group[row(x)], col(x)), sum) xsum3<- aggregate(x,list(group),sum)