| colSums {base} | R Documentation |
Form Row and Column Sums and Means
Description
Form (generalized) row and column sums and means for numeric arrays (or data frames).
Usage
colSums (x, na.rm = FALSE, dims = 1)
rowSums (x, na.rm = FALSE, dims = 1)
colMeans(x, na.rm = FALSE, dims = 1)
rowMeans(x, na.rm = FALSE, dims = 1)
.colSums (x, m, n, na.rm = FALSE)
.rowSums (x, m, n, na.rm = FALSE)
.colMeans(x, m, n, na.rm = FALSE)
.rowMeans(x, m, n, na.rm = FALSE)
Arguments
x |
an array of two or more dimensions, containing numeric,
complex, integer or logical values, or a numeric data frame. For
|
na.rm |
logical. Should missing values (including |
dims |
integer number: Which dimensions are regarded as ‘rows’ or
‘columns’ to sum over. For |
m, n |
the dimensions of the matrix |
Details
These functions are equivalent to use of apply with
FUN = mean or FUN = sum with appropriate margins, but
are a lot faster. As they are written for speed, they blur over some
of the subtleties of NaN and NA. If na.rm =
FALSE and either NaN or NA appears in a sum, the
result will be one of NaN or NA, but which might be
platform-dependent.
Notice that omission of missing values is done on a per-column or
per-row basis, so column means may not be over the same set of rows,
and vice versa. To use only complete rows or columns, first select
them with na.omit or complete.cases
(possibly on the transpose of x).
The versions with an initial dot in the name (.colSums() etc)
are ‘bare-bones’ versions for use in programming: they apply
only to numeric (like) matrices and do not name the result.
Value
A numeric or complex array of suitable size, or a vector if the result
is one-dimensional. For the first four functions the dimnames
(or names for a vector result) are taken from the original
array.
If there are no values in a range to be summed over (after removing
missing values with na.rm = TRUE), that
component of the output is set to 0 (*Sums) or NaN
(*Means), consistent with sum and
mean.
See Also
Examples
## Compute row and column sums for a matrix:
x <- cbind(x1 = 3, x2 = c(4:1, 2:5))
rowSums(x); colSums(x)
dimnames(x)[[1]] <- letters[1:8]
rowSums(x); colSums(x); rowMeans(x); colMeans(x)
x[] <- as.integer(x)
rowSums(x); colSums(x)
x[] <- x < 3
rowSums(x); colSums(x)
x <- cbind(x1 = 3, x2 = c(4:1, 2:5))
x[3, ] <- NA; x[4, 2] <- NA
rowSums(x); colSums(x); rowMeans(x); colMeans(x)
rowSums(x, na.rm = TRUE); colSums(x, na.rm = TRUE)
rowMeans(x, na.rm = TRUE); colMeans(x, na.rm = TRUE)
## an array
dim(UCBAdmissions)
rowSums(UCBAdmissions); rowSums(UCBAdmissions, dims = 2)
colSums(UCBAdmissions); colSums(UCBAdmissions, dims = 2)
## complex case
x <- cbind(x1 = 3 + 2i, x2 = c(4:1, 2:5) - 5i)
x[3, ] <- NA; x[4, 2] <- NA
rowSums(x); colSums(x); rowMeans(x); colMeans(x)
rowSums(x, na.rm = TRUE); colSums(x, na.rm = TRUE)
rowMeans(x, na.rm = TRUE); colMeans(x, na.rm = TRUE)