colSums {base} | R Documentation |

Form row and column sums and means for numeric arrays.

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)

`x` |
an array of two or more dimensions, containing numeric, complex, integer or logical values, or a numeric data frame. |

`na.rm` |
logical. Should missing values (including |

`dims` |
integer: Which dimensions are regarded as ‘rows’ or
‘columns’ to sum over. For |

`X` |
a numeric matrix. |

`m, n` |
the dimensions of X. |

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 are ‘bare-bones’ versions for use in programming: they apply only to numeric matrices and do not name the result.

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`

.

## 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)

[Package *base* version 3.0.0 Index]