rowSums(): Calculating the Sum of Rows of a Matrix or Data Frame in R

The rowSums() function calculates the sum of values in each numeric row of a matrix, array, or data frame.

It quickly sums up data across rows without having to write loops, making it faster and more memory-efficient than manual iteration.

In the above figure, we showed the sum of each row in a data frame using the rowSums() function. 

# Create a data frame.
df <- data.frame(
  col1 = c(1, 2, 3),
  col2 = c(4, 5, 6),
  col3 = c(7, 8, 9)
)

# Calculate the row sums.
rowSums(df)


# Output: [1] 12 15 18

The sum of the first row is 12.

The sum of the second row is 15.

The sum of the third row is 18.

Syntax

rowSums(x, na.rm = FALSE, dims = 1)) 

Parameters

Handling NA values

If the row contains an NA value, the output will be NA because it does not know what NA means. So, it returns NA.

# Create a data frame.
df <- data.frame(
  col1 = c(NA, 2, 3),
  col2 = c(4, NA, 6),
  col3 = c(7, 8, NA)
)

# Calculate the row sums.
rowSums(df)

# Output: [1] NA  NA  NA

To ignore the NA values in a data frame and calculate the sum of the remaining values of rows, pass the na.rm = TRUE.

# Create a data frame.
df <- data.frame(
  col1 = c(NA, 2, 3),
  col2 = c(4, NA, 6),
  col3 = c(7, 8, NA)
)

# Calculate the row sums.
rowSums(df, na.rm = TRUE)

# Output: [1] 11  10  9

In the first row, it only adds 4 + 7 and ignores NA. So, the output is 11.

The same thing happened with the second row. It only counts 2 and 8, and their sum is 10.

Working with specific rows of a data frame

You can use indexing to select the specific rows for summation. Pass those selections to the rowSums() function. Let’s say I want the sum of row 1 and the sum of row 2.

# Create a data frame.
df <- data.frame(
  col1 = c(NA, 2, 3),
  col2 = c(4, NA, 6),
  col3 = c(7, 8, NA)
)

# Calculate the row sums.
rowSums(df[c(1, 2), ], na.rm = TRUE)

# Output:
#  1    2
# 11   10

Matrix

In a matrix, there are rows and columns, and rowSums() only focus on rows. If you pass the whole matrix to this function, it will return a vector with the sum of each row.

rv <- rep(1:9)

mtrx <- matrix(rv, 3, 3)
mtrx

cat("The sum of rows is: ", "\n")
rowSums(mtrx)

For other types of row-wise operations (like concatenation of strings), you would use different functions or approaches.

Multi-Dimensional Array

Let’s take a multi-dimensional array as input and find the sum of rows based on dimensions.

arr <- array(1:24, dim = c(2, 3, 4))

rowSums(arr, dims = 1)

# Output: [1] 144 156

rowSums(arr, dims = 2)

# Output:
#      [,1]  [,2]  [,3]
# [1,]  40   48     56
# [2,]  44   52     60

In this code:

1. dims=1: It is a 2×1 matrix with sums over the 3×4 plane per row.
   
2. dims=2: It is a 2×3 matrix with sums over the 4 layers per row-column.

Empty input

What if the input matrix or data frame is empty? Well, in that case, it returns numeric(0) (empty numeric vector).

empty_vec <- matrix(numeric(0), nrow = 0, ncol = 3)

rowSums(empty_vec)

# Output: numeric(0)

Non-numeric columns

The rowSums() function can only operate on numeric columns. If your input data frame contains character columns, it will throw this error: ‘x’ must be numeric.

df <- data.frame(a = c(1, 2), b = c("A", "B")) # Mixed types

rowSums(df)

# Output:
# Error in rowSums(df) : 'x' must be numeric
# Execution halted

Ensure that the input rows are numeric to prevent this type of error, or convert to numeric if compatible.

That’s it!