Compute the Sum of Rows of a Matrix or Array – rowSums Function

rowSums Function in detail

The rowSums() function in R is used to compute the sum of rows in a matrix, array, or data frame. It is particularly useful when dealing with large datasets where row-wise summation is required.

Syntax:

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

Parameters:

• x: A matrix, array, or data frame.
• na.rm: A logical argument. If set to TRUE, it removes missing values (NA) before calculating the sum. Default is FALSE.
• dims: An integer specifying the dimensions regarded as ‘rows’ to sum over. It applies summation over dims+1, dims+2, ...

Compute the Sum of Rows of a Matrix in R

Let’s create a matrix and use rowSums() to calculate the sum of its rows.

Example:

# Creating a matrix
mat <- matrix(c(3, 6, 9, 4, 7, 10, 5, 8, 11), nrow = 3, byrow = TRUE)

# Display the matrix
print("Matrix:")
print(mat)

# Compute row-wise sums
row_sums <- rowSums(mat)

# Print row sums
print("Row Sums:")
print(row_sums)

Output:

[1] "Matrix:"
     [,1] [,2] [,3]
[1,]    3    6    9
[2,]    4    7   10
[3,]    5    8   11

[1] "Row Sums:"
[1] 18 21 24

Compute the Sum of Rows of an Array in R

Now, let’s create a 3D array and use rowSums() to calculate row-wise summation.

Example:

# Creating a 3D array
arr <- array(1:12, dim = c(2, 3, 2))

# Display the array
print("Array:")
print(arr)

# Compute row-wise sums across specified dimensions
row_sums <- rowSums(arr, dims = 1)

# Print row sums
print("Row Sums:")
print(row_sums)

Output:

[1] "Array:"
,,1
     [,1] [,2] [,3]
[1,]    1    3    5
[2,]    2    4    6

,,2
     [,1] [,2] [,3]
[1,]    7    9   11
[2,]    8   10   12

[1] "Row Sums:"
[1] 42 48

Compute the Sum of Rows of a Data Frame in R

Now, let’s compute the row sums of a data frame with numerical values.

Example:

# Creating a data frame
df <- data.frame(
  ID = c(101, 102, 103),
  Score1 = c(12, 18, 24),
  Score2 = c(8, 14, 22)
)

# Display the data frame
print("Data Frame:")
print(df)

# Compute row-wise sums
row_sums <- rowSums(df[, c("Score1", "Score2")])

# Print row sums
print("Row Sums:")
print(row_sums)

Output:

[1] "Data Frame:"
   ID Score1 Score2
1 101     12      8
2 102     18     14
3 103     24     22

[1] "Row Sums:"
[1] 20 32 46

Use rowSums() with NA Values in a Data Frame

Now, let’s create a dataset containing missing values and compute row sums while treating NA values as zero.

Example:

# Creating a data frame with missing values
df_na <- data.frame(
  ID = c(201, 202, 203),
  Score1 = c(10, NA, 28),
  Score2 = c(6, 14, NA)
)

# Display the data frame with missing values
print("Data Frame with Missing Values:")
print(df_na)

# Compute row-wise sums while ignoring NA values
row_sums <- rowSums(df_na[, c("Score1", "Score2")], na.rm = TRUE)

# Print row sums
print("Row Sums:")
print(row_sums)

Output:

[1] "Data Frame with Missing Values:"
   ID Score1 Score2
1 201     10      6
2 202     NA     14
3 203     28     NA

[1] "Row Sums:"
[1] 16 14 28

We use the argument na.rm = TRUE in rowSums() to treat missing values as zero during summation.

Use rowSums() with Specific Columns in a Data Frame

We can also select specific columns from a data frame and compute their row-wise sum.

Example:

# Creating a data frame with missing values
df_selected <- data.frame(
  ID = c(301, 302, 303),
  Exam1 = c(15, NA, 26),
  Exam2 = c(9, 17, NA),
  Exam3 = c(NA, 20, 7),
  Exam4 = c(18, 25, NA)
)

# Display the original data frame
print("Data Frame with Missing Values:")
print(df_selected)

# Compute row-wise sums for specific columns while ignoring NA values
row_sums <- rowSums(df_selected[, c("Exam2", "Exam4")], na.rm = TRUE)

# Print row sums
print("Row Sums:")
print(row_sums)

Output:

[1] "Data Frame with Missing Values:"
   ID Exam1 Exam2 Exam3 Exam4
1 301    15     9    NA    18
2 302    NA    17    20    25
3 303    26    NA     7    NA

[1] "Row Sums:"
[1] 27 42  0