colMeans(): Calculating the Mean of Columns in R Data Frame

The colMeans() function in R calculates the arithmetic mean of columns in a numeric matrix, data frame, or array. It efficiently calculates the average value for each column by summing the elements and dividing by the number of elements (or non-missing elements if specified).

In the above figure, we defined an input data frame, df, that contains three columns.

The colMeans() function accepts the whole data frame and returns a column-wise mean.

Here is the program that demonstrates the above figure:

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

# Calculating the mean of every columns.
colMeans(df)

#  Output:
#  col1    col2    col3
#    2       5      8

Syntax

colMeans(x, na.rm = FALSE)

Parameters

Mean of each column and exclude NA values

What if a data frame contains NA values, and we try to calculate the mean of every column?

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

# Calculate the mean of every columns.
colMeans(df)

#  Output:
#  col1  col2   col3
#   NA    NA     NA

We obtained the output ‘NA’ for every column, as shown in the above figure and code, because ‘NA’ represents a missing value.

To ignore NA values in a data frame, you need to pass 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 mean of every columns.
colMeans(df, na.rm = TRUE)

# Output:
#  col1   col2   col3
#  2.5    5.0    7.5

Calculating the mean of specific columns

You can calculate the mean of specific columns based on your requirement by passing the column’s index.

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

# Calculate the mean col1 and col3
colMeans(df[c("col1", "col3")])

#  Output:
#  col1    col3
#    2      8

For row-wise means, you can use the rowMeans() function.

With a Matrix

A matrix contains rows and columns, and we are only interested in the columns. It works the same as it did with a data frame.

mat <- matrix(1:6,
  nrow = 2, ncol = 3,
  dimnames = list(NULL, c("A", "B", "C"))
)

colMeans(mat)

# Output:
#  A   B   C
#  3   4   5

And it returns the mean of each column.

Matrix with a single element

If the input matrix contains a single element, it returns that element as a mean because there is nothing to compute against. Mean of a single value is that value only.

single_mat <- matrix(5)

colMeans(single_mat)

# Output: 5

That’s all!