During data analysis, you will often be asked to calculate the mean of one or more variables in a data frame. The R programming language provides the `colMeans()`

function that can help you with this requirement. Please read this article to learn about `colMeans`

in R and how to use it. Let’s go.

**What is the colMeans in R**?

The `colMeans()`

function in R calculates the average value of columns in a data frame or matrix.

The `colMeans()`

function returns a numeric vector containing the average value of each column.

**Syntax:**

`colMeans(dataframe[c(...)], na.rm)`

**Parameters:**

**dataframe[c(…)]**: several columns in a dataframe or numeric vector.**na.rm**: discard NA values. The default is FALSE.

**How to use the colMeans() function in R**?

Here we will give some examples to show how to use the `colMeans()`

function in practice.

**Mean of all columns**

Suppose we set the first parameter to the name of the matrix or data frame without selecting specific columns for that data frame. The `colMeans()`

function will return the means of all columns in the input object.

In the following example, we have a numeric matrix with 4 rows and 4 columns consisting of 16 integers from 1 to 16.

We will use the `colMeans()`

function to calculate the mean of all the columns of this matrix.

**Example:**

# Create a numeric matrix num_matrix <- matrix(1:16, nrow = 4) # Calculate the means of all columns cat("Means of all columns\n") means <- colMeans(num_matrix) means

**Output:**

```
Means of all columns
[1] 2.5 6.5 10.5 14.5
```

**Mean of specific columns**

If we use the `colMeans()`

function in a data frame with some non-numeric values, there will be an error. We must ensure that only columns with numeric values are selected to avoid errors.

We have a data frame that includes several students’ names and test scores.

In the following example, we will use the `colMeans()`

function to calculate the mean score of each subject for all students in the list.

**Example:**

# Create a data frame scores <- data.frame( Name = c( "Ali", "Beatriz", "Charles", "Diya", "Eric", "Fatima", "Gabriel", "Hanna" ), Math = c(54, 72, 68, 44, 26, 92, 88, 56), Biology = c(42, 70, NA, 34, 60, 84, 94, 42), English = c(44, 74, 82, 56, 62, 84, 68, 76), Physics = c(24, 36, 44, 38, 52, 28, 98, 46) ) # Calculate the means score of each subject for all students mean <- colMeans(scores[c("Math", "Biology", "English", "Physics")], na.rm = TRUE) # Returns the same result # mean <- colMeans(scores[c(2,3,4,5)], na.rm = TRUE) mean

**Output:**

```
Math Biology English Physics
62.50000 60.85714 68.25000 45.75000
```

The `na.rm`

parameter is set to `TRUE`

to ignore NA values.

**Summary**

So we have shared with you how to use `colMeans`

in R. You must make sure the input columns must be numeric, or else an error will occur. If the input contains NA values, set the `na.rm`

parameter to `TRUE`

. Thanks for reading.

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Hello, my name’s Bruce Warren. You can call me Bruce. I’m interested in programming languages, so I am here to share my knowledge of programming languages with you, especially knowledge of C, C++, Java, JS, PHP.

**Name of the university: **KMA

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**Programming Languages**: C, C++, Java, JS, PHP