What is the mean() method in R?
The R programming language is used to perform statistical analysis. We can use built-in functions to accomplish our tasks. The mean() method is used to compute the arithmetic mean of the argument vector x. We can use the mean() method either column-wise or row-wise, depending on the logic of the program.
The mean is calculated by dividing the sum of all values by the total number of values in the dataset.
Syntax
The syntax of the mean() function to calculate the average of values of x is as follows:
mean(x, trim = 0, na.rm = FALSE,...)
Parameters
x: A vector of numeric, logical, date, or date-time values. For complex vectors,trimshould be zero.trim: Used to drop values from both sides of vectorxbefore computing the mean. The default value is 0.na.rm: A boolean field that can be set toTRUEto removeNA(Not Available) values before computing the mean. The default value isFalse.
Return value
mean() returns a numeric or complex vector with length one or NA_real_.
Code
In the code snippet below, we calculate the mean of vector x in line 5. In line 6, we return the return type.
# Create a vector.x <- c(6,14,6,14.2,18,2,63,-21,9,-5,-4)# Evaluate mean of numbersmean_value <- mean(x,trim = 0)typeof(mean_value)# Printing resultscat("Mean is:", mean_value)
The demo code below also calculates the mean of the vector x. trim = 0.2, which means it will drop two values (6,14) from the left and two values (-5,-4) from the right. Then mean() method will evaluate the arithmetic mean of the remaining values, (6,14.2,18,2,63,-21,9).
# Create a vector.x <- c(6,14,6,14.2,18,2,63,-21,9,-5,-4)# Find Mean with trim = 0.2mean_value <- mean(x,trim = 0.2)cat("Trimed Mean: ", mean_value)
In line 2, we have a vector of numeric values containing an NA value. The mean() method in line 4 will return NA. So, in line 7, we set na.rm= TRUE, which removes NA values, and compute the mean of the remaining values.
# Create a vector.x <- c(6,14,6,14.2,18,NA,2,63,-21,9,-5,-4)# Find mean.mean_value <- mean(x)cat("Wrong Output before: ", mean_value)# Find mean dropping NA values.mean_value <- mean(x,na.rm = TRUE)cat("\nAfter removing : ", mean_value)
