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What is the mean() method in R?

Salman Yousaf

Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

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, trim should be zero.
  • trim: Used to drop values from both sides of vector x before computing the mean. The default value is 0.
  • na.rm: A boolean field that can be set to TRUE to remove NA(Not Available) values before computing the mean. The default value is False.

Return value

mean() returns a numeric or complex vector with length one or NA_real_.

Calculating the mean of table data

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 numbers
mean_value <- mean(x,trim = 0)
typeof(mean_value)
# Printing results
cat("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 = 0.2
mean_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)

RELATED TAGS

r
communitycreator

Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

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