How to Create a Covariance Matrix for R Data Frame

To create a covariance matrix for a data frame in R, you can use the cov() function. A covariance matrix is a table that shows the covariance between pairs of variables in a data set.

In this article, we will explore how to create a covariance matrix for an R data frame using the cov() function.

Method: Use cov() Function

The cov() function in R is used to calculate the covariance matrix for a data frame. Here’s the syntax:

cov(df)

The following example shows how to create a covariance matrix in R using the cov() function.

Create Covariance Matrix for R Data Frame Using cov() Function

Let’s see how we can use the cov() function to create a covariance matrix in R:

# Create data frame
df <- data.frame(Value = c(108, 120, 135, 95, 98, 105),
                 Reading = c(110, 97, 91, 89, 80, 85))

# Create covariance matrix
matrix <- cov(df)

# Print covariance matrix
print(matrix)

Output: 👇️

            Value   Reading
Value    186.5667  172.5667
Reading  172.5667  178.5667

In this example, the cov() function calculates the covariance matrix for the Value and Reading columns of the data frame.