Correlation in R

Correlation in R can be calculated using cor() function. In R, Cor() function is used to calculate correlation among vectors, Matrices and data frames.

Syntax for correlation function in R:

Correlation of vector in R:

# correlation of vectors in R
x <- c(0,1,1,2,3,5,8,13,21,34)
y <- log(x+1)
cor(x,y)

the above code calculates correlation coefficient of vectors x and y which results in the output

Which says that these two vectors are highly positively correlated

Correlation of vector in R with NA:

Note: Correlation in R cannot be calculated if values has NA. So use = “complete.obs”  neglects NAs while calculating correlation coefficient in R

# correlation in R : handling NA
x <- c(0,1,1,2,3,5,8,13,21,NA)
y <- log(x+1)
cor(x,y,use = "complete.obs")

so the output will be

Correlation matrix of data frame in R:

Lets use mtcars data frame to demonstrate example of correlation matrix in R. lets create a correlation matrix of mpg,cyl,display and hp against gear and carb.

# correlation matrix in R using mtcars dataframe
x <- mtcars[1:4]
y <- mtcars[10:11]
cor(x, y)

so the output will be a correlation matrix

Correlation of Matrix in R:

In the below example we have calculated correlation of matrices.

# correlation of Matrix in R
matA<-matrix(1:9,3,3)
matB<-matrix(c(10,11,12,15,16,20,21,26,28),3,3)
cor(matA,matB)

output will be a correlation matrix as shown below