Get % of variance explained by Principal Component Analysis

PCA_Variance_Explained.R

# Get % of variance explained by Principal Component Analysis

library(psych)

pca_variance_explained <- function(data, n_components) {
  pca <- psych::principal(data, n_components, rotate = "none")
  list(
    by_variable = colSums(cor(pca$scores, data)^2),
    total = summary(prcomp(data))$importance["Cumulative Proportion", paste0("PC", n_components)]
  )
}

# Example
data <- iris[, -5]
n_components <- 2
pca_variance_explained(data, n_components)
#> $by_variable
#> Sepal.Length  Sepal.Width Petal.Length  Petal.Width 
#>    0.9225986    0.9909193    0.9837300    0.9352804 
#> 
#> $total
#> [1] 0.97769