Draw PCA Biplot & Loading Plot in R (Example) | Apply & Visualize Principal Component Analysis

How to perform a PCA and how to draw loading plots and biplots using R programming. Check out my comprehensive online course on Principal Component Analysis (PCA) – From Theory to Application in R for more details: https://statisticsglobe.com/online-co...

R code of this video:

install.packages("factoextra") # Install & load factoextra
library(factoextra)

data(iris) # Load iris data
head(iris) # Print first six rows

iris_pca ＜- prcomp(iris[, 1:4], # Perform PCA on numeric columns
scale = TRUE) # Scale the data before PCA

summary(iris_pca) # PCA summary statistics

fviz_pca_var(iris_pca, # Create loading plot
col.var = "contrib", # Color variables by contribution
repel = TRUE) # Prevent overlapping text labels

fviz_pca_biplot(iris_pca, # Create biplot
label = "var", # Label only the variables
habillage = iris$Species) # Color by groups

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