Here is a course with videos that present Principal Component Analysis in a French way. Three videos present a course on PCA, highlighting the way to interpret the data. Then  you will find videos presenting the way to implement in FactoMineR, to deal with missing values in PCA thanks to the package missMDA and lastly a video to draw interactive graphs with Factoshiny. And finally you will see that the new package FactoInvestigate allows you to obtain automatically an interpretation of your PCA results.

With this course, you will be stand-alone to perform and interpret results obtain with PCA.

• Course
  1. Part 1: Introduction: data – practicalities
  2. Part 2: Studying individuals and variables
  3. Part 3: Interpretation aids
  4. Material on the course videos: the slides, the PCA_transcription
• Tutorial in R
  • PCA in practice with FactoMineR
  • Handling missing values in PCA with missMDA and FactoMineR
  • Interactive graphs with Factoshiny
• Automatic interpretation
  • The package FactoInvestigate allows you to obtain a first automatic description of your PCA results. Here is the automatic interpretation of the decathlon dataset (dataset used in the tutorial video). This automatic interpretation is simply obtained with the following lines of code:

    library(FactoMineR)
    data(decathlon)
    res=PCA(decathlon,quanti.sup=11:12,quali.sup=13,graph=F)
    library(FactoInvestigate)
    Investigate(res,document="pdf_document")

For more information, you can see the book blow. Here are some reviews on the book and a link to order the book.