Analyse factorielle des correspondences

L?Analyse des correspondences (AFC) est r?alis?e en utilisant la fonction CA() [dans FactoMineR] et le jeu de donn?es housetasks [dans factoextra]:

# Installer et charger FactoMineR pour effectuer une CA
# install.packages("FactoMineR")
 library("FactoMineR")
 data("housetasks")
 res.ca <- CA(housetasks, graph = FALSE)

Extraire les r?sultats pour les variables colonnes

# r?sultats pour les variables de colonnes
col <- get_ca_col(res.ca)
col # afficher

Correspondence Analysis - Results for columns
 ===================================================
  Name       Description                   
1 "$coord"   "Coordinates for the columns" 
2 "$cos2"    "Cos2 for the columns"        
3 "$contrib" "contributions of the columns"
4 "$inertia" "Inertia of the columns"      

head(col$coord) # coordonn?es des colonnes

                  Dim 1      Dim 2       Dim 3
Wife        -0.83762154  0.3652207 -0.19991139
Alternating -0.06218462  0.2915938  0.84858939
Husband      1.16091847  0.6019199 -0.18885924
Jointly      0.14942609 -1.0265791 -0.04644302

head(col$cos2) # cos2 des colonnes

                  Dim 1     Dim 2       Dim 3
Wife        0.801875947 0.1524482 0.045675847
Alternating 0.004779897 0.1051016 0.890118521
Husband     0.772026244 0.2075420 0.020431728
Jointly     0.020705858 0.9772939 0.002000236

head(col$contrib) # contribution des colonnes

                Dim 1     Dim 2      Dim 3
Wife        44.462018 10.312237 10.8220753
Alternating  0.103739  2.782794 82.5492464
Husband     54.233879 17.786612  6.1331792
Jointly      1.200364 69.118357  0.4954991

Extraire les r?sultats pour les variables lignes

# r?sultats pour les variables lignes
row <- get_ca_row(res.ca)
row # print

Correspondence Analysis - Results for rows
 ===================================================
  Name       Description                
1 "$coord"   "Coordinates for the rows" 
2 "$cos2"    "Cos2 for the rows"        
3 "$contrib" "contributions of the rows"
4 "$inertia" "Inertia of the rows"      

head(row$coord) # coordonn?es des lignes

                Dim 1      Dim 2       Dim 3
Laundry    -0.9918368  0.4953220 -0.31672897
Main_meal  -0.8755855  0.4901092 -0.16406487
Dinner     -0.6925740  0.3081043 -0.20741377
Breakfeast -0.5086002  0.4528038  0.22040453
Tidying    -0.3938084 -0.4343444 -0.09421375
Dishes     -0.1889641 -0.4419662  0.26694926

head(row$cos2) # cos2 des lignes

               Dim 1     Dim 2      Dim 3
Laundry    0.7399874 0.1845521 0.07546047
Main_meal  0.7416028 0.2323593 0.02603787
Dinner     0.7766401 0.1537032 0.06965666
Breakfeast 0.5049433 0.4002300 0.09482670
Tidying    0.4398124 0.5350151 0.02517249
Dishes     0.1181178 0.6461525 0.23572969

head(row$contrib) # contributions des lignes

                Dim 1    Dim 2    Dim 3
Laundry    18.2867003 5.563891 7.968424
Main_meal  12.3888433 4.735523 1.858689
Dinner      5.4713982 1.321022 2.096926
Breakfeast  3.8249284 3.698613 3.069399
Tidying     1.9983518 2.965644 0.488734
Dishes      0.4261663 2.844117 3.634294

get_ca: extraire les r?sultats pour les lignes et colonnes ? la fois

 # Vous pouvez aussi utiliser la fonction get_ca()
 get_ca(res.ca, "row") # R?sultats pour les lignes

Correspondence Analysis - Results for rows
 ===================================================
  Name       Description                
1 "$coord"   "Coordinates for the rows" 
2 "$cos2"    "Cos2 for the rows"        
3 "$contrib" "contributions of the rows"
4 "$inertia" "Inertia of the rows"      

 get_ca(res.ca, "col") # R?sultats pour les colonnes

Correspondence Analysis - Results for columns
 ===================================================
  Name       Description                   
1 "$coord"   "Coordinates for the columns" 
2 "$cos2"    "Cos2 for the columns"        
3 "$contrib" "contributions of the columns"
4 "$inertia" "Inertia of the columns"