# Before loading the data, load the following packages
library(dplyr)
library(knitr)
library(kableExtra)
library(ggplot2)
# Load the data with the following commands
data("winesOf3Colors", package = "data4PCCAR")
# Define the colors for the plots
wineColors <- winesOf3Colors$winesDescriptors$color
wineColors <- as.character(recode(wineColors, red = 'indianred4', white = 'gold', rose = 'lightpink2'))The data for the wines of the 3 colors example are shown in the following tables for the 3 countries of origin: Argentina, Canada, and USA.
| origin | color | varietal | Price | Acidity | Alcohol | Sugar | Tannin | fruity | floral | vegetal | spicy | woody | sweet | astringent | acidic | hedonic | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| A1 | Argentina | red | merlot | 11 | 5.33 | 13.8 | 2.75 | 559 | 6 | 2 | 1 | 4 | 5 | 3 | 5 | 4 | 2 |
| A2 | Argentina | red | cabernet | 5 | 5.14 | 13.9 | 2.41 | 672 | 5 | 3 | 2 | 3 | 4 | 2 | 6 | 3 | 2 |
| A3 | Argentina | red | shiraz | 7 | 5.16 | 14.3 | 2.20 | 455 | 7 | 1 | 2 | 6 | 5 | 3 | 4 | 2 | 2 |
| A4 | Argentina | red | pinot | 16 | 4.37 | 13.5 | 3.00 | 348 | 5 | 3 | 2 | 2 | 4 | 1 | 3 | 4 | 4 |
| A5 | Argentina | white | chardonnay | 14 | 4.34 | 13.3 | 2.61 | 46 | 5 | 4 | 1 | 3 | 4 | 2 | 1 | 4 | 6 |
| A6 | Argentina | white | sauvignon | 8 | 6.60 | 13.3 | 3.17 | 54 | 7 | 5 | 6 | 1 | 1 | 4 | 1 | 5 | 8 |
| A7 | Argentina | white | riesling | 9 | 7.70 | 12.3 | 2.15 | 42 | 6 | 7 | 2 | 2 | 2 | 3 | 1 | 6 | 9 |
| A8 | Argentina | white | gewurzt | 11 | 6.70 | 12.5 | 2.51 | 51 | 5 | 8 | 2 | 1 | 1 | 4 | 1 | 4 | 9 |
| A9 | Argentina | rose | malbec | 4 | 6.50 | 13.0 | 7.24 | 84 | 8 | 4 | 3 | 2 | 2 | 6 | 2 | 3 | 8 |
| A10 | Argentina | rose | cabernet | 3 | 4.39 | 12.0 | 4.50 | 90 | 6 | 3 | 2 | 1 | 1 | 5 | 2 | 3 | 8 |
| A11 | Argentina | rose | pinot | 6 | 4.89 | 12.0 | 6.37 | 76 | 7 | 2 | 1 | 1 | 1 | 4 | 1 | 4 | 9 |
| A12 | Argentina | rose | syrah | 5 | 5.90 | 13.5 | 4.20 | 80 | 8 | 4 | 1 | 3 | 2 | 5 | 2 | 3 | 7 |
| origin | color | varietal | Price | Acidity | Alcohol | Sugar | Tannin | fruity | floral | vegetal | spicy | woody | sweet | astringent | acidic | hedonic | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| C1 | Canada | red | merlot | 20 | 7.42 | 14.9 | 2.1 | 483 | 5 | 3 | 2 | 3 | 4 | 3 | 4 | 4 | 3 |
| C2 | Canada | red | cabernet | 15 | 7.35 | 14.5 | 1.9 | 698 | 6 | 3 | 2 | 2 | 5 | 2 | 5 | 4 | 2 |
| C3 | Canada | red | shiraz | 20 | 7.50 | 14.5 | 1.5 | 413 | 6 | 2 | 3 | 4 | 3 | 3 | 5 | 1 | 2 |
| C4 | Canada | red | pinot | 25 | 5.70 | 13.3 | 1.7 | 320 | 4 | 2 | 3 | 1 | 3 | 2 | 4 | 4 | 4 |
| C5 | Canada | white | chardonnay | 20 | 6.00 | 13.5 | 3.0 | 35 | 4 | 3 | 2 | 1 | 3 | 2 | 2 | 3 | 5 |
| C6 | Canada | white | sauvignon | 15 | 7.50 | 12.0 | 3.5 | 40 | 8 | 4 | 3 | 2 | 1 | 3 | 1 | 4 | 8 |
| C7 | Canada | white | riesling | 15 | 7.00 | 11.9 | 3.4 | 48 | 7 | 5 | 1 | 1 | 3 | 3 | 1 | 7 | 8 |
| C8 | Canada | white | gewurzt | 18 | 6.30 | 13.9 | 2.8 | 39 | 6 | 5 | 2 | 2 | 2 | 3 | 2 | 5 | 6 |
| C9 | Canada | rose | malbec | 8 | 5.90 | 12.0 | 5.5 | 90 | 6 | 3 | 3 | 3 | 2 | 4 | 2 | 4 | 8 |
| C10 | Canada | rose | cabernet | 6 | 5.60 | 12.5 | 4.0 | 85 | 5 | 4 | 1 | 3 | 2 | 4 | 2 | 4 | 7 |
| C11 | Canada | rose | pinot | 9 | 6.20 | 13.0 | 6.0 | 75 | 5 | 3 | 2 | 1 | 2 | 3 | 2 | 3 | 7 |
| C12 | Canada | rose | syrah | 9 | 5.80 | 13.0 | 3.5 | 83 | 7 | 3 | 2 | 3 | 3 | 4 | 1 | 4 | 7 |
| origin | color | varietal | Price | Acidity | Alcohol | Sugar | Tannin | fruity | floral | vegetal | spicy | woody | sweet | astringent | acidic | hedonic | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| U1 | USA | red | merlot | 25 | 6.00 | 13.6 | 3.50 | 578 | 7 | 2 | 2 | 5 | 6 | 3 | 4 | 3 | 2 |
| U2 | USA | red | cabernet | 15 | 6.50 | 14.6 | 3.50 | 710 | 8 | 3 | 1 | 4 | 5 | 3 | 5 | 3 | 2 |
| U3 | USA | red | shiraz | 25 | 5.30 | 13.9 | 1.99 | 610 | 8 | 2 | 3 | 7 | 6 | 4 | 5 | 3 | 1 |
| U4 | USA | red | pinot | 28 | 6.10 | 14.0 | 0.00 | 340 | 6 | 3 | 2 | 2 | 5 | 2 | 4 | 4 | 2 |
| U5 | USA | white | chardonnay | 15 | 7.20 | 13.3 | 1.10 | 41 | 6 | 4 | 2 | 3 | 6 | 3 | 2 | 4 | 5 |
| U6 | USA | white | sauvignon | 8 | 7.20 | 13.5 | 1.00 | 50 | 6 | 5 | 5 | 1 | 2 | 4 | 2 | 4 | 7 |
| U7 | USA | white | riesling | 10 | 8.60 | 12.0 | 1.65 | 47 | 5 | 5 | 3 | 2 | 2 | 4 | 2 | 5 | 8 |
| U8 | USA | white | gewurzt | 20 | 9.60 | 12.0 | 0.00 | 45 | 6 | 6 | 3 | 2 | 2 | 4 | 2 | 3 | 8 |
| U9 | USA | rose | malbec | 3 | 6.20 | 12.5 | 4.00 | 84 | 8 | 2 | 1 | 4 | 3 | 5 | 2 | 4 | 7 |
| U10 | USA | rose | cabernet | 4 | 5.71 | 12.5 | 4.30 | 93 | 8 | 3 | 3 | 3 | 2 | 6 | 2 | 3 | 8 |
| U11 | USA | rose | pinot | 8 | 5.40 | 13.0 | 3.10 | 79 | 6 | 1 | 1 | 2 | 3 | 4 | 1 | 3 | 6 |
| U12 | USA | rose | syrah | 6 | 6.50 | 13.5 | 3.00 | 89 | 9 | 3 | 2 | 5 | 4 | 3 | 2 | 3 | 5 |
There are four types of variables in the data:
origin, color and varietal;Price;Acidity, Alcohol, Sugar, and Tannin;fruity, floral, vegetal, spicy, woody, sweet, astringent, and hedonic.
The illustrative (albeit fictitious) data used for this example come from a chapter by Hervé Abdi and Dominique Valentin: Multiple factor analysis. In N.J. Salkind (Ed.): Encyclopedia of Measurement and Statistics. Thousand Oaks (CA): Sage. pp. 657—663. This chapter can be downloaded from the home page of Hervé Abdi: (look for number C40) or directly here).
In this example, three different assessors (named e1, e2, and e3) evaluated 6 wines on a 9-point scale using their own descriptors:
| Assessor | Descriptors |
|---|---|
| e1 | fruity, woody, coffee |
| e2 | red.fruit, roasted, vanillin, woody |
| e3 | fruity, butter, woody |
The scores are presented in the following table.
data('wines2007', package = "ExPosition")
# your data (a concatenated data tables)
# Have a look at the table:
wines2007$data| e1.fruity | e1.woody | e1.coffee | e2.red.fruit | e2.roasted | e2.vanillin | e2.woody | e3.fruity | e3.butter | e3.woody | |
|---|---|---|---|---|---|---|---|---|---|---|
| W1 | 1 | 6 | 7 | 2 | 5 | 7 | 6 | 3 | 6 | 7 |
| W2 | 5 | 3 | 2 | 4 | 4 | 4 | 2 | 4 | 4 | 3 |
| W3 | 6 | 1 | 1 | 5 | 2 | 1 | 1 | 7 | 1 | 1 |
| W4 | 7 | 1 | 2 | 7 | 2 | 1 | 2 | 2 | 2 | 2 |
| W5 | 2 | 5 | 4 | 3 | 5 | 6 | 5 | 2 | 6 | 6 |
| W6 | 3 | 4 | 4 | 3 | 5 | 4 | 5 | 1 | 7 | 5 |