In Class Ex 9 - Interactive Multivariate

Author

Cheng Chun Chieh

Published

June 15, 2024

Modified

June 19, 2024

Use of ScatterPlotMatrix

https://cran.r-project.org/web/packages/scatterPlotMatrix/vignettes/introduction-to-scatterplotmatrix.html

Using widgets instead of wrapping

Code 
pacman::p_load(scatterPlotMatrix, parallelPlot, cluster, factoextra, tidyverse)

We will be using the wine data from the hands on exercise.

Code 
wine <- read_csv("data/wine_quality.csv")
Code 
ggplot(data = wine,
       aes(x=type)) +
  geom_bar()

Code 
whitewine <- wine %>%
  filter(type== "white") %>%
  select (1:11)

These widgets usually need a special definition of the size of the container, i.e. width and height = 500 = pixels.

Code 
scatterPlotMatrix(whitewine,
                  corrPlotType = "Text",
                  distribType = 1,
                  width = 700,
                  height = 700)

Using the interactive tools - we can use visual inspection to check on the outliers. For example, here we can select the outlier and see that the point is outliers for other factors as well. Then we can choose to investigate further into the data. (Point 2782)

This package is available for use with Shiny - but need to read the documentation carefully. The code may be different, for example here: scatterPlotMatrixOutput and at the server end: renderScatterPlotMatrix, instead of the typical code in R.

Clustering

Code 
set.seed(1234)

gap.stat <- clusGap(whitewine, 
                    FUNcluster = kmeans, 
                    K.max = 8)

fviz_gap_stat(gap.stat)

Code 
set.seed(123)
kmeans4 <- kmeans(whitewine,4, nstart =25)

print(kmeans4)
K-means clustering with 4 clusters of sizes 757, 978, 1444, 1719

Cluster means:
  fixed acidity volatile acidity citric acid residual sugar  chlorides
1      6.981506        0.2965786   0.3563540       9.705878 0.05227081
2      6.805112        0.2759356   0.3168814       3.607822 0.04012781
3      6.908172        0.2776939   0.3455402       7.780852 0.04919668
4      6.782403        0.2719372   0.3247469       5.348342 0.04324549
  free sulfur dioxide total sulfur dioxide   density       pH sulphates
1            52.83421             206.8164 0.9965522 3.176975 0.5179392
2            20.52761              83.1411 0.9919192 3.175256 0.4707566
3            42.31129             160.3061 0.9951215 3.193996 0.4940651
4            30.11635             121.1963 0.9931958 3.195829 0.4847935
    alcohol
1  9.611471
2 11.233930
3 10.120392
4 10.833256

Clustering vector:
   [1] 3 4 2 1 1 2 4 3 4 4 2 4 2 3 3 4 2 2 3 4 2 2 4 3 4 1 3 4 4 4 4 2 2 4 3 4 3
  [38] 4 3 3 3 3 3 3 3 3 1 1 3 3 3 4 2 4 4 1 1 3 2 4 4 3 3 2 4 4 4 3 2 4 1 1 1 2
  [75] 2 4 2 2 4 4 4 3 3 1 3 3 3 1 3 3 3 1 4 4 3 1 3 2 2 3 1 3 3 3 1 4 3 3 3 1 3
 [112] 1 1 3 3 2 4 2 1 1 2 4 4 4 3 3 4 1 3 3 2 1 1 1 1 3 4 3 2 2 2 3 4 2 2 4 3 2
 [149] 2 4 3 3 4 2 2 1 1 4 4 4 4 3 2 1 1 3 1 2 3 4 4 2 2 4 3 3 2 3 4 3 3 1 3 1 1
 [186] 1 3 4 4 1 1 3 4 4 1 1 1 1 1 1 1 1 1 4 4 3 4 4 2 3 2 4 4 4 4 3 3 3 3 3 3 3
 [223] 4 3 4 3 1 1 1 3 4 1 1 1 1 1 1 1 4 3 1 2 2 1 3 1 4 2 2 4 1 1 3 4 3 3 2 2 4
 [260] 2 4 3 2 1 3 3 3 3 3 3 3 3 3 4 1 3 3 2 2 4 4 4 1 1 1 3 1 1 1 1 1 3 1 3 3 3
 [297] 3 1 3 4 2 2 2 3 3 3 3 3 4 3 2 3 3 3 3 4 4 4 4 2 2 4 4 4 1 1 1 3 1 2 4 4 2
 [334] 4 2 2 4 3 4 3 3 4 4 3 3 4 2 3 4 3 3 4 4 4 1 1 1 3 3 3 3 2 4 1 2 4 3 3 3 2
 [371] 3 3 1 3 2 2 4 2 3 4 2 3 3 3 4 2 4 1 4 1 1 2 4 2 3 3 2 4 3 2 4 3 4 1 3 3 4
 [408] 4 4 2 3 3 2 2 3 3 2 1 2 4 4 1 1 1 3 1 1 1 2 1 1 2 1 3 4 2 1 1 1 4 2 4 4 1
 [445] 3 2 3 4 4 4 3 4 3 4 4 4 2 4 1 1 4 3 3 2 3 4 3 2 3 1 3 1 2 4 4 1 4 4 3 3 3
 [482] 4 4 3 1 4 4 2 3 3 2 2 3 3 4 3 1 3 3 1 1 3 1 1 3 3 4 3 3 3 3 3 4 2 4 3 3 3
 [519] 2 2 4 4 2 2 2 4 2 4 4 4 4 3 3 3 3 3 3 3 2 1 3 1 3 3 3 3 3 2 4 1 3 2 4 3 4
 [556] 2 3 4 3 3 3 4 3 4 3 2 2 3 3 3 1 4 3 3 4 1 1 3 4 4 1 4 3 2 4 2 3 4 4 4 4 4
 [593] 3 4 4 4 3 4 4 2 3 4 4 4 4 4 3 3 3 2 4 2 4 4 4 4 2 1 1 4 1 3 4 2 4 4 3 1 1
 [630] 2 3 3 4 1 3 4 4 3 1 1 4 1 1 3 3 3 3 3 1 1 1 1 1 4 3 4 2 4 1 1 2 4 3 2 3 4
 [667] 1 3 3 1 1 2 3 4 1 1 1 2 2 2 3 3 3 3 3 1 4 1 1 4 4 1 1 3 1 1 2 1 1 1 1 4 2
 [704] 4 4 2 1 3 4 2 3 4 4 1 1 3 1 3 3 4 3 3 4 2 4 4 4 2 3 3 4 1 2 3 1 4 3 1 3 4
 [741] 2 2 4 3 3 4 1 3 3 3 3 3 3 1 4 4 3 3 3 4 3 3 1 4 3 4 1 2 4 4 4 3 3 3 4 4 2
 [778] 1 3 3 2 1 3 3 1 4 4 4 4 4 4 2 3 2 3 3 1 3 4 2 3 1 1 3 4 3 1 1 1 1 1 4 3 3
 [815] 1 4 2 4 4 4 2 1 4 4 2 3 3 4 2 2 4 3 4 2 4 4 3 3 3 4 4 3 3 4 4 4 3 2 3 4 4
 [852] 3 4 3 4 4 3 3 3 3 4 1 3 4 3 4 4 3 3 2 3 3 4 2 2 4 4 4 4 4 4 4 4 4 1 4 3 2
 [889] 3 2 3 4 4 4 4 2 1 2 2 1 3 4 1 1 3 2 2 4 3 1 4 4 4 2 2 2 4 4 4 4 3 3 3 1 3
 [926] 2 2 3 3 4 2 1 1 1 1 1 2 4 1 1 1 1 2 4 4 4 1 3 2 2 4 4 2 4 4 4 4 2 2 3 3 4
 [963] 3 4 3 2 1 3 2 2 2 4 3 2 4 4 4 1 3 2 2 3 2 2 3 4 3 3 3 4 3 2 1 2 3 3 2 3 3
[1000] 3 2 1 1 4 3 2 3 2 1 3 4 3 2 1 3 4 4 4 3 1 4 4 1 3 3 4 3 2 4 1 3 1 1 1 1 3
[1037] 2 2 4 2 4 2 4 1 2 2 4 2 2 4 3 4 2 4 2 4 4 1 4 3 4 1 1 1 3 4 3 4 2 3 3 4 4
[1074] 1 3 4 3 4 1 1 4 3 3 1 4 3 4 4 1 4 1 3 3 4 1 2 3 4 4 4 3 4 3 4 3 1 4 2 2 3
[1111] 2 2 3 2 2 2 2 1 2 4 4 4 2 4 4 3 3 2 2 4 3 4 3 4 4 3 3 3 4 2 2 3 4 4 4 1 3
[1148] 3 4 1 1 1 2 2 3 3 4 4 1 4 3 4 3 1 2 4 2 4 2 3 4 4 4 4 1 3 1 3 3 4 4 4 4 4
[1185] 4 1 3 4 3 2 4 4 4 4 1 3 4 4 4 2 2 2 1 2 2 1 3 1 4 4 2 3 3 2 2 3 2 1 4 2 1
[1222] 4 4 3 4 2 4 4 4 2 1 4 2 4 3 1 2 4 4 3 3 3 3 4 4 1 3 2 2 1 3 3 3 3 3 4 3 1
[1259] 1 1 1 3 3 1 2 3 4 3 4 1 3 4 3 4 1 4 3 4 4 3 4 3 3 3 3 4 3 4 4 2 2 1 2 2 2
[1296] 1 4 4 3 3 3 3 1 3 1 4 4 4 4 2 3 4 3 3 3 3 1 3 2 1 4 4 3 3 3 4 3 3 2 4 4 4
[1333] 1 3 4 1 3 1 1 4 4 3 4 3 3 4 3 3 3 2 4 4 1 1 3 3 1 3 4 4 3 1 4 2 3 4 2 4 1
[1370] 1 4 3 3 3 4 4 4 4 4 4 3 2 2 2 4 4 4 2 4 1 4 2 2 2 4 2 4 1 1 2 1 1 4 4 2 4
[1407] 2 2 1 4 2 2 3 4 4 2 4 1 4 4 4 2 4 1 4 4 4 3 2 2 4 2 2 2 3 2 1 2 1 1 3 4 4
[1444] 4 3 4 2 3 3 3 3 4 3 3 1 3 2 4 3 4 4 3 3 4 3 3 3 2 2 4 3 3 2 4 2 3 3 2 3 4
[1481] 3 4 1 2 4 4 2 3 1 1 4 2 1 3 1 1 2 4 2 3 4 3 4 4 4 4 1 3 3 4 4 4 4 3 4 4 3
[1518] 3 2 3 3 4 3 3 3 3 3 1 3 3 3 3 1 4 3 4 2 3 4 4 3 2 4 2 2 3 3 3 4 4 3 4 3 3
[1555] 3 3 3 3 4 2 3 4 4 3 4 4 3 4 1 3 3 1 3 4 4 1 2 4 3 1 4 2 4 3 1 3 3 1 3 4 3
[1592] 3 4 2 4 1 4 1 4 2 4 1 2 2 4 4 4 4 1 1 4 2 2 4 4 3 1 4 1 4 2 4 3 4 4 3 1 4
[1629] 4 2 4 4 4 4 1 4 3 3 1 4 3 3 4 3 4 3 3 2 2 3 4 1 4 3 3 4 2 3 1 1 1 1 4 3 3
[1666] 4 2 4 2 4 3 2 3 3 1 1 2 3 3 4 1 1 1 1 1 1 3 1 1 4 3 1 1 1 3 4 1 1 1 3 4 1
[1703] 4 3 3 4 3 3 3 3 2 4 3 4 4 3 4 4 3 2 3 1 3 3 4 3 2 1 4 4 4 1 4 4 1 3 2 1 2
[1740] 2 3 3 3 3 4 1 2 3 2 4 3 3 1 3 2 3 1 1 2 1 1 4 2 4 1 1 1 3 3 4 3 3 3 3 2 4
[1777] 3 3 3 3 3 1 3 2 4 3 4 3 4 1 3 4 3 1 4 3 4 4 3 3 1 2 3 3 1 4 4 1 4 1 3 4 2
[1814] 4 2 3 4 4 2 4 3 4 2 1 3 2 3 1 1 3 3 3 3 3 3 1 4 4 1 4 3 4 1 4 2 3 3 3 1 1
[1851] 3 2 4 4 3 1 3 3 3 1 3 1 4 1 4 4 1 4 3 3 3 3 3 3 3 3 3 2 1 2 1 2 1 1 4 2 4
[1888] 3 1 4 1 1 3 3 3 1 3 3 2 4 3 4 3 4 1 3 4 3 2 4 3 2 4 3 4 2 3 2 3 1 3 4 4 2
[1925] 2 2 2 3 1 3 1 1 2 3 2 3 1 3 2 3 1 3 1 1 1 3 3 1 4 3 1 3 4 3 1 3 2 2 1 2 2
[1962] 4 2 1 3 3 4 1 3 3 4 3 4 4 4 1 1 3 4 1 1 1 1 1 1 3 3 3 1 4 4 1 2 3 3 3 3 3
[1999] 3 1 3 3 3 3 3 3 3 2 3 2 2 3 3 4 2 2 4 2 4 4 3 3 1 3 1 3 2 3 3 1 4 3 2 1 4
[2036] 2 3 3 4 2 1 4 4 4 4 2 4 3 3 3 4 3 3 2 2 3 3 3 1 3 1 2 4 4 3 4 4 3 4 4 3 4
[2073] 3 1 3 4 4 1 4 4 4 2 4 4 3 3 2 3 4 3 3 3 2 4 4 3 4 3 3 3 3 2 1 4 3 4 1 3 3
[2110] 1 3 3 3 2 1 3 2 4 4 4 3 4 3 3 4 3 3 1 3 4 4 3 3 3 4 1 4 1 2 2 4 4 3 2 3 3
[2147] 4 4 2 2 4 4 2 2 1 3 2 2 4 2 4 2 4 2 4 3 3 1 1 1 1 1 4 3 1 1 4 4 3 4 3 4 3
[2184] 3 4 2 2 4 2 4 4 3 3 4 2 4 2 2 1 1 3 3 1 3 3 3 4 4 4 4 3 4 4 4 4 3 2 4 3 4
[2221] 4 3 3 3 3 3 3 3 4 3 4 3 2 3 2 4 1 3 3 4 3 1 3 3 1 4 3 3 2 1 1 4 3 1 3 4 4
[2258] 4 1 4 1 4 2 3 3 3 3 3 3 3 4 3 4 2 4 3 1 2 1 3 2 2 1 1 1 1 3 3 1 2 4 3 1 2
[2295] 4 3 3 1 4 4 4 4 1 4 3 3 4 3 4 4 3 4 4 2 4 3 4 3 3 2 4 3 4 3 1 4 4 4 4 3 1
[2332] 3 1 4 1 4 1 3 3 2 3 3 2 3 2 1 3 2 4 3 1 1 4 2 2 4 4 2 1 4 4 2 3 3 1 4 1 1
[2369] 3 3 4 1 2 2 1 3 1 2 1 1 1 3 4 2 4 3 3 3 2 2 4 3 4 4 1 1 1 2 2 2 2 4 1 4 4
[2406] 1 2 4 1 4 1 1 1 4 1 4 1 1 2 1 4 1 1 4 1 4 3 1 3 1 1 3 1 1 1 4 3 3 3 4 3 3
[2443] 1 1 1 1 1 4 4 1 3 3 4 4 1 1 3 3 1 3 3 2 2 3 4 3 3 4 2 4 3 3 2 4 2 4 3 2 1
[2480] 4 4 1 1 1 1 1 4 4 4 3 4 1 3 4 4 3 2 4 4 3 4 1 4 4 3 1 1 4 3 4 1 1 2 4 3 2
[2517] 3 1 2 1 3 4 3 3 3 3 4 4 4 3 3 3 3 3 2 3 4 4 4 4 3 3 3 4 4 3 3 4 1 1 4 1 4
[2554] 3 3 3 3 3 3 4 2 4 2 4 3 1 2 4 1 4 4 2 2 3 3 1 1 1 4 4 3 3 3 3 3 3 3 2 3 3
[2591] 4 3 3 3 4 3 1 4 1 1 4 1 4 4 4 2 3 1 1 2 3 1 4 4 2 4 4 4 4 3 3 4 4 4 2 3 4
[2628] 4 1 1 4 4 1 3 1 2 3 1 4 2 2 3 2 3 3 4 2 4 3 3 3 3 2 3 1 1 1 4 3 2 3 3 4 2
[2665] 2 4 3 4 4 3 3 3 4 2 4 4 2 3 4 4 4 3 4 4 4 2 4 1 3 4 4 4 3 4 4 4 3 2 3 4 2
[2702] 4 4 4 1 1 1 4 1 1 1 3 3 1 1 3 1 3 2 3 2 3 4 4 3 3 2 4 1 2 1 3 4 2 3 1 4 2
[2739] 4 2 3 4 3 2 2 2 3 4 3 4 3 4 4 2 2 1 1 2 2 4 3 3 3 4 3 4 2 3 4 3 1 4 4 2 4
[2776] 4 4 4 2 4 4 3 1 1 1 3 2 3 3 3 1 1 1 4 3 2 4 3 4 4 1 1 2 2 2 4 3 3 1 3 2 4
[2813] 4 3 2 2 4 2 3 4 4 1 3 2 3 3 1 3 3 3 3 3 2 4 4 3 1 3 2 2 2 2 2 2 2 2 2 2 3
[2850] 1 3 2 3 4 2 3 4 2 3 4 3 2 2 2 4 4 4 4 4 4 4 2 3 2 4 2 3 3 4 2 2 2 4 2 4 2
[2887] 2 2 2 4 3 3 1 3 2 3 1 1 2 3 2 2 3 2 4 3 1 2 2 2 3 3 2 1 2 2 4 4 2 4 2 1 4
[2924] 4 4 1 2 3 3 4 3 2 1 4 2 2 2 1 4 4 4 4 3 4 4 3 4 4 1 4 4 2 4 4 2 4 2 2 2 2
[2961] 4 4 2 4 4 4 4 4 3 2 3 4 4 4 4 3 4 4 4 4 4 2 1 3 2 4 4 4 2 1 3 3 4 4 4 4 4
[2998] 3 4 4 4 4 3 2 4 3 1 3 3 1 1 4 2 4 2 2 4 3 4 2 2 2 4 2 4 3 4 3 4 4 4 4 2 1
[3035] 3 2 1 3 4 1 4 3 3 4 4 2 4 3 4 1 1 1 3 4 2 4 2 4 1 2 3 3 4 3 1 4 1 4 4 2 4
[3072] 2 3 4 4 2 4 1 2 4 2 3 2 2 2 2 2 1 2 2 2 1 3 4 2 2 2 4 4 4 4 2 4 4 4 3 3 3
[3109] 3 1 4 2 4 4 4 4 2 2 3 2 1 4 4 2 4 3 4 2 2 4 3 1 4 4 4 1 4 4 4 4 1 2 4 4 4
[3146] 4 4 3 4 3 2 4 1 2 4 4 4 4 4 4 2 4 4 4 1 4 4 4 2 4 3 2 4 4 4 3 2 3 2 4 2 4
[3183] 4 2 2 4 2 4 4 3 4 3 4 4 2 4 4 4 4 4 3 4 2 4 3 3 2 4 3 3 4 3 4 3 2 2 4 4 4
[3220] 2 2 2 4 3 3 2 4 1 1 4 3 4 2 2 4 3 3 3 4 2 4 4 4 2 2 4 4 3 3 3 4 3 4 4 1 1
[3257] 1 1 1 1 1 2 1 2 1 3 4 3 4 1 4 2 2 4 4 2 3 4 1 4 4 4 4 3 4 4 4 4 3 1 2 2 1
[3294] 2 4 1 1 1 4 4 2 2 2 2 3 2 3 1 4 2 4 3 2 2 1 2 2 4 4 3 4 2 4 2 4 4 3 2 4 4
[3331] 3 3 3 3 2 1 1 1 2 2 4 2 4 1 1 1 1 3 2 2 4 2 2 2 4 4 3 2 2 2 2 2 4 2 2 2 4
[3368] 4 3 4 4 4 3 4 3 4 3 1 3 1 4 4 4 3 3 4 3 1 2 2 4 4 2 4 1 1 4 1 1 2 4 4 4 4
[3405] 2 4 2 1 1 4 3 4 3 1 3 3 1 2 1 3 3 2 4 3 4 3 3 3 4 3 3 3 4 2 2 2 2 4 1 4 4
[3442] 4 2 4 1 4 3 2 4 4 4 4 4 2 4 2 3 3 4 3 4 1 4 4 3 4 4 1 2 3 1 4 4 2 1 3 2 3
[3479] 3 2 2 4 2 2 2 4 2 1 2 2 3 4 4 4 4 4 3 3 4 4 4 4 3 2 4 4 3 4 3 3 3 2 4 2 2
[3516] 2 3 4 4 4 1 3 3 1 4 4 4 3 2 4 3 3 2 3 3 3 2 4 4 2 2 4 3 3 3 1 3 1 4 3 4 4
[3553] 4 4 2 4 4 2 4 2 2 2 3 2 2 2 4 2 2 2 2 2 4 2 4 4 3 4 4 2 3 4 2 2 2 4 3 4 4
[3590] 4 4 3 3 3 4 4 4 3 3 1 2 4 4 4 2 3 3 2 3 3 3 2 4 3 3 2 1 4 4 4 3 4 2 4 2 1
[3627] 4 1 3 3 4 4 4 4 3 2 2 4 2 2 4 3 3 4 4 3 2 2 4 4 4 1 4 1 4 4 1 4 3 4 4 3 2
[3664] 3 3 4 3 4 2 4 3 2 2 2 4 3 2 3 4 4 1 4 4 1 4 1 3 2 1 4 3 4 4 4 4 3 4 1 2 3
[3701] 3 4 3 3 3 3 2 4 1 3 2 3 3 1 2 1 3 4 4 1 3 4 4 3 4 4 4 3 2 4 1 3 4 4 4 2 2
[3738] 4 4 3 3 3 3 3 3 3 4 1 4 3 3 4 3 3 4 4 4 3 3 4 4 2 2 2 4 1 1 1 4 1 4 4 4 4
[3775] 1 4 4 4 4 2 1 4 2 1 4 2 1 1 1 1 1 1 4 3 4 4 2 2 4 3 2 2 4 4 2 2 2 4 4 4 3
[3812] 3 4 3 3 4 4 4 4 4 4 3 1 1 4 2 4 2 4 2 4 4 4 4 3 4 4 4 3 4 2 1 4 4 2 3 4 3
[3849] 2 2 4 4 2 4 4 3 2 4 4 1 1 3 1 1 2 4 4 1 1 3 3 1 1 3 1 4 3 2 3 2 4 4 4 3 4
[3886] 2 3 2 4 4 2 4 4 2 4 2 3 3 4 4 2 2 2 2 4 2 2 2 4 4 3 4 2 4 4 4 3 1 4 4 4 3
[3923] 2 4 4 2 2 4 3 3 2 4 4 2 2 1 4 3 2 3 3 3 4 4 3 3 4 3 4 3 3 3 2 4 3 2 4 2 4
[3960] 4 3 3 4 4 3 2 4 1 1 4 3 4 2 1 1 3 4 4 1 1 3 3 3 4 4 4 4 1 4 4 1 4 2 4 4 4
[3997] 4 3 4 4 4 4 2 4 4 4 2 4 2 3 4 3 4 3 1 2 3 4 1 2 2 4 3 3 3 2 3 3 2 4 4 4 4
[4034] 4 4 3 3 3 4 4 1 3 4 4 4 4 3 4 4 2 4 2 3 4 3 2 4 4 4 2 2 2 4 4 2 4 3 3 3 4
[4071] 3 2 3 4 2 4 4 4 4 2 4 4 3 3 2 2 2 4 2 4 3 2 4 2 2 2 4 2 4 4 2 3 3 2 2 4 3
[4108] 3 4 3 1 2 2 2 4 2 3 3 4 3 4 3 3 2 2 3 3 1 1 2 4 1 1 4 2 4 4 1 2 3 3 3 4 4
[4145] 3 3 4 3 4 2 1 1 4 1 1 1 1 3 3 3 3 3 3 4 4 2 3 4 4 4 3 4 3 2 3 3 3 4 4 1 4
[4182] 2 3 2 2 1 2 4 4 4 2 4 2 2 2 2 2 3 3 2 2 2 4 3 4 2 3 4 2 2 4 1 3 2 1 1 1 4
[4219] 3 1 2 4 4 2 2 1 3 2 1 4 4 2 2 4 4 4 4 2 4 2 4 3 3 2 4 4 2 4 4 3 2 2 2 2 4
[4256] 4 4 4 4 4 3 4 3 3 4 3 4 4 3 1 3 1 4 4 4 4 4 3 2 4 4 4 4 2 2 2 2 4 2 4 4 1
[4293] 4 1 4 1 4 4 4 3 3 3 1 4 4 4 4 4 2 4 3 4 4 2 4 4 2 3 4 4 1 3 4 4 4 3 3 3 3
[4330] 3 3 3 3 3 3 3 3 3 3 2 3 4 3 4 4 4 4 3 3 1 2 4 3 3 3 4 3 1 3 1 3 4 4 4 4 3
[4367] 4 4 4 4 4 2 4 2 3 1 4 2 4 4 3 3 4 2 3 3 3 2 2 4 3 1 3 3 3 3 3 3 3 3 3 4 3
[4404] 1 1 1 4 2 1 4 3 2 4 2 4 4 3 4 4 4 4 4 4 4 4 4 4 1 3 3 3 2 2 1 3 3 2 3 4 4
[4441] 3 4 3 4 4 4 4 2 4 3 4 1 3 2 3 3 3 3 4 4 3 3 4 4 4 4 3 3 2 4 2 2 2 4 4 4 4
[4478] 3 3 4 4 3 3 4 4 2 2 2 4 4 4 2 2 3 2 1 2 3 4 2 3 3 3 4 4 3 4 2 3 2 3 4 4 2
[4515] 1 4 2 2 2 3 1 1 2 3 3 3 1 2 2 3 3 3 4 4 4 3 3 2 4 2 4 4 2 2 4 4 2 2 1 2 2
[4552] 4 4 4 4 2 4 1 4 4 4 2 4 4 4 3 3 3 4 4 2 2 2 2 4 4 2 2 2 4 4 4 3 3 4 3 4 4
[4589] 4 4 3 1 3 4 4 4 4 2 4 2 4 4 3 4 3 2 4 3 2 2 2 2 3 3 3 4 2 4 4 1 4 2 4 4 2
[4626] 3 1 2 2 2 4 4 1 1 4 4 3 4 3 1 4 4 2 1 4 3 2 4 1 2 2 4 1 2 3 3 3 3 4 2 2 3
[4663] 4 4 4 4 1 4 4 4 3 3 3 4 3 3 4 4 3 3 4 2 2 4 1 4 4 3 3 3 3 3 3 3 3 4 2 4 4
[4700] 3 3 3 3 2 1 4 4 4 4 3 4 4 4 2 4 2 2 4 4 2 2 2 4 3 2 4 2 4 4 2 4 3 3 4 2 2
[4737] 2 4 4 2 1 4 4 3 2 1 4 2 3 3 3 1 2 4 4 2 4 4 4 4 4 4 2 4 4 2 4 3 3 3 3 3 1
[4774] 2 4 4 4 4 4 2 4 3 4 4 3 2 4 4 3 4 4 4 4 3 3 3 3 2 4 4 4 3 4 4 2 2 4 4 2 3
[4811] 3 2 4 3 4 4 3 4 2 4 3 4 3 4 3 4 4 2 3 2 4 4 4 2 2 4 2 1 4 2 4 1 2 3 3 2 3
[4848] 4 3 3 3 3 4 2 2 3 3 4 3 4 4 2 2 2 3 2 4 2 4 2 4 2 3 4 4 2 4 2 2 3 3 4 3 3
[4885] 3 3 4 2 4 4 2 4 4 2 3 4 4 2

Within cluster sum of squares by cluster:
[1] 681403.3 357903.9 579703.3 462118.7
 (between_SS / total_SS =  80.0 %)

Available components:

[1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss"
[6] "betweenss"    "size"         "iter"         "ifault"
Code 
fviz_cluster(kmeans4,data = whitewine)

Code 
whitewine <- whitewine %>%
  mutate (Cluster = kmeans4$cluster)
Code 
whitewine$Cluster <- as.factor(whitewine$Cluster)
Code 
histoVisibility <- rep(TRUE, ncol(whitewine))

whitewine %>%
  parallelPlot(whitewine,
              rotateTitle = TRUE,
              histoVisibility = histoVisibility)

Parallel Plot is also available for Shiny - refer to the documentation!

parallelPlotOutput()

renderParallelPlot()

Shiny App Built

https://zjjgithub.shinyapps.io/MultivariateAnalysis/