C6T1_Document_v2
David Chávez
2025-01-19
Parte 1 PCA de wine
##_Explque en sua palabras los beneficios de RMD
Se puede obtener visualizaciones dinámicas que el ggplot no los puede hacer como desplegar información adicional como tooltio, drag and drop, efectos.
##Proceda a cargar los datos de wine.csv
#cargue los datos a un dataframe y visualice las primera 5 lineas
# Cargar los datos
data <- read.csv("C:\\R\\wine.csv",header=TRUE, sep=",")
summary(data)## Cultivar Alcohol Malic.acid Ash
## Min. :1.000 Min. :11.03 Min. :0.740 Min. :1.360
## 1st Qu.:1.000 1st Qu.:12.36 1st Qu.:1.603 1st Qu.:2.210
## Median :2.000 Median :13.05 Median :1.865 Median :2.360
## Mean :1.938 Mean :13.00 Mean :2.336 Mean :2.367
## 3rd Qu.:3.000 3rd Qu.:13.68 3rd Qu.:3.083 3rd Qu.:2.558
## Max. :3.000 Max. :14.83 Max. :5.800 Max. :3.230
## Alcalinity.of.ash Magnesium Total.phenols Flavanoids
## Min. :10.60 Min. : 70.00 Min. :0.980 Min. :0.340
## 1st Qu.:17.20 1st Qu.: 88.00 1st Qu.:1.742 1st Qu.:1.205
## Median :19.50 Median : 98.00 Median :2.355 Median :2.135
## Mean :19.49 Mean : 99.74 Mean :2.295 Mean :2.029
## 3rd Qu.:21.50 3rd Qu.:107.00 3rd Qu.:2.800 3rd Qu.:2.875
## Max. :30.00 Max. :162.00 Max. :3.880 Max. :5.080
## Nonflavanoid.phenols Proanthocyanins Color.intensity Hue
## Min. :0.1300 Min. :0.410 Min. : 1.280 Min. :0.4800
## 1st Qu.:0.2700 1st Qu.:1.250 1st Qu.: 3.220 1st Qu.:0.7825
## Median :0.3400 Median :1.555 Median : 4.690 Median :0.9650
## Mean :0.3619 Mean :1.591 Mean : 5.058 Mean :0.9574
## 3rd Qu.:0.4375 3rd Qu.:1.950 3rd Qu.: 6.200 3rd Qu.:1.1200
## Max. :0.6600 Max. :3.580 Max. :13.000 Max. :1.7100
## OD280.OD315.of.diluted.wines Proline
## Min. :1.270 Min. : 278.0
## 1st Qu.:1.938 1st Qu.: 500.5
## Median :2.780 Median : 673.5
## Mean :2.612 Mean : 746.9
## 3rd Qu.:3.170 3rd Qu.: 985.0
## Max. :4.000 Max. :1680.0##Indique aqu? de que se trata el dataset que acaba de cargar y los tipos de cada ##variable. Nos interesa especialmente aquellas que no sean num?ricas
Se puede anaizar a simple vista que es informacion de los cultivos de VINO , tenemos información como acerca de los vinos diluidos, información de Intensidad del color,Alcalinidad de las cenizas Magnesio,Flavonoides Fenoles no flavonoides,Proantocianinas, diversas sustancias que intervienen en el proceso
Aplicaci?n de PCA
#El objetivo de PCA es : #Reducir la cantidad de dimensiones en los datos #Encontrar patrones en datos de alta dimensi?n #Visualizar datos de alta dimensionalidad, esta caracter?stica es la que veremos
#A continuacion proceda a revisar la data para asegurarse que no tiene variables con valor 0 #o negativos
# Cargar librerías necesarias
library(dplyr)##
## Adjuntando el paquete: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union# Cargar los datos
data <- read.csv("C:\\R\\wine.csv",header=TRUE, sep=",")
# Inspeccionar si hay valores cero o negativos en las columnas numéricas
zero_negative_check <- data %>%
select(where(is.numeric)) %>%
summarise(across(everything(), list(
Zero_Values = ~ sum(. == 0),
Negative_Values = ~ sum(. < 0)
)))
# Transponer para una mejor visualización
zero_negative_check <- t(zero_negative_check)
# Mostrar resultados
print("Revisión de valores cero y negativos:")## [1] "Revisión de valores cero y negativos:"print(zero_negative_check)## [,1]
## Cultivar_Zero_Values 0
## Cultivar_Negative_Values 0
## Alcohol_Zero_Values 0
## Alcohol_Negative_Values 0
## Malic.acid_Zero_Values 0
## Malic.acid_Negative_Values 0
## Ash_Zero_Values 0
## Ash_Negative_Values 0
## Alcalinity.of.ash_Zero_Values 0
## Alcalinity.of.ash_Negative_Values 0
## Magnesium_Zero_Values 0
## Magnesium_Negative_Values 0
## Total.phenols_Zero_Values 0
## Total.phenols_Negative_Values 0
## Flavanoids_Zero_Values 0
## Flavanoids_Negative_Values 0
## Nonflavanoid.phenols_Zero_Values 0
## Nonflavanoid.phenols_Negative_Values 0
## Proanthocyanins_Zero_Values 0
## Proanthocyanins_Negative_Values 0
## Color.intensity_Zero_Values 0
## Color.intensity_Negative_Values 0
## Hue_Zero_Values 0
## Hue_Negative_Values 0
## OD280.OD315.of.diluted.wines_Zero_Values 0
## OD280.OD315.of.diluted.wines_Negative_Values 0
## Proline_Zero_Values 0
## Proline_Negative_Values 0#A continuaci?n proceda a revisar la data para asegurarse que no tiene variables con valor 0 #o negativos
# Cargar librerías necesarias
library(dplyr)
# Cargar los datos
data <- read.csv("C:\\R\\wine.csv",header=TRUE, sep=",")
# Verificar y eliminar filas con valores negativos o ceros en columnas numéricas
cleaned_data <- data %>%
filter(across(where(is.numeric), ~ . > 0))## Warning: Using `across()` in `filter()` was deprecated in dplyr 1.0.8.
## ℹ Please use `if_any()` or `if_all()` instead.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.# Confirmar eliminación
str(cleaned_data)## 'data.frame': 178 obs. of 14 variables:
## $ Cultivar : int 1 1 1 1 1 1 1 1 1 1 ...
## $ Alcohol : num 14.2 13.2 13.2 14.4 13.2 ...
## $ Malic.acid : num 1.71 1.78 2.36 1.95 2.59 1.76 1.87 2.15 1.64 1.35 ...
## $ Ash : num 2.43 2.14 2.67 2.5 2.87 2.45 2.45 2.61 2.17 2.27 ...
## $ Alcalinity.of.ash : num 15.6 11.2 18.6 16.8 21 15.2 14.6 17.6 14 16 ...
## $ Magnesium : int 127 100 101 113 118 112 96 121 97 98 ...
## $ Total.phenols : num 2.8 2.65 2.8 3.85 2.8 3.27 2.5 2.6 2.8 2.98 ...
## $ Flavanoids : num 3.06 2.76 3.24 3.49 2.69 3.39 2.52 2.51 2.98 3.15 ...
## $ Nonflavanoid.phenols : num 0.28 0.26 0.3 0.24 0.39 0.34 0.3 0.31 0.29 0.22 ...
## $ Proanthocyanins : num 2.29 1.28 2.81 2.18 1.82 1.97 1.98 1.25 1.98 1.85 ...
## $ Color.intensity : num 5.64 4.38 5.68 7.8 4.32 6.75 5.25 5.05 5.2 7.22 ...
## $ Hue : num 1.04 1.05 1.03 0.86 1.04 1.05 1.02 1.06 1.08 1.01 ...
## $ OD280.OD315.of.diluted.wines: num 3.92 3.4 3.17 3.45 2.93 2.85 3.58 3.58 2.85 3.55 ...
## $ Proline : int 1065 1050 1185 1480 735 1450 1290 1295 1045 1045 ...# Guardar el dataset limpio
write.csv(cleaned_data, "C://R//cleaned_data.csv", row.names = FALSE)
# Mensaje final
print("Dataset limpio guardado como 'cleaned_data.csv'.")## [1] "Dataset limpio guardado como 'cleaned_data.csv'."# Cargar librerías necesarias
library(dplyr)
# Cargar los datos
data2 <- read.csv("C:\\R\\cleaned_data.csv",header=TRUE, sep=",")
summary(data2)## Cultivar Alcohol Malic.acid Ash
## Min. :1.000 Min. :11.03 Min. :0.740 Min. :1.360
## 1st Qu.:1.000 1st Qu.:12.36 1st Qu.:1.603 1st Qu.:2.210
## Median :2.000 Median :13.05 Median :1.865 Median :2.360
## Mean :1.938 Mean :13.00 Mean :2.336 Mean :2.367
## 3rd Qu.:3.000 3rd Qu.:13.68 3rd Qu.:3.083 3rd Qu.:2.558
## Max. :3.000 Max. :14.83 Max. :5.800 Max. :3.230
## Alcalinity.of.ash Magnesium Total.phenols Flavanoids
## Min. :10.60 Min. : 70.00 Min. :0.980 Min. :0.340
## 1st Qu.:17.20 1st Qu.: 88.00 1st Qu.:1.742 1st Qu.:1.205
## Median :19.50 Median : 98.00 Median :2.355 Median :2.135
## Mean :19.49 Mean : 99.74 Mean :2.295 Mean :2.029
## 3rd Qu.:21.50 3rd Qu.:107.00 3rd Qu.:2.800 3rd Qu.:2.875
## Max. :30.00 Max. :162.00 Max. :3.880 Max. :5.080
## Nonflavanoid.phenols Proanthocyanins Color.intensity Hue
## Min. :0.1300 Min. :0.410 Min. : 1.280 Min. :0.4800
## 1st Qu.:0.2700 1st Qu.:1.250 1st Qu.: 3.220 1st Qu.:0.7825
## Median :0.3400 Median :1.555 Median : 4.690 Median :0.9650
## Mean :0.3619 Mean :1.591 Mean : 5.058 Mean :0.9574
## 3rd Qu.:0.4375 3rd Qu.:1.950 3rd Qu.: 6.200 3rd Qu.:1.1200
## Max. :0.6600 Max. :3.580 Max. :13.000 Max. :1.7100
## OD280.OD315.of.diluted.wines Proline
## Min. :1.270 Min. : 278.0
## 1st Qu.:1.938 1st Qu.: 500.5
## Median :2.780 Median : 673.5
## Mean :2.612 Mean : 746.9
## 3rd Qu.:3.170 3rd Qu.: 985.0
## Max. :4.000 Max. :1680.0###Indique en este lugar cual es el prop?sito de la funci?n prcomp_
Aplicando PRCOMP
Permite realizar un análisis de componentes principales (PCA) en una matriz de datos. El resultado es un objeto que contiene varios componentes, entre ellos las desviaciones estándar, la matriz de cargas variables, las medias de las variables, la escala y las coordenadas de los datos.
## [1] "Valores propios (Eigenvalues):"## [1] 5.53594804 2.49707625 1.44607422 0.92791783 0.87750252 0.67277834
## [7] 0.55379896 0.35003417 0.29454194 0.26230610 0.22584842 0.16879672
## [13] 0.12956418 0.05781232## [1] "Vectores propios (Eigenvectors):"## PC1 PC2 PC3 PC4
## Cultivar 0.393669533 -0.005690412 -0.001217953 0.12246373
## Alcohol -0.136325011 -0.484160868 0.207400812 -0.08191848
## Malic.acid 0.222676383 -0.223590947 -0.088796064 0.46988824
## Ash -0.002257932 -0.315855884 -0.626102363 -0.24984122
## Alcalinity.of.ash 0.224298489 0.011615737 -0.611989600 0.07199322
## Magnesium -0.124630159 -0.300551432 -0.130984580 -0.16321412
## Total.phenols -0.359264042 -0.067119829 -0.146507749 0.19098521
## Flavanoids -0.390711715 0.001313454 -0.150962746 0.14461667
## Nonflavanoid.phenols 0.267001203 -0.026988703 -0.169975512 -0.32801272
## Proanthocyanins -0.279062504 -0.041222563 -0.149879586 0.46275771
## Color.intensity 0.089318293 -0.529782740 0.137266298 0.07211248
## Hue -0.276822650 0.277907354 -0.085328539 -0.43466618
## OD280.OD315.of.diluted.wines -0.350526181 0.162776250 -0.166204360 0.15672341
## Proline -0.269515252 -0.366058862 0.126686846 -0.25579490
## PC5 PC6 PC7 PC8
## Cultivar 0.15758395 0.20033864 -0.05938234 0.07179553
## Alcohol -0.25089415 -0.13517139 -0.09269887 0.42154435
## Malic.acid -0.18860015 -0.59841948 0.37436980 0.08757556
## Ash -0.09352360 -0.10799983 -0.16708856 -0.17208034
## Alcalinity.of.ash 0.04656750 0.08811224 -0.26872469 0.41324857
## Magnesium 0.77833048 -0.14483831 0.32957951 -0.14881189
## Total.phenols -0.14466563 0.14809748 -0.03789829 -0.36343884
## Flavanoids -0.11200553 0.06247252 -0.06773223 -0.17540500
## Nonflavanoid.phenols -0.43257916 0.25868639 0.61111195 -0.23075135
## Proanthocyanins 0.09158820 0.46627764 0.42292282 0.34373920
## Color.intensity -0.04626960 0.42525454 -0.18613617 -0.04069617
## Hue -0.02986657 -0.01565089 0.19204101 0.48362564
## OD280.OD315.of.diluted.wines -0.14419358 -0.21770365 -0.07850980 -0.06865116
## Proline -0.08440794 -0.06656550 0.05420370 0.11146671
## PC9 PC10 PC11 PC12
## Cultivar -0.162368819 -0.19899373 0.01444169 -0.01575769
## Alcohol -0.450190708 0.31127983 -0.22154641 0.26411262
## Malic.acid -0.006025687 -0.32592413 0.06839251 -0.11921210
## Ash 0.262494455 -0.12452347 -0.49452428 0.04502305
## Alcalinity.of.ash -0.118633417 0.15716811 0.47461722 0.06131271
## Magnesium -0.252536278 0.12773363 0.07119731 -0.06116074
## Total.phenols -0.406373544 -0.30772263 0.29740957 0.30087591
## Flavanoids -0.090919334 -0.14044000 -0.03219187 0.05001396
## Nonflavanoid.phenols -0.159122818 0.24054263 0.12200984 -0.04266558
## Proanthocyanins 0.265786794 0.10869629 -0.23292405 0.09334264
## Color.intensity -0.075264592 -0.21704255 0.01972448 -0.59795428
## Hue -0.212416815 -0.50966073 -0.06140493 -0.25774292
## OD280.OD315.of.diluted.wines -0.084264837 0.45570504 0.06646166 -0.61109218
## Proline 0.544905394 -0.04620802 0.55130818 0.07268036
## PC13 PC14
## Cultivar -0.49224318 -0.669045280
## Alcohol -0.05610645 -0.090626055
## Malic.acid 0.06675544 0.025225306
## Ash -0.19201787 0.001635816
## Alcalinity.of.ash 0.20007784 0.095361066
## Magnesium 0.05829909 -0.022300745
## Total.phenols -0.35952714 0.253037788
## Flavanoids 0.59834288 -0.601909165
## Nonflavanoid.phenols 0.06403952 -0.082230935
## Proanthocyanins -0.11013538 0.058641979
## Color.intensity 0.15917751 0.178821145
## Hue -0.04923091 0.022582562
## OD280.OD315.of.diluted.wines -0.32941979 -0.135092159
## Proline -0.17322892 -0.216043617## [1] "Scores (Componentes principales):"## PC1 PC2 PC3 PC4 PC5
## 1 -3.513024083 -1.44901095 0.164331927 -0.0132354868 0.7352712495
## 2 -2.521744523 0.32909093 2.021005638 -0.4159709585 -0.2824170691
## 3 -2.777194851 -1.03401911 -0.980471909 0.6623639624 -0.3864747681
## 4 -3.911554382 -2.76042344 0.174475992 0.5634982615 -0.3234473063
## 5 -1.403551861 -0.86533209 -2.020130938 -0.4396655603 0.2273080377
## 6 -3.278880486 -2.12418306 0.627223018 -0.6036690217 -0.4084741747
## 7 -2.742840318 -1.17585305 0.974588274 -0.3525938619 -1.0213955679
## 8 -2.386135518 -1.60674987 -0.145319533 -1.2420979161 0.2068543466
## 9 -2.787393428 -0.92058266 1.765943961 -0.1563853889 -0.8560500287
## 10 -2.997142086 -0.79404427 0.980974418 0.2695328266 -0.4705179079
## 11 -3.668340606 -1.30883136 0.420667517 0.0020641733 -0.2591095954
## 12 -2.103700480 -0.61125770 1.188218133 -1.0954534601 -0.5563297061
## 13 -2.431597118 -0.67661466 0.863079058 -0.6569263584 -1.0846618504
## 14 -3.663161193 -1.13691426 1.200382567 -0.2307148420 -1.8174847430
## 15 -4.429081842 -2.10438296 1.258899205 0.2034302321 -0.8421767145
## 16 -2.601585110 -1.66173047 -0.217020571 -1.5141875503 -0.0993603741
## 17 -2.468465215 -2.32434003 -0.829262820 -0.8947559752 0.2104437913
## 18 -2.219970165 -1.62899496 -0.792322900 -1.1470164581 -0.1301127546
## 19 -3.731742493 -2.52129300 0.483468544 -1.0517270184 -0.7203326906
## 20 -2.387676152 -1.06153499 0.164248436 0.5657676657 0.5355417469
## 21 -3.327183368 -0.79377365 0.362828827 0.2460633165 0.9659055564
## 22 -1.477236883 -0.23941013 -0.933597405 0.8972332665 -0.2092843901
## 23 -2.820113471 0.08661323 0.311089177 -0.2063638159 -0.4862010173
## 24 -2.002066457 0.51416609 -0.142851007 -0.5766810317 -0.3755931522
## 25 -2.108687681 0.31503190 -0.887220699 -0.3306825055 -0.6221761937
## 26 -1.393606311 -0.93557614 -3.809097443 -1.3437600270 0.3416893362
## 27 -2.127486643 -0.68516927 0.087212048 -0.5743975719 -1.1272041930
## 28 -1.625119559 0.09092753 1.383913414 -0.6725541885 -0.3736816112
## 29 -2.500553765 -0.69080117 -1.390249800 -0.9842005795 -0.6296900736
## 30 -2.552283493 -0.19492305 1.089605707 0.1314594809 -0.5732839737
## 31 -2.764645791 -1.24284687 -1.382356023 -0.4453631101 -0.4093778814
## 32 -2.926877371 -1.47412052 0.330919192 -0.3201106169 0.0574711790
## 33 -1.985647144 -0.05310222 0.167342712 -0.9315926959 -0.4862800756
## 34 -2.239392808 -1.63007087 -1.168088719 -2.3488460169 0.3504664856
## 35 -1.781959583 -0.69551841 -0.477611427 -1.0973471140 0.2233640082
## 36 -2.221372441 -0.17878459 -0.449455981 0.2015024704 -0.2722279181
## 37 -1.763055105 -0.65602175 -0.456232639 -1.3829910011 -0.0000909193
## 38 -1.518893365 -0.11190937 0.039998863 -1.0962609938 -0.2040317644
## 39 -1.867098082 0.76714174 1.422805688 -0.8429806630 -0.0654146334
## 40 -2.789246215 -1.80372079 0.341693195 1.3400651300 0.7390136544
## 41 -2.832944297 -0.78395014 0.117450556 0.5997674680 0.3234324933
## 42 -1.102462188 -0.16541830 0.782362035 0.9753745009 -0.9692610714
## 43 -3.297592710 -1.16068133 0.311321750 0.4527754947 -0.4487258743
## 44 -0.902253275 -0.32515521 0.202014386 1.2465061207 -0.3859798701
## 45 -2.390093523 0.06671774 0.653643575 0.8384543292 0.2477136628
## 46 -1.533486566 -1.77008445 -0.027590759 0.4444440465 -0.5367447936
## 47 -2.982802310 -1.19425370 0.537948354 1.1630797384 -0.9194897999
## 48 -3.050710625 -0.65198279 1.151509681 0.9943126920 -0.2012736508
## 49 -2.312248880 -1.24671983 0.057136838 0.1388179196 -0.4034442457
## 50 -2.951147454 -1.75365679 0.640847869 -0.1453572609 -0.3404551050
## 51 -3.402583023 -0.17641815 1.966734122 1.2019811189 -0.1051906911
## 52 -3.107612066 -0.74999309 -0.004984078 -0.3655687766 -0.6349122583
## 53 -3.689802644 -1.61852620 0.518406089 0.0391276724 -0.4914206657
## 54 -2.530410292 -1.87324374 -0.338228062 -1.3272359836 -0.2757676005
## 55 -2.437912181 -1.01784394 0.954877345 -0.0581426554 0.8348386884
## 56 -2.715155381 -1.33148772 -0.512742467 0.5072379620 0.8573653468
## 57 -2.976919241 -1.43957671 0.610072535 0.3314729598 0.3934957803
## 58 -2.481147879 -1.21207339 -0.260757766 -0.6786912183 -0.5660882366
## 59 -3.341859666 -1.73570661 0.283934186 0.3148888067 0.1126734748
## 60 0.872463924 3.06906636 4.572747016 -0.9563997544 0.6275758550
## 61 1.410681395 1.38604434 0.874005360 -3.0912998406 -0.2744946030
## 62 1.709058108 0.83649642 1.602551167 -1.5174852564 0.0470183441
## 63 -0.012262270 1.25914400 1.779585217 -1.2505752226 -0.0611418366
## 64 -1.827944810 1.90800383 0.005293848 0.8946565543 0.0366697373
## 65 0.572919811 1.90577501 -0.676769930 -2.1054805416 0.4774320067
## 66 -0.789244791 0.75659127 -0.572580565 -0.5541012381 0.2292950887
## 67 -2.014349238 1.86686522 2.023991089 1.4233673830 -0.7164993234
## 68 -0.142877938 2.41893339 1.066506203 0.0393480459 -0.4761304712
## 69 0.749393715 0.22457552 0.706161729 -2.5840378504 0.0231580473
## 70 -1.735430290 1.38709532 1.232125446 0.0429697814 4.4364724920
## 71 1.472147656 0.88973874 0.628170741 -0.9767367476 1.1131030281
## 72 -1.487780934 0.94526061 -1.948340937 0.0977860970 -0.6012808281
## 73 0.692014768 1.06386229 -0.079639585 -0.1550748596 -0.2033526420
## 74 -2.292988910 -0.27358675 -3.367318406 -0.2951990697 2.3365157106
## 75 -1.629534655 1.27379658 -0.458893645 0.5571709203 1.0990547206
## 76 0.826667392 2.44082053 1.559305570 -0.6612385100 0.8440438939
## 77 -0.299586657 2.14501373 2.441851283 -0.0049350335 0.2551069248
## 78 1.357349276 1.38643530 0.227660494 -0.5636538362 0.9770814485
## 79 -1.092965398 0.76049755 1.179046816 -0.1108679886 2.9193995414
## 80 -0.318321791 1.02188781 -1.789772178 0.8905992971 -0.4187367854
## 81 -0.669369362 3.36104386 0.355699086 -0.2904468514 0.0829047192
## 82 -0.921511435 1.44104161 0.361149182 0.2892456616 -0.2669378978
## 83 0.466177014 2.37706017 -1.331385398 -1.2403044957 -0.6944024953
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## 87 0.762423688 2.23121016 -0.770097379 -1.0504000997 -0.0129179547
## 88 0.526763293 2.36901453 -2.300558102 -1.1289412214 -0.2076102023
## 89 1.034935645 1.80278255 -0.955565596 -0.5559240661 -0.6826831004
## 90 0.519957513 2.65290035 -0.846122506 -0.3342281562 -1.2758223296
## 91 1.249832965 2.11877956 0.048664596 -0.7154600389 -0.7806202456
## 92 1.456600366 1.85446817 -0.777742334 -0.7494541293 -0.3732225821
## 93 1.786207616 1.56474926 0.090606491 -0.8470575623 -1.0369338318
## 94 -0.651466573 2.30189958 -0.115233376 1.2876361057 -0.0542681006
## 95 -0.833793070 2.21131104 -0.143248503 0.5972760582 0.8929325984
## 96 -2.254248359 -0.18376798 -0.789480800 0.1107719397 4.0663648536
## 97 0.553910314 0.36908618 -1.305556225 -0.4963563021 3.3841378308
## 98 -0.912422670 2.55243922 1.082317859 0.3189957414 -0.0981641925
## 99 -2.015298555 1.41622541 0.227409987 1.0617973221 -0.1452220471
## 100 -1.261867189 2.15241081 -0.748018962 1.0980510341 -0.8215622229
## 101 -0.699459195 2.36554300 1.562836762 0.1625605281 0.6465004756
## 102 0.529376478 2.28889834 1.494953851 -0.2444700318 0.3501542988
## 103 0.175661199 1.16151354 -1.000937507 0.6641368609 0.0448806635
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## 108 1.508862423 1.35952123 -0.285205159 -0.2225251768 -0.5973127479
## 109 -0.030011598 2.29802529 0.461615311 1.0126145072 0.2047521677
## 110 -1.405437791 1.44902406 -1.776215153 0.8067413279 0.3142213345
## 111 -1.214817581 1.40423165 -0.141470234 3.9709574525 1.3886533397
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## 113 1.192733062 0.76827541 -1.992431363 -1.9505827082 -0.4048226953
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## 118 0.137071803 1.92302889 -0.688550173 0.0008419067 1.0905968925
## 119 2.244146166 1.26575475 1.899538915 0.5186917999 -0.9440158700
## 120 0.529252028 2.21815964 0.355418409 1.2772205306 -0.2719341234
## 121 -0.639483447 1.40036246 -1.123135333 1.3102893198 0.1558250277
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## 124 0.457357792 0.61814477 -0.482109421 3.3300635245 -1.0124024926
## 125 -0.843727170 1.43506066 -1.478597872 3.8010786747 -0.4672855010
## 126 0.116208906 2.10396851 -0.433730192 0.9370399364 -0.5706199849
## 127 0.007066766 1.26195130 -0.686109852 1.2117517948 -0.5507040746
## 128 1.491102408 1.21225981 -3.350613092 -0.4045531092 -0.5827758165
## 129 0.477255414 1.93482045 -1.292892678 0.6692306399 -0.1918360272
## 130 1.659463471 1.15593073 -0.779240086 1.1203010811 -1.1076570698
## 131 1.773941467 -0.17183005 1.175553358 -0.8066887624 2.6710636154
## 132 2.734206054 -0.36981404 0.721605538 0.0090219131 1.3148085834
## 133 3.245142808 -0.25683895 0.167311462 -0.1349493514 1.1336306922
## 134 2.523248571 -0.36495915 0.451519908 0.4463207772 1.5845266541
## 135 2.705392785 0.46256928 1.098523718 -0.9732550533 -0.6214219049
## 136 3.339568060 -0.34459011 1.096809718 -0.8707710846 -0.4653633175
## 137 4.105585600 -0.14157372 -0.219600186 -0.2617053616 -0.5717873043
## 138 4.132471237 -0.64539266 -1.705885922 0.2423082453 -0.8599124042
## 139 3.356457341 -0.33945309 1.024956287 -0.3781338207 -1.0568608727
## 140 2.705046169 -0.28665576 -1.238069126 -0.8170712107 -0.1988655388
## 141 3.063004861 -0.27901886 -0.607095387 -1.0343148309 -0.3775463093
## 142 2.618758258 -0.36719705 0.969247208 -0.4623116185 -0.2649908488
## 143 3.251225399 -0.47973752 -0.943208733 -1.2210394810 -0.4088805064
## 144 2.696440656 -0.47611678 0.252649495 0.4100798642 -0.9009926235
## 145 2.583559833 -1.15424388 1.241122061 0.7074794712 1.4999146288
## 146 2.945701626 -0.55628229 0.853732986 0.3764587661 0.4772543183
## 147 4.447404469 -0.63369144 1.455803574 0.7936772470 -0.9177679323
## 148 3.818478101 -1.25877875 0.111535135 0.7844840132 -0.8996515477
## 149 3.124835228 -1.56024487 0.471405998 0.5711314663 -0.3545820071
## 150 3.225615029 -2.02959917 0.494455986 0.7943659978 1.2372108549
## 151 2.704934424 -2.34725826 -0.437160957 0.5260405066 2.1799516027
## 152 2.922695870 -2.03623954 0.310676967 0.8992601375 1.7741733763
## 153 2.244243506 -1.52365809 -1.359923625 0.3763904736 1.9010819150
## 154 3.088807178 -2.12748039 0.961988851 0.6150367169 -0.4799689521
## 155 3.068400079 -0.40365232 1.186977880 -0.4202871571 0.7767855032
## 156 3.845311076 -1.78704838 0.094754987 1.0014256800 -0.9929652397
## 157 3.199363404 -1.91343033 0.780424797 1.1448242335 -0.8605794321
## 158 3.648203029 -1.29891673 -1.596585827 -0.6226842135 -0.4871611758
## 159 1.548613374 -3.50919410 -1.158329264 1.0054843213 -0.6143268621
## 160 2.052494053 -2.40077381 -0.548025852 0.7489594810 -0.7405670611
## 161 3.428876889 -0.72848827 0.091211835 0.8394013061 -0.6362868496
## 162 2.577218124 -1.16803350 0.101493698 -1.2012463379 0.0178686047
## 163 3.135612031 -0.54749143 -0.801213829 -0.9623182516 -0.0609850333
## 164 2.917065291 -0.69070844 0.882697528 -0.1303817871 0.7208687878
## 165 3.252651435 -1.54423447 0.981033103 -0.0392067762 -0.2891452141
## 166 3.766961021 -0.86985778 0.465819479 0.3126326238 -0.8957322714
## 167 2.766834344 -2.58142276 -0.427200494 -0.0081609314 0.5630765673
## 168 3.233494876 -1.26428151 1.210301113 0.2395309073 -0.2911058026
## 169 2.556532083 -2.06907266 -0.761927237 -0.2060270681 0.5619280216
## 170 2.740997451 -2.57781035 -1.414277551 0.8070590823 0.8625966388
## 171 3.481375653 0.25873035 0.845357270 -0.1243268311 0.5474030675
## 172 3.918081965 -0.83503051 1.336577475 -0.2311936957 -0.3968441849
## 173 2.807376194 -2.18317766 0.916342551 -0.0809192597 -0.5584224011
## 174 3.617790848 -2.20040992 0.342700950 0.7495901505 -1.0012845827
## 175 2.934451479 -1.74733418 -0.206896115 0.3982573193 0.1537892027
## 176 3.018756881 -2.74828765 0.938156609 0.6060488662 1.1249629591
## 177 2.747471377 -2.28733179 0.548925224 -0.3904689551 1.0640813934
## 178 3.486500654 -2.75284255 -1.010301210 0.3486468140 -1.0023088794
## PC6 PC7 PC8 PC9 PC10
## 1 -0.299870285 0.572261286 -0.055480771 -0.457474579 1.062572157
## 2 -0.881821897 -0.029632889 -1.007529774 0.218190602 -0.020125260
## 3 0.467522784 0.486931824 0.268200489 1.219329902 -0.105950252
## 4 0.261877693 -0.397243535 -0.617102916 -0.114335795 0.107368253
## 5 -0.592091911 0.446615701 -0.433713850 -0.260812021 0.112118049
## 6 0.257549435 0.377511025 -0.365793608 0.044785952 -0.217353076
## 7 -0.461318788 -0.024690576 0.349679028 0.591076796 0.776935402
## 8 -1.385078298 -0.100285359 -0.212688006 -0.060780781 0.622593999
## 9 0.014200394 0.084395484 0.526326337 -0.531269228 0.327330764
## 10 0.296824392 -0.861406406 -0.159662457 -0.171674223 0.241558013
## 11 -0.039608393 0.188595988 1.225008970 0.449282832 -0.377774162
## 12 -0.402839920 -0.492162831 0.952768897 0.563402415 0.148380877
## 13 -0.019228886 -0.283919623 0.439162759 0.830010491 -0.304196708
## 14 1.007162809 1.453011942 0.439585290 -0.099983560 -0.314810258
## 15 0.999317750 0.996343630 0.438403302 0.635605691 -0.669856197
## 16 -0.242466994 -0.247455297 -0.046570534 0.182063406 -0.894553695
## 17 -0.058218077 0.103759439 0.386446567 0.004404340 0.099593022
## 18 0.416688871 0.119269231 -0.108343550 -0.385808700 -0.200898637
## 19 0.628974362 -0.073847345 0.089121714 0.181315477 -0.946945281
## 20 -1.539171921 -0.192752218 -0.563881465 -0.111290263 -0.122468282
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## 27 -0.422939777 -0.506795823 -0.939145103 0.731707565 0.182778638
## 28 -0.602774581 -0.392270162 0.176860964 0.820291496 0.159014454
## 29 -0.431454399 0.031381896 0.124065944 -0.492584270 0.040062530
## 30 -0.277472234 -0.189244445 0.447606181 0.045794331 0.791702150
## 31 0.713866790 -0.377166887 1.021001240 0.558666432 -0.335855112
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## 35 -0.735179399 -0.269822758 0.187373550 0.478502945 0.163724167
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## 38 -0.391546036 -0.421949027 -0.020009462 0.823976189 -0.413793805
## 39 -0.422070033 -0.051264914 0.009292604 0.259222982 -0.267618584
## 40 -1.820501661 0.854134222 -0.708090247 -0.767926504 0.142661063
## 41 0.557519813 0.635870786 -0.716917056 -0.682317590 0.567804171
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## 48 0.282434224 -0.433255121 -0.161210010 -0.292929087 0.393963317
## 49 0.491698285 0.282145637 0.764686971 0.014928583 0.140983927
## 50 0.804611992 0.059801284 0.245886837 -0.167586320 -0.174955285
## 51 1.152980538 0.377938496 0.402199838 1.159493377 -0.752534627
## 52 0.002237947 -0.398147944 1.041942571 0.991105135 -0.128895270
## 53 0.346676846 0.128751812 -1.343395872 -0.632756760 -0.456314587
## 54 -0.147123569 0.419644572 -0.380338536 0.214333251 -0.226437007
## 55 -0.493709673 -0.402382255 -0.325472170 -0.122744339 0.570035104
## 56 0.391682959 -0.267737225 0.468863523 0.298031375 0.252272895
## 57 0.055297521 -0.017590387 -0.339556051 -0.814501457 0.572953596
## 58 -0.136972484 -0.249822377 -0.616864231 0.668092680 -0.662061472
## 59 0.417084706 -0.802469065 -0.649233835 0.351605489 -0.283781567
## 60 -0.426045638 -0.116133214 -0.643777735 -0.480556957 -0.327747691
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## 64 1.047242469 -1.064026946 -0.191200705 -0.962492718 -1.286082765
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## 72 0.167019457 -1.605779104 1.653139371 -1.291988690 -0.465249897
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## 79 1.124975428 2.183742024 0.115854270 0.323982050 0.563229856
## 80 -0.666877766 1.091382416 0.441837126 -0.972414783 -0.465118774
## 81 0.441263880 -0.441492971 0.315798032 -0.819602858 -0.517733728
## 82 0.092873799 -0.505754397 0.630263080 0.213160864 -0.235705459
## 83 0.367243804 -0.667302164 0.936287817 0.510881363 -0.250567980
## 84 -0.007745477 1.204077032 0.446704255 0.003628677 0.387227503
## 85 0.778548754 -0.711556746 -0.671630405 1.349153086 0.529074145
## 86 -0.019103207 -0.316900461 0.198166934 -0.541885368 0.164452986
## 87 0.383781568 0.275456599 1.050911630 0.066088474 -0.380674145
## 88 -0.074222932 -0.531932890 0.862114993 0.389886741 -0.240088486
## 89 0.069969911 0.104734033 -0.367706999 0.929707234 0.074021188
## 90 0.269446742 -0.773912538 0.401670401 0.470067392 0.524591106
## 91 0.458952715 0.805663875 0.066725425 0.693779124 0.112172586
## 92 0.657109729 0.232103869 0.348562110 0.655799223 0.610101624
## 93 0.852424202 0.640588107 0.452065413 0.441032036 0.851110778
## 94 -0.510850111 0.142241999 0.253232245 -0.250147883 -0.437058214
## 95 -0.332802174 -0.802314932 -0.816945619 -0.468894752 -1.296102741
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## 99 1.295585625 -0.827816132 -0.688090349 -0.525616367 -0.948048335
## 100 0.664255581 2.062594865 0.700720753 -0.462845962 -1.224916825
## 101 -0.272607347 0.229776298 0.440103887 -0.286942278 -0.634176934
## 102 -0.188111924 -0.404477048 0.747974521 0.270073269 0.694974056
## 103 -0.694597119 -0.534942282 -0.955953573 -0.268342879 0.574269296
## 104 0.349604671 0.017960924 -0.460198881 -0.205381272 0.004814913
## 105 -0.128247770 -0.491282837 0.401936874 -0.060042242 0.664299512
## 106 -0.021463123 1.110390043 -0.456212863 -0.407054197 1.589832136
## 107 0.217931676 -0.213531952 0.231676566 0.502014428 0.578995987
## 108 0.490118164 0.013878010 0.581196831 0.424261266 1.063344598
## 109 0.953622220 0.337111953 -0.350922915 -0.313886097 0.968973936
## 110 0.833678846 -0.216250262 -0.660806174 1.188738667 -0.106671906
## 111 0.869876391 1.867223487 -0.092144183 0.556548663 -0.254149371
## 112 -0.675978350 -0.890760418 -0.262327201 -0.607569727 -0.014582555
## 113 -0.459360014 1.070483542 -0.820079232 0.484157400 -0.705740071
## 114 1.068671694 -0.409195560 -0.768158284 0.323004255 -0.539649835
## 115 0.139582202 -0.985294012 -0.955376154 -0.335970418 0.395022008
## 116 1.134455209 1.408743898 0.764301338 -0.228687345 -1.374550261
## 117 -0.017594189 -0.533075504 0.082267433 0.363978399 0.783405519
## 118 -0.107969633 0.014165692 0.350202500 -0.620542951 0.701332231
## 119 -1.012182232 0.221346552 -0.673651627 -0.022500113 0.303550184
## 120 -0.779585278 0.935880029 0.166660018 0.554142375 0.302178047
## 121 0.035005832 -0.177116743 -1.409976218 0.550246418 -0.065026486
## 122 0.867563096 -0.531938184 -1.753871961 -0.528495879 -0.176094268
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## 125 -0.325140690 0.198072312 -0.128872301 0.744106290 -0.197302108
## 126 -0.078218996 -0.532475389 -0.835107239 -0.405988737 0.355282140
## 127 0.971757715 -0.702172430 -1.022395294 -0.362895746 0.624395259
## 128 0.780342449 0.247529576 0.032374300 0.349237454 0.348050849
## 129 0.615942328 -0.319954619 0.240216948 -0.150546589 0.812259133
## 130 -1.145360337 0.268484127 -0.288260927 0.699614475 -0.218797244
## 131 -0.233296306 -0.822748941 -0.270825240 0.117696562 -0.111673138
## 132 -0.769022312 -0.972457196 0.145402606 0.259088952 -0.520070917
## 133 -0.135433308 -1.566956914 0.509433557 0.460080354 0.043463075
## 134 -1.098983957 -1.081482886 0.321728269 0.177571812 -1.118543135
## 135 1.587356834 0.431605353 -0.856516337 0.279475653 0.163671354
## 136 0.871611928 0.774390337 -0.750111358 0.072210540 0.095646352
## 137 -1.196250812 0.797349605 -0.194230793 0.981976224 -0.797400673
## 138 -0.992752769 1.372691931 0.120990630 -0.121299166 -0.648765982
## 139 -0.266348943 0.694251343 0.211352502 -0.570347789 0.146048547
## 140 -0.238758684 -0.013262033 -0.239908574 -0.699259803 -0.147972278
## 141 -0.578637031 -0.084018697 -0.406255917 0.140658407 0.488483743
## 142 -0.688126304 -1.069068234 0.160626257 0.297424568 0.652937067
## 143 -1.003947423 -0.383306845 0.395058462 -0.550807850 0.230617343
## 144 -1.421013697 0.766178113 0.518021704 -0.785319300 -0.581294054
## 145 -0.559885466 0.014992359 -0.311997654 0.878194826 -0.489331282
## 146 -0.588365612 0.546828758 0.378555713 0.431583939 0.579176676
## 147 -1.672581796 -0.200195932 0.773904817 -0.054542092 0.052310558
## 148 -0.611576644 -0.228231175 -0.422021386 0.334420759 -0.285750708
## 149 0.572200837 -0.393357764 -0.137425098 -0.024729789 0.040293356
## 150 -0.059912699 -0.327684836 -0.069577718 -0.104808630 -0.421599891
## 151 -0.129099827 -1.209609951 0.433764201 -0.231316034 -0.156971573
## 152 0.762767169 -1.463279229 -0.350782349 0.218685543 -0.244777971
## 153 0.885728019 -1.417611318 0.050191863 -0.317062571 -0.091888033
## 154 1.678664535 1.180954925 -0.407803539 0.069876758 0.134034753
## 155 1.740914151 0.222921889 -0.483352271 0.252721846 0.876427229
## 156 0.031439163 1.436428765 0.198319025 0.141832818 -0.212170004
## 157 0.417062662 0.251330066 0.148947138 -0.344385868 -0.029132190
## 158 0.828456056 0.168790648 -0.150173681 0.481753622 0.176008617
## 159 3.463744672 -0.383205926 0.493062002 -0.740431949 0.627922147
## 160 3.080319213 -0.470653621 -0.181713746 -0.108836896 0.168212900
## 161 0.371598265 -0.028728410 -1.079109928 -0.027816576 -0.663704783
## 162 -0.615301793 0.404570107 0.247608396 -0.749011318 -0.296705226
## 163 -0.250060137 0.810385176 -0.198921228 -0.370047265 0.182906892
## 164 -0.807706928 0.214306214 -0.249062536 0.289121877 0.040938532
## 165 0.604592347 -0.942596523 0.768419955 -0.248050153 0.176581424
## 166 -0.448054067 0.465340370 1.102160861 -0.420916454 0.171364472
## 167 0.552434551 0.074718730 0.701278607 -0.287352068 -0.737215297
## 168 0.438950275 -0.606983692 -0.011848436 0.379678521 -0.670451615
## 169 0.689037383 -0.699519890 0.895002792 0.212978726 0.218715724
## 170 -1.014221257 -1.005322879 0.336287067 -0.164991988 -0.706859139
## 171 -0.495041075 -0.296548339 -0.612000878 0.572127062 -0.022182487
## 172 0.893632156 -0.919905217 -0.724722902 0.038781204 0.067470540
## 173 0.863023729 -0.786661504 0.292329710 -0.244013326 0.340934411
## 174 -1.139939246 0.841082264 0.206044724 -0.125065905 -0.391514872
## 175 -0.062289046 0.139553613 0.563996559 0.055185648 -0.235602201
## 176 0.005275476 0.730964144 -0.052396746 -0.027802925 -0.212150899
## 177 1.009714032 0.753298285 -0.425312224 0.048646933 0.478443539
## 178 0.376162259 0.015263586 0.324087919 -0.717958122 0.079682974
## PC11 PC12 PC13 PC14
## 1 -0.419311078 -0.551372411 -0.302125915 -2.002924e-01
## 2 -0.129653891 -0.393860128 -0.146232803 -1.260468e-01
## 3 -0.278289088 -0.001892654 0.021218163 5.559469e-02
## 4 0.771688951 0.230279641 -0.499866743 -1.984687e-02
## 5 -0.536418018 0.226048523 0.273337857 5.160422e-01
## 6 0.406638322 0.375655765 -0.017393570 -2.388884e-01
## 7 -0.401144507 -0.159682213 -0.573752772 -1.571678e-01
## 8 0.319654339 -0.389910627 -0.307340232 -1.162721e-01
## 9 -0.506734442 0.634450713 0.101395098 -7.208372e-02
## 10 0.015045667 -0.548060428 0.021433151 1.047683e-01
## 11 0.730295547 0.078689862 -0.034377295 -2.540316e-01
## 12 0.047574990 0.162718688 0.125702870 -7.859019e-03
## 13 0.057200416 0.087292083 -0.045667483 -4.573412e-03
## 14 -1.227597359 0.764258779 -0.081607879 -4.556787e-01
## 15 -0.309962009 0.131286792 -0.394273611 -3.591457e-01
## 16 0.083663937 -0.492127392 0.052444968 1.335718e-01
## 17 0.073015643 0.506466363 0.375842629 -3.878994e-02
## 18 0.285640056 0.279678569 0.724870242 2.425497e-06
## 19 0.899795909 -0.160189018 0.313333365 -4.932805e-01
## 20 -0.837910776 -0.284449852 0.126957345 9.719401e-02
## 21 -0.457918747 -0.470738666 0.040820927 9.170078e-02
## 22 -0.659972141 -0.677887989 -0.013051006 5.296748e-01
## 23 -0.059141553 -0.493242752 -0.304846085 -2.229935e-01
## 24 -0.012858421 -0.490548192 -0.321335240 2.417081e-01
## 25 -0.359108507 -0.319646123 -0.223217249 1.703698e-01
## 26 -0.431750853 0.112615461 0.139230799 3.619403e-01
## 27 -0.011872668 0.199844720 -0.168952586 -1.024942e-01
## 28 0.871493026 0.377734736 0.100082464 2.019070e-01
## 29 -0.535327145 -0.052133061 -0.170344007 1.219043e-01
## 30 -0.097574341 -0.145303795 -0.434683405 2.525539e-01
## 31 0.362800416 0.615221055 0.237118399 1.577463e-01
## 32 1.065540864 0.003289926 0.301468243 -5.452623e-02
## 33 -0.220080286 0.208330577 0.288215349 2.020110e-02
## 34 0.623281390 -0.107013907 0.072545643 2.574100e-02
## 35 -0.171299383 0.221919526 0.182702397 1.351032e-01
## 36 0.199199423 -0.225959650 0.286488201 1.880307e-01
## 37 -1.100732106 0.148237214 0.042613416 2.120576e-01
## 38 -0.006331597 0.408361693 0.229178312 3.305682e-01
## 39 0.270281671 0.189274912 0.459414350 9.112164e-02
## 40 -1.189357198 -0.171110587 -0.144559855 1.339277e-01
## 41 -0.282244193 -0.190271797 0.233366862 1.918090e-01
## 42 0.814467408 0.087220201 0.641617258 1.756224e-01
## 43 -0.426057495 0.176358945 -0.252737574 -2.239559e-01
## 44 -0.085928789 0.065307529 0.590079867 4.745373e-01
## 45 0.472678263 -0.049496470 0.272167229 2.622616e-01
## 46 0.593112800 -0.042583331 0.174619061 1.756565e-01
## 47 0.047420763 0.199562466 -0.179865338 2.124277e-02
## 48 0.122841972 0.089854603 0.249221674 2.914183e-02
## 49 -0.113865530 0.327373033 0.365849328 2.690395e-01
## 50 0.528660258 -0.725444392 0.643750457 -1.105953e-01
## 51 -0.381210855 -0.403046087 0.226595035 1.322432e-01
## 52 -0.535677231 -0.323372039 -0.208294720 -1.343351e-01
## 53 0.284457857 0.086582358 -0.196510172 -7.133751e-02
## 54 0.311878507 -0.003982141 -0.180983459 6.228677e-02
## 55 0.177275244 -0.172555036 0.355557584 2.725616e-02
## 56 0.328030058 0.175971344 0.078939025 5.076298e-01
## 57 -0.040280424 0.055246235 -0.024195628 2.467617e-01
## 58 0.076562562 0.127011403 0.103432656 -2.505831e-02
## 59 0.254164895 0.559169145 0.156378044 -5.582207e-02
## 60 0.350305311 0.603278404 -0.206599427 5.056228e-01
## 61 0.132177226 0.305758267 0.020830388 1.761041e-01
## 62 0.116293816 0.105863349 0.749899516 3.904870e-01
## 63 0.237305764 0.145212476 0.151569112 -1.452982e-01
## 64 -0.030018263 0.234195918 -0.236102848 1.325675e-01
## 65 -0.911150675 -0.281427947 0.199054287 1.158830e-01
## 66 -0.819279698 0.203763724 0.022064127 -2.289588e-01
## 67 -0.164709679 -0.180129323 -0.054108573 -3.779094e-01
## 68 0.480054364 -1.096825023 -0.021278088 -4.375724e-02
## 69 0.236190868 0.992214650 -0.327381959 6.819688e-02
## 70 0.242606717 -0.728809158 -0.473888191 1.538005e-01
## 71 0.241618888 0.458603326 0.427684364 4.179757e-02
## 72 -0.756048843 0.459445913 -0.368138728 -5.723547e-02
## 73 0.095261942 0.183845273 0.356476811 3.109822e-02
## 74 1.772533874 0.101315890 -0.399317651 -2.306761e-01
## 75 1.077114936 0.446710474 -1.038428157 2.730546e-01
## 76 -0.205554469 -0.581635924 0.559317234 1.952610e-01
## 77 -0.406809164 -0.209575849 0.402879583 1.198674e-02
## 78 0.061699007 -0.339973712 0.206429593 1.115953e-01
## 79 -0.367792564 0.182633641 -0.024246874 -1.886460e-01
## 80 0.247070609 -0.011953181 -0.069752730 -6.539942e-02
## 81 -0.142499750 -0.481884016 -0.062903982 3.674748e-02
## 82 -0.128074378 -0.366161160 -0.114945228 -4.351062e-01
## 83 0.127560537 0.038184161 -0.268338423 1.662357e-01
## 84 0.024478939 0.213787961 0.844659732 1.690583e-01
## 85 -1.221059381 0.194746144 -0.558334380 -6.963697e-02
## 86 -0.591859496 -0.278389371 -0.424158370 -1.083328e-01
## 87 -0.041538759 0.100032604 0.349361065 1.566881e-01
## 88 0.315997649 -0.791118721 -0.220476254 2.012243e-01
## 89 0.333722517 -0.155749721 -0.054712430 -1.068537e-02
## 90 0.641759217 0.062202450 -0.465277123 8.114360e-02
## 91 -0.662568071 0.180643104 0.141211259 3.219185e-02
## 92 -0.395682822 -0.441060093 0.144818263 2.666972e-01
## 93 -0.423495435 0.466207546 0.547647968 -1.724250e-02
## 94 -0.799089293 -0.262314160 -0.395862677 3.350125e-02
## 95 -0.202275478 -0.215710790 -0.439524441 3.985851e-01
## 96 0.256542532 0.444304565 -0.355866473 -2.898951e-01
## 97 -0.672506479 0.213466367 -0.246594462 5.217980e-01
## 98 -0.410326780 0.067145619 -0.071397273 -1.339747e-01
## 99 0.472993931 0.586894835 0.121222927 -4.529788e-01
## 100 -0.643817539 0.082434301 -0.103521757 -2.431198e-01
## 101 0.952397591 -0.635434538 0.121534194 -2.221077e-01
## 102 -0.015203004 -0.123583738 0.073240988 -5.586943e-02
## 103 -0.004511193 -0.057417032 -0.337865213 -1.067782e-02
## 104 0.664312646 0.572003354 0.036576730 4.051316e-01
## 105 0.744810915 -0.521831614 -0.348668065 -2.053581e-01
## 106 0.044183639 -0.550362863 0.395095961 -2.728733e-01
## 107 -0.258031047 -0.607801899 0.154653855 -2.980685e-01
## 108 -0.245221885 0.236884290 0.666432356 -1.363482e-01
## 109 -0.047971051 0.178652303 -0.012168260 8.601325e-02
## 110 -0.568930079 0.214709604 -0.590549693 -3.752495e-01
## 111 0.735615066 0.623412010 -0.154137403 3.482463e-01
## 112 0.078660746 0.598382620 0.152477935 6.570078e-02
## 113 -0.693680931 -0.706261547 0.247088968 -2.809547e-01
## 114 -0.171999945 0.331719258 0.010882339 3.163300e-01
## 115 0.120499348 -0.021791075 -0.076245495 -4.318472e-02
## 116 0.258367532 -0.715929944 -0.097430826 1.623530e-01
## 117 0.496016154 -0.299920813 -0.226550067 7.692405e-02
## 118 0.006120640 0.015076562 0.317284786 -8.426638e-02
## 119 -0.329134323 0.312377117 0.495320883 2.009219e-01
## 120 0.330767282 0.009152936 -0.199298377 -2.696511e-02
## 121 0.395898115 -0.150339289 -0.294362366 -2.394172e-01
## 122 0.133515816 -0.833373649 1.103369349 -1.132066e+00
## 123 -0.026994082 0.005120869 0.205420551 5.730117e-02
## 124 0.189287442 0.364380598 0.322083196 -1.155165e-01
## 125 -0.445389974 -0.036775275 -0.284518432 -8.953603e-02
## 126 0.393234211 -0.048844594 0.185347209 -2.304369e-01
## 127 -0.015737509 0.574121421 0.557519936 -3.105152e-01
## 128 0.345844581 0.376844646 0.641545633 9.614070e-02
## 129 0.065074821 0.618061190 0.473370891 -1.030181e-01
## 130 0.416131234 0.262613021 0.204047808 1.432466e-01
## 131 -0.535316955 1.017342492 -0.004143416 -5.768163e-01
## 132 -0.561186334 0.397360179 0.310359004 -4.120753e-01
## 133 -0.011876987 0.528773370 0.562615365 -2.920870e-01
## 134 0.031734286 0.694492749 0.188310957 -1.690039e-01
## 135 0.004553365 0.650194749 -0.678551873 -7.366263e-02
## 136 0.408949326 -0.171512710 -0.078553918 -2.142815e-01
## 137 0.193057550 0.571426289 -0.125759587 -1.806482e-01
## 138 0.426123667 0.071986575 -0.081820525 1.182596e-01
## 139 0.134417253 0.075983746 -0.313578833 -1.817526e-01
## 140 0.549011788 0.205129315 -0.849500737 1.019443e-01
## 141 -0.379269652 -0.075808581 -0.803960373 -3.239036e-01
## 142 0.120758130 -0.260617991 -0.762385024 -4.431325e-01
## 143 -0.335743473 0.231976084 -0.537088182 -2.253459e-01
## 144 -0.078675173 0.268366949 -0.618158741 -2.223151e-01
## 145 0.498856957 -0.994842346 -0.089162844 -2.074232e-01
## 146 0.667585040 0.850996345 -0.308153976 -3.699405e-01
## 147 -0.598613712 0.661897895 0.257795257 -1.194931e-01
## 148 0.222071461 -0.282816688 -0.149241323 5.824272e-02
## 149 0.178160518 0.156668455 -0.170975177 1.358834e-01
## 150 -0.104942033 -0.332520457 0.877982107 -1.824441e-01
## 151 -0.606316553 0.194454835 0.823806727 -2.312916e-01
## 152 -0.437330170 -0.572723334 0.722739448 8.394095e-02
## 153 -0.474682514 1.004743309 -0.004154291 2.747870e-01
## 154 -0.120632383 -0.441409476 0.012539614 8.146901e-02
## 155 0.377347554 0.010717956 0.052854085 -3.828702e-02
## 156 0.571687574 0.006605533 0.065051116 7.556944e-02
## 157 -0.665944154 -0.041839100 -0.093559981 1.227862e-01
## 158 1.326308401 -0.024421607 -0.198830040 1.073614e-01
## 159 -0.278215538 -0.093309590 -0.585735387 4.790010e-01
## 160 -0.364882734 -0.091226683 -0.588880011 4.926426e-01
## 161 0.449840196 0.115592440 -0.131176801 2.853592e-01
## 162 -0.217844295 0.088372011 -0.658024359 -1.833743e-01
## 163 0.021446906 -0.327255509 -0.438853089 -1.887735e-01
## 164 -0.196476193 0.158350184 -0.244613942 -3.790340e-01
## 165 -0.080275816 -0.470908999 0.192106698 2.510633e-02
## 166 -0.009415628 -0.117955601 0.088198638 -4.672457e-02
## 167 -0.125549749 -0.788480062 0.131882983 1.760682e-01
## 168 0.060332382 -1.072554369 0.028098695 1.359398e-01
## 169 -0.217910235 -0.156844681 -0.195987742 -3.888823e-02
## 170 -0.169193338 -0.250893595 -0.263014837 2.081887e-01
## 171 -0.187930939 -0.250201682 -0.138953326 -1.125676e-01
## 172 -0.135547013 -0.795321881 0.226878455 2.174743e-01
## 173 -0.598772128 -0.104632309 -0.306587295 7.278809e-03
## 174 0.136398554 -0.174315544 -0.198243688 -9.368622e-02
## 175 0.253570543 0.276738278 -0.184543121 2.420908e-02
## 176 0.501226372 -0.691386023 0.166565798 3.160658e-02
## 177 0.312903079 -0.343151836 -0.109206813 -1.025339e-01
## 178 -0.237612114 0.189332048 -0.163628435 2.641713e-01## [1] "Los valores propios, vectores propios y scores los guarde por si acaso los necesite mas adelantecomo archivos CSV."Componentes PRINCIPALES
###Indique aqu? cu?l es el concepto que se utiliza para la selecci?n de componentes_ ##principales_
La importancia de elegir los componentes principales radica en que permiten extraer la información más relevante de un conjunto de datos,la elección depende del juicio que se tenga y del problema en cuestión. Se puede elegir 2 o mas componentes.
## [1] "Muestro los resultados de la varianza y varianza acumulad:"## Component Eigenvalue Explained_Variance Cumulative_Variance
## 1 1 5.53594804 39.5424860 39.54249
## 2 2 2.49707625 17.8362589 57.37874
## 3 3 1.44607422 10.3291016 67.70785
## 4 4 0.92791783 6.6279845 74.33583
## 5 5 0.87750252 6.2678751 80.60371
## 6 6 0.67277834 4.8055596 85.40927
## 7 7 0.55379896 3.9557068 89.36497
## 8 8 0.35003417 2.5002441 91.86522
## 9 9 0.29454194 2.1038710 93.96909
## 10 10 0.26230610 1.8736150 95.84270
## 11 11 0.22584842 1.6132030 97.45591
## 12 12 0.16879672 1.2056908 98.66160
## 13 13 0.12956418 0.9254584 99.58705
## 14 14 0.05781232 0.4129451 100.00000##Realice un an?lisis de la visualizaci?n anterior, que indica
Relaci?n entre las variables originales y las Componentes Principales
Realice un an?lisis de la visualizaci?n anterior, que indica
El biplot muestra cómo las variables originales están relacionadas con los componentes principales y entre ellas.
El mismo Identifica cuáles variables contribuyen más a los componentes principales.
Indique cual es el concepto de la calidad de la representaci?n cos2
## Cargando paquete requerido: viridisLite
##Realice un an?lisis de la visualizaci?n anterior, que indica_
El gráfico muestra varios puntos donde cada punto en el gráfico representa una observación. El color indica la calidad de representación (cos2), donde los colores más oscuros representan observaciones mejor representadas.
Parte 2 MDS de wine
En sus propias palabras indique cuales son los beneficios de hacer un an?lisis de conglomerados, en que nos ayuda en la visualizaci?n de los datos
Según se visualiza este tipo de gráficos no solo muestra la calidad de representación de las observaciones, sino que también sugiere agrupamientos implícitos.
Estos conglomerados pueden guiar análisis posteriores, como la identificación de patrones específicos o la segmentación de los datos.
En caso de ser necesario, se podría complementar con un algoritmo de clustering explícito para definir estos grupos más claramente
Indique aqu? que es la matriz de distancias, que algoritmos de distancias existen
Una matriz de distancia es una matriz que contiene la distancia entre cada par de elementos de un conjunto de datos Hay varias funciones disponibles para crear una matriz de distancia, como dist(), daisy() y vegdist() de los paquetes stats, cluster y vegan respectivamente
LOs Algoritmos de distancia que se conoce pueden ser los siguientes: Distancia de Minkowski: generaliza las distancias euclidianas y manhattan. Distancia de Mahalanobis: considera la correlación entre variables. Distancia Coseno: mide la similitud entre dos vectores en términos de su ángulo.
Cree el diagrama de los componentes principales del MDS
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Los widgets de Shiny son herramientas interactivas que permiten a los usuarios ingresar argumentos y valores en aplicaciones web. Facilitan la comunicación entre la interfaz de usuario y el servidor, permitiendo que los datos se modifiquen en tiempo real según la interacción del usuario. Cada widget tiene argumentos específicos que definen su comportamiento y apariencia, como el nombre del widget, tipo de entrada, valor inicial y opciones personalizadas.
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