Boxplot outlier values into a table - r

Question

I was wondering how I could go about trying to take outliers from Boxplot$out (returns the outliers within the data) and put them into a table which shows the class they belong to e.g. if outlier is from class "Van", "Bus, "Saab" etc..
I have tried using which() function but this returns only the index of the outlier and not the class. I am not sure how to go about putting this into a table.
Any help would be greatly appreciated!
library(reshape2)
vehData <-
structure(
list(
Samples = 1:6,
Comp = c(95L, 91L, 104L, 93L, 85L,
107L),
Circ = c(48L, 41L, 50L, 41L, 44L, 57L),
D.Circ = c(83L,
84L, 106L, 82L, 70L, 106L),
Rad.Ra = c(178L, 141L, 209L, 159L,
205L, 172L),
Pr.Axis.Ra = c(72L, 57L, 66L, 63L, 103L, 50L),
Max.L.Ra = c(10L,
9L, 10L, 9L, 52L, 6L),
Scat.Ra = c(162L, 149L, 207L, 144L, 149L,
255L),
Elong = c(42L, 45L, 32L, 46L, 45L, 26L),
Pr.Axis.Rect = c(20L,
19L, 23L, 19L, 19L, 28L),
Max.L.Rect = c(159L, 143L, 158L, 143L,
144L, 169L),
Sc.Var.Maxis = c(176L, 170L, 223L, 160L, 241L, 280L),
Sc.Var.maxis = c(379L, 330L, 635L, 309L, 325L, 957L),
Ra.Gyr = c(184L,
158L, 220L, 127L, 188L, 264L),
Skew.Maxis = c(70L, 72L, 73L,
63L, 127L, 85L),
Skew.maxis = c(6L, 9L, 14L, 6L, 9L, 5L),
Kurt.maxis = c(16L,
14L, 9L, 10L, 11L, 9L),
Kurt.Maxis = c(187L, 189L, 188L, 199L,
180L, 181L),
Holl.Ra = c(197L, 199L, 196L, 207L, 183L, 183L),
Class = c("van", "van", "saab", "van", "bus", "bus")
),
row.names = c(NA,
6L), class = "data.frame")
#Remove outliers
removeOutliers <- function(data) {
OutVals <- boxplot(data)$out
remOutliers <- sapply(data, function(x) x[!x %in% OutVals])
return (remOutliers)
}
vehDataRemove1 <- vehData[, -1]
vehDataRemove2 <- vehDataRemove1[,-19]
vehData <- vehDataRemove2
vehClass <- vehData$Class
boxplot(vehData)
#Begin removing outliers
removeOutliers1 <- removeOutliers(vehData)
removeOutliers2 <- removeOutliers(removeOutliers1)

Answer 1

This can be simplified. Starting with your data frame vehData. First get the rownumbers of the outliers. In my comment I accidentally left out the seq() function:
vehDataRemove <- vehData[, -c(1, 20)]
OutVals <- boxplot(vehDataRemove)
idx <- sapply(seq(length(OutVals$out)), function(x) which(vehDataRemove[, OutVals$group[x]] == OutVals$out[x]))
idx
# [1] 5 5 6 5 3
Notice that three outliers are in the 5th row. Now remove the rows with outliers:
NoOuts <- vehDataRemove[-unique(idx), ]
NoOuts
# Comp Circ D.Circ Rad.Ra Pr.Axis.Ra Max.L.Ra Scat.Ra Elong Pr.Axis.Rect Max.L.Rect Sc.Var.Maxis Sc.Var.maxis Ra.Gyr Skew.Maxis Skew.maxis Kurt.maxis Kurt.Maxis Holl.Ra
# 1 95 48 83 178 72 10 162 42 20 159 176 379 184 70 6 16 187 197
# 2 91 41 84 141 57 9 149 45 19 143 170 330 158 72 9 14 189 199
# 4 93 41 82 159 63 9 144 46 19 143 160 309 127 63 6 10 199 207
So you have lost half of your data! Alternatively set the outliers to missing values:
Outs2NA <- vehDataRemove
Outs2NA[cbind(idx, OutVals$group)] <- NA
Outs2NA
# Comp Circ D.Circ Rad.Ra Pr.Axis.Ra Max.L.Ra Scat.Ra Elong Pr.Axis.Rect Max.L.Rect Sc.Var.Maxis Sc.Var.maxis Ra.Gyr Skew.Maxis Skew.maxis Kurt.maxis Kurt.Maxis Holl.Ra
# 1 95 48 83 178 72 10 162 42 20 159 176 379 184 70 6 16 187 197
# 2 91 41 84 141 57 9 149 45 19 143 170 330 158 72 9 14 189 199
# 3 104 50 106 209 66 10 207 32 23 158 223 635 220 73 NA 9 188 196
# 4 93 41 82 159 63 9 144 46 19 143 160 309 127 63 6 10 199 207
# 5 85 44 70 205 NA NA 149 45 19 144 241 325 188 NA 9 11 180 183
# 6 107 57 106 172 50 NA 255 26 28 169 280 957 264 85 5 9 181 183