I am trying to build a customized function to detect outliers on a dataset. The output that should return is the same as the function identify_outliers in rstatix()
identify_outliers_custom <- function(dt, values) {
q1 <- quantile(dt)[2]
q3 <- quantile(dt)[4]
iqr <- q3 - q1
lower_bound <- q1 - 1.5* iqr
upper_bound <- q3 + 1.5* iqr
dt$is.outlier <- ifelse(dt > upper_bound | dt < lower_bound, TRUE, FALSE)
dt$is.extreme <- ifelse(dt > q3 + 3 * iqr | dt < q1 - 3 * iqr, TRUE, FALSE)
return(dt)
}
Anyway, by applying this function on a dataset it turns back an error
mtcars %>% identify_outliers_custom(mpg)
Error in xtfrm.data.frame(x) : it is not possible xtfrm the data frame
How could it be corrected?
You are using dt at wrong places in your custom function. The error can be reproduced by passing a dataframe to quantile function.
quantile(mtcars)
Error in xtfrm.data.frame(x) : cannot xtfrm data frames
You may try this function.
identify_outliers_custom <- function(dt, values) {
# replace dt with values since we want to get quantile of one column
q1 <- quantile(values)[2]
q3 <- quantile(values)[4]
iqr <- q3 - q1
lower_bound <- q1 - 1.5* iqr
upper_bound <- q3 + 1.5* iqr
# Compare with values and not dt. Also no need for ifelse
dt$is.outlier <- values > upper_bound | values < lower_bound
dt$is.extreme <- values > q3 + 3 * iqr | values < q1 - 3 * iqr
return(dt)
}
mtcars %>% identify_outliers_custom(.$mpg)
# mpg cyl disp hp drat wt qsec vs am gear carb is.outlier is.extreme
#Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 FALSE FALSE
#Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 FALSE FALSE
#Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 FALSE FALSE
#Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 FALSE FALSE
#Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 FALSE FALSE
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