Dot plot of outliers by detection method

For each numeric column of df, draws a dot plot with observations coloured by outlier status and row-name labels repelled away from flagged points. Three outlier-detection rules are available via method: mean ± 2 SD, median ± 2 MAD (rescaled), or boxplot IQR fences. Reference lines for the centre and the upper / lower bounds are overlaid on each plot.

Usage

plot_outlier(df, method = "mean", title = "", base_size = 10, pb = FALSE)

Arguments

df

Data frame or numeric vector. Non-numeric columns are silently dropped.

method

Character string selecting the outlier-detection rule:

"mean"

Flags observations more than 2 standard deviations from the mean.

"median"

Flags observations more than 2 rescaled MADs (\(2 \times \mathrm{MAD}/0.6745\)) from the median.

"boxplot"

Flags observations outside \(Q1 - 1.5 \times IQR\) or \(Q3 + 1.5 \times IQR\).

Default is "mean".

title

Character string used as the plot title. Default is "".

base_size

Base font size passed to theme_bw(). Default is 10.

pb

Logical; whether to display a progress bar in the console. Default is FALSE.

Value

A named list of ggplot objects, one per numeric column.

Author

unknown

Examples

vector <- generate_missing(rnorm(50), missing = 10)
df <- generate_missing(mtcars[, 1:2], missing = 10)
plot_outlier(df = vector, method = "mean", title = "random vector")

plot_outlier(df = vector, method = "median")

plot_outlier(df = vector, method = "boxplot")

plot_outlier(df = df, method = "mean", title = "random vector")


plot_outlier(df = df, method = "median")


plot_outlier(df = df, method = "boxplot")


plot_multiplot(plotlist = plot_outlier(df = mtcars[1:5, 2:5], method = "mean"), cols = 2)