detect_outliers: Flag outliers
In lewinfox/fast-ai-structured: Tools for Working With Structured Data

Flag any values that fall outside a specified range. By default, any observation more than 1.5x the interquartile range will be tagged. The 'clip_outliers' option controls whether values outside this range will be trimmed to the appropriate max or min.

1 2	detect_outliers(df, col, outlier_threshold = 1.5, clip_outliers = FALSE, flag_outliers_both_directions = FALSE)

`df`	The data.frame to be transformed
`col`	The column of interest
`outlier_threshold`	Values more than `outlier_threshold` times the interquartile range outside the interquartile range are considered outliers.
`clip_outliers`	If `TRUE`, values above or below the specified threshold will be clipped to the relevant threshold.
`flag_outliers_both_directions`	If `TRUE`, two boolean columns will be added to indicate whether the values was above or below the detection threshold.