generalize: Generalize a Column

In shuklak13/anonymizeR: Simple Functions to Anonymize Data

Description

Generalize a Column

Usage

generalize(x, col, splits = NULL, numSplits = NULL, rightClosed = FALSE,
  newCategories = NULL, mapping = NULL)

Arguments

x	a data.frame
col	the column that is to be generalized - may be numeric (column indices) or character (column names)
splits	numeric - numeric vector containing the numbers which should serve as boundary points between each numeric category. Either this or numSplits is a required argument for numeric generalization.
numSplits	numeric - number of splits desired. Either this or numeric is a required argument for numeric generalization
rightClosed	numeric - should boundaries be closed right? False by default
newCategories	categorical - new categories to replace the old
mapping	categorical - a numeric vector containing a mapping of old categories to new categories. See details for more information.

Details

This function calls either generalize_numeric or generalize_categorical depending on which arguments are provided. splits or numSplits are required for generalize_numeric, so if either of these arguments are provided, generalize_numeric will be called. newCategories and mapping are required for generalize_categorical. If neither splits nor numSplits is provided, and both newCategories and mapping are provided, then generalize_categorical is called.

Value

data.frame with with specified column generalized

See Also

Other generalize.functions: generalizeCategorical; generalizeNumeric

Examples

age <- c(51, 42, 23, 44, 25)
maritalStatus <- c("Married", "Single", "Single", "Divorced", "Married")
data <- data.frame(age, maritalStatus)

generalize(data, 1, splits=c(30, 50))
generalize(data, 2, newCategories=c("Has Been Married","Has Not Been Married"), mapping=c(1,2,1,1))

shuklak13/anonymizeR documentation built on May 29, 2019, 9:27 p.m.