add_group: Add aggregation to pipelines

In deident: Persistent Data Anonymization Pipeline

Add aggregation to pipelines

Description

add_group() allows for the injection of aggregation into the transformation pipeline. Should you need to apply a transformation under aggregation (e.g. add_shuffle) this helper creates a grouped data.frame as would be done with dplyr::group_by(). The function add_ungroup() is supplied to perform the inverse operation.

Usage

add_group(object, ...)

add_ungroup(object, ...)

Arguments

object	Either a data.frame, tibble, or existing DeidentList pipeline.
...	Variables on which data is to be grouped.

Value

A 'DeidentList' representing the untrained transformation pipeline. The object contains fields:

• deident_methods a list of each step in the pipeline (consisting of variables and method)

and methods:

• mutate apply the pipeline to a new data set

• to_yaml serialize the pipeline to a '.yml' file

Examples

pipe.grouped <- add_group(ShiftsWorked, Date, Shift)
pipe.grouped_shuffle <- add_shuffle(pipe.grouped, `Daily Pay`)
add_ungroup(pipe.grouped_shuffle, `Daily Pay`)

deident documentation built on April 3, 2025, 6:14 p.m.