clean_messy_groups: Simplify data to a single value within a group

In billdenney/pknca.portation: Import and Export Data from PKNCA Using Data Standards

Description

During dataset generation, sometimes data from different sources may put missing values where consistent results should be present.

Usage

clean_messy_groups(data, keys, values, missing_value = NA)

replace_messy_groups(data, keys, values, missing_value = NA)

Arguments

data	The dataset (typically a data.frame or similar) to simplify
keys	Column names (as character strings) for grouping
values	Columns to from the original data as values that must be unique within a group (defaults to all columns other than keys)
missing_value	A scalar value indicating what should be considered missing and should be used for replacement if all values are missing (typically NA).

Value

A dataset with one row per key and one value in each column.

Functions

• replace_messy_groups: Both clean the groups and replace them back in the original dataset.

billdenney/pknca.portation documentation built on May 3, 2019, 2:55 p.m.