check_data_dict_missing_categories: Assess categorical variables for non-Boolean values in...

In madshapR: Support Technical Processes Following 'Maelstrom Research' Standards

Assess categorical variables for non-Boolean values in 'missing' column

Description

Generates a data frame report of any categorical variables with non-Boolean (or compatible with boolean) values in the 'missing' column of the 'Categories' element. This report can be used to help assess data structure, presence of fields, coherence across elements, and taxonomy or data dictionary formats.

Usage

check_data_dict_missing_categories(data_dict)

Arguments

data_dict

A list of data frame(s) representing metadata to be evaluated.

Details

A data dictionary contains the list of variables in a dataset and metadata about the variables and can be associated with a dataset. A data dictionary object is a list of data frame(s) named 'Variables' (required) and 'Categories' (if any). To be usable in any function, the data frame 'Variables' must contain at least the name column, with all unique and non-missing entries, and the data frame 'Categories' must contain at least the variable and name columns, with unique combination of variable and name.

Value

A data frame providing categorical values which 'missing' column is not a boolean.

Examples

{

# use madshapR_DEMO provided by the package

data_dict <- madshapR_DEMO$`data_dict_TOKYO - errors`
check_data_dict_missing_categories(data_dict)

}

madshapR documentation built on May 29, 2024, 7:43 a.m.