create_edges: Create a Data Frame of Table Inclusion Relationships

In InseeFrLab/rtauargus: Using Tau-Argus from R

Create a Data Frame of Table Inclusion Relationships

Description

This function analyzes a list of data frames (clusters of tables) and identifies inclusion relationships between tables. A table is considered to include another if all its spanning variables (columns defining the structure of the table) are contained within the spanning variables of the other table.

Usage

create_edges(list_split)

Arguments

list_split

A list of clusters of tables, where each cluster contains nested data frames. Typically, this is the output of the split_in_clusters function.

Details

For example, consider two tables to be published:

• T1: ⁠company_turnover = {nuts x size}⁠

• T2: ⁠company_turnover = {nuts x size x pollution}⁠

All the information in T1 is included in T2. By protecting T2, all cells in T1 will also be protected. This function identifies such inclusion relationships and outputs a data frame that describes these links.

Value

A list of data frames (list_desc_links), where each data frame describes the inclusion relationships (from and to) within a cluster of tables. Each row in a data frame indicates that the table in the from column is fully included in the table in the to column.

Examples

## Not run: 
data(metadata_pizza_lettuce)

# Convert wide metadata to long format
metadata_pizza_lettuce_long <- wide_to_long(metadata_pizza_lettuce)

# Identify hierarchical relationships
list_hrc_identified <- identify_hrc(metadata_pizza_lettuce_long)

# Split tables into clusters
list_split <- split_in_clusters(list_hrc_identified)

# Identify inclusion relationships between tables
list_desc_links <- create_edges(list_split)

# View the structure of the result
str(list_desc_links)

## End(Not run)

InseeFrLab/rtauargus documentation built on Feb. 25, 2025, 6:32 a.m.