tab_to_treat: Unnest Data Frames to Create a Usable Flat Format

In InseeFrLab/rtauargus: Using Tau-Argus from R

Unnest Data Frames to Create a Usable Flat Format

Description

This function processes nested data frames representing tables from hierarchical clusters, and transforms them into a flat, easy-to-read format. Each column corresponds to a dplyr::distinct variable, simplifying downstream analysis and use.

Usage

tab_to_treat(list_independent_tables)

Arguments

list_independent_tables

A list of nested tibbles, typically the output of grp_tab_in_cluster(), where each tibble represents independent tables grouped by clusters.

Value

A list of unnested tibbles, where each tibble contains the following columns:

• table_name: The name of the table.

• field: The field name associated with the table.

• indicator: Indicators related to the table.

• ⁠spanning_*⁠: Columns derived from the spanning metadata (expanded into multiple columns).

• ⁠hrc_spanning_*⁠: Columns derived from hierarchical spanning metadata (expanded into multiple columns).

Examples

## Not run: 
# Example data
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)

# Detect inclusion relationships
list_desc_links <- create_edges(list_split)

# Group tables based on inclusion relationships
list_translation_tables <- grp_tab_names(list_desc_links)

# Regroup tables within each cluster
list_independent_tables <- grp_tab_in_cluster(list_split, list_translation_tables)

# Flatten the nested data for downstream use
list_tab_to_treat <- tab_to_treat(list_independent_tables)

# View structure of the results
str(list_tab_to_treat)

## End(Not run)

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