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Combine List of Dataframes into a Single Dataframe with Cluster Identification

Source: R/tab_to_treat.R
dataframe_result.Rd

This function consolidates a list of dataframes, each representing a cluster of tables, into a single dataframe. It includes an additional column, cluster, to identify the cluster each table belongs to.

Usage

dataframe_result(list_independent_tables)

Arguments

list_independent_tables

A list of tibbles, typically the output of grp_tab_in_cluster() or tab_to_treat(). Each tibble contains metadata for tables grouped within a specific cluster.

Value

A single dataframe (dfMetadata_to_treat) with the following structure:

  • cluster: Identifier for the cluster each table belongs to.

  • 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, ordered by numeric suffix.

  • hrc_spanning_*: Columns derived from hierarchical spanning metadata, ordered by numeric suffix.

Examples

if (FALSE) { # \dontrun{
# 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)

# Create a dataframe with a cluster id
dataframe_cluster_id <- dataframe_result(list_tab_to_treat)

# View the result dataframe
dataframe_cluster_id
} # }