1. The Hierarchical Format (YAML or JSON)

This is often the most intuitive and human-readable format, as itsindented structure visually represents the tree’s hierarchy. It ishighly recommended for creating and managing trees in a text editor.

Required Fields:

• name: The name of the node.
• nodes: A list of child nodes (this key is used insteadof the reserved wordchildren).
• rule : Required for parent nodes, can beAND orOR
• question : Required for leaf nodes

name: Invest in Company Xrule: ANDnodes:-name: Financial Viabilityrule: ANDnodes:-name: Profitability and Growth Signalsrule: ORquestion:"Is the company showing strong signs of profitability?"nodes:-name: FIN1question:"Company demonstrates consistent, high revenue growth."# ... and so on

# This code shows how to load a YAML file from the package's example datayaml_path<-system.file("extdata","ethical.yml",package ="andorR")tree_from_yaml<-load_tree_yaml(yaml_path)# View the loaded treeprint(tree_from_yaml)

{"name":"Invest in Company X","rule":"AND","nodes":[{"name":"Financial Viability","rule":"AND","nodes":[{"name":"Profitability and Growth Signals","rule":"OR","question":"Is the company showing strong signs of profitability?","nodes":[{"name":"FIN1","question":"Company demonstrates consistent, high revenue growth."},#...andsoon

# This code shows how to load a JSON file from the package's example datajson_path<-system.file("extdata","ethical.json",package ="andorR")tree_from_json<-load_tree_json(json_path)# View the loaded treeprint(tree_from_json)

2. The Relational (ID/Parent) Format

This is a flat, tabular format common in spreadsheets and databases.The tree structure is defined by aparent column thatcontains theid of its parent node. This is also the formatof theethical dataset included in the package.

Required Fields:

• id: A unique numeric ID for every node. The root musthaveid = 0.
• name: The name/code for the node.
• parent: Theid of the parent node. Theroot’s parent should beNA.
• rule : Required for parent nodes, can beAND orOR
• question : Required for leaf nodes

The first few rows of theethical dataset look likethis:

To load this format, you can useload_tree_df() if youalready have a data frame, orload_tree_csv() to read itfrom a.csv file.

# Load the example 'ethical' data frame that comes with the packagedata(ethical)# Build the tree from the data frame objecttree_from_df<-load_tree_df(ethical)# The structure is identical to the one loaded from YAMLprint(tree_from_df$children[[1]]$name)# Prints "Financial Viability"#> [1] "Financial Viability"

3. The Path String Format

This is another flat-file format that is very robust. The hierarchyis defined by a singlepath column that contains the full,delimited path from the root to each node.

Required Fields:

• path: A string with a character (like/)separating the names of the nodes in the hierarchy.
• question: Required for leaves, NA for parentnodes.
• rule: Required for parent nodes, NA for leaves.

An excerpt from a CSV file in this format would look like this:

To load this format from a CSV file, use theload_tree_csv_path() function.

# This code shows how to load a path string CSV from the package's example datapath_csv_path<-system.file("extdata","ethical_path.csv",package ="andorR")tree_from_path<-load_tree_csv_path(path_csv_path)print(tree_from_path)