def METHOD_NAME(dest_dir: str) -> None:
    # Load the dataset for FAOSTAT food explorer from garden.
    dataset_garden: catalog.Dataset = paths.load_dependency("faostat_food_explorer")
    # Get the table of all food products.
    table_garden = dataset_garden["all_products"]
    # Initialize new garden dataset.
    dataset = catalog.Dataset.create_empty(dest_dir)
    # Add dataset metadata.
    dataset.metadata = deepcopy(dataset_garden.metadata)
    dataset.metadata.namespace = "owid"
    dataset.metadata.short_name = "food_explorer"
    dataset.metadata.version = "latest"
    # Create new dataset in garden.
    dataset.save()
    # List all products in table
    products = sorted(table_garden.index.get_level_values("product").unique().tolist())
    for product in tqdm(products, file=sys.stdout):
        # Save a table (as a separate csv file) for each food product.
        table_product = table_garden.loc[product].copy()
        # Update table metadata.
        table_product.title = product
        # Rename columns, select the required ones, and sort columns and rows conveniently.
        table_product = table_product[list(EXPECTED_COLUMNS)].rename(columns=EXPECTED_COLUMNS)
        table_product = table_product[
            ["population"] + [column for column in sorted(table_product.columns) if column not in ["population"]]
        ]
        table_product = table_product.sort_index()
        table_product.metadata.short_name = (
            catalog.utils.underscore(name=product, validate=True).replace("__", "_").replace("_e_g_", "_eg_")
        )
        # Add table to dataset. Force publication in csv.
        dataset.add(table_product, formats=["csv"])