def METHOD_NAME(table_data, list_column_names):
    """Compute a categorical column to the table_data indicating where NaNs are.
    Args:
        table_data (pandas.DataFrame):
            The table data.
        list_column_names (list):
            The list of column names to check for NaNs.
    Returns:
        A dict with the column name as key and the column indicating where NaNs are as value.
        Empty dict if there are no NaNs.
    """
    nan_column_name = '#'.join(list_column_names) + '.nan_component'
    column = table_data[list_column_names].apply(get_nan_component_value, axis=1)
    if not (column == 'None').all():
        return pd.Series(column, name=nan_column_name)
    return None