code: def adapt_airlines(airlines_dataset):
      airlines_dataset[
          "table_for_h2o_import.origin"
      ] = airlines_dataset["table_for_h2o_import.origin"].asfactor()
      airlines_dataset[
          "table_for_h2o_import.fdayofweek"
      ] = airlines_dataset["table_for_h2o_import.fdayofweek"].asfactor()
      airlines_dataset[
          "table_for_h2o_import.uniquecarrier"
      ] = airlines_dataset[
          "table_for_h2o_import.uniquecarrier"
      ].asfactor()
      airlines_dataset["table_for_h2o_import.dest"] = airlines_dataset[
          "table_for_h2o_import.dest"
      ].asfactor()
      airlines_dataset["table_for_h2o_import.fyear"] = airlines_dataset[
          "table_for_h2o_import.fyear"
      ].asfactor()
      airlines_dataset[
          "table_for_h2o_import.fdayofmonth"
      ] = airlines_dataset[
          "table_for_h2o_import.fdayofmonth"
      ].asfactor()
      airlines_dataset[
          "table_for_h2o_import.isdepdelayed"
      ] = airlines_dataset[
          "table_for_h2o_import.isdepdelayed"
      ].asfactor()
      airlines_dataset[
          "table_for_h2o_import.fmonth"
      ] = airlines_dataset["table_for_h2o_import.fmonth"].asfactor()
      return airlines_dataset
  
imports: import sys
  import os
  from tests import pyunit_utils
  import h2o
  from numpy import isclose
  from h2o.estimators.gbm import H2OGradientBoostingEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: adapt_airlines(airlines_dataset) and returns: airlines_dataset