code: def h_stats_data_with_empty_col():
      target = "CAPSULE"
      params = {
          "ntrees": 10,
          "learn_rate": 0.1,
          "max_depth": 2,
          "min_rows": 1,
          "seed": 1234,
      }
  
      train_frame_empty_col = h2o.import_file(
          path=pyunit_utils.locate(
              "smalldata/logreg/prostate_train.csv"
          )
      )
      train_frame_empty_col["DPROS"] = np.nan
      train_frame_empty_col[target] = train_frame_empty_col[
          target
      ].asfactor()
  
      gbm_h2o = H2OGradientBoostingEstimator(**params)
      xgb_h2o = H2OXGBoostEstimator(**params)
  
      test_model_empty_col(gbm_h2o, target, train_frame_empty_col)
      test_model_empty_col(xgb_h2o, target, train_frame_empty_col)
  
imports: import sys, os
  import h2o
  from tests import pyunit_utils
  from h2o.estimators import H2OGradientBoostingEstimator, H2OXGBoostEstimator
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: h_stats_data_with_empty_col() without return types