code: def spaces_in_column_names():
      train_data = h2o.upload_file(
          path=pyunit_utils.locate(
              "smalldata/jira/spaces_in_column_names.csv"
          )
      )
      train_data.show()
      train_data.describe()
      train_data["r e s p o n s e"] = train_data[
          "r e s p o n s e"
      ].asfactor()
      X = [
          "p r e d i c t o r 1",
          "predictor2",
          "p r e d i ctor3",
          "pre d ictor4",
          "predictor5",
      ]
      gbm = H2OGradientBoostingEstimator(
          ntrees=1, distribution="bernoulli", min_rows=1
      )
      gbm.train(x=X, y="r e s p o n s e", training_frame=train_data)
      gbm.show()
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.gbm import H2OGradientBoostingEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: spaces_in_column_names() without return types