code: def coxph_concordance_and_baseline():
      shelter = read_csv(
          pyunit_utils.locate("smalldata/coxph_test/shelter.csv"),
          low_memory=False,
      )
      shelter.drop("animal_id", axis=1, inplace=True)
      for colname in [
          "animal_type",
          "animal_breed",
          "activity_number",
          "census_tract",
          "activity_sequence",
          "intake_condition1",
          "intake_condition2",
          "intake_condition3",
          "council_district",
          "intake_type",
          "intake_subtype",
          "due_out",
          "outcome_type",
          "outcome_subtype",
          "intake_condition",
          "outcome_condition",
          "chip_status",
      ]:
          shelter[colname] = shelter[colname].astype("category")
      for colname in [
          "end_ts",
          "intake_date",
          "intake_time",
          "start_ts",
      ]:
          shelter[colname] = shelter[colname].astype("datetime64")
  
      without_strata(shelter)
      with_strata(shelter)
      with_strata_one_column(shelter)
  
file_path: h2o-3/h2o-py/tests/testdir_algos/coxph/pyunit_coxph_baseline_names_shelter.py
imports: import sys
  import h2o
  from lifelines import CoxPHFitter
  from pandas.testing import assert_frame_equal
  from pandas import read_csv
  import numpy
  from tests import pyunit_utils
  from h2o.estimators.coxph import H2OCoxProportionalHazardsEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: coxph_concordance_and_baseline() without return types