code: def test_proportional_hazard_test_with_kmf_with_some_censorship():
      """
  
      library(survival)
      df <- data.frame(
        "var1" = c(0.209325, 0.693919, 0.443804, 0.065636, 0.386294),
        "T" = c(5.269797, 6.601666, 7.335846, 11.684092, 12.678458),
        "E" = c(1, 1, 1, 0, 1)
      )
  
      c = coxph(formula=Surv(T, E) ~ var1 , data=df)
      cox.zph(c, transform='km')
      """
  
      df = pd.DataFrame(
          {
              "var1": [
                  0.209325,
                  0.693919,
                  0.443804,
                  0.065636,
                  0.386294,
              ],
              "T": [5.269797, 6.601666, 7.335846, 11.684092, 12.678458],
              "E": [1, 1, 1, 0, 1],
          }
      )
  
      cph = CoxPHFitter()
      cph.fit(df, "T", "E")
  
      results = stats.proportional_hazard_test(cph, df)
      npt.assert_allclose(
          results.summary.loc["var1"]["test_statistic"],
          1.013802,
          rtol=1e-3,
      )
  
imports: import numpy
  import pandas
  import numpy.testing
  import pytest
  from pandas.testing import assert_frame_equal
  from lifelines import statistics
  from lifelines import CoxPHFitter, KaplanMeierFitter, WeibullFitter
  from lifelines.exceptions import StatisticalWarning
  from lifelines.datasets import load_waltons, load_g3, load_lymphoma, load_dd, load_regression_dataset, load_leukemia
label_desc: Use image node_id 34 for calling a global function with example usage: test_proportional_hazard_test_with_kmf_with_some_censorship() without return types