Using the lifelines library, you can easily plot Kaplan-Meier plots, e.g. as seen in our previous post Minimal Python Kaplan-Meier Plot example:
from lifelines.datasets import load_leukemia from lifelines import KaplanMeierFitter df = load_leukemia() kmf = KaplanMeierFitter() kmf.fit(df['t'], df['Rx']) # t = Timepoints, Rx: 0=censored, 1=event kmf.plot()
What if you want a custom label instead of KM_estimates to appear in the legend?
Use kmf.fit(..., label='Your label'). Since we use the leukemias dataset for this example, we use the label 'Leukemia'
Full example:
from lifelines.datasets import load_leukemia from lifelines import KaplanMeierFitter # Load datasets df_leukemia = load_leukemia() # Fit & plot leukemia dataset kmf_leukemia = KaplanMeierFitter() kmf_leukemia.fit(df_leukemia['t'], df_leukemia['Rx'], label="Leukemia") ax = kmf_leukemia.plot() # Set Y axis to fixed scale ax.set_ylim([0.0, 1.0])
