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 to make the Y axis start from 0.0 and not from approx. 0.2 as in this example?
Remember that lifelines just calls matplotlib internally and km.plot() returns the ax object that you can use to manipulate the plot. In this specific case, you can use
ax.set_ylim([0.0, 1.0])
to stop autoranging the Y axis and set its range to fixed [0.0, 1.0].
Full 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 ax = kmf.plot() # Set Y axis range to [0.0, 1.0] ax.set_ylim([0.0, 1.0])
