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Comparing patient soreness treatments

There is an experiment for a new soreness treatment, and you want to compare patients that received the new treatment versus the old one. You will fit a Kaplan-Meier estimator to each set of patient data and visualize their survival curves side-by-side.

The DataFrame is called recur and contains columns

  • age: the age of the patient;
  • treat: the treatment that the patient received (0 if new, 1 if old);
  • duration: the duration post treatment in hours;
  • censor: whether the event is censored;

The pandas package is loaded as pd, the KaplanMeierFitter class is imported from lifelines, and the pyplot module has been import from matplotlib as plt.

Additionally, a KaplanMeierFitter instance called kmf and a subplot figure called ax have been created for you.

This exercise is part of the course

Survival Analysis in Python

View Course

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Mask for new treatment
new = (____)
Edit and Run Code