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  3. Survival Analysis in Python

Exercise

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.

Instructions 1/4

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  • Create a Boolean mask for patients that received the new treatment.