Creating Kaplan-Meier curves in Python

One of the best ways of presenting survival data is by constructing a specific data visualization called the Kaplan-Meier curve. What is the Kaplan-Meier curve? It is a graph that has two axes, X and Y, where X represents time and Y represents the probability of survival. Alternatively, Y can represent the proportion of the events occurring. The time axis (X) can be defined in days, months, or years and can be used to create equal intervals for presenting the survival data. The survival axis is relevant for the outcomes such as survival, mortality, progression of disease, or other clinical events relevant to specific clinical research questions. The Y axis can also be used to indicate whether the data was censored or not. This function most often looks like descending stairs, as shown in the following screenshot, due to the stepwise nature of the function.

This stepwise nature is due to each time point being a step at which the probability...