Throughout this course, we will use the well-known IBM Telco customer churn dataset as example to demonstrate the utility of survival analysis for deriving business insights. The Python package
lifelines and R package
survival both provide easy implementations to plot KM survival curves of a dataset that contains (at least) two parameters for each subject observed: 1) whether the event of interest has occurred and 2) if so, when did it occur relative to the start point of observation. For the Telco data set, this correspond to the
Tenure columns, respectively.