I have a dataset that contains some categorical info about my users (like gender and country), whether they have churned or not and what's the time from their subscription to churn.
I want to use survival analysis and estimate the time between subscription to churn. My data has both censored data and event data. I want to plot Kaplan–Meier curve for two cohorts of male and female. But the data is highly skewed towards female (90% of the data is female users and 10% male users). For more context: I'm using Lifelines library and its KaplanMeierFitter.
Should I first balance the data for this two cohorts and then draw the Kaplan–Meier curve? or do I need not to care about the class imbalance in survival analysis.