this is my first time asking a question here, so if I'm doing something wrong please guide me to the right place. I have a big and clean dataset. (29000+ , 24). The thing is that I have to calculate the churn rate based on 4 different categorical columns, and I'm given just 1 column that contains the subs for a given period. I have a date column too. My idea on calculating the churn is to do
churn_rate= (Sub_start_period-Sub_end_period)/Sub_start_period*100 The Problem
I don't know how to group the data using these 4 different categorical variables. Also If I manage to do so I would end up with more than 200 different tables, so I don't believe this would be a good approach.
My goal is able to predict the churn rate using the information in the table but I should be able to determine the churn rate based on these variables. The churn is not given, it has to be calculated, so I'm having problems here as I can't think of a way of working through this.