I'm trying to create a feature for a churn model (binary classifier). The feature is mean of sales growth rates for several months. But if I just take the mean of sales for several months, I often get NAN or inf. since sales are often zeros. I could impute some numbers like 0 or mean as the missing sales but I feel I'm modifying the pattern/underling distribution. How would you go by creating such a feature for a classification model?