This question could go here or on S.O. perhaps...Suppose that your training dataset contains both categorical and continuous data such as this setup:  Animal, breed,  sex, age, weight, blood_pressure, annual_cost cat,    calico, M,   10,  15    ,   100         , 100  cat,    tabby,  F,   5,   10    ,   80          , 200 dog,    beagle, M,   3,   30    ,   90          , 200 dog,    lab,    F,   8,   75    ,   80          , 100And the dependent variable to be predicted is the annual vet cost. I'm a bit confused as to the specific techniques available to deal with such a dataset. What are the methods commonly used to deal with datasets that are a mixture of both continuous and categorical data? 
Machine Learning With Categorical and Continuous Data
python;machine learning