How to start building a statistical regression analysis model with multiple categorical/discrete input variables of high dimension in Python
First, you have to pre-process your data. it includes encoding your categorical variables. You can either do it using pandas.get_dummies, or sklearn.preprocessing.OneHotEncoder in your pipeline. Based on the algorithm you want to use, you usually have to standardize your numerical variables. this can be done using any of sklearn.preprocessing methods such as StandardScaler.

If you want to do logistic regression, you have to categorize your output variable - time - to classes like ['less than 1000 min', 'more than 1000 min']. Otherwise, if you want to keep time as it is, you are doing a multiple regression.