Hi Nicholas, thankyou so much.
Okay ! I understand.
My goal that I want to achive is that I want to “ask” to the program:
"(1)What is the probability of a name called ‘JOHN’ ?. (2)And what is the probability to find customer whose name is ‘JOHN’(name_customer distribution) and his ‘id’(id_customers distribution) is 13467780 ?".
(I wrote the example for name and id here, but most commonly I look for name and age (that it is also an continuous distribution like ‘id’))
And the program could give me the probabilities between 0 and 1. (Note that ‘JOHN’ is inside a dictionary and his value is, for example, 30 in the name_customers distribution)
The first part of the question I learn right now how to do. (with an independent model as you told me)
But the second part, I need to combine both distributions in one model, but knowing that one is continuous(id_customers), and the other discrete(name_customers), I don’t know how to get that joint probability I want to get.
And the last thing you’re telling me, I use large numbers to make them as close as possible to a normal country identifier, so the 8-digit numbers.
Thankyou so much for you attention, I appreciate too much ! (from a PyMC beginner) 