Build a Rating Matrix

Problem

Build a dense user-item rating matrix from sparse ratings.

ratings is a list of [user_index, item_index, rating] triples and missing entries are 0.0. Ignore out-of-range indices and let later duplicates overwrite earlier ratings. Return num_users rows of num_items floats.

Hint

Zero is the missing-value sentinel, so ratings must be positive to be observed.

Test cases

case 1

in: [[[0,0,5],[1,1,3]],2,2]

expected: [[5,0],[0,3]]

case 2

in: [[],2,3]

expected: [[0,0,0],[0,0,0]]

case 3

in: [[[0,0,4],[0,0,5]],1,1]

expected: [[5]]

case 4

in: [[[2,0,1]],2,2]

expected: [[0,0],[0,0]]

Starter codePython

def rating_matrix(ratings, num_users, num_items):
    # Your code here
    pass

4 test cases · run your code against them in the editor