TypeError：列表索引必须是整数或切片，而不是电影分级数据的元组

Question

I tried looking in other articles on how to solve this issue but I am not getting anywhere for some reason. I get the error "TypeError: list indices must be integers or slices, not tuple" and wanted to see if anybody can point out the reason in my code.

Thanks in advance!

nb_users = int(max(max(training_set[:,0]), max(test_set[:,0])))
nb_movies = int(max(max(training_set[:,1]), max(test_set[:,1])))

def convert(data):
    new_data = [] expects that. 1 list per user
    for id_users in range(1, nb_users + 1):
        id_movies = data[:,1][data[:,0] == id_users]
        id_ratings = data[:,2][data[:,0] == id_users]
        ratings = np.zeros(nb_movies)
        ratings[id_movies - 1] = id_ratings
        new_data.append(list(ratings))
    return new_data

training_set = convert(training_set)
test_set = convert(test_set)


TypeError: Traceback (most recent call last)
<ipython-input-35-d2825f049d11> in <module>()
      3 
      4 #take max user id/movie id for total numbers for test and train set.
----> 5 nb_users = int(max(max(training_set[:,0]), max(test_set[:,0])))
      6 nb_movies = int(max(max(training_set[:,1]), max(test_set[:,1])))
      7 

TypeError: list indices must be integers or slices, not tuple

Answer 1

You seem to use training_set as a Pandas dataframe, but it is actually a list.

You should first convert it to a dataframe; and the way to do this depends on the structure of training_set 's elements. For instance, if they are dictionaries, you can do this:

training_set_df = pandas.DataFrame(training_set)

And then use training_set_df instead of training_set .