mappings for users and movies

mappings.py

def map_movies(movie_ids):
    '''takes a list of movie_ids and returns a list of dictionaries with movies information'''
    df = pd.read_csv('ml-1m/movies.dat', delimiter='::', header=None, 
        names=['movie_id', 'title', 'genre'], engine='python')

    # add years to a new column 'year' and remove them from the movie title
    df['year'] = df['title'].str[-5:-1]
    df['title'] = df['title'].str[:-6]

    # creates an ordered list of dictionaries with the movie information for all movie_ids 
    mapped_movies = [df[df['movie_id'] == i].to_dict('records')[0] for i in movie_ids]

    return mapped_movies


def map_users(user_ids):
    '''takes a list of user_ids and returns a list of dictionaries with user information'''
    df = pd.read_csv('ml-1m/users.dat', delimiter='::', header=None, 
        names=['user_id', 'gender', 'agerange', 'occupation', 'timestamp'], engine='python')
    df = df.drop(['timestamp'], axis=1)

    mapped_users = [df[df['user_id'] == i].to_dict('records')[0] for i in user_ids]

    return mapped_users