Scissors - Lindsey #66
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| def get_watched_avg_rating(user_data): | ||
| avg_rating = 0.0 | ||
| for movie in user_data["watched"]: | ||
| avg_rating = (movie["rating"])/len(user_data["watched"]) + avg_rating |
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This is a neat way to generate the average!
As an aside, another way to write this line is:
avg_rating += (movie["rating")/len(user_data["watched"])
| # print(user_data["watched"]) | ||
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| watched = user_data["watched"] | ||
| genre_freq_dict = calculate_genre_freq(watched) |
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| def get_friends_unique_watched(user_data): | ||
| unique_movie = [] |
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For readability I recommend naming variables to reflect their contents - in this case this is a list of unique movies, so I would name it unique_movies or unique_movie_list
| def get_new_rec_by_genre(user_data): | ||
| most_watched_genre = get_most_watched_genre(user_data) | ||
| print(most_watched_genre) | ||
| new_genre_recs = [] | ||
| for friend in user_data["friends"]: | ||
| for movie in friend["watched"]: | ||
| if movie["genre"] == most_watched_genre and movie not in user_data["watched"]: | ||
| new_genre_recs.append(movie) | ||
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| return new_genre_recs |
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Could you use the function get_friends_unique_watched in this function? Also, this will pass the tests as written, but what if two friends have watched the same movie that fits the criteria (it's not in the user's watched list & it's the most watched genre)? Currently this will repeat the recommendation rather than giving only unique recommendations.
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Great job! You hit the learning goals here. Overall, this was a fantastic first project, you should be proud! I left a few minor comments in the code, we will go over those at our 1:1. |
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