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Original file line number | Diff line number | Diff line change |
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import pandas as pd | ||
import warnings | ||
import os | ||
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app_dir = os.path.dirname(os.path.abspath(__file__)) | ||
code_dir = os.path.dirname(app_dir) | ||
project_dir = os.path.dirname(code_dir) | ||
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#warnings.filterwarnings("ignore") | ||
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def recommendForNewUser(user_rating): | ||
ratings = pd.read_csv(project_dir + "/data/ratings.csv") | ||
movies = pd.read_csv(project_dir + "/data/movies.csv") | ||
def recommend_for_new_user(user_rating): | ||
ratings = pd.read_csv(os.path.join(project_dir, "data", "ratings.csv")) | ||
movies = pd.read_csv(os.path.join(project_dir, "data", "movies.csv")) | ||
user = pd.DataFrame(user_rating) | ||
userMovieID = movies[movies["title"].isin(user["title"])] | ||
userRatings = pd.merge(userMovieID, user) | ||
user_movie_id = movies[movies["title"].isin(user["title"])] | ||
user_ratings = pd.merge(user_movie_id, user) | ||
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moviesGenreFilled = movies.copy(deep=True) | ||
copyOfMovies = movies.copy(deep=True) | ||
for index, row in copyOfMovies.iterrows(): | ||
copyOfMovies.at[index, "genres"] = row["genres"].split("|") | ||
for index, row in copyOfMovies.iterrows(): | ||
movies_genre_filled = movies.copy(deep=True) | ||
copy_of_movies = movies.copy(deep=True) | ||
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for index, row in copy_of_movies.iterrows(): | ||
copy_of_movies.at[index, "genres"] = row["genres"].split("|") | ||
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for index, row in copy_of_movies.iterrows(): | ||
for genre in row["genres"]: | ||
moviesGenreFilled.at[index, genre] = 1 | ||
moviesGenreFilled = moviesGenreFilled.fillna(0) | ||
movies_genre_filled.at[index, genre] = 1 | ||
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movies_genre_filled = movies_genre_filled.fillna(0) | ||
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userGenre = moviesGenreFilled[moviesGenreFilled.movieId.isin(userRatings.movieId)] | ||
userGenre.drop(["movieId", "title", "genres"], axis=1, inplace=True) | ||
userProfile = userGenre.T.dot(userRatings.rating.to_numpy()) | ||
moviesGenreFilled.set_index(moviesGenreFilled.movieId) | ||
moviesGenreFilled.drop(["movieId", "title", "genres"], axis=1, inplace=True) | ||
user_genre = movies_genre_filled[movies_genre_filled.movieId.isin(user_ratings.movieId)] | ||
user_genre.drop(["movieId", "title", "genres"], axis=1, inplace=True) | ||
user_profile = user_genre.T.dot(user_ratings.rating.to_numpy()) | ||
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movies_genre_filled.set_index(movies_genre_filled.movieId) | ||
movies_genre_filled.drop(["movieId", "title", "genres"], axis=1, inplace=True) | ||
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recommendations = (moviesGenreFilled.dot(userProfile)) / userProfile.sum() | ||
joinMoviesAndRecommendations = movies.copy(deep=True) | ||
joinMoviesAndRecommendations["recommended"] = recommendations | ||
joinMoviesAndRecommendations.sort_values( | ||
recommendations = (movies_genre_filled.dot(user_profile)) / user_profile.sum() | ||
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join_movies_and_recommendations = movies.copy(deep=True) | ||
join_movies_and_recommendations["recommended"] = recommendations | ||
join_movies_and_recommendations.sort_values( | ||
by="recommended", ascending=False, inplace=True | ||
) | ||
return [x for x in joinMoviesAndRecommendations["title"]][:201] | ||
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return list(join_movies_and_recommendations["title"][:201]) |
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