import pandas as pd from google.colab import files import io # Step 1: Upload the files uploaded_files = files.upload() all_data = [] # Step 2, 3, and 4: Read each uploaded CSV, add genre column, and concatenate for filename in uploaded_files.keys(): # Read the file content into a pandas DataFrame df = pd.read_csv(io.StringIO(uploaded_files[filename].decode('utf-8'))) # Assume that the filename before '.csv' is the genre name genre_name = filename.split('.csv')[0] df['genre'] = genre_name all_data.append(df) # Concatenate all dataframes final_df = pd.concat(all_data, ignore_index=True) # Step 5: Save the combined DataFrame into a new CSV file final_df.to_csv('combined_movies.csv', index=False) # Download the combined CSV files.download('combined_movies.csv')

!pip install spotipy

import spotipy from spotipy.oauth2 import SpotifyOAuth # Spotify API Credentials SPOTIPY_CLIENT_ID = 'ecec60c9a316409a84a45c923f7473ee' SPOTIPY_CLIENT_SECRET = '3129b9225476463d86ddc4074cfc8500' SPOTIPY_REDIRECT_URI = 'http://localhost/' # Create OAuth2 object sp_oauth = SpotifyOAuth(client_id=SPOTIPY_CLIENT_ID, client_secret=SPOTIPY_CLIENT_SECRET, redirect_uri=SPOTIPY_REDIRECT_URI, scope=["user-top-read"]) # Get the authorization URL auth_url = sp_oauth.get_authorize_url() print("Please go to the following URL to authorize:") print(auth_url) # After clicking the URL and authorizing, you'll be redirected to your specified redirect_uri. # Extract the code parameter from that URL. code = input("Enter the code from the URL (localhost/code='...'): ") token = sp_oauth.get_access_token(code, as_dict=False) sp = spotipy.Spotify(auth=token) # Fetch user's top artists over the past 30 days top_artists = sp.current_user_top_artists(time_range='short_term') # Count the frequency of each genre genre_count = {} for artist in top_artists['items']: for genre in artist['genres']: genre_capitalized = genre.capitalize() # Capitalize first letter of each genre if genre_capitalized in genre_count: genre_count[genre_capitalized] += 1 else: genre_count[genre_capitalized] = 1 # Sort genres by frequency and get top 5 top_5_genres = sorted(genre_count, key=genre_count.get, reverse=True)[:5] print("Your Top 5 Genres from Spotify over the past 30 days:") for genre in top_5_genres: print(genre)

# Genre mapping genre_mapping = { # Main genres 'pop': ['action', 'adventure', 'romance'], 'art pop': ['animation', 'fantasy', 'romance'], 'reggaeton': ['action', 'adventure'], 'urbano latino': ['action', 'adventure'], 'trap latino': ['crime', 'thriller'], 'rock': ['action', 'adventure', 'war'], 'indie rock': ['drama', 'romance', 'adventure'], 'classical': ['biography', 'history', 'romance'], 'hip hop': ['action', 'crime', 'drama'], 'jazz': ['film-noir', 'romance', 'biography'], 'country': ['family', 'romance', 'history'], 'electronic': ['sci-fi', 'mystery', 'thriller'], 'metal': ['action', 'horror', 'war'], 'folk': ['family', 'history', 'biography'], 'blues': ['drama', 'biography', 'film-noir'], 'r&b': ['drama', 'romance', 'crime'], 'soul': ['drama', 'family', 'romance'], 'punk': ['action', 'thriller', 'mystery'], 'disco': ['comedy', 'romance', 'family'], 'house': ['sci-fi', 'thriller', 'mystery'], 'techno': ['sci-fi', 'action'], 'edm': ['action', 'adventure', 'sci-fi'], 'latin': ['romance', 'family', 'adventure'], 'reggae': ['comedy', 'adventure', 'family'], 'funk': ['comedy', 'romance', 'action'], 'k-pop': ['romance', 'comedy', 'action'], 'psychedelic': ['animation', 'fantasy', 'mystery'], 'world': ['history', 'family', 'biography'], 'ambient': ['mystery', 'sci-fi', 'animation'], # Subgenres 'lo-fi beats': ['drama', 'romance', 'animation'], 'vaporwave': ['sci-fi', 'mystery', 'animation'], 'emo': ['drama', 'romance', 'mystery'], 'hardcore': ['action', 'thriller', 'war'], 'dubstep': ['sci-fi', 'action', 'thriller'], 'ska': ['comedy', 'family', 'adventure'], 'swing': ['history', 'romance', 'family'], 'trance': ['sci-fi', 'fantasy', 'thriller'], 'grime': ['action', 'crime', 'drama'], 'bluegrass': ['family', 'history', 'drama'], 'new wave': ['drama', 'sci-fi', 'mystery'], 'post-punk': ['drama', 'mystery', 'thriller'], 'trip hop': ['mystery', 'drama', 'sci-fi'], 'neosoul': ['drama', 'romance', 'family'], 'afrobeat': ['history', 'drama', 'family'], 'chillhop': ['drama', 'animation', 'romance'], 'synthwave': ['sci-fi', 'action', 'drama'] } # Convert genre_mapping to DataFrame df = pd.DataFrame.from_dict(genre_mapping, orient='index').reset_index() df.columns = ['Music Genre', 'Movie Genre 1', 'Movie Genre 2', 'Movie Genre 3'] # Capitalize the first letter of each entry in the specified columns df['Music Genre'] = df['Music Genre'].str.capitalize() df['Movie Genre 1'] = df['Movie Genre 1'].str.capitalize() df['Movie Genre 2'] = df['Movie Genre 2'].str.capitalize() df['Movie Genre 3'] = df['Movie Genre 3'].str.capitalize() # Display DataFrame df

import spotipy from spotipy.oauth2 import SpotifyOAuth import pandas as pd # Spotify API Credentials SPOTIPY_CLIENT_ID = 'ecec60c9a316409a84a45c923f7473ee' SPOTIPY_CLIENT_SECRET = '3129b9225476463d86ddc4074cfc8500' SPOTIPY_REDIRECT_URI = 'http://localhost/' # Create OAuth2 object sp_oauth = SpotifyOAuth(client_id=SPOTIPY_CLIENT_ID, client_secret=SPOTIPY_CLIENT_SECRET, redirect_uri=SPOTIPY_REDIRECT_URI, scope=["user-top-read"]) # Get the authorization URL auth_url = sp_oauth.get_authorize_url() print("Please go to the following URL to authorize:") print(auth_url) # Extract the code from the redirected URL code = input("Enter the code from the URL (localhost/code='...'): ") token = sp_oauth.get_access_token(code, as_dict=False) sp = spotipy.Spotify(auth=token) # Fetch user's top artists top_artists = sp.current_user_top_artists() # Count frequency of each genre genre_count = {} for artist in top_artists['items']: for genre in artist['genres']: if genre in genre_count: genre_count[genre] += 1 else: genre_count[genre] = 1 # Sort genres by frequency and get top 5 top_5_genres = sorted(genre_count, key=genre_count.get, reverse=True)[:5] # Genre mapping genre_mapping = { # Main genres 'pop': ['action', 'adventure', 'romance'], 'art pop': ['animation', 'fantasy', 'romance'], 'reggaeton': ['action', 'adventure'], 'urbano latino': ['action', 'adventure'], 'trap latino': ['crime', 'thriller'], 'rock': ['action', 'adventure', 'war'], 'indie rock': ['drama', 'romance', 'adventure'], 'classical': ['biography', 'history', 'romance'], 'hip hop': ['action', 'crime', 'drama'], 'jazz': ['film-noir', 'romance', 'biography'], 'country': ['family', 'romance', 'history'], 'electronic': ['sci-fi', 'mystery', 'thriller'], 'metal': ['action', 'horror', 'war'], 'folk': ['family', 'history', 'biography'], 'blues': ['drama', 'biography', 'film-noir'], 'r&b': ['drama', 'romance', 'crime'], 'soul': ['drama', 'family', 'romance'], 'punk': ['action', 'thriller', 'mystery'], 'disco': ['comedy', 'romance', 'family'], 'house': ['sci-fi', 'thriller', 'mystery'], 'techno': ['sci-fi', 'action'], 'edm': ['action', 'adventure', 'sci-fi'], 'latin': ['romance', 'family', 'adventure'], 'reggae': ['comedy', 'adventure', 'family'], 'funk': ['comedy', 'romance', 'action'], 'k-pop': ['romance', 'comedy', 'action'], 'psychedelic': ['animation', 'fantasy', 'mystery'], 'world': ['history', 'family', 'biography'], 'ambient': ['mystery', 'sci-fi', 'animation'], # Subgenres 'lo-fi beats': ['drama', 'romance', 'animation'], 'vaporwave': ['sci-fi', 'mystery', 'animation'], 'emo': ['drama', 'romance', 'mystery'], 'hardcore': ['action', 'thriller', 'war'], 'dubstep': ['sci-fi', 'action', 'thriller'], 'ska': ['comedy', 'family', 'adventure'], 'swing': ['history', 'romance', 'family'], 'trance': ['sci-fi', 'fantasy', 'thriller'], 'grime': ['action', 'crime', 'drama'], 'bluegrass': ['family', 'history', 'drama'], 'new wave': ['drama', 'sci-fi', 'mystery'], 'post-punk': ['drama', 'mystery', 'thriller'], 'trip hop': ['mystery', 'drama', 'sci-fi'], 'neosoul': ['drama', 'romance', 'family'], 'afrobeat': ['history', 'drama', 'family'], 'chillhop': ['drama', 'animation', 'romance'], 'synthwave': ['sci-fi', 'action', 'drama'] } # Using the genre mapping to find corresponding movie genres matching_genres = set() for spotify_genre in top_5_genres: if spotify_genre in genre_mapping: for movie_genre in genre_mapping[spotify_genre]: matching_genres.add(movie_genre.title()) # capitalize each word print("Matching Genres between Spotify and Movies:", list(matching_genres))

import spotipy from spotipy.oauth2 import SpotifyOAuth import pandas as pd import random # Spotify API Credentials SPOTIPY_CLIENT_ID = 'ecec60c9a316409a84a45c923f7473ee' SPOTIPY_CLIENT_SECRET = '3129b9225476463d86ddc4074cfc8500' SPOTIPY_REDIRECT_URI = 'http://localhost/' # Create OAuth2 object sp_oauth = SpotifyOAuth(client_id=SPOTIPY_CLIENT_ID, client_secret=SPOTIPY_CLIENT_SECRET, redirect_uri=SPOTIPY_REDIRECT_URI, scope=["user-top-read"]) # Get the authorization URL auth_url = sp_oauth.get_authorize_url() print("Please go to the following URL to authorize:") print(auth_url) # Extract the code from the redirected URL code = input("Enter the code from the URL (localhost/code='...'): ") token = sp_oauth.get_access_token(code, as_dict=False) sp = spotipy.Spotify(auth=token) # Fetch user's top artists top_artists = sp.current_user_top_artists() # Count frequency of each genre genre_count = {} for artist in top_artists['items']: for genre in artist['genres']: if genre in genre_count: genre_count[genre] += 1 else: genre_count[genre] = 1 # Sort genres by frequency and get top 5 top_5_genres = sorted(genre_count, key=genre_count.get, reverse=True)[:5] # Genre mapping genre_mapping = { # Main genres 'pop': ['action', 'adventure', 'romance'], 'art pop': ['animation', 'fantasy', 'romance'], 'reggaeton': ['action', 'adventure'], 'urbano latino': ['action', 'adventure'], 'trap latino': ['crime', 'thriller'], 'rock': ['action', 'adventure', 'war'], 'indie rock': ['drama', 'romance', 'adventure'], 'classical': ['biography', 'history', 'romance'], 'hip hop': ['action', 'crime', 'drama'], 'jazz': ['film-noir', 'romance', 'biography'], 'country': ['family', 'romance', 'history'], 'electronic': ['sci-fi', 'mystery', 'thriller'], 'metal': ['action', 'horror', 'war'], 'folk': ['family', 'history', 'biography'], 'blues': ['drama', 'biography', 'film-noir'], 'r&b': ['drama', 'romance', 'crime'], 'soul': ['drama', 'family', 'romance'], 'punk': ['action', 'thriller', 'mystery'], 'disco': ['comedy', 'romance', 'family'], 'house': ['sci-fi', 'thriller', 'mystery'], 'techno': ['sci-fi', 'action'], 'edm': ['action', 'adventure', 'sci-fi'], 'latin': ['romance', 'family', 'adventure'], 'reggae': ['comedy', 'adventure', 'family'], 'funk': ['comedy', 'romance', 'action'], 'k-pop': ['romance', 'comedy', 'action'], 'psychedelic': ['animation', 'fantasy', 'mystery'], 'world': ['history', 'family', 'biography'], 'ambient': ['mystery', 'sci-fi', 'animation'], # Subgenres 'lo-fi beats': ['drama', 'romance', 'animation'], 'vaporwave': ['sci-fi', 'mystery', 'animation'], 'emo': ['drama', 'romance', 'mystery'], 'hardcore': ['action', 'thriller', 'war'], 'dubstep': ['sci-fi', 'action', 'thriller'], 'ska': ['comedy', 'family', 'adventure'], 'swing': ['history', 'romance', 'family'], 'trance': ['sci-fi', 'fantasy', 'thriller'], 'grime': ['action', 'crime', 'drama'], 'bluegrass': ['family', 'history', 'drama'], 'new wave': ['drama', 'sci-fi', 'mystery'], 'post-punk': ['drama', 'mystery', 'thriller'], 'trip hop': ['mystery', 'drama', 'sci-fi'], 'neosoul': ['drama', 'romance', 'family'], 'afrobeat': ['history', 'drama', 'family'], 'chillhop': ['drama', 'animation', 'romance'], 'synthwave': ['sci-fi', 'action', 'drama'] } # Using the genre mapping to find corresponding movie genres matching_genres_weighted = [] for spotify_genre in top_5_genres: if spotify_genre in genre_mapping: for movie_genre in genre_mapping[spotify_genre]: # Add the movie genre according to its frequency matching_genres_weighted.extend([movie_genre] * genre_count[spotify_genre]) # Read the CSV df = pd.read_csv('/content/combined_movies.csv') # Filter movies with rating 8 and above df = df[df['rating'] >= 8] # Filter movies with votes greater than or equal to 20,000 df = df[df['votes'] >= 20000] # Filter movies based on matching genres filtered_movies = df[df['genre'].isin(matching_genres_weighted)] # If there are no movies matching the criteria, print a message if filtered_movies.empty: print("No movies found matching the criteria.") else: # Recommend a movie from the filtered movies based on the weighted genres recommended_genre = random.choice(matching_genres_weighted) recommended_movie = filtered_movies[filtered_movies['genre'] == recommended_genre].sample().iloc[0] print(f"Recommended Movie: {recommended_movie['movie_name']} (Genre: {recommended_movie['genre'].capitalize()}, Rating: {recommended_movie['rating']}, Release Year: {recommended_movie['year']})")

!pip install spotipy

import pandas as pd # Read the CSV file into a DataFrame df = pd.read_csv('/content/tvshowdata.csv') # Filter rows where the 'certificate' column contains "TV" df = df[df['certificate'].str.contains("TV", na=False)] # Drop rows where the 'genre' column is NaN df = df.dropna(subset=['genre']) # Split the genres on commas and flatten the list all_genres = [genre.strip() for sublist in df['genre'].str.split(',') for genre in sublist] # Get unique genres using a set unique_genres = set(all_genres) # Convert unique genres into a DataFrame df_genres = pd.DataFrame(sorted(unique_genres), columns=['Genres']) df_genres

import spotipy from spotipy.oauth2 import SpotifyOAuth # Spotify API Credentials SPOTIPY_CLIENT_ID = 'ecec60c9a316409a84a45c923f7473ee' SPOTIPY_CLIENT_SECRET = '3129b9225476463d86ddc4074cfc8500' SPOTIPY_REDIRECT_URI = 'http://localhost/' # Create OAuth2 object sp_oauth = SpotifyOAuth(client_id=SPOTIPY_CLIENT_ID, client_secret=SPOTIPY_CLIENT_SECRET, redirect_uri=SPOTIPY_REDIRECT_URI, scope=["user-top-read"]) # Get the authorization URL auth_url = sp_oauth.get_authorize_url() print("Please go to the following URL to authorize:") print(auth_url) # After clicking the URL and authorizing, you'll be redirected to your specified redirect_uri. # Extract the code parameter from that URL. code = input("Enter the code from the URL (localhost/code='...'): ") token = sp_oauth.get_access_token(code, as_dict=False) sp = spotipy.Spotify(auth=token) # Fetch user's top artists over the past 30 days top_artists = sp.current_user_top_artists(time_range='short_term') # Count the frequency of each genre genre_count = {} for artist in top_artists['items']: for genre in artist['genres']: genre_capitalized = genre.capitalize() # Capitalize first letter of each genre if genre_capitalized in genre_count: genre_count[genre_capitalized] += 1 else: genre_count[genre_capitalized] = 1 # Sort genres by frequency and get top 5 top_5_genres = sorted(genre_count, key=genre_count.get, reverse=True)[:5] print("Your Top 5 Genres from Spotify over the past 30 days:") for genre in top_5_genres: print(genre)

# Genre mapping genre_mapping = { # Main genres 'pop': ['Action', 'Adventure', 'Romance'], 'art pop': ['Animation', 'Fantasy', 'Romance'], 'reggaeton': ['Action', 'Adventure'], 'urbano latino': ['Action', 'Adventure'], 'trap latino': ['Crime', 'Thriller'], 'rock': ['Action', 'Adventure', 'War'], 'indie rock': ['Drama', 'Romance', 'Adventure'], 'classical': ['Biography', 'History', 'Romance'], 'hip hop': ['Action', 'Crime', 'Drama'], 'jazz': ['Musical', 'Romance', 'Biography'], 'country': ['Family', 'Romance', 'History'], 'electronic': ['Sci-Fi', 'Mystery', 'Thriller'], 'metal': ['Action', 'Horror', 'War'], 'folk': ['Family', 'History', 'Biography'], 'blues': ['Drama', 'Biography', 'Music'], 'r&b': ['Drama', 'Romance', 'Crime'], 'soul': ['Drama', 'Family', 'Romance'], 'punk': ['Action', 'Thriller', 'Mystery'], 'disco': ['Comedy', 'Romance', 'Family'], 'house': ['Sci-Fi', 'Thriller', 'Mystery'], 'techno': ['Sci-Fi', 'Action'], 'edm': ['Action', 'Adventure', 'Sci-Fi'], 'latin': ['Romance', 'Family', 'Adventure'], 'reggae': ['Comedy', 'Adventure', 'Family'], 'funk': ['Comedy', 'Romance', 'Action'], 'k-pop': ['Romance', 'Comedy', 'Action'], 'psychedelic': ['Animation', 'Fantasy', 'Mystery'], 'world': ['History', 'Family', 'Biography'], 'ambient': ['Mystery', 'Sci-Fi', 'Animation'], # Subgenres 'lo-fi beats': ['Drama', 'Romance', 'Animation'], 'vaporwave': ['Sci-Fi', 'Mystery', 'Animation'], 'emo': ['Drama', 'Romance', 'Mystery'], 'hardcore': ['Action', 'Thriller', 'War'], 'dubstep': ['Sci-Fi', 'Action', 'Thriller'], 'ska': ['Comedy', 'Family', 'Adventure'], 'swing': ['History', 'Romance', 'Family'], 'trance': ['Sci-Fi', 'Fantasy', 'Thriller'], 'grime': ['Action', 'Crime', 'Drama'], 'bluegrass': ['Family', 'History', 'Drama'], 'new wave': ['Drama', 'Sci-Fi', 'Mystery'], 'post-punk': ['Drama', 'Mystery', 'Thriller'], 'trip hop': ['Mystery', 'Drama', 'Sci-Fi'], 'neosoul': ['Drama', 'Romance', 'Family'], 'afrobeat': ['History', 'Drama', 'Family'], 'chillhop': ['Drama', 'Animation', 'Romance'], 'synthwave': ['Sci-Fi', 'Action', 'Drama'] } # Convert genre_mapping to DataFrame df = pd.DataFrame.from_records([(key,) + tuple(val) + (None,) * (3 - len(val)) for key, val in genre_mapping.items()]) df.columns = ['Music Genre', 'TV Genre 1', 'TV Genre 2', 'TV Genre 3'] # Capitalize the first letter of every music genre in the 'Music Genre' column df['Music Genre'] = df['Music Genre'].str.capitalize() # Display DataFrame df

import spotipy from spotipy.oauth2 import SpotifyOAuth import pandas as pd # Spotify API Credentials SPOTIPY_CLIENT_ID = 'ecec60c9a316409a84a45c923f7473ee' SPOTIPY_CLIENT_SECRET = '3129b9225476463d86ddc4074cfc8500' SPOTIPY_REDIRECT_URI = 'http://localhost/' # Create OAuth2 object sp_oauth = SpotifyOAuth(client_id=SPOTIPY_CLIENT_ID, client_secret=SPOTIPY_CLIENT_SECRET, redirect_uri=SPOTIPY_REDIRECT_URI, scope=["user-top-read"]) # Get the authorization URL auth_url = sp_oauth.get_authorize_url() print("Please go to the following URL to authorize:") print(auth_url) # Extract the code from the redirected URL code = input("Enter the code from the URL (localhost/code='...'): ") token = sp_oauth.get_access_token(code, as_dict=False) sp = spotipy.Spotify(auth=token) # Fetch user's top artists top_artists = sp.current_user_top_artists() # Count frequency of each genre genre_count = {} for artist in top_artists['items']: for genre in artist['genres']: if genre in genre_count: genre_count[genre] += 1 else: genre_count[genre] = 1 # Sort genres by frequency and get top 5 top_5_genres = sorted(genre_count, key=genre_count.get, reverse=True)[:5] # Genre mapping for TV Shows genre_mapping = { # Main genres 'pop': ['Action', 'Adventure', 'Romance'], 'art pop': ['Animation', 'Fantasy', 'Romance'], 'reggaeton': ['Action', 'Adventure'], 'urbano latino': ['Action', 'Adventure'], 'trap latino': ['Crime', 'Thriller'], 'rock': ['Action', 'Adventure', 'War'], 'indie rock': ['Drama', 'Romance', 'Adventure'], 'classical': ['Biography', 'History', 'Romance'], 'hip hop': ['Action', 'Crime', 'Drama'], 'jazz': ['Musical', 'Romance', 'Biography'], 'country': ['Family', 'Romance', 'History'], 'electronic': ['Sci-Fi', 'Mystery', 'Thriller'], 'metal': ['Action', 'Horror', 'War'], 'folk': ['Family', 'History', 'Biography'], 'blues': ['Drama', 'Biography', 'Music'], 'r&b': ['Drama', 'Romance', 'Crime'], 'soul': ['Drama', 'Family', 'Romance'], 'punk': ['Action', 'Thriller', 'Mystery'], 'disco': ['Comedy', 'Romance', 'Family'], 'house': ['Sci-Fi', 'Thriller', 'Mystery'], 'techno': ['Sci-Fi', 'Action'], 'edm': ['Action', 'Adventure', 'Sci-Fi'], 'latin': ['Romance', 'Family', 'Adventure'], 'reggae': ['Comedy', 'Adventure', 'Family'], 'funk': ['Comedy', 'Romance', 'Action'], 'k-pop': ['Romance', 'Comedy', 'Action'], 'psychedelic': ['Animation', 'Fantasy', 'Mystery'], 'world': ['History', 'Family', 'Biography'], 'ambient': ['Mystery', 'Sci-Fi', 'Animation'], # Subgenres 'lo-fi beats': ['Drama', 'Romance', 'Animation'], 'vaporwave': ['Sci-Fi', 'Mystery', 'Animation'], 'emo': ['Drama', 'Romance', 'Mystery'], 'hardcore': ['Action', 'Thriller', 'War'], 'dubstep': ['Sci-Fi', 'Action', 'Thriller'], 'ska': ['Comedy', 'Family', 'Adventure'], 'swing': ['History', 'Romance', 'Family'], 'trance': ['Sci-Fi', 'Fantasy', 'Thriller'], 'grime': ['Action', 'Crime', 'Drama'], 'bluegrass': ['Family', 'History', 'Drama'], 'new wave': ['Drama', 'Sci-Fi', 'Mystery'], 'post-punk': ['Drama', 'Mystery', 'Thriller'], 'trip hop': ['Mystery', 'Drama', 'Sci-Fi'], 'neosoul': ['Drama', 'Romance', 'Family'], 'afrobeat': ['History', 'Drama', 'Family'], 'chillhop': ['Drama', 'Animation', 'Romance'], 'synthwave': ['Sci-Fi', 'Action', 'Drama'] } # Using the genre mapping to find corresponding TV show genres matching_genres = set() for spotify_genre in top_5_genres: if spotify_genre in genre_mapping: for tvshow_genre in genre_mapping[spotify_genre]: matching_genres.add(tvshow_genre) print("Matching Genres between Spotify and TV Shows:", list(matching_genres))

import spotipy from spotipy.oauth2 import SpotifyOAuth import pandas as pd import random # Spotify API Credentials SPOTIPY_CLIENT_ID = 'ecec60c9a316409a84a45c923f7473ee' SPOTIPY_CLIENT_SECRET = '3129b9225476463d86ddc4074cfc8500' SPOTIPY_REDIRECT_URI = 'http://localhost/' # Create OAuth2 object sp_oauth = SpotifyOAuth(client_id=SPOTIPY_CLIENT_ID, client_secret=SPOTIPY_CLIENT_SECRET, redirect_uri=SPOTIPY_REDIRECT_URI, scope=["user-top-read"]) # Get the authorization URL auth_url = sp_oauth.get_authorize_url() print("Please go to the following URL to authorize:") print(auth_url) # Extract the code from the redirected URL code = input("Enter the code from the URL (localhost/code='...'): ") token = sp_oauth.get_access_token(code, as_dict=False) sp = spotipy.Spotify(auth=token) # Fetch user's top artists top_artists = sp.current_user_top_artists() # Count frequency of each genre genre_count = {} for artist in top_artists['items']: for genre in artist['genres']: if genre in genre_count: genre_count[genre] += 1 else: genre_count[genre] = 1 # Sort genres by frequency and get top 5 top_5_genres = sorted(genre_count, key=genre_count.get, reverse=True)[:5] # Update the genre mapping with TV Show genres genre_mapping = { # Main genres 'pop': ['Action', 'Adventure', 'Romance'], 'art pop': ['Animation', 'Fantasy', 'Romance'], 'reggaeton': ['Action', 'Adventure'], 'urbano latino': ['Action', 'Adventure'], 'trap latino': ['Crime', 'Thriller'], 'rock': ['Action', 'Adventure', 'War'], 'indie rock': ['Drama', 'Romance', 'Adventure'], 'classical': ['Biography', 'History', 'Romance'], 'hip hop': ['Action', 'Crime', 'Drama'], 'jazz': ['Musical', 'Romance', 'Biography'], 'country': ['Family', 'Romance', 'History'], 'electronic': ['Sci-Fi', 'Mystery', 'Thriller'], 'metal': ['Action', 'Horror', 'War'], 'folk': ['Family', 'History', 'Biography'], 'blues': ['Drama', 'Biography', 'Music'], 'r&b': ['Drama', 'Romance', 'Crime'], 'soul': ['Drama', 'Family', 'Romance'], 'punk': ['Action', 'Thriller', 'Mystery'], 'disco': ['Comedy', 'Romance', 'Family'], 'house': ['Sci-Fi', 'Thriller', 'Mystery'], 'techno': ['Sci-Fi', 'Action'], 'edm': ['Action', 'Adventure', 'Sci-Fi'], 'latin': ['Romance', 'Family', 'Adventure'], 'reggae': ['Comedy', 'Adventure', 'Family'], 'funk': ['Comedy', 'Romance', 'Action'], 'k-pop': ['Romance', 'Comedy', 'Action'], 'psychedelic': ['Animation', 'Fantasy', 'Mystery'], 'world': ['History', 'Family', 'Biography'], 'ambient': ['Mystery', 'Sci-Fi', 'Animation'], # Subgenres 'lo-fi beats': ['Drama', 'Romance', 'Animation'], 'vaporwave': ['Sci-Fi', 'Mystery', 'Animation'], 'emo': ['Drama', 'Romance', 'Mystery'], 'hardcore': ['Action', 'Thriller', 'War'], 'dubstep': ['Sci-Fi', 'Action', 'Thriller'], 'ska': ['Comedy', 'Family', 'Adventure'], 'swing': ['History', 'Romance', 'Family'], 'trance': ['Sci-Fi', 'Fantasy', 'Thriller'], 'grime': ['Action', 'Crime', 'Drama'], 'bluegrass': ['Family', 'History', 'Drama'], 'new wave': ['Drama', 'Sci-Fi', 'Mystery'], 'post-punk': ['Drama', 'Mystery', 'Thriller'], 'trip hop': ['Mystery', 'Drama', 'Sci-Fi'], 'neosoul': ['Drama', 'Romance', 'Family'], 'afrobeat': ['History', 'Drama', 'Family'], 'chillhop': ['Drama', 'Animation', 'Romance'], 'synthwave': ['Sci-Fi', 'Action', 'Drama'] } # Using the genre mapping to find corresponding TV show genres matching_genres_weighted = [] for spotify_genre in top_5_genres: if spotify_genre in genre_mapping: for tvshow_genre in genre_mapping[spotify_genre]: # Add the TV show genre according to its frequency matching_genres_weighted.extend([tvshow_genre] * genre_count[spotify_genre]) # Read the CSV for TV Shows df = pd.read_csv('/content/tvshowdata.csv') # Make a copy of the original dataframe to avoid SettingWithCopyWarning df_copy = df.copy() # Convert "votes" to strings df_copy['votes'] = df_copy['votes'].astype(str) # Remove commas and convert to float df_copy['votes'] = df_copy['votes'].str.replace(',', '').astype(float) # Now, convert to integers, but only for non-NaN values df_copy.loc[df_copy['votes'].notna(), 'votes'] = df_copy['votes'].dropna().astype(int) # Convert 'genre' column to string type df_copy['genre'] = df_copy['genre'].astype(str) # Now proceed with the genre filtering filtered_tvshows = df_copy[df_copy['genre'].str.split(', ').apply(lambda x: bool(set(x) & set(matching_genres_weighted)) if x != 'nan' else False)] # Continue with the rating and votes filters filtered_tvshows = filtered_tvshows[filtered_tvshows['rating'] >= 8] filtered_tvshows = filtered_tvshows[filtered_tvshows['votes'] >= 20000] # Recommend a TV show from the filtered shows based on the weighted genres if filtered_tvshows.empty: print("No TV shows found matching the criteria.") else: recommended_genre = random.choice(matching_genres_weighted) recommended_show = filtered_tvshows[filtered_tvshows['genre'].str.contains(recommended_genre)].sample().iloc[0] # Extract the earliest year from the 'year' column # Extract the earliest year from the 'year' column and remove any preceding '-' earliest_year = str(recommended_show['year']).split('–')[0].strip().replace('-', '') print(f"Recommended TV Show: {recommended_show['title']} (Genre: {recommended_genre}, Rating: {recommended_show['rating']}, Release Year: {earliest_year.strip('()')})")

! pip install pandas

! pip install spotipy

import spotipy from spotipy.oauth2 import SpotifyOAuth import pandas as pd import random import ipywidgets as widgets from IPython.display import display # Spotify API Credentials SPOTIPY_CLIENT_ID = 'ecec60c9a316409a84a45c923f7473ee' SPOTIPY_CLIENT_SECRET = '3129b9225476463d86ddc4074cfc8500' SPOTIPY_REDIRECT_URI = 'http://localhost/' # Create OAuth2 object sp_oauth = SpotifyOAuth(client_id=SPOTIPY_CLIENT_ID, client_secret=SPOTIPY_CLIENT_SECRET, redirect_uri=SPOTIPY_REDIRECT_URI, scope=["user-top-read"]) # Get the authorization URL auth_url = sp_oauth.get_authorize_url() print("Please go to the following URL to authorize:") print(auth_url) # Extract the code from the redirected URL code = input("Enter the code from the URL (localhost/code='...'): ") token = sp_oauth.get_access_token(code, as_dict=False) sp = spotipy.Spotify(auth=token) # Fetch user's top artists top_artists = sp.current_user_top_artists() # Count frequency of each genre genre_count = {} for artist in top_artists['items']: for genre in artist['genres']: if genre in genre_count: genre_count[genre] += 1 else: genre_count[genre] = 1 # Sort genres by frequency and get top 5 top_5_genres = sorted(genre_count, key=genre_count.get, reverse=True)[:5] # Movie genre mapping movie_genre_mapping = { # Main genres 'pop': ['action', 'adventure', 'romance'], 'art pop': ['animation', 'fantasy', 'romance'], 'reggaeton': ['action', 'adventure'], 'urbano latino': ['action', 'adventure'], 'trap latino': ['crime', 'thriller'], 'rock': ['action', 'adventure', 'war'], 'indie rock': ['drama', 'romance', 'adventure'], 'classical': ['biography', 'history', 'romance'], 'hip hop': ['action', 'crime', 'drama'], 'jazz': ['film-noir', 'romance', 'biography'], 'country': ['family', 'romance', 'history'], 'electronic': ['sci-fi', 'mystery', 'thriller'], 'metal': ['action', 'horror', 'war'], 'folk': ['family', 'history', 'biography'], 'blues': ['drama', 'biography', 'film-noir'], 'r&b': ['drama', 'romance', 'crime'], 'soul': ['drama', 'family', 'romance'], 'punk': ['action', 'thriller', 'mystery'], 'disco': ['comedy', 'romance', 'family'], 'house': ['sci-fi', 'thriller', 'mystery'], 'techno': ['sci-fi', 'action'], 'edm': ['action', 'adventure', 'sci-fi'], 'latin': ['romance', 'family', 'adventure'], 'reggae': ['comedy', 'adventure', 'family'], 'funk': ['comedy', 'romance', 'action'], 'k-pop': ['romance', 'comedy', 'action'], 'psychedelic': ['animation', 'fantasy', 'mystery'], 'world': ['history', 'family', 'biography'], 'ambient': ['mystery', 'sci-fi', 'animation'], # Subgenres 'lo-fi beats': ['drama', 'romance', 'animation'], 'vaporwave': ['sci-fi', 'mystery', 'animation'], 'emo': ['drama', 'romance', 'mystery'], 'hardcore': ['action', 'thriller', 'war'], 'dubstep': ['sci-fi', 'action', 'thriller'], 'ska': ['comedy', 'family', 'adventure'], 'swing': ['history', 'romance', 'family'], 'trance': ['sci-fi', 'fantasy', 'thriller'], 'grime': ['action', 'crime', 'drama'], 'bluegrass': ['family', 'history', 'drama'], 'new wave': ['drama', 'sci-fi', 'mystery'], 'post-punk': ['drama', 'mystery', 'thriller'], 'trip hop': ['mystery', 'drama', 'sci-fi'], 'neosoul': ['drama', 'romance', 'family'], 'afrobeat': ['history', 'drama', 'family'], 'chillhop': ['drama', 'animation', 'romance'], 'synthwave': ['sci-fi', 'action', 'drama'] } # TV genre mapping tv_genre_mapping = { # Main genres 'pop': ['Action', 'Adventure', 'Romance'], 'art pop': ['Animation', 'Fantasy', 'Romance'], 'reggaeton': ['Action', 'Adventure'], 'urbano latino': ['Action', 'Adventure'], 'trap latino': ['Crime', 'Thriller'], 'rock': ['Action', 'Adventure', 'War'], 'indie rock': ['Drama', 'Romance', 'Adventure'], 'classical': ['Biography', 'History', 'Romance'], 'hip hop': ['Action', 'Crime', 'Drama'], 'jazz': ['Musical', 'Romance', 'Biography'], 'country': ['Family', 'Romance', 'History'], 'electronic': ['Sci-Fi', 'Mystery', 'Thriller'], 'metal': ['Action', 'Horror', 'War'], 'folk': ['Family', 'History', 'Biography'], 'blues': ['Drama', 'Biography', 'Music'], 'r&b': ['Drama', 'Romance', 'Crime'], 'soul': ['Drama', 'Family', 'Romance'], 'punk': ['Action', 'Thriller', 'Mystery'], 'disco': ['Comedy', 'Romance', 'Family'], 'house': ['Sci-Fi', 'Thriller', 'Mystery'], 'techno': ['Sci-Fi', 'Action'], 'edm': ['Action', 'Adventure', 'Sci-Fi'], 'latin': ['Romance', 'Family', 'Adventure'], 'reggae': ['Comedy', 'Adventure', 'Family'], 'funk': ['Comedy', 'Romance', 'Action'], 'k-pop': ['Romance', 'Comedy', 'Action'], 'psychedelic': ['Animation', 'Fantasy', 'Mystery'], 'world': ['History', 'Family', 'Biography'], 'ambient': ['Mystery', 'Sci-Fi', 'Animation'], # Subgenres 'lo-fi beats': ['Drama', 'Romance', 'Animation'], 'vaporwave': ['Sci-Fi', 'Mystery', 'Animation'], 'emo': ['Drama', 'Romance', 'Mystery'], 'hardcore': ['Action', 'Thriller', 'War'], 'dubstep': ['Sci-Fi', 'Action', 'Thriller'], 'ska': ['Comedy', 'Family', 'Adventure'], 'swing': ['History', 'Romance', 'Family'], 'trance': ['Sci-Fi', 'Fantasy', 'Thriller'], 'grime': ['Action', 'Crime', 'Drama'], 'bluegrass': ['Family', 'History', 'Drama'], 'new wave': ['Drama', 'Sci-Fi', 'Mystery'], 'post-punk': ['Drama', 'Mystery', 'Thriller'], 'trip hop': ['Mystery', 'Drama', 'Sci-Fi'], 'neosoul': ['Drama', 'Romance', 'Family'], 'afrobeat': ['History', 'Drama', 'Family'], 'chillhop': ['Drama', 'Animation', 'Romance'], 'synthwave': ['Sci-Fi', 'Action', 'Drama'] } def recommend(choice): matching_genres_weighted = [] if choice == "movie": genre_mapping = movie_genre_mapping elif choice == "tvshow": genre_mapping = tv_genre_mapping else: print("Invalid choice!") return for spotify_genre in top_5_genres: if spotify_genre in genre_mapping: for corresponding_genre in genre_mapping[spotify_genre]: matching_genres_weighted.extend([corresponding_genre] * genre_count[spotify_genre]) # Movie Filtering if choice == "movie": df = pd.read_csv('/content/combined_movies.csv', on_bad_lines='warn') # Filtering criteria df = df[df['rating'] >= 8] df = df[df['votes'] >= 20000] filtered_movies = df[df['genre'].isin(matching_genres_weighted)] if filtered_movies.empty: print("No movies found matching the criteria.") else: recommended_genre = random.choice(matching_genres_weighted) recommended_movie = filtered_movies[filtered_movies['genre'] == recommended_genre].sample().iloc[0] print(f"Recommended Movie: {recommended_movie['movie_name']} (Genre: {recommended_movie['genre'].capitalize()}, Rating: {recommended_movie['rating']}, Release Year: {recommended_movie['year']})") # TV Show Filtering elif choice == "tvshow": df = pd.read_csv('/content/tvshowdata.csv', on_bad_lines='warn') df_copy = df.copy() df_copy['votes'] = df_copy['votes'].astype(str) df_copy['votes'] = df_copy['votes'].str.replace(',', '').astype(float) df_copy.loc[df_copy['votes'].notna(), 'votes'] = df_copy['votes'].dropna().astype(int) df_copy['genre'] = df_copy['genre'].astype(str) filtered_tvshows = df_copy[df_copy['genre'].str.split(', ').apply(lambda x: bool(set(x) & set(matching_genres_weighted)) if x != 'nan' else False)] filtered_tvshows = filtered_tvshows[filtered_tvshows['rating'] >= 8] filtered_tvshows = filtered_tvshows[filtered_tvshows['votes'] >= 20000] if filtered_tvshows.empty: print("No TV shows found matching the criteria.") else: recommended_genre = random.choice(matching_genres_weighted) recommended_show = filtered_tvshows[filtered_tvshows['genre'].str.contains(recommended_genre)].sample().iloc[0] earliest_year = str(recommended_show['year']).split('–')[0].strip().replace('-', '') print(f"Recommended TV Show: {recommended_show['title']} (Genre: {recommended_genre}, Rating: {recommended_show['rating']}, Release Year: {earliest_year.strip('()')})") def on_button_click(button): choice = button.description.lower().replace(' ', '') recommend(choice) movie_button = widgets.Button(description="Movie") tv_button = widgets.Button(description="TV Show") movie_button.on_click(on_button_click) tv_button.on_click(on_button_click) # Display the buttons display(movie_button, tv_button)

/movierecs /templates - index.html - loginpage.html - displayrecommendation.html - displayhistory.html - __pycache__ - .DS_Store - .cache - .env - .gitignore - LICENSE.md - README.md - Watchify.py

from flask import Flask, render_template, request, redirect, url_for, flash, session import spotipy from spotipy.oauth2 import SpotifyOAuth import pandas as pd import random app = Flask(__name__) app.secret_key = 'SECRET_KEY' SPOTIPY_CLIENT_ID = 'ecec60c9a316409a84a45c923f7473ee' SPOTIPY_CLIENT_SECRET = '3129b9225476463d86ddc4074cfc8500' SPOTIPY_REDIRECT_URI = 'http://localhost:5000/callback' # Spotify session sp = None # Define functions provided in the earlier response def get_user_top_genres(token, limit=50): global sp sp = spotipy.Spotify(auth=token) results = sp.current_user_top_artists(limit=limit) genres = [] for artist in results['items']: genres.extend(artist['genres']) return genres def get_top_genres_and_counts(token, top_n=5): genres = get_user_top_genres(token) genre_counts = pd.Series(genres).value_counts() top_5_genres = genre_counts.head(top_n).index.tolist() return top_5_genres, genre_counts def get_recommendation(genres_weighted): return random.choice(genres_weighted) # Movie genre mapping movie_genre_mapping = { # Main genres 'pop': ['action', 'adventure', 'romance'], 'art pop': ['animation', 'fantasy', 'romance'], 'reggaeton': ['action', 'adventure'], 'urbano latino': ['action', 'adventure'], 'trap latino': ['crime', 'thriller'], 'rock': ['action', 'adventure', 'war'], 'indie rock': ['drama', 'romance', 'adventure'], 'classical': ['biography', 'history', 'romance'], 'hip hop': ['action', 'crime', 'drama'], 'jazz': ['film-noir', 'romance', 'biography'], 'country': ['family', 'romance', 'history'], 'electronic': ['sci-fi', 'mystery', 'thriller'], 'metal': ['action', 'horror', 'war'], 'folk': ['family', 'history', 'biography'], 'blues': ['drama', 'biography', 'film-noir'], 'r&b': ['drama', 'romance', 'crime'], 'soul': ['drama', 'family', 'romance'], 'punk': ['action', 'thriller', 'mystery'], 'disco': ['comedy', 'romance', 'family'], 'house': ['sci-fi', 'thriller', 'mystery'], 'techno': ['sci-fi', 'action'], 'edm': ['action', 'adventure', 'sci-fi'], 'latin': ['romance', 'family', 'adventure'], 'reggae': ['comedy', 'adventure', 'family'], 'funk': ['comedy', 'romance', 'action'], 'k-pop': ['romance', 'comedy', 'action'], 'psychedelic': ['animation', 'fantasy', 'mystery'], 'world': ['history', 'family', 'biography'], 'ambient': ['mystery', 'sci-fi', 'animation'], # Subgenres 'lo-fi beats': ['drama', 'romance', 'animation'], 'vaporwave': ['sci-fi', 'mystery', 'animation'], 'emo': ['drama', 'romance', 'mystery'], 'hardcore': ['action', 'thriller', 'war'], 'dubstep': ['sci-fi', 'action', 'thriller'], 'ska': ['comedy', 'family', 'adventure'], 'swing': ['history', 'romance', 'family'], 'trance': ['sci-fi', 'fantasy', 'thriller'], 'grime': ['action', 'crime', 'drama'], 'bluegrass': ['family', 'history', 'drama'], 'new wave': ['drama', 'sci-fi', 'mystery'], 'post-punk': ['drama', 'mystery', 'thriller'], 'trip hop': ['mystery', 'drama', 'sci-fi'], 'neosoul': ['drama', 'romance', 'family'], 'afrobeat': ['history', 'drama', 'family'], 'chillhop': ['drama', 'animation', 'romance'], 'synthwave': ['sci-fi', 'action', 'drama'] } # TV genre mapping tv_genre_mapping = { # Main genres 'pop': ['Action', 'Adventure', 'Romance'], 'art pop': ['Animation', 'Fantasy', 'Romance'], 'reggaeton': ['Action', 'Adventure'], 'urbano latino': ['Action', 'Adventure'], 'trap latino': ['Crime', 'Thriller'], 'rock': ['Action', 'Adventure', 'War'], 'indie rock': ['Drama', 'Romance', 'Adventure'], 'classical': ['Biography', 'History', 'Romance'], 'hip hop': ['Action', 'Crime', 'Drama'], 'jazz': ['Musical', 'Romance', 'Biography'], 'country': ['Family', 'Romance', 'History'], 'electronic': ['Sci-Fi', 'Mystery', 'Thriller'], 'metal': ['Action', 'Horror', 'War'], 'folk': ['Family', 'History', 'Biography'], 'blues': ['Drama', 'Biography', 'Music'], 'r&b': ['Drama', 'Romance', 'Crime'], 'soul': ['Drama', 'Family', 'Romance'], 'punk': ['Action', 'Thriller', 'Mystery'], 'disco': ['Comedy', 'Romance', 'Family'], 'house': ['Sci-Fi', 'Thriller', 'Mystery'], 'techno': ['Sci-Fi', 'Action'], 'edm': ['Action', 'Adventure', 'Sci-Fi'], 'latin': ['Romance', 'Family', 'Adventure'], 'reggae': ['Comedy', 'Adventure', 'Family'], 'funk': ['Comedy', 'Romance', 'Action'], 'k-pop': ['Romance', 'Comedy', 'Action'], 'psychedelic': ['Animation', 'Fantasy', 'Mystery'], 'world': ['History', 'Family', 'Biography'], 'ambient': ['Mystery', 'Sci-Fi', 'Animation'], # Subgenres 'lo-fi beats': ['Drama', 'Romance', 'Animation'], 'vaporwave': ['Sci-Fi', 'Mystery', 'Animation'], 'emo': ['Drama', 'Romance', 'Mystery'], 'hardcore': ['Action', 'Thriller', 'War'], 'dubstep': ['Sci-Fi', 'Action', 'Thriller'], 'ska': ['Comedy', 'Family', 'Adventure'], 'swing': ['History', 'Romance', 'Family'], 'trance': ['Sci-Fi', 'Fantasy', 'Thriller'], 'grime': ['Action', 'Crime', 'Drama'], 'bluegrass': ['Family', 'History', 'Drama'], 'new wave': ['Drama', 'Sci-Fi', 'Mystery'], 'post-punk': ['Drama', 'Mystery', 'Thriller'], 'trip hop': ['Mystery', 'Drama', 'Sci-Fi'], 'neosoul': ['Drama', 'Romance', 'Family'], 'afrobeat': ['History', 'Drama', 'Family'], 'chillhop': ['Drama', 'Animation', 'Romance'], 'synthwave': ['Sci-Fi', 'Action', 'Drama'] } @app.route('/') def index(): return render_template('index.html') @app.route('/login') def login(): sp_oauth = SpotifyOAuth(client_id=SPOTIPY_CLIENT_ID, client_secret=SPOTIPY_CLIENT_SECRET, redirect_uri=SPOTIPY_REDIRECT_URI, scope=["user-top-read"]) auth_url = sp_oauth.get_authorize_url() return render_template('loginpage.html', auth_url=auth_url) @app.route('/callback') def callback(): sp_oauth = SpotifyOAuth(client_id=SPOTIPY_CLIENT_ID, client_secret=SPOTIPY_CLIENT_SECRET, redirect_uri=SPOTIPY_REDIRECT_URI, scope=["user-top-read"]) token_info = sp_oauth.get_access_token(request.args['code']) session['token'] = token_info['access_token'] return redirect(url_for('recommend')) @app.route('/recommend', methods=['POST']) def recommend(): choice = request.form.get('choice', None) if not choice: flash('Choice is missing!', 'danger') return redirect(url_for('index')) # Assuming top_5_genres and genre_count are computed based on the session['token'] top_5_genres, genre_count = get_top_genres_and_counts(session['token']) matching_genres_weighted = [] if choice == "movie": genre_mapping = movie_genre_mapping elif choice == "tvshow": genre_mapping = tv_genre_mapping else: flash('Invalid choice!', 'danger') return redirect(url_for('index')) for spotify_genre in top_5_genres: if spotify_genre in genre_mapping: for corresponding_genre in genre_mapping[spotify_genre]: matching_genres_weighted.extend([corresponding_genre] * genre_count[spotify_genre]) # Create a result variable based on matching_genres_weighted result = get_recommendation(matching_genres_weighted) return render_template('displayrecommendation.html', recommendation=result) if __name__ == '__main__': app.run(debug=True)