popularity_model.py

import pandas as pd

def preprocessing():
    """Function to return user_song_list_count which has data of all users and the count of songs the user has listened to."""
    track_metadata = pd.read_csv('/home/sachet/Artificial Intelligence/song_data.csv')
    count_play = pd.read_csv('/home/sachet/Artificial Intelligence/10000.txt', sep='\t', header=None, names=['user','song','play_count'])
    unique_track_metadata = track_metadata.groupby('song_id').max().reset_index()
    user_song_list = pd.merge(count_play, unique_track_metadata, how='left', left_on='song', right_on='song_id')
    user_song_list.rename(columns={'play_count':'listen_count'},inplace=True)
    del(user_song_list['song_id'])
    return user_song_list
    
user_song_list_count = preprocessing()
score_list=user_song_list_count.groupby(['title']).agg({'user': 'count'}).reset_index()
score_list.rename(columns={'user': 'score'}, inplace=True)
sorted_score_list=score_list.sort_values(['score','title'], ascending=[0,1])
popularity_recommendations = sorted_score_list.head(10)
print(popularity_recommendations)