series-recommendation (2).ipynb

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.7.10","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2021-07-23T07:47:16.961788Z","iopub.execute_input":"2021-07-23T07:47:16.962666Z","iopub.status.idle":"2021-07-23T07:47:16.990180Z","shell.execute_reply.started":"2021-07-23T07:47:16.962540Z","shell.execute_reply":"2021-07-23T07:47:16.988271Z"},"trusted":true},"execution_count":1,"outputs":[{"name":"stdout","text":"/kaggle/input/imdb-dataset-of-top-1000-movies-and-tv-shows/imdb_top_1000.csv\n","output_type":"stream"}]},{"cell_type":"code","source":"import nltk\nnltk.download(\"stopwords\")","metadata":{"execution":{"iopub.status.busy":"2021-07-23T07:47:26.357305Z","iopub.execute_input":"2021-07-23T07:47:26.357688Z","iopub.status.idle":"2021-07-23T07:47:28.176025Z","shell.execute_reply.started":"2021-07-23T07:47:26.357657Z","shell.execute_reply":"2021-07-23T07:47:28.174845Z"},"trusted":true},"execution_count":2,"outputs":[{"name":"stdout","text":"[nltk_data] Downloading package stopwords to /usr/share/nltk_data...\n[nltk_data]   Package stopwords is already up-to-date!\n","output_type":"stream"},{"execution_count":2,"output_type":"execute_result","data":{"text/plain":"True"},"metadata":{}}]},{"cell_type":"code","source":"movies=pd.read_csv(\"/kaggle/input/imdb-dataset-of-top-1000-movies-and-tv-shows/imdb_top_1000.csv\")","metadata":{"execution":{"iopub.status.busy":"2021-07-23T07:47:28.177452Z","iopub.execute_input":"2021-07-23T07:47:28.177759Z","iopub.status.idle":"2021-07-23T07:47:28.215236Z","shell.execute_reply.started":"2021-07-23T07:47:28.177731Z","shell.execute_reply":"2021-07-23T07:47:28.214077Z"},"trusted":true},"execution_count":3,"outputs":[]},{"cell_type":"code","source":"movies.head()","metadata":{"execution":{"iopub.status.busy":"2021-07-23T07:47:28.217284Z","iopub.execute_input":"2021-07-23T07:47:28.217684Z","iopub.status.idle":"2021-07-23T07:47:28.257349Z","shell.execute_reply.started":"2021-07-23T07:47:28.217648Z","shell.execute_reply":"2021-07-23T07:47:28.256270Z"},"trusted":true},"execution_count":4,"outputs":[{"execution_count":4,"output_type":"execute_result","data":{"text/plain":"                                         Poster_Link  \\\n0  https://m.media-amazon.com/images/M/MV5BMDFkYT...   \n1  https://m.media-amazon.com/images/M/MV5BM2MyNj...   \n2  https://m.media-amazon.com/images/M/MV5BMTMxNT...   \n3  https://m.media-amazon.com/images/M/MV5BMWMwMG...   \n4  https://m.media-amazon.com/images/M/MV5BMWU4N2...   \n\n               Series_Title Released_Year Certificate  Runtime  \\\n0  The Shawshank Redemption          1994           A  142 min   \n1             The Godfather          1972           A  175 min   \n2           The Dark Knight          2008          UA  152 min   \n3    The Godfather: Part II          1974           A  202 min   \n4              12 Angry Men          1957           U   96 min   \n\n                  Genre  IMDB_Rating  \\\n0                 Drama          9.3   \n1          Crime, Drama          9.2   \n2  Action, Crime, Drama          9.0   \n3          Crime, Drama          9.0   \n4          Crime, Drama          9.0   \n\n                                            Overview  Meta_score  \\\n0  Two imprisoned men bond over a number of years...        80.0   \n1  An organized crime dynasty's aging patriarch t...       100.0   \n2  When the menace known as the Joker wreaks havo...        84.0   \n3  The early life and career of Vito Corleone in ...        90.0   \n4  A jury holdout attempts to prevent a miscarria...        96.0   \n\n               Director           Star1           Star2          Star3  \\\n0        Frank Darabont     Tim Robbins  Morgan Freeman     Bob Gunton   \n1  Francis Ford Coppola   Marlon Brando       Al Pacino     James Caan   \n2     Christopher Nolan  Christian Bale    Heath Ledger  Aaron Eckhart   \n3  Francis Ford Coppola       Al Pacino  Robert De Niro  Robert Duvall   \n4          Sidney Lumet     Henry Fonda     Lee J. Cobb  Martin Balsam   \n\n            Star4  No_of_Votes        Gross  \n0  William Sadler      2343110   28,341,469  \n1    Diane Keaton      1620367  134,966,411  \n2   Michael Caine      2303232  534,858,444  \n3    Diane Keaton      1129952   57,300,000  \n4    John Fiedler       689845    4,360,000  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Poster_Link</th>\n      <th>Series_Title</th>\n      <th>Released_Year</th>\n      <th>Certificate</th>\n      <th>Runtime</th>\n      <th>Genre</th>\n      <th>IMDB_Rating</th>\n      <th>Overview</th>\n      <th>Meta_score</th>\n      <th>Director</th>\n      <th>Star1</th>\n      <th>Star2</th>\n      <th>Star3</th>\n      <th>Star4</th>\n      <th>No_of_Votes</th>\n      <th>Gross</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>https://m.media-amazon.com/images/M/MV5BMDFkYT...</td>\n      <td>The Shawshank Redemption</td>\n      <td>1994</td>\n      <td>A</td>\n      <td>142 min</td>\n      <td>Drama</td>\n      <td>9.3</td>\n      <td>Two imprisoned men bond over a number of years...</td>\n      <td>80.0</td>\n      <td>Frank Darabont</td>\n      <td>Tim Robbins</td>\n      <td>Morgan Freeman</td>\n      <td>Bob Gunton</td>\n      <td>William Sadler</td>\n      <td>2343110</td>\n      <td>28,341,469</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>https://m.media-amazon.com/images/M/MV5BM2MyNj...</td>\n      <td>The Godfather</td>\n      <td>1972</td>\n      <td>A</td>\n      <td>175 min</td>\n      <td>Crime, Drama</td>\n      <td>9.2</td>\n      <td>An organized crime dynasty's aging patriarch t...</td>\n      <td>100.0</td>\n      <td>Francis Ford Coppola</td>\n      <td>Marlon Brando</td>\n      <td>Al Pacino</td>\n      <td>James Caan</td>\n      <td>Diane Keaton</td>\n      <td>1620367</td>\n      <td>134,966,411</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>https://m.media-amazon.com/images/M/MV5BMTMxNT...</td>\n      <td>The Dark Knight</td>\n      <td>2008</td>\n      <td>UA</td>\n      <td>152 min</td>\n      <td>Action, Crime, Drama</td>\n      <td>9.0</td>\n      <td>When the menace known as the Joker wreaks havo...</td>\n      <td>84.0</td>\n      <td>Christopher Nolan</td>\n      <td>Christian Bale</td>\n      <td>Heath Ledger</td>\n      <td>Aaron Eckhart</td>\n      <td>Michael Caine</td>\n      <td>2303232</td>\n      <td>534,858,444</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>https://m.media-amazon.com/images/M/MV5BMWMwMG...</td>\n      <td>The Godfather: Part II</td>\n      <td>1974</td>\n      <td>A</td>\n      <td>202 min</td>\n      <td>Crime, Drama</td>\n      <td>9.0</td>\n      <td>The early life and career of Vito Corleone in ...</td>\n      <td>90.0</td>\n      <td>Francis Ford Coppola</td>\n      <td>Al Pacino</td>\n      <td>Robert De Niro</td>\n      <td>Robert Duvall</td>\n      <td>Diane Keaton</td>\n      <td>1129952</td>\n      <td>57,300,000</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>https://m.media-amazon.com/images/M/MV5BMWU4N2...</td>\n      <td>12 Angry Men</td>\n      <td>1957</td>\n      <td>U</td>\n      <td>96 min</td>\n      <td>Crime, Drama</td>\n      <td>9.0</td>\n      <td>A jury holdout attempts to prevent a miscarria...</td>\n      <td>96.0</td>\n      <td>Sidney Lumet</td>\n      <td>Henry Fonda</td>\n      <td>Lee J. Cobb</td>\n      <td>Martin Balsam</td>\n      <td>John Fiedler</td>\n      <td>689845</td>\n      <td>4,360,000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"movies[\"Overview\"].head(10)","metadata":{"execution":{"iopub.status.busy":"2021-07-23T07:47:28.258528Z","iopub.execute_input":"2021-07-23T07:47:28.258845Z","iopub.status.idle":"2021-07-23T07:47:28.269012Z","shell.execute_reply.started":"2021-07-23T07:47:28.258815Z","shell.execute_reply":"2021-07-23T07:47:28.267724Z"},"trusted":true},"execution_count":5,"outputs":[{"execution_count":5,"output_type":"execute_result","data":{"text/plain":"0    Two imprisoned men bond over a number of years...\n1    An organized crime dynasty's aging patriarch t...\n2    When the menace known as the Joker wreaks havo...\n3    The early life and career of Vito Corleone in ...\n4    A jury holdout attempts to prevent a miscarria...\n5    Gandalf and Aragorn lead the World of Men agai...\n6    The lives of two mob hitmen, a boxer, a gangst...\n7    In German-occupied Poland during World War II,...\n8    A thief who steals corporate secrets through t...\n9    An insomniac office worker and a devil-may-car...\nName: Overview, dtype: object"},"metadata":{}}]},{"cell_type":"code","source":"from sklearn.feature_extraction.text import TfidfVectorizer\n\n\ntfv = TfidfVectorizer(min_df=3,  max_features=None, \n            strip_accents='unicode', analyzer='word',token_pattern=r'\\w{1,}',\n            ngram_range=(1, 3),\n            stop_words = 'english')","metadata":{"execution":{"iopub.status.busy":"2021-07-23T07:47:28.495969Z","iopub.execute_input":"2021-07-23T07:47:28.496430Z","iopub.status.idle":"2021-07-23T07:47:28.501956Z","shell.execute_reply.started":"2021-07-23T07:47:28.496374Z","shell.execute_reply":"2021-07-23T07:47:28.500736Z"},"trusted":true},"execution_count":6,"outputs":[]},{"cell_type":"code","source":"matrix = tfv.fit_transform(movies['Overview'])","metadata":{"execution":{"iopub.status.busy":"2021-07-23T07:47:29.028155Z","iopub.execute_input":"2021-07-23T07:47:29.028549Z","iopub.status.idle":"2021-07-23T07:47:29.144760Z","shell.execute_reply.started":"2021-07-23T07:47:29.028510Z","shell.execute_reply":"2021-07-23T07:47:29.143800Z"},"trusted":true},"execution_count":7,"outputs":[]},{"cell_type":"code","source":"matrix","metadata":{"execution":{"iopub.status.busy":"2021-07-23T07:47:29.568197Z","iopub.execute_input":"2021-07-23T07:47:29.568772Z","iopub.status.idle":"2021-07-23T07:47:29.575046Z","shell.execute_reply.started":"2021-07-23T07:47:29.568736Z","shell.execute_reply":"2021-07-23T07:47:29.573942Z"},"trusted":true},"execution_count":8,"outputs":[{"execution_count":8,"output_type":"execute_result","data":{"text/plain":"<1000x1319 sparse matrix of type '<class 'numpy.float64'>'\n\twith 9384 stored elements in Compressed Sparse Row format>"},"metadata":{}}]},{"cell_type":"code","source":"matrix.shape","metadata":{"execution":{"iopub.status.busy":"2021-07-23T07:47:30.290769Z","iopub.execute_input":"2021-07-23T07:47:30.291125Z","iopub.status.idle":"2021-07-23T07:47:30.296527Z","shell.execute_reply.started":"2021-07-23T07:47:30.291095Z","shell.execute_reply":"2021-07-23T07:47:30.295700Z"},"trusted":true},"execution_count":9,"outputs":[{"execution_count":9,"output_type":"execute_result","data":{"text/plain":"(1000, 1319)"},"metadata":{}}]},{"cell_type":"code","source":"from sklearn.metrics.pairwise import sigmoid_kernel\nsig = sigmoid_kernel(matrix, matrix)","metadata":{"execution":{"iopub.status.busy":"2021-07-23T07:47:30.838917Z","iopub.execute_input":"2021-07-23T07:47:30.839523Z","iopub.status.idle":"2021-07-23T07:47:30.899761Z","shell.execute_reply.started":"2021-07-23T07:47:30.839469Z","shell.execute_reply":"2021-07-23T07:47:30.898821Z"},"trusted":true},"execution_count":10,"outputs":[]},{"cell_type":"code","source":"sig[0]","metadata":{"execution":{"iopub.status.busy":"2021-07-23T07:47:31.416099Z","iopub.execute_input":"2021-07-23T07:47:31.416897Z","iopub.status.idle":"2021-07-23T07:47:31.436064Z","shell.execute_reply.started":"2021-07-23T07:47:31.416851Z","shell.execute_reply":"2021-07-23T07:47:31.434911Z"},"trusted":true},"execution_count":11,"outputs":[{"execution_count":11,"output_type":"execute_result","data":{"text/plain":"array([0.76191238, 0.76159416, 0.76159416, 0.76159416, 0.76159416,\n       0.76162352, 0.76163481, 0.76159416, 0.76159416, 0.76159416,\n       0.76159416, 0.76159416, 0.76161941, 0.76159416, 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index=movies['Series_Title']).drop_duplicates()","metadata":{"execution":{"iopub.status.busy":"2021-07-23T07:47:32.019967Z","iopub.execute_input":"2021-07-23T07:47:32.020388Z","iopub.status.idle":"2021-07-23T07:47:32.027404Z","shell.execute_reply.started":"2021-07-23T07:47:32.020350Z","shell.execute_reply":"2021-07-23T07:47:32.026083Z"},"trusted":true},"execution_count":12,"outputs":[]},{"cell_type":"code","source":"indices","metadata":{"execution":{"iopub.status.busy":"2021-07-23T07:47:32.737049Z","iopub.execute_input":"2021-07-23T07:47:32.737404Z","iopub.status.idle":"2021-07-23T07:47:32.747391Z","shell.execute_reply.started":"2021-07-23T07:47:32.737374Z","shell.execute_reply":"2021-07-23T07:47:32.746204Z"},"trusted":true},"execution_count":13,"outputs":[{"execution_count":13,"output_type":"execute_result","data":{"text/plain":"Series_Title\nThe Shawshank Redemption      0\nThe Godfather                 1\nThe Dark Knight               2\nThe Godfather: Part II        3\n12 Angry Men                  4\n                           ... \nBreakfast at Tiffany's      995\nGiant                       996\nFrom Here to Eternity       997\nLifeboat                    998\nThe 39 Steps                999\nLength: 1000, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"indices[\"Giant\"]","metadata":{"execution":{"iopub.status.busy":"2021-07-23T07:47:33.217652Z","iopub.execute_input":"2021-07-23T07:47:33.218033Z","iopub.status.idle":"2021-07-23T07:47:33.227548Z","shell.execute_reply.started":"2021-07-23T07:47:33.218001Z","shell.execute_reply":"2021-07-23T07:47:33.226269Z"},"trusted":true},"execution_count":14,"outputs":[{"execution_count":14,"output_type":"execute_result","data":{"text/plain":"996"},"metadata":{}}]},{"cell_type":"code","source":"sig[996]","metadata":{"execution":{"iopub.status.busy":"2021-07-23T07:47:33.804929Z","iopub.execute_input":"2021-07-23T07:47:33.805346Z","iopub.status.idle":"2021-07-23T07:47:33.827314Z","shell.execute_reply.started":"2021-07-23T07:47:33.805309Z","shell.execute_reply":"2021-07-23T07:47:33.825981Z"},"trusted":true},"execution_count":15,"outputs":[{"execution_count":15,"output_type":"execute_result","data":{"text/plain":"array([0.76159416, 0.76159416, 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scores[1:11]\n    series_indices = [i[0] for i in scores]\n    return pd.DataFrame({\"title\":movies['Series_Title'].iloc[series_indices],\"scores\":scores})","metadata":{"execution":{"iopub.status.busy":"2021-07-23T07:51:45.232902Z","iopub.execute_input":"2021-07-23T07:51:45.233267Z","iopub.status.idle":"2021-07-23T07:51:45.239704Z","shell.execute_reply.started":"2021-07-23T07:51:45.233234Z","shell.execute_reply":"2021-07-23T07:51:45.238534Z"},"trusted":true},"execution_count":53,"outputs":[]},{"cell_type":"code","source":"give_rec('The Dark Knight')","metadata":{"execution":{"iopub.status.busy":"2021-07-23T07:51:46.236275Z","iopub.execute_input":"2021-07-23T07:51:46.236802Z","iopub.status.idle":"2021-07-23T07:51:46.254952Z","shell.execute_reply.started":"2021-07-23T07:51:46.236762Z","shell.execute_reply":"2021-07-23T07:51:46.253693Z"},"trusted":true},"execution_count":54,"outputs":[{"execution_count":54,"output_type":"execute_result","data":{"text/plain":"                      title                     scores\n63    The Dark Knight Rises   (63, 0.7617112407199571)\n155           Batman Begins  (155, 0.7617069140189602)\n33                    Joker   (33, 0.7616569206456091)\n291  La battaglia di Algeri  (291, 0.7616542491630411)\n952           The Hurricane  (952, 0.7616485734409543)\n174                 Stalker  (174, 0.7616423329834426)\n272    Pink Floyd: The Wall   (272, 0.761640589381175)\n762   Death Note: Desu nôto  (762, 0.7616398109058052)\n956                   Mulan  (956, 0.7616390682950251)\n647               Cast Away  (647, 0.7616386168670897)","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>title</th>\n      <th>scores</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>63</th>\n      <td>The Dark Knight Rises</td>\n      <td>(63, 0.7617112407199571)</td>\n    </tr>\n    <tr>\n      <th>155</th>\n      <td>Batman Begins</td>\n      <td>(155, 0.7617069140189602)</td>\n    </tr>\n    <tr>\n      <th>33</th>\n      <td>Joker</td>\n      <td>(33, 0.7616569206456091)</td>\n    </tr>\n    <tr>\n      <th>291</th>\n      <td>La battaglia di Algeri</td>\n      <td>(291, 0.7616542491630411)</td>\n    </tr>\n    <tr>\n      <th>952</th>\n      <td>The Hurricane</td>\n      <td>(952, 0.7616485734409543)</td>\n    </tr>\n    <tr>\n      <th>174</th>\n      <td>Stalker</td>\n      <td>(174, 0.7616423329834426)</td>\n    </tr>\n    <tr>\n      <th>272</th>\n      <td>Pink Floyd: The Wall</td>\n      <td>(272, 0.761640589381175)</td>\n    </tr>\n    <tr>\n      <th>762</th>\n      <td>Death Note: Desu nôto</td>\n      <td>(762, 0.7616398109058052)</td>\n    </tr>\n    <tr>\n      <th>956</th>\n      <td>Mulan</td>\n      <td>(956, 0.7616390682950251)</td>\n    </tr>\n    <tr>\n      <th>647</th>\n      <td>Cast Away</td>\n      <td>(647, 0.7616386168670897)</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}