{ "cells": [ { "cell_type": "code", "execution_count": 2, "id": "04fb6bab", "metadata": {}, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 3, "id": "0442ec60", "metadata": {}, "outputs": [], "source": [ "movies = pd.read_csv('./data/movies.csv')\n", "credits = pd.read_csv('./data/credits.csv')" ] }, { "cell_type": "code", "execution_count": 4, "id": "2e772eac", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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The squad investigates to find out what has happened there. 1\n", " ..\n", "After 29-year-old Adaline recovers from a nearly lethal accident, she inexplicably stops growing older. As the years stretch on and on, Adaline keeps her secret to herself until she meets a man who changes her life. 1\n", "After denying a woman the extension she needs to keep her home, loan officer Christine Brown sees her once-promising life take a startling turn for the worse. Christine is convinced she's been cursed by a Gypsy, but her boyfriend is skeptical. Her only hope seems to lie in a psychic who claims he can help her lift the curse and keep her soul from being dragged straight to hell. 1\n", "Billy \"The Great\" Hope, the reigning junior middleweight boxing champion, has an impressive career, a loving wife and daughter, and a lavish lifestyle. However, when tragedy strikes, Billy hits rock bottom, losing his family, his house and his manager. 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{\"name\": \"lucky crow films\", \"id\": 87987}] 1\n", "Name: count, Length: 3697, dtype: int64\n", "-------------------\n", "production_countries\n", "[{\"iso_3166_1\": \"US\", \"name\": \"United States of America\"}] 2977\n", "[{\"iso_3166_1\": \"GB\", \"name\": \"United Kingdom\"}, {\"iso_3166_1\": \"US\", \"name\": \"United States of America\"}] 181\n", "[] 174\n", "[{\"iso_3166_1\": \"GB\", \"name\": \"United Kingdom\"}] 131\n", "[{\"iso_3166_1\": \"DE\", \"name\": \"Germany\"}, {\"iso_3166_1\": \"US\", \"name\": \"United States of America\"}] 119\n", " ... \n", "[{\"iso_3166_1\": \"GB\", \"name\": \"United Kingdom\"}, {\"iso_3166_1\": \"FR\", \"name\": \"France\"}, {\"iso_3166_1\": \"US\", \"name\": \"United States of America\"}] 1\n", "[{\"iso_3166_1\": \"US\", \"name\": \"United States of America\"}, {\"iso_3166_1\": \"ZA\", \"name\": \"South Africa\"}] 1\n", "[{\"iso_3166_1\": \"FR\", \"name\": \"France\"}, {\"iso_3166_1\": \"IS\", \"name\": \"Iceland\"}, {\"iso_3166_1\": \"GB\", \"name\": \"United Kingdom\"}, {\"iso_3166_1\": \"US\", \"name\": \"United States of America\"}] 1\n", "[{\"iso_3166_1\": \"CA\", \"name\": \"Canada\"}, {\"iso_3166_1\": \"KR\", \"name\": \"South Korea\"}] 1\n", "[{\"iso_3166_1\": \"US\", \"name\": \"United States of America\"}, {\"iso_3166_1\": \"CN\", \"name\": \"China\"}] 1\n", "Name: count, Length: 469, dtype: int64\n", "-------------------\n", "release_date\n", "2006-01-01 10\n", "2002-01-01 8\n", "2004-09-03 7\n", "1999-10-22 7\n", "2013-07-18 7\n", " ..\n", "2002-12-30 1\n", "2002-08-20 1\n", "1987-11-05 1\n", "2004-11-11 1\n", "2012-05-03 1\n", "Name: count, Length: 3280, dtype: int64\n", "-------------------\n", "revenue\n", "0 1427\n", "7000000 6\n", "8000000 6\n", "6000000 5\n", "12000000 5\n", " ... \n", "124827316 1\n", "75505856 1\n", "124731534 1\n", "158733820 1\n", "2040920 1\n", "Name: count, Length: 3297, dtype: int64\n", "-------------------\n", "runtime\n", "90.0 163\n", "100.0 149\n", "98.0 140\n", "97.0 133\n", "95.0 123\n", " ... \n", "338.0 1\n", "216.0 1\n", "166.0 1\n", "194.0 1\n", "60.0 1\n", "Name: count, Length: 156, dtype: int64\n", "-------------------\n", "spoken_languages\n", "[{\"iso_639_1\": \"en\", \"name\": \"English\"}] 3171\n", "[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso_639_1\": \"es\", \"name\": \"Espa\\u00f1ol\"}] 127\n", "[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"}] 114\n", "[] 86\n", "[{\"iso_639_1\": \"es\", \"name\": \"Espa\\u00f1ol\"}, {\"iso_639_1\": \"en\", \"name\": \"English\"}] 54\n", " ... \n", "[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso_639_1\": \"pl\", \"name\": \"Polski\"}, {\"iso_639_1\": \"pt\", \"name\": \"Portugu\\u00eas\"}] 1\n", "[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso_639_1\": \"es\", \"name\": \"Espa\\u00f1ol\"}, {\"iso_639_1\": \"ru\", \"name\": \"P\\u0443\\u0441\\u0441\\u043a\\u0438\\u0439\"}] 1\n", "[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso_639_1\": \"ar\", \"name\": \"\\u0627\\u0644\\u0639\\u0631\\u0628\\u064a\\u0629\"}, {\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"}, {\"iso_639_1\": \"de\", \"name\": \"Deutsch\"}, {\"iso_639_1\": \"ru\", \"name\": \"P\\u0443\\u0441\\u0441\\u043a\\u0438\\u0439\"}, {\"iso_639_1\": \"cs\", \"name\": \"\\u010cesk\\u00fd\"}, {\"iso_639_1\": \"sk\", \"name\": \"Sloven\\u010dina\"}] 1\n", "[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso_639_1\": \"de\", \"name\": \"Deutsch\"}, {\"iso_639_1\": \"tr\", \"name\": \"T\\u00fcrk\\u00e7e\"}, {\"iso_639_1\": \"ar\", \"name\": \"\\u0627\\u0644\\u0639\\u0631\\u0628\\u064a\\u0629\"}] 1\n", "[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso_639_1\": \"de\", \"name\": \"Deutsch\"}, {\"iso_639_1\": \"mn\", \"name\": \"\"}] 1\n", "Name: count, Length: 544, dtype: int64\n", "-------------------\n", "status\n", "Released 4795\n", "Rumored 5\n", "Post Production 3\n", "Name: count, dtype: int64\n", "-------------------\n", "tagline\n", "Based on a true story. 3\n", "From zero to hero. 2\n", "The only way out is down. 2\n", "Be careful what you wish for. 2\n", "What could go wrong? 2\n", " ..\n", "Life is Not Child-Proof. 1\n", "Every war has a beginning. 1\n", "First came love... then came Reverend Frank. 1\n", "Get off the bench and get into the game. 1\n", "A New Yorker in Shanghai 1\n", "Name: count, Length: 3944, dtype: int64\n", "-------------------\n", "title\n", "The Host 2\n", "Batman 2\n", "Out of the Blue 2\n", "Avatar 1\n", "The Girl on the Train 1\n", " ..\n", "Step Up 3D 1\n", "Secondhand Lions 1\n", "The Age of Adaline 1\n", "Drag Me to Hell 1\n", "My Date with Drew 1\n", "Name: count, Length: 4800, dtype: int64\n", "-------------------\n", "vote_average\n", "6.5 216\n", "6.0 216\n", "6.7 213\n", "6.3 207\n", "6.1 201\n", " ... \n", "2.7 1\n", "0.5 1\n", "2.2 1\n", "1.9 1\n", "2.4 1\n", "Name: count, Length: 71, dtype: int64\n", "-------------------\n", "vote_count\n", "0 62\n", "1 53\n", "2 46\n", "4 43\n", "3 41\n", " ..\n", "648 1\n", "5862 1\n", "3583 1\n", "1174 1\n", "2078 1\n", "Name: count, Length: 1609, dtype: int64\n", "-------------------\n", "cast\n", "[] 43\n", "[{\"cast_id\": 242, \"character\": \"Jake Sully\", \"credit_id\": \"5602a8a7c3a3685532001c9a\", \"gender\": 2, \"id\": 65731, \"name\": \"Sam Worthington\", \"order\": 0}, {\"cast_id\": 3, \"character\": \"Neytiri\", \"credit_id\": \"52fe48009251416c750ac9cb\", \"gender\": 1, \"id\": 8691, \"name\": \"Zoe Saldana\", \"order\": 1}, {\"cast_id\": 25, \"character\": \"Dr. Grace Augustine\", \"credit_id\": \"52fe48009251416c750aca39\", \"gender\": 1, \"id\": 10205, \"name\": \"Sigourney Weaver\", \"order\": 2}, {\"cast_id\": 4, \"character\": \"Col. Quaritch\", \"credit_id\": \"52fe48009251416c750ac9cf\", \"gender\": 2, \"id\": 32747, \"name\": \"Stephen Lang\", \"order\": 3}, {\"cast_id\": 5, \"character\": \"Trudy Chacon\", \"credit_id\": \"52fe48009251416c750ac9d3\", \"gender\": 1, \"id\": 17647, \"name\": \"Michelle Rodriguez\", \"order\": 4}, {\"cast_id\": 8, \"character\": \"Selfridge\", \"credit_id\": \"52fe48009251416c750ac9e1\", \"gender\": 2, \"id\": 1771, \"name\": \"Giovanni Ribisi\", \"order\": 5}, {\"cast_id\": 7, \"character\": \"Norm Spellman\", \"credit_id\": \"52fe48009251416c750ac9dd\", \"gender\": 2, \"id\": 59231, \"name\": \"Joel David Moore\", \"order\": 6}, {\"cast_id\": 9, \"character\": \"Moat\", \"credit_id\": \"52fe48009251416c750ac9e5\", \"gender\": 1, \"id\": 30485, \"name\": \"CCH Pounder\", \"order\": 7}, {\"cast_id\": 11, \"character\": \"Eytukan\", \"credit_id\": \"52fe48009251416c750ac9ed\", \"gender\": 2, \"id\": 15853, \"name\": \"Wes Studi\", \"order\": 8}, {\"cast_id\": 10, \"character\": \"Tsu'Tey\", \"credit_id\": \"52fe48009251416c750ac9e9\", \"gender\": 2, \"id\": 10964, \"name\": \"Laz Alonso\", \"order\": 9}, {\"cast_id\": 12, \"character\": \"Dr. Max Patel\", \"credit_id\": \"52fe48009251416c750ac9f1\", \"gender\": 2, \"id\": 95697, \"name\": \"Dileep Rao\", \"order\": 10}, {\"cast_id\": 13, \"character\": \"Lyle Wainfleet\", \"credit_id\": \"52fe48009251416c750ac9f5\", \"gender\": 2, \"id\": 98215, \"name\": \"Matt Gerald\", \"order\": 11}, {\"cast_id\": 32, \"character\": \"Private Fike\", \"credit_id\": \"52fe48009251416c750aca5b\", \"gender\": 2, \"id\": 154153, \"name\": \"Sean Anthony Moran\", \"order\": 12}, {\"cast_id\": 33, \"character\": \"Cryo Vault Med Tech\", \"credit_id\": \"52fe48009251416c750aca5f\", \"gender\": 2, \"id\": 397312, \"name\": \"Jason Whyte\", \"order\": 13}, {\"cast_id\": 34, \"character\": \"Venture Star Crew Chief\", \"credit_id\": \"52fe48009251416c750aca63\", \"gender\": 2, \"id\": 42317, \"name\": \"Scott Lawrence\", \"order\": 14}, {\"cast_id\": 35, \"character\": \"Lock Up Trooper\", \"credit_id\": \"52fe48009251416c750aca67\", \"gender\": 2, \"id\": 986734, \"name\": \"Kelly Kilgour\", \"order\": 15}, {\"cast_id\": 36, \"character\": \"Shuttle Pilot\", \"credit_id\": \"52fe48009251416c750aca6b\", \"gender\": 0, \"id\": 1207227, \"name\": \"James Patrick Pitt\", \"order\": 16}, {\"cast_id\": 37, \"character\": \"Shuttle Co-Pilot\", \"credit_id\": \"52fe48009251416c750aca6f\", \"gender\": 0, \"id\": 1180936, \"name\": \"Sean Patrick Murphy\", \"order\": 17}, {\"cast_id\": 38, \"character\": \"Shuttle Crew Chief\", \"credit_id\": \"52fe48009251416c750aca73\", \"gender\": 2, \"id\": 1019578, \"name\": \"Peter Dillon\", \"order\": 18}, {\"cast_id\": 39, \"character\": \"Tractor Operator / Troupe\", \"credit_id\": \"52fe48009251416c750aca77\", \"gender\": 0, \"id\": 91443, \"name\": \"Kevin Dorman\", \"order\": 19}, {\"cast_id\": 40, \"character\": \"Dragon Gunship Pilot\", \"credit_id\": \"52fe48009251416c750aca7b\", \"gender\": 2, \"id\": 173391, \"name\": \"Kelson Henderson\", \"order\": 20}, {\"cast_id\": 41, \"character\": \"Dragon Gunship Gunner\", \"credit_id\": \"52fe48009251416c750aca7f\", \"gender\": 0, \"id\": 1207236, \"name\": \"David Van Horn\", \"order\": 21}, {\"cast_id\": 42, \"character\": \"Dragon Gunship Navigator\", \"credit_id\": \"52fe48009251416c750aca83\", \"gender\": 0, \"id\": 215913, \"name\": \"Jacob Tomuri\", \"order\": 22}, {\"cast_id\": 43, \"character\": \"Suit #1\", \"credit_id\": \"52fe48009251416c750aca87\", \"gender\": 0, \"id\": 143206, \"name\": \"Michael Blain-Rozgay\", \"order\": 23}, {\"cast_id\": 44, \"character\": \"Suit #2\", \"credit_id\": \"52fe48009251416c750aca8b\", \"gender\": 2, \"id\": 169676, \"name\": \"Jon Curry\", \"order\": 24}, {\"cast_id\": 46, \"character\": \"Ambient Room Tech\", \"credit_id\": \"52fe48009251416c750aca8f\", \"gender\": 0, \"id\": 1048610, \"name\": \"Luke Hawker\", \"order\": 25}, {\"cast_id\": 47, \"character\": \"Ambient Room Tech / Troupe\", \"credit_id\": \"52fe48009251416c750aca93\", \"gender\": 0, \"id\": 42288, \"name\": \"Woody Schultz\", \"order\": 26}, {\"cast_id\": 48, \"character\": \"Horse Clan Leader\", \"credit_id\": \"52fe48009251416c750aca97\", \"gender\": 2, \"id\": 68278, \"name\": \"Peter Mensah\", \"order\": 27}, {\"cast_id\": 49, \"character\": \"Link Room Tech\", \"credit_id\": \"52fe48009251416c750aca9b\", \"gender\": 0, \"id\": 1207247, \"name\": \"Sonia Yee\", \"order\": 28}, {\"cast_id\": 50, \"character\": \"Basketball Avatar / Troupe\", \"credit_id\": \"52fe48009251416c750aca9f\", \"gender\": 1, \"id\": 1207248, \"name\": \"Jahnel Curfman\", \"order\": 29}, {\"cast_id\": 51, \"character\": \"Basketball Avatar\", \"credit_id\": \"52fe48009251416c750acaa3\", \"gender\": 0, \"id\": 89714, \"name\": \"Ilram Choi\", \"order\": 30}, {\"cast_id\": 52, \"character\": \"Na'vi Child\", \"credit_id\": \"52fe48009251416c750acaa7\", \"gender\": 0, \"id\": 1207249, \"name\": \"Kyla Warren\", \"order\": 31}, {\"cast_id\": 53, \"character\": \"Troupe\", \"credit_id\": \"52fe48009251416c750acaab\", \"gender\": 0, \"id\": 1207250, \"name\": \"Lisa Roumain\", \"order\": 32}, {\"cast_id\": 54, \"character\": \"Troupe\", \"credit_id\": \"52fe48009251416c750acaaf\", \"gender\": 1, \"id\": 83105, \"name\": \"Debra Wilson\", \"order\": 33}, {\"cast_id\": 57, \"character\": \"Troupe\", \"credit_id\": \"52fe48009251416c750acabb\", \"gender\": 0, \"id\": 1207253, \"name\": \"Chris Mala\", \"order\": 34}, {\"cast_id\": 55, \"character\": \"Troupe\", \"credit_id\": \"52fe48009251416c750acab3\", \"gender\": 0, \"id\": 1207251, \"name\": \"Taylor Kibby\", \"order\": 35}, {\"cast_id\": 56, \"character\": \"Troupe\", \"credit_id\": \"52fe48009251416c750acab7\", \"gender\": 0, \"id\": 1207252, \"name\": \"Jodie Landau\", \"order\": 36}, {\"cast_id\": 58, \"character\": \"Troupe\", \"credit_id\": \"52fe48009251416c750acabf\", \"gender\": 0, \"id\": 1207254, \"name\": \"Julie Lamm\", \"order\": 37}, {\"cast_id\": 59, \"character\": \"Troupe\", \"credit_id\": \"52fe48009251416c750acac3\", \"gender\": 0, \"id\": 1207257, \"name\": \"Cullen B. 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" ], "text/plain": [ " movie_id title \\\n", "0 19995 Avatar \n", "1 285 Pirates of the Caribbean: At World's End \n", "\n", " tags \n", "0 [Action, Adventure, Fantasy, ScienceFiction, c... \n", "1 [Adventure, Fantasy, Action, ocean, drugabuse,... " ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.head(2)" ] }, { "cell_type": "code", "execution_count": 43, "id": "ead2c3af", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/var/folders/2x/3726z2cx2vq26ly47yc6qy100000gn/T/ipykernel_2385/4000147982.py:1: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", " data['tags'] = data['tags'].apply(lambda x : \" \".join(x))\n" ] } ], "source": [ "data['tags'] = data['tags'].apply(lambda x : \" \".join(x))" ] }, { "cell_type": "code", "execution_count": 44, "id": "79062364", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Action Adventure Fantasy dccomics vigilante superhero basedoncomicbook revenge superpowers clarkkent brucewayne dcextendeduniverse BenAffleck HenryCavill GalGadot ZackSnyder Fearing the actions of a god-like Super Hero left unchecked, Gotham City’s own formidable, forceful vigilante takes on Metropolis’s most revered, modern-day savior, while the world wrestles with what sort of hero it really needs. And with Batman and Superman at war with one another, a new threat quickly arises, putting mankind in greater danger than it’s ever known before.'" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data['tags'][9]" ] }, { "cell_type": "code", "execution_count": 45, "id": "c61db110", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/var/folders/2x/3726z2cx2vq26ly47yc6qy100000gn/T/ipykernel_2385/999398172.py:1: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", " data['tags'] = data['tags'].apply(lambda x : x.lower())\n" ] } ], "source": [ "data['tags'] = data['tags'].apply(lambda x : x.lower())" ] }, { "cell_type": "code", "execution_count": 46, "id": "971019c1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'action adventure fantasy sciencefiction cultureclash future spacewar spacecolony society spacetravel futuristic romance space alien tribe alienplanet cgi marine soldier battle loveaffair antiwar powerrelations mindandsoul 3d samworthington zoesaldana sigourneyweaver jamescameron in the 22nd century, a paraplegic marine is dispatched to the moon pandora on a unique mission, but becomes torn between following orders and protecting an alien civilization.'" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data['tags'][0]" ] }, { "cell_type": "code", "execution_count": 47, "id": "7aac867a", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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1285Pirates of the Caribbean: At World's Endadventure fantasy action ocean drugabuse exoti...
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" ], "text/plain": [ " movie_id title \\\n", "0 19995 Avatar \n", "1 285 Pirates of the Caribbean: At World's End \n", "\n", " tags \n", "0 action adventure fantasy sciencefiction cultur... \n", "1 adventure fantasy action ocean drugabuse exoti... " ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.head(2)" ] }, { "cell_type": "code", "execution_count": 48, "id": "abf13639", "metadata": {}, "outputs": [], "source": [ "import nltk" ] }, { "cell_type": "code", "execution_count": 49, "id": "a1bb3d88", "metadata": {}, "outputs": [], "source": [ "from nltk.stem.porter import PorterStemmer" ] }, { "cell_type": "code", "execution_count": 50, "id": "558be403", "metadata": {}, "outputs": [], "source": [ "ps = PorterStemmer()" ] }, { "cell_type": "code", "execution_count": 51, "id": "5c800a22", "metadata": {}, "outputs": [], "source": [ "def stemmer(text):\n", " l = []\n", " for i in text.split():\n", " l.append(ps.stem(i))\n", " return \" \".join(l)" ] }, { "cell_type": "code", "execution_count": 52, "id": "2526d621", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/var/folders/2x/3726z2cx2vq26ly47yc6qy100000gn/T/ipykernel_2385/411577946.py:1: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", " data['tags'] = data['tags'].apply(stemmer)\n" ] } ], "source": [ "data['tags'] = data['tags'].apply(stemmer)" ] }, { "cell_type": "code", "execution_count": 53, "id": "dbd67c5f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 action adventur fantasi sciencefict culturecla...\n", "1 adventur fantasi action ocean drugabus exotici...\n", "2 action adventur crime spi basedonnovel secreta...\n", "3 action crime drama thriller dccomic crimefight...\n", "4 action adventur sciencefict basedonnovel mar m...\n", " ... \n", "4798 action crime thriller unitedstates–mexicobarri...\n", "4799 comedi romanc edwardburn kerrybishé marshadiet...\n", "4800 comedi drama romanc tvmovi date loveatfirstsig...\n", "4801 danielhenney elizacoup billpaxton danielhsia w...\n", "4802 documentari obsess camcord crush dreamgirl dre...\n", "Name: tags, Length: 4800, dtype: object" ] }, "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data['tags']" ] }, { "cell_type": "code", "execution_count": 54, "id": "9779f9bf", "metadata": {}, "outputs": [], "source": [ "from sklearn.feature_extraction.text import CountVectorizer\n", "cv = CountVectorizer(max_features=5000,stop_words='english')" ] }, { "cell_type": "code", "execution_count": 55, "id": "0275fa82", "metadata": {}, "outputs": [], "source": [ "vector = cv.fit_transform(data['tags']).toarray()" ] }, { "cell_type": "code", "execution_count": 56, "id": "fa56aa25", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(4800, 5000)" ] }, "execution_count": 56, "metadata": {}, "output_type": "execute_result" } ], "source": [ "vector.shape" ] }, { "cell_type": "code", "execution_count": 57, "id": "6a72a667", "metadata": {}, "outputs": [], "source": [ "from sklearn.metrics.pairwise import cosine_similarity" ] }, { "cell_type": "code", "execution_count": 58, "id": "94bab6f0", "metadata": {}, "outputs": [], "source": [ "similarity = cosine_similarity(vector)" ] }, { "cell_type": "code", "execution_count": 59, "id": "ad1dbd1c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(4800, 4800)" ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "source": [ "similarity.shape" ] }, { "cell_type": "code", "execution_count": 60, "id": "16f61a61", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[1. , 0.08346223, 0.0860309 , ..., 0.04499213, 0. ,\n", " 0. ],\n", " [0.08346223, 1. , 0.06063391, ..., 0.02378257, 0. ,\n", " 0.02615329],\n", " [0.0860309 , 0.06063391, 1. , ..., 0.02451452, 0. ,\n", " 0. ],\n", " ...,\n", " [0.04499213, 0.02378257, 0.02451452, ..., 1. , 0.03962144,\n", " 0.04229549],\n", " [0. , 0. , 0. , ..., 0.03962144, 1. ,\n", " 0.08714204],\n", " [0. , 0.02615329, 0. , ..., 0.04229549, 0.08714204,\n", " 1. ]])" ] }, "execution_count": 60, "metadata": {}, "output_type": "execute_result" } ], "source": [ "similarity" ] }, { "cell_type": "code", "execution_count": 61, "id": "c066ec08", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[(1213, 0.28676966733820225),\n", " (2403, 0.26901379342448517),\n", " (3723, 0.2605130246476754),\n", " (507, 0.255608593705383),\n", " (539, 0.25038669783359574)]" ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sorted((list(enumerate(similarity[0]))),reverse=True,key=lambda x : x[1])[1:6]" ] }, { "cell_type": "code", "execution_count": 62, "id": "8858f237", "metadata": {}, "outputs": [], "source": [ "def recommend(movie):\n", " movie_index = data[data['title']==movie].index[0]\n", " distance = similarity[movie_index]\n", " movie_list = sorted((list(enumerate(distance))),reverse=True,key=lambda x : x[1])[1:6]\n", " # return movie_list\n", " for i in movie_list:\n", " print(data.iloc[i[0]].title)" ] }, { "cell_type": "code", "execution_count": 63, "id": "dd2e7f92", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Mr. & Mrs. Smith\n", "From Russia with Love\n", "The Bourne Legacy\n", "Silent Trigger\n", "The Sentinel\n" ] } ], "source": [ "recommend('Hitman')" ] }, { "cell_type": "code", "execution_count": 64, "id": "33c4883a", "metadata": {}, "outputs": [], "source": [ "import pickle" ] }, { "cell_type": "code", "execution_count": 65, "id": "4c21f7c3", "metadata": {}, "outputs": [], "source": [ "pickle.dump(data,open(\"movies.pkl\",\"wb\"))" ] }, { "cell_type": "code", "execution_count": 66, "id": "5810bb79", "metadata": {}, "outputs": [], "source": [ "pickle.dump(similarity,open(\"similarity.pkl\",\"wb\"))" ] }, { "cell_type": "code", "execution_count": null, "id": "74b57d82", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "011d06bb", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "599de381", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.5" } }, "nbformat": 4, "nbformat_minor": 5 }