Movie Recommendation System.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "694eaff4",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "90d87651",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies = pd.read_csv('tmdb_5000_movies.csv')\n",
    "credits = pd.read_csv('tmdb_5000_credits.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3f6e4021",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>budget</th>\n",
       "      <th>genres</th>\n",
       "      <th>homepage</th>\n",
       "      <th>id</th>\n",
       "      <th>keywords</th>\n",
       "      <th>original_language</th>\n",
       "      <th>original_title</th>\n",
       "      <th>overview</th>\n",
       "      <th>popularity</th>\n",
       "      <th>production_companies</th>\n",
       "      <th>production_countries</th>\n",
       "      <th>release_date</th>\n",
       "      <th>revenue</th>\n",
       "      <th>runtime</th>\n",
       "      <th>spoken_languages</th>\n",
       "      <th>status</th>\n",
       "      <th>tagline</th>\n",
       "      <th>title</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4703</th>\n",
       "      <td>150000</td>\n",
       "      <td>[{\"id\": 35, \"name\": \"Comedy\"}, {\"id\": 18, \"nam...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39141</td>\n",
       "      <td>[{\"id\": 10183, \"name\": \"independent film\"}]</td>\n",
       "      <td>en</td>\n",
       "      <td>Tadpole</td>\n",
       "      <td>Beautiful, sophisticated women are all over Os...</td>\n",
       "      <td>8.570328</td>\n",
       "      <td>[{\"name\": \"IFC Productions\", \"id\": 26468}, {\"n...</td>\n",
       "      <td>[{\"iso_3166_1\": \"US\", \"name\": \"United States o...</td>\n",
       "      <td>2002-11-01</td>\n",
       "      <td>2891288</td>\n",
       "      <td>78.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...</td>\n",
       "      <td>Released</td>\n",
       "      <td>Everyone says he should date girls his own age...</td>\n",
       "      <td>Tadpole</td>\n",
       "      <td>5.5</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>640</th>\n",
       "      <td>95000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9342</td>\n",
       "      <td>[{\"id\": 387, \"name\": \"california\"}, {\"id\": 470...</td>\n",
       "      <td>en</td>\n",
       "      <td>The Mask of Zorro</td>\n",
       "      <td>It has been twenty years since Don Diego de la...</td>\n",
       "      <td>31.086791</td>\n",
       "      <td>[{\"name\": \"Amblin Entertainment\", \"id\": 56}, {...</td>\n",
       "      <td>[{\"iso_3166_1\": \"US\", \"name\": \"United States o...</td>\n",
       "      <td>1998-07-16</td>\n",
       "      <td>250288523</td>\n",
       "      <td>136.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>No one has seen his face... but everyone ... k...</td>\n",
       "      <td>The Mask of Zorro</td>\n",
       "      <td>6.3</td>\n",
       "      <td>1183</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        budget                                             genres homepage  \\\n",
       "4703    150000  [{\"id\": 35, \"name\": \"Comedy\"}, {\"id\": 18, \"nam...      NaN   \n",
       "640   95000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...      NaN   \n",
       "\n",
       "         id                                           keywords  \\\n",
       "4703  39141        [{\"id\": 10183, \"name\": \"independent film\"}]   \n",
       "640    9342  [{\"id\": 387, \"name\": \"california\"}, {\"id\": 470...   \n",
       "\n",
       "     original_language     original_title  \\\n",
       "4703                en            Tadpole   \n",
       "640                 en  The Mask of Zorro   \n",
       "\n",
       "                                               overview  popularity  \\\n",
       "4703  Beautiful, sophisticated women are all over Os...    8.570328   \n",
       "640   It has been twenty years since Don Diego de la...   31.086791   \n",
       "\n",
       "                                   production_companies  \\\n",
       "4703  [{\"name\": \"IFC Productions\", \"id\": 26468}, {\"n...   \n",
       "640   [{\"name\": \"Amblin Entertainment\", \"id\": 56}, {...   \n",
       "\n",
       "                                   production_countries release_date  \\\n",
       "4703  [{\"iso_3166_1\": \"US\", \"name\": \"United States o...   2002-11-01   \n",
       "640   [{\"iso_3166_1\": \"US\", \"name\": \"United States o...   1998-07-16   \n",
       "\n",
       "        revenue  runtime                                   spoken_languages  \\\n",
       "4703    2891288     78.0  [{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...   \n",
       "640   250288523    136.0           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]   \n",
       "\n",
       "        status                                            tagline  \\\n",
       "4703  Released  Everyone says he should date girls his own age...   \n",
       "640   Released  No one has seen his face... but everyone ... k...   \n",
       "\n",
       "                  title  vote_average  vote_count  \n",
       "4703            Tadpole           5.5          19  \n",
       "640   The Mask of Zorro           6.3        1183  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.sample(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "eba2e7b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>movie_id</th>\n",
       "      <th>title</th>\n",
       "      <th>cast</th>\n",
       "      <th>crew</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3911</th>\n",
       "      <td>29463</td>\n",
       "      <td>Krush Groove</td>\n",
       "      <td>[{\"cast_id\": 1, \"character\": \"Russell Walker\",...</td>\n",
       "      <td>[{\"credit_id\": \"52fe45e2c3a368484e07460d\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4199</th>\n",
       "      <td>25312</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[{\"cast_id\": 1, \"character\": \"She\", \"credit_id...</td>\n",
       "      <td>[{\"credit_id\": \"52fe44c1c3a368484e035289\", \"de...</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "      movie_id         title  \\\n",
       "3911     29463  Krush Groove   \n",
       "4199     25312           Yes   \n",
       "\n",
       "                                                   cast  \\\n",
       "3911  [{\"cast_id\": 1, \"character\": \"Russell Walker\",...   \n",
       "4199  [{\"cast_id\": 1, \"character\": \"She\", \"credit_id...   \n",
       "\n",
       "                                                   crew  \n",
       "3911  [{\"credit_id\": \"52fe45e2c3a368484e07460d\", \"de...  \n",
       "4199  [{\"credit_id\": \"52fe44c1c3a368484e035289\", \"de...  "
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     "execution_count": 4,
     "metadata": {},
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   "source": [
    "credits.sample(2)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e98070a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies_credit = movies.merge(credits, on='title') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3d381fd7",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies_credit = movies_credit.drop(['movie_id'],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8d408725",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>budget</th>\n",
       "      <th>genres</th>\n",
       "      <th>homepage</th>\n",
       "      <th>id</th>\n",
       "      <th>keywords</th>\n",
       "      <th>original_language</th>\n",
       "      <th>original_title</th>\n",
       "      <th>overview</th>\n",
       "      <th>popularity</th>\n",
       "      <th>production_companies</th>\n",
       "      <th>...</th>\n",
       "      <th>revenue</th>\n",
       "      <th>runtime</th>\n",
       "      <th>spoken_languages</th>\n",
       "      <th>status</th>\n",
       "      <th>tagline</th>\n",
       "      <th>title</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>vote_count</th>\n",
       "      <th>cast</th>\n",
       "      <th>crew</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2343</th>\n",
       "      <td>18000000</td>\n",
       "      <td>[{\"id\": 10749, \"name\": \"Romance\"}, {\"id\": 1040...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10028</td>\n",
       "      <td>[{\"id\": 242, \"name\": \"new york\"}, {\"id\": 246, ...</td>\n",
       "      <td>en</td>\n",
       "      <td>Honey</td>\n",
       "      <td>Honey Daniels (Jessica Alba) dreams of making ...</td>\n",
       "      <td>18.492655</td>\n",
       "      <td>[{\"name\": \"Universal Pictures\", \"id\": 33}, {\"n...</td>\n",
       "      <td>...</td>\n",
       "      <td>62646763</td>\n",
       "      <td>94.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>Her dream. Her terms</td>\n",
       "      <td>Honey</td>\n",
       "      <td>6.0</td>\n",
       "      <td>303</td>\n",
       "      <td>[{\"cast_id\": 16, \"character\": \"Honey Daniels\",...</td>\n",
       "      <td>[{\"credit_id\": \"52fe430b9251416c75001641\", \"de...</td>\n",
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       "    <tr>\n",
       "      <th>3251</th>\n",
       "      <td>0</td>\n",
       "      <td>[{\"id\": 27, \"name\": \"Horror\"}, {\"id\": 9648, \"n...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10885</td>\n",
       "      <td>[{\"id\": 233, \"name\": \"japan\"}, {\"id\": 236, \"na...</td>\n",
       "      <td>en</td>\n",
       "      <td>Shutter</td>\n",
       "      <td>A newly married couple discovers disturbing, g...</td>\n",
       "      <td>8.864368</td>\n",
       "      <td>[{\"name\": \"Regency Enterprises\", \"id\": 508}, {...</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...</td>\n",
       "      <td>Released</td>\n",
       "      <td>The most terrifying images are the ones that a...</td>\n",
       "      <td>Shutter</td>\n",
       "      <td>5.3</td>\n",
       "      <td>180</td>\n",
       "      <td>[{\"cast_id\": 3, \"character\": \"Benjamin Shaw\", ...</td>\n",
       "      <td>[{\"credit_id\": \"52fe43c99251416c7501e31b\", \"de...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        budget                                             genres homepage  \\\n",
       "2343  18000000  [{\"id\": 10749, \"name\": \"Romance\"}, {\"id\": 1040...      NaN   \n",
       "3251         0  [{\"id\": 27, \"name\": \"Horror\"}, {\"id\": 9648, \"n...      NaN   \n",
       "\n",
       "         id                                           keywords  \\\n",
       "2343  10028  [{\"id\": 242, \"name\": \"new york\"}, {\"id\": 246, ...   \n",
       "3251  10885  [{\"id\": 233, \"name\": \"japan\"}, {\"id\": 236, \"na...   \n",
       "\n",
       "     original_language original_title  \\\n",
       "2343                en          Honey   \n",
       "3251                en        Shutter   \n",
       "\n",
       "                                               overview  popularity  \\\n",
       "2343  Honey Daniels (Jessica Alba) dreams of making ...   18.492655   \n",
       "3251  A newly married couple discovers disturbing, g...    8.864368   \n",
       "\n",
       "                                   production_companies  ...   revenue  \\\n",
       "2343  [{\"name\": \"Universal Pictures\", \"id\": 33}, {\"n...  ...  62646763   \n",
       "3251  [{\"name\": \"Regency Enterprises\", \"id\": 508}, {...  ...         0   \n",
       "\n",
       "     runtime                                   spoken_languages    status  \\\n",
       "2343    94.0           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
       "3251    85.0  [{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...  Released   \n",
       "\n",
       "                                                tagline    title vote_average  \\\n",
       "2343                               Her dream. Her terms    Honey          6.0   \n",
       "3251  The most terrifying images are the ones that a...  Shutter          5.3   \n",
       "\n",
       "     vote_count                                               cast  \\\n",
       "2343        303  [{\"cast_id\": 16, \"character\": \"Honey Daniels\",...   \n",
       "3251        180  [{\"cast_id\": 3, \"character\": \"Benjamin Shaw\", ...   \n",
       "\n",
       "                                                   crew  \n",
       "2343  [{\"credit_id\": \"52fe430b9251416c75001641\", \"de...  \n",
       "3251  [{\"credit_id\": \"52fe43c99251416c7501e31b\", \"de...  \n",
       "\n",
       "[2 rows x 22 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_credit.sample(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "aa2ed46b",
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       "'[{\"credit_id\": \"52fe48009251416c750aca23\", \"department\": \"Editing\", \"gender\": 0, \"id\": 1721, \"job\": \"Editor\", \"name\": \"Stephen E. 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Hernandez\"}, {\"credit_id\": \"5495a0ddc3a3686ae10046fe\", \"department\": \"Editing\", \"gender\": 0, \"id\": 1401815, \"job\": \"Digital Intermediate\", \"name\": \"Marvin Hall\"}, {\"credit_id\": \"5495a1f7c3a3686ae3004443\", \"department\": \"Production\", \"gender\": 0, \"id\": 1401816, \"job\": \"Publicist\", \"name\": \"Judy Alley\"}, {\"credit_id\": \"5592b29fc3a36869d100002f\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1418381, \"job\": \"CG Supervisor\", \"name\": \"Mike Perry\"}, {\"credit_id\": \"5592b23a9251415df8001081\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1426854, \"job\": \"CG Supervisor\", \"name\": \"Andrew Morley\"}, {\"credit_id\": \"55491e1192514104c40002d8\", \"department\": \"Art\", \"gender\": 0, \"id\": 1438901, \"job\": \"Conceptual Design\", \"name\": \"Seth Engstrom\"}, {\"credit_id\": \"5525d5809251417276002b06\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1447362, \"job\": \"Visual Effects Art Director\", \"name\": \"Eric Oliver\"}, {\"credit_id\": \"554427ca925141586500312a\", \"department\": \"Visual Effects\", \"gender\": 0, \"id\": 1447503, \"job\": \"Modeling\", \"name\": \"Matsune Suzuki\"}, {\"credit_id\": \"551906889251415aab001c88\", \"department\": \"Art\", \"gender\": 0, \"id\": 1447524, \"job\": \"Art Department Manager\", \"name\": \"Paul Tobin\"}, {\"credit_id\": \"5592af8492514152cc0010de\", \"department\": \"Costume & Make-Up\", \"gender\": 0, \"id\": 1452643, \"job\": \"Hairstylist\", \"name\": \"Roxane Griffin\"}, {\"credit_id\": \"553d3c109251415852001318\", \"department\": \"Lighting\", \"gender\": 0, \"id\": 1453938, \"job\": \"Lighting Artist\", \"name\": \"Arun Ram-Mohan\"}, {\"credit_id\": \"5592af4692514152d5001355\", \"department\": \"Costume & Make-Up\", \"gender\": 0, \"id\": 1457305, \"job\": \"Makeup Artist\", \"name\": \"Georgia Lockhart-Adams\"}, {\"credit_id\": \"5592b2eac3a36877470012a5\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1466035, \"job\": \"CG Supervisor\", \"name\": \"Thrain Shadbolt\"}, {\"credit_id\": \"5592b032c3a36877450015f1\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483220, \"job\": \"CG Supervisor\", \"name\": \"Brad Alexander\"}, {\"credit_id\": \"5592b05592514152d80012f6\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483221, \"job\": \"CG Supervisor\", \"name\": \"Shadi Almassizadeh\"}, {\"credit_id\": \"5592b090c3a36877570010b5\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483222, \"job\": \"CG Supervisor\", \"name\": \"Simon Clutterbuck\"}, {\"credit_id\": \"5592b0dbc3a368774b00112c\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483223, \"job\": \"CG Supervisor\", \"name\": \"Graeme Demmocks\"}, {\"credit_id\": \"5592b0fe92514152db0010c1\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483224, \"job\": \"CG Supervisor\", \"name\": \"Adrian Fernandes\"}, {\"credit_id\": \"5592b11f9251415df8001059\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483225, \"job\": \"CG Supervisor\", \"name\": \"Mitch Gates\"}, {\"credit_id\": \"5592b15dc3a3687745001645\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483226, \"job\": \"CG Supervisor\", \"name\": \"Jerry Kung\"}, {\"credit_id\": \"5592b18e925141645a0004ae\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483227, \"job\": \"CG Supervisor\", \"name\": \"Andy Lomas\"}, {\"credit_id\": \"5592b1bfc3a368775d0010e7\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483228, \"job\": \"CG Supervisor\", \"name\": \"Sebastian Marino\"}, {\"credit_id\": \"5592b2049251415df8001078\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483229, \"job\": \"CG Supervisor\", \"name\": \"Matthias Menz\"}, {\"credit_id\": \"5592b27b92514152d800136a\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483230, \"job\": \"CG Supervisor\", \"name\": \"Sergei Nevshupov\"}, {\"credit_id\": \"5592b2c3c3a36869e800003c\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483231, \"job\": \"CG Supervisor\", \"name\": \"Philippe Rebours\"}, {\"credit_id\": \"5592b317c3a36877470012af\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483232, \"job\": \"CG Supervisor\", \"name\": \"Michael Takarangi\"}, {\"credit_id\": \"5592b345c3a36877470012bb\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483233, \"job\": \"CG Supervisor\", \"name\": \"David Weitzberg\"}, {\"credit_id\": \"5592b37cc3a368775100113b\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483234, \"job\": \"CG Supervisor\", \"name\": \"Ben White\"}, {\"credit_id\": \"573c8e2f9251413f5d000094\", \"department\": \"Crew\", \"gender\": 1, \"id\": 1621932, \"job\": \"Stunts\", \"name\": \"Min Windle\"}]'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_credit['crew'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ceab0588",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 4809 entries, 0 to 4808\n",
      "Data columns (total 22 columns):\n",
      " #   Column                Non-Null Count  Dtype  \n",
      "---  ------                --------------  -----  \n",
      " 0   budget                4809 non-null   int64  \n",
      " 1   genres                4809 non-null   object \n",
      " 2   homepage              1713 non-null   object \n",
      " 3   id                    4809 non-null   int64  \n",
      " 4   keywords              4809 non-null   object \n",
      " 5   original_language     4809 non-null   object \n",
      " 6   original_title        4809 non-null   object \n",
      " 7   overview              4806 non-null   object \n",
      " 8   popularity            4809 non-null   float64\n",
      " 9   production_companies  4809 non-null   object \n",
      " 10  production_countries  4809 non-null   object \n",
      " 11  release_date          4808 non-null   object \n",
      " 12  revenue               4809 non-null   int64  \n",
      " 13  runtime               4807 non-null   float64\n",
      " 14  spoken_languages      4809 non-null   object \n",
      " 15  status                4809 non-null   object \n",
      " 16  tagline               3965 non-null   object \n",
      " 17  title                 4809 non-null   object \n",
      " 18  vote_average          4809 non-null   float64\n",
      " 19  vote_count            4809 non-null   int64  \n",
      " 20  cast                  4809 non-null   object \n",
      " 21  crew                  4809 non-null   object \n",
      "dtypes: float64(3), int64(4), object(15)\n",
      "memory usage: 993.2+ KB\n"
     ]
    }
   ],
   "source": [
    "movies_credit.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b1b12703",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4809, 22)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df = pd.DataFrame()\n",
    "movies_df = movies_credit \n",
    "movies_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "72a62f2a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>id</th>\n",
       "      <th>title</th>\n",
       "      <th>overview</th>\n",
       "      <th>budget</th>\n",
       "      <th>genres</th>\n",
       "      <th>keywords</th>\n",
       "      <th>cast</th>\n",
       "      <th>runtime</th>\n",
       "      <th>revenue</th>\n",
       "      <th>crew</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19995</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>In the 22nd century, a paraplegic Marine is di...</td>\n",
       "      <td>237000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
       "      <td>[{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...</td>\n",
       "      <td>[{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...</td>\n",
       "      <td>162.0</td>\n",
       "      <td>2787965087</td>\n",
       "      <td>[{\"credit_id\": \"52fe48009251416c750aca23\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>285</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>Captain Barbossa, long believed to be dead, ha...</td>\n",
       "      <td>300000000</td>\n",
       "      <td>[{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...</td>\n",
       "      <td>[{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...</td>\n",
       "      <td>[{\"cast_id\": 4, \"character\": \"Captain Jack Spa...</td>\n",
       "      <td>169.0</td>\n",
       "      <td>961000000</td>\n",
       "      <td>[{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>206647</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>A cryptic message from Bond’s past sends him o...</td>\n",
       "      <td>245000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
       "      <td>[{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...</td>\n",
       "      <td>[{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...</td>\n",
       "      <td>148.0</td>\n",
       "      <td>880674609</td>\n",
       "      <td>[{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>49026</td>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>Following the death of District Attorney Harve...</td>\n",
       "      <td>250000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam...</td>\n",
       "      <td>[{\"id\": 849, \"name\": \"dc comics\"}, {\"id\": 853,...</td>\n",
       "      <td>[{\"cast_id\": 2, \"character\": \"Bruce Wayne / Ba...</td>\n",
       "      <td>165.0</td>\n",
       "      <td>1084939099</td>\n",
       "      <td>[{\"credit_id\": \"52fe4781c3a36847f81398c3\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>49529</td>\n",
       "      <td>John Carter</td>\n",
       "      <td>John Carter is a war-weary, former military ca...</td>\n",
       "      <td>260000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
       "      <td>[{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...</td>\n",
       "      <td>[{\"cast_id\": 5, \"character\": \"John Carter\", \"c...</td>\n",
       "      <td>132.0</td>\n",
       "      <td>284139100</td>\n",
       "      <td>[{\"credit_id\": \"52fe479ac3a36847f813eaa3\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4804</th>\n",
       "      <td>9367</td>\n",
       "      <td>El Mariachi</td>\n",
       "      <td>El Mariachi just wants to play his guitar and ...</td>\n",
       "      <td>220000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam...</td>\n",
       "      <td>[{\"id\": 5616, \"name\": \"united states\\u2013mexi...</td>\n",
       "      <td>[{\"cast_id\": 1, \"character\": \"El Mariachi\", \"c...</td>\n",
       "      <td>81.0</td>\n",
       "      <td>2040920</td>\n",
       "      <td>[{\"credit_id\": \"52fe44eec3a36847f80b280b\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4805</th>\n",
       "      <td>72766</td>\n",
       "      <td>Newlyweds</td>\n",
       "      <td>A newlywed couple's honeymoon is upended by th...</td>\n",
       "      <td>9000</td>\n",
       "      <td>[{\"id\": 35, \"name\": \"Comedy\"}, {\"id\": 10749, \"...</td>\n",
       "      <td>[]</td>\n",
       "      <td>[{\"cast_id\": 1, \"character\": \"Buzzy\", \"credit_...</td>\n",
       "      <td>85.0</td>\n",
       "      <td>0</td>\n",
       "      <td>[{\"credit_id\": \"52fe487dc3a368484e0fb013\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4806</th>\n",
       "      <td>231617</td>\n",
       "      <td>Signed, Sealed, Delivered</td>\n",
       "      <td>\"Signed, Sealed, Delivered\" introduces a dedic...</td>\n",
       "      <td>0</td>\n",
       "      <td>[{\"id\": 35, \"name\": \"Comedy\"}, {\"id\": 18, \"nam...</td>\n",
       "      <td>[{\"id\": 248, \"name\": \"date\"}, {\"id\": 699, \"nam...</td>\n",
       "      <td>[{\"cast_id\": 8, \"character\": \"Oliver O\\u2019To...</td>\n",
       "      <td>120.0</td>\n",
       "      <td>0</td>\n",
       "      <td>[{\"credit_id\": \"52fe4df3c3a36847f8275ecf\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4807</th>\n",
       "      <td>126186</td>\n",
       "      <td>Shanghai Calling</td>\n",
       "      <td>When ambitious New York attorney Sam is sent t...</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[{\"cast_id\": 3, \"character\": \"Sam\", \"credit_id...</td>\n",
       "      <td>98.0</td>\n",
       "      <td>0</td>\n",
       "      <td>[{\"credit_id\": \"52fe4ad9c3a368484e16a36b\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4808</th>\n",
       "      <td>25975</td>\n",
       "      <td>My Date with Drew</td>\n",
       "      <td>Ever since the second grade when he first saw ...</td>\n",
       "      <td>0</td>\n",
       "      <td>[{\"id\": 99, \"name\": \"Documentary\"}]</td>\n",
       "      <td>[{\"id\": 1523, \"name\": \"obsession\"}, {\"id\": 224...</td>\n",
       "      <td>[{\"cast_id\": 3, \"character\": \"Herself\", \"credi...</td>\n",
       "      <td>90.0</td>\n",
       "      <td>0</td>\n",
       "      <td>[{\"credit_id\": \"58ce021b9251415a390165d9\", \"de...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4809 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id                                     title  \\\n",
       "0      19995                                    Avatar   \n",
       "1        285  Pirates of the Caribbean: At World's End   \n",
       "2     206647                                   Spectre   \n",
       "3      49026                     The Dark Knight Rises   \n",
       "4      49529                               John Carter   \n",
       "...      ...                                       ...   \n",
       "4804    9367                               El Mariachi   \n",
       "4805   72766                                 Newlyweds   \n",
       "4806  231617                 Signed, Sealed, Delivered   \n",
       "4807  126186                          Shanghai Calling   \n",
       "4808   25975                         My Date with Drew   \n",
       "\n",
       "                                               overview     budget  \\\n",
       "0     In the 22nd century, a paraplegic Marine is di...  237000000   \n",
       "1     Captain Barbossa, long believed to be dead, ha...  300000000   \n",
       "2     A cryptic message from Bond’s past sends him o...  245000000   \n",
       "3     Following the death of District Attorney Harve...  250000000   \n",
       "4     John Carter is a war-weary, former military ca...  260000000   \n",
       "...                                                 ...        ...   \n",
       "4804  El Mariachi just wants to play his guitar and ...     220000   \n",
       "4805  A newlywed couple's honeymoon is upended by th...       9000   \n",
       "4806  \"Signed, Sealed, Delivered\" introduces a dedic...          0   \n",
       "4807  When ambitious New York attorney Sam is sent t...          0   \n",
       "4808  Ever since the second grade when he first saw ...          0   \n",
       "\n",
       "                                                 genres  \\\n",
       "0     [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
       "1     [{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...   \n",
       "2     [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
       "3     [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam...   \n",
       "4     [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
       "...                                                 ...   \n",
       "4804  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam...   \n",
       "4805  [{\"id\": 35, \"name\": \"Comedy\"}, {\"id\": 10749, \"...   \n",
       "4806  [{\"id\": 35, \"name\": \"Comedy\"}, {\"id\": 18, \"nam...   \n",
       "4807                                                 []   \n",
       "4808                [{\"id\": 99, \"name\": \"Documentary\"}]   \n",
       "\n",
       "                                               keywords  \\\n",
       "0     [{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...   \n",
       "1     [{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...   \n",
       "2     [{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...   \n",
       "3     [{\"id\": 849, \"name\": \"dc comics\"}, {\"id\": 853,...   \n",
       "4     [{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...   \n",
       "...                                                 ...   \n",
       "4804  [{\"id\": 5616, \"name\": \"united states\\u2013mexi...   \n",
       "4805                                                 []   \n",
       "4806  [{\"id\": 248, \"name\": \"date\"}, {\"id\": 699, \"nam...   \n",
       "4807                                                 []   \n",
       "4808  [{\"id\": 1523, \"name\": \"obsession\"}, {\"id\": 224...   \n",
       "\n",
       "                                                   cast  runtime     revenue  \\\n",
       "0     [{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...    162.0  2787965087   \n",
       "1     [{\"cast_id\": 4, \"character\": \"Captain Jack Spa...    169.0   961000000   \n",
       "2     [{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...    148.0   880674609   \n",
       "3     [{\"cast_id\": 2, \"character\": \"Bruce Wayne / Ba...    165.0  1084939099   \n",
       "4     [{\"cast_id\": 5, \"character\": \"John Carter\", \"c...    132.0   284139100   \n",
       "...                                                 ...      ...         ...   \n",
       "4804  [{\"cast_id\": 1, \"character\": \"El Mariachi\", \"c...     81.0     2040920   \n",
       "4805  [{\"cast_id\": 1, \"character\": \"Buzzy\", \"credit_...     85.0           0   \n",
       "4806  [{\"cast_id\": 8, \"character\": \"Oliver O\\u2019To...    120.0           0   \n",
       "4807  [{\"cast_id\": 3, \"character\": \"Sam\", \"credit_id...     98.0           0   \n",
       "4808  [{\"cast_id\": 3, \"character\": \"Herself\", \"credi...     90.0           0   \n",
       "\n",
       "                                                   crew  \n",
       "0     [{\"credit_id\": \"52fe48009251416c750aca23\", \"de...  \n",
       "1     [{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...  \n",
       "2     [{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...  \n",
       "3     [{\"credit_id\": \"52fe4781c3a36847f81398c3\", \"de...  \n",
       "4     [{\"credit_id\": \"52fe479ac3a36847f813eaa3\", \"de...  \n",
       "...                                                 ...  \n",
       "4804  [{\"credit_id\": \"52fe44eec3a36847f80b280b\", \"de...  \n",
       "4805  [{\"credit_id\": \"52fe487dc3a368484e0fb013\", \"de...  \n",
       "4806  [{\"credit_id\": \"52fe4df3c3a36847f8275ecf\", \"de...  \n",
       "4807  [{\"credit_id\": \"52fe4ad9c3a368484e16a36b\", \"de...  \n",
       "4808  [{\"credit_id\": \"58ce021b9251415a390165d9\", \"de...  \n",
       "\n",
       "[4809 rows x 10 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df = movies_df[ ['id', 'title', 'overview', 'budget', 'genres','keywords', 'cast', 'runtime', 'revenue','crew'] ]\n",
    "movies_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "650c8e2f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       [{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...\n",
       "1       [{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...\n",
       "2       [{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...\n",
       "3       [{\"id\": 849, \"name\": \"dc comics\"}, {\"id\": 853,...\n",
       "4       [{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...\n",
       "                              ...                        \n",
       "4804    [{\"id\": 5616, \"name\": \"united states\\u2013mexi...\n",
       "4805                                                   []\n",
       "4806    [{\"id\": 248, \"name\": \"date\"}, {\"id\": 699, \"nam...\n",
       "4807                                                   []\n",
       "4808    [{\"id\": 1523, \"name\": \"obsession\"}, {\"id\": 224...\n",
       "Name: keywords, Length: 4809, dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df['keywords']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2617d728",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id          0\n",
       "title       0\n",
       "overview    3\n",
       "budget      0\n",
       "genres      0\n",
       "keywords    0\n",
       "cast        0\n",
       "runtime     2\n",
       "revenue     0\n",
       "crew        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0905033f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Rajan\\AppData\\Local\\Temp\\ipykernel_15052\\2909182366.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\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",
      "  movies_df.dropna(inplace=True)\n"
     ]
    }
   ],
   "source": [
    "#Drop NaN values\n",
    "movies_df.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6afae141",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id          0\n",
       "title       0\n",
       "overview    0\n",
       "budget      0\n",
       "genres      0\n",
       "keywords    0\n",
       "cast        0\n",
       "runtime     0\n",
       "revenue     0\n",
       "crew        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7784812b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ace5bf89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"name\": \"Fantasy\"}, {\"id\": 878, \"name\": \"Science Fiction\"}]'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.iloc[0].genres"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "71c3b60c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import ast\n",
    "'''Converts dictionary to lists of lists'''\n",
    "def convert(obj):\n",
    "    L=[]\n",
    "    for i in ast.literal_eval(obj):\n",
    "        L.append(i['name'])\n",
    "    return L    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2f2b0c7e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'id': 28, 'name': 'Action'},\n",
       " {'id': 12, 'name': 'Adventure'},\n",
       " {'id': 14, 'name': 'Fantasy'},\n",
       " {'id': 878, 'name': 'Science Fiction'}]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p='[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"name\": \"Fantasy\"}, {\"id\": 878, \"name\": \"Science Fiction\"}]'\n",
    "ast.literal_eval(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6228d122",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       [Action, Adventure, Fantasy, Science Fiction]\n",
       "1                        [Adventure, Fantasy, Action]\n",
       "2                          [Action, Adventure, Crime]\n",
       "3                    [Action, Crime, Drama, Thriller]\n",
       "4                [Action, Adventure, Science Fiction]\n",
       "                            ...                      \n",
       "4804                        [Action, Crime, Thriller]\n",
       "4805                                [Comedy, Romance]\n",
       "4806               [Comedy, Drama, Romance, TV Movie]\n",
       "4807                                               []\n",
       "4808                                    [Documentary]\n",
       "Name: genres, Length: 4806, dtype: object"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df['genres'].apply(convert)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "437d8f24",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Rajan\\AppData\\Local\\Temp\\ipykernel_15052\\589800086.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",
      "  movies_df['genres'] = movies_df['genres'].apply(convert)\n"
     ]
    }
   ],
   "source": [
    "movies_df['genres'] = movies_df['genres'].apply(convert)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "303f4547",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>id</th>\n",
       "      <th>title</th>\n",
       "      <th>overview</th>\n",
       "      <th>budget</th>\n",
       "      <th>genres</th>\n",
       "      <th>keywords</th>\n",
       "      <th>cast</th>\n",
       "      <th>runtime</th>\n",
       "      <th>revenue</th>\n",
       "      <th>crew</th>\n",
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       "      <th>0</th>\n",
       "      <td>19995</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>In the 22nd century, a paraplegic Marine is di...</td>\n",
       "      <td>237000000</td>\n",
       "      <td>[Action, Adventure, Fantasy, Science Fiction]</td>\n",
       "      <td>[{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...</td>\n",
       "      <td>[{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...</td>\n",
       "      <td>162.0</td>\n",
       "      <td>2787965087</td>\n",
       "      <td>[{\"credit_id\": \"52fe48009251416c750aca23\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>285</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>Captain Barbossa, long believed to be dead, ha...</td>\n",
       "      <td>300000000</td>\n",
       "      <td>[Adventure, Fantasy, Action]</td>\n",
       "      <td>[{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...</td>\n",
       "      <td>[{\"cast_id\": 4, \"character\": \"Captain Jack Spa...</td>\n",
       "      <td>169.0</td>\n",
       "      <td>961000000</td>\n",
       "      <td>[{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>206647</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>A cryptic message from Bond’s past sends him o...</td>\n",
       "      <td>245000000</td>\n",
       "      <td>[Action, Adventure, Crime]</td>\n",
       "      <td>[{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...</td>\n",
       "      <td>[{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...</td>\n",
       "      <td>148.0</td>\n",
       "      <td>880674609</td>\n",
       "      <td>[{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>49026</td>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>Following the death of District Attorney Harve...</td>\n",
       "      <td>250000000</td>\n",
       "      <td>[Action, Crime, Drama, Thriller]</td>\n",
       "      <td>[{\"id\": 849, \"name\": \"dc comics\"}, {\"id\": 853,...</td>\n",
       "      <td>[{\"cast_id\": 2, \"character\": \"Bruce Wayne / Ba...</td>\n",
       "      <td>165.0</td>\n",
       "      <td>1084939099</td>\n",
       "      <td>[{\"credit_id\": \"52fe4781c3a36847f81398c3\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>49529</td>\n",
       "      <td>John Carter</td>\n",
       "      <td>John Carter is a war-weary, former military ca...</td>\n",
       "      <td>260000000</td>\n",
       "      <td>[Action, Adventure, Science Fiction]</td>\n",
       "      <td>[{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...</td>\n",
       "      <td>[{\"cast_id\": 5, \"character\": \"John Carter\", \"c...</td>\n",
       "      <td>132.0</td>\n",
       "      <td>284139100</td>\n",
       "      <td>[{\"credit_id\": \"52fe479ac3a36847f813eaa3\", \"de...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id                                     title  \\\n",
       "0   19995                                    Avatar   \n",
       "1     285  Pirates of the Caribbean: At World's End   \n",
       "2  206647                                   Spectre   \n",
       "3   49026                     The Dark Knight Rises   \n",
       "4   49529                               John Carter   \n",
       "\n",
       "                                            overview     budget  \\\n",
       "0  In the 22nd century, a paraplegic Marine is di...  237000000   \n",
       "1  Captain Barbossa, long believed to be dead, ha...  300000000   \n",
       "2  A cryptic message from Bond’s past sends him o...  245000000   \n",
       "3  Following the death of District Attorney Harve...  250000000   \n",
       "4  John Carter is a war-weary, former military ca...  260000000   \n",
       "\n",
       "                                          genres  \\\n",
       "0  [Action, Adventure, Fantasy, Science Fiction]   \n",
       "1                   [Adventure, Fantasy, Action]   \n",
       "2                     [Action, Adventure, Crime]   \n",
       "3               [Action, Crime, Drama, Thriller]   \n",
       "4           [Action, Adventure, Science Fiction]   \n",
       "\n",
       "                                            keywords  \\\n",
       "0  [{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...   \n",
       "1  [{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...   \n",
       "2  [{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...   \n",
       "3  [{\"id\": 849, \"name\": \"dc comics\"}, {\"id\": 853,...   \n",
       "4  [{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...   \n",
       "\n",
       "                                                cast  runtime     revenue  \\\n",
       "0  [{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...    162.0  2787965087   \n",
       "1  [{\"cast_id\": 4, \"character\": \"Captain Jack Spa...    169.0   961000000   \n",
       "2  [{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...    148.0   880674609   \n",
       "3  [{\"cast_id\": 2, \"character\": \"Bruce Wayne / Ba...    165.0  1084939099   \n",
       "4  [{\"cast_id\": 5, \"character\": \"John Carter\", \"c...    132.0   284139100   \n",
       "\n",
       "                                                crew  \n",
       "0  [{\"credit_id\": \"52fe48009251416c750aca23\", \"de...  \n",
       "1  [{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...  \n",
       "2  [{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...  \n",
       "3  [{\"credit_id\": \"52fe4781c3a36847f81398c3\", \"de...  \n",
       "4  [{\"credit_id\": \"52fe479ac3a36847f813eaa3\", \"de...  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "a6d75190",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Rajan\\AppData\\Local\\Temp\\ipykernel_15052\\1082450020.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",
      "  movies_df['keywords'] = movies_df['keywords'].apply(convert)\n"
     ]
    }
   ],
   "source": [
    "movies_df['keywords'] = movies_df['keywords'].apply(convert)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "ed559258",
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
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       "      <td>Avatar</td>\n",
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       "      <td>[Action, Adventure, Fantasy, Science Fiction]</td>\n",
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       "      <td>[{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...</td>\n",
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       "      <td>[{\"credit_id\": \"52fe48009251416c750aca23\", \"de...</td>\n",
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       "      <td>285</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>Captain Barbossa, long believed to be dead, ha...</td>\n",
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       "      <td>[{\"cast_id\": 4, \"character\": \"Captain Jack Spa...</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>206647</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>A cryptic message from Bond’s past sends him o...</td>\n",
       "      <td>245000000</td>\n",
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       "      <td>[{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...</td>\n",
       "      <td>148.0</td>\n",
       "      <td>880674609</td>\n",
       "      <td>[{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...</td>\n",
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       "      <th>3</th>\n",
       "      <td>49026</td>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>Following the death of District Attorney Harve...</td>\n",
       "      <td>250000000</td>\n",
       "      <td>[Action, Crime, Drama, Thriller]</td>\n",
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       "      <td>[{\"cast_id\": 2, \"character\": \"Bruce Wayne / Ba...</td>\n",
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       "      <th>4</th>\n",
       "      <td>49529</td>\n",
       "      <td>John Carter</td>\n",
       "      <td>John Carter is a war-weary, former military ca...</td>\n",
       "      <td>260000000</td>\n",
       "      <td>[Action, Adventure, Science Fiction]</td>\n",
       "      <td>[based on novel, mars, medallion, space travel...</td>\n",
       "      <td>[{\"cast_id\": 5, \"character\": \"John Carter\", \"c...</td>\n",
       "      <td>132.0</td>\n",
       "      <td>284139100</td>\n",
       "      <td>[{\"credit_id\": \"52fe479ac3a36847f813eaa3\", \"de...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id                                     title  \\\n",
       "0   19995                                    Avatar   \n",
       "1     285  Pirates of the Caribbean: At World's End   \n",
       "2  206647                                   Spectre   \n",
       "3   49026                     The Dark Knight Rises   \n",
       "4   49529                               John Carter   \n",
       "\n",
       "                                            overview     budget  \\\n",
       "0  In the 22nd century, a paraplegic Marine is di...  237000000   \n",
       "1  Captain Barbossa, long believed to be dead, ha...  300000000   \n",
       "2  A cryptic message from Bond’s past sends him o...  245000000   \n",
       "3  Following the death of District Attorney Harve...  250000000   \n",
       "4  John Carter is a war-weary, former military ca...  260000000   \n",
       "\n",
       "                                          genres  \\\n",
       "0  [Action, Adventure, Fantasy, Science Fiction]   \n",
       "1                   [Adventure, Fantasy, Action]   \n",
       "2                     [Action, Adventure, Crime]   \n",
       "3               [Action, Crime, Drama, Thriller]   \n",
       "4           [Action, Adventure, Science Fiction]   \n",
       "\n",
       "                                            keywords  \\\n",
       "0  [culture clash, future, space war, space colon...   \n",
       "1  [ocean, drug abuse, exotic island, east india ...   \n",
       "2  [spy, based on novel, secret agent, sequel, mi...   \n",
       "3  [dc comics, crime fighter, terrorist, secret i...   \n",
       "4  [based on novel, mars, medallion, space travel...   \n",
       "\n",
       "                                                cast  runtime     revenue  \\\n",
       "0  [{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...    162.0  2787965087   \n",
       "1  [{\"cast_id\": 4, \"character\": \"Captain Jack Spa...    169.0   961000000   \n",
       "2  [{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...    148.0   880674609   \n",
       "3  [{\"cast_id\": 2, \"character\": \"Bruce Wayne / Ba...    165.0  1084939099   \n",
       "4  [{\"cast_id\": 5, \"character\": \"John Carter\", \"c...    132.0   284139100   \n",
       "\n",
       "                                                crew  \n",
       "0  [{\"credit_id\": \"52fe48009251416c750aca23\", \"de...  \n",
       "1  [{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...  \n",
       "2  [{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...  \n",
       "3  [{\"credit_id\": \"52fe4781c3a36847f81398c3\", \"de...  \n",
       "4  [{\"credit_id\": \"52fe479ac3a36847f813eaa3\", \"de...  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "416783c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'[{\"cast_id\": 4, \"character\": \"Captain Jack Sparrow\", \"credit_id\": \"52fe4232c3a36847f800b50d\", \"gender\": 2, \"id\": 85, \"name\": \"Johnny Depp\", \"order\": 0}, {\"cast_id\": 5, \"character\": \"Will Turner\", \"credit_id\": \"52fe4232c3a36847f800b511\", \"gender\": 2, \"id\": 114, \"name\": \"Orlando Bloom\", \"order\": 1}, {\"cast_id\": 6, \"character\": \"Elizabeth Swann\", \"credit_id\": \"52fe4232c3a36847f800b515\", \"gender\": 1, \"id\": 116, \"name\": \"Keira Knightley\", \"order\": 2}, {\"cast_id\": 12, \"character\": \"William \\\\\"Bootstrap Bill\\\\\" Turner\", \"credit_id\": \"52fe4232c3a36847f800b52d\", \"gender\": 2, \"id\": 1640, \"name\": \"Stellan Skarsg\\\\u00e5rd\", \"order\": 3}, {\"cast_id\": 10, \"character\": \"Captain Sao Feng\", \"credit_id\": \"52fe4232c3a36847f800b525\", \"gender\": 2, \"id\": 1619, \"name\": \"Chow Yun-fat\", \"order\": 4}, {\"cast_id\": 9, \"character\": \"Captain Davy Jones\", \"credit_id\": \"52fe4232c3a36847f800b521\", \"gender\": 2, \"id\": 2440, \"name\": \"Bill Nighy\", \"order\": 5}, {\"cast_id\": 7, \"character\": \"Captain Hector Barbossa\", \"credit_id\": \"52fe4232c3a36847f800b519\", \"gender\": 2, \"id\": 118, \"name\": \"Geoffrey Rush\", \"order\": 6}, {\"cast_id\": 14, \"character\": \"Admiral James Norrington\", \"credit_id\": \"52fe4232c3a36847f800b535\", \"gender\": 2, \"id\": 1709, \"name\": \"Jack Davenport\", \"order\": 7}, {\"cast_id\": 13, \"character\": \"Joshamee Gibbs\", \"credit_id\": \"52fe4232c3a36847f800b531\", \"gender\": 2, \"id\": 2449, \"name\": \"Kevin McNally\", \"order\": 8}, {\"cast_id\": 11, \"character\": \"Lord Cutler Beckett\", \"credit_id\": \"52fe4232c3a36847f800b529\", \"gender\": 2, \"id\": 2441, \"name\": \"Tom Hollander\", \"order\": 9}, {\"cast_id\": 19, \"character\": \"Tia Dalma\", \"credit_id\": \"52fe4232c3a36847f800b549\", \"gender\": 1, \"id\": 2038, \"name\": \"Naomie Harris\", \"order\": 10}, {\"cast_id\": 8, \"character\": \"Governor Weatherby Swann\", \"credit_id\": \"52fe4232c3a36847f800b51d\", \"gender\": 2, \"id\": 378, \"name\": \"Jonathan Pryce\", \"order\": 11}, {\"cast_id\": 37, \"character\": \"Captain Teague Sparrow\", \"credit_id\": \"52fe4232c3a36847f800b5b3\", \"gender\": 2, \"id\": 1430, \"name\": \"Keith Richards\", \"order\": 12}, {\"cast_id\": 16, \"character\": \"Pintel\", \"credit_id\": \"52fe4232c3a36847f800b53d\", \"gender\": 2, \"id\": 1710, \"name\": \"Lee Arenberg\", \"order\": 13}, {\"cast_id\": 15, \"character\": \"Ragetti\", \"credit_id\": \"52fe4232c3a36847f800b539\", \"gender\": 2, \"id\": 1711, \"name\": \"Mackenzie Crook\", \"order\": 14}, {\"cast_id\": 18, \"character\": \"Lieutenant Theodore Groves\", \"credit_id\": \"52fe4232c3a36847f800b545\", \"gender\": 2, \"id\": 4031, \"name\": \"Greg Ellis\", \"order\": 15}, {\"cast_id\": 55, \"character\": \"Cotton\", \"credit_id\": \"57e28d2ec3a3681a01005b5c\", \"gender\": 2, \"id\": 1715, \"name\": \"David Bailie\", \"order\": 16}, {\"cast_id\": 17, \"character\": \"Marty\", \"credit_id\": \"52fe4232c3a36847f800b541\", \"gender\": 2, \"id\": 4030, \"name\": \"Martin Klebba\", \"order\": 17}, {\"cast_id\": 57, \"character\": \"Ian Mercer\", \"credit_id\": \"57e28d78c3a36808b900bf4f\", \"gender\": 0, \"id\": 939, \"name\": \"David Schofield\", \"order\": 18}, {\"cast_id\": 62, \"character\": \"Scarlett\", \"credit_id\": \"57e28ec5c3a3681a50005855\", \"gender\": 1, \"id\": 2450, \"name\": \"Lauren Maher\", \"order\": 19}, {\"cast_id\": 63, \"character\": \"Giselle\", \"credit_id\": \"57e28ed692514123f5005635\", \"gender\": 1, \"id\": 2452, \"name\": \"Vanessa Branch\", \"order\": 20}, {\"cast_id\": 60, \"character\": \"Mullroy\", \"credit_id\": \"57e28db2c3a3681a01005bc7\", \"gender\": 2, \"id\": 1714, \"name\": \"Angus Barnett\", \"order\": 21}, {\"cast_id\": 59, \"character\": \"Murtogg\", \"credit_id\": \"57e28da192514118f7006008\", \"gender\": 0, \"id\": 1713, \"name\": \"Giles New\", \"order\": 22}, {\"cast_id\": 58, \"character\": \"Tai Huang\", \"credit_id\": \"57e28d8ec3a3681a01005bab\", \"gender\": 2, \"id\": 22075, \"name\": \"Reggie Lee\", \"order\": 23}, {\"cast_id\": 64, \"character\": \"Henry Turner\", \"credit_id\": \"57e29119925141151100a6cc\", \"gender\": 2, \"id\": 61259, \"name\": \"Dominic Scott Kay\", \"order\": 24}, {\"cast_id\": 39, \"character\": \"Mistress Ching\", \"credit_id\": \"52fe4232c3a36847f800b5bd\", \"gender\": 1, \"id\": 33500, \"name\": \"Takayo Fischer\", \"order\": 25}, {\"cast_id\": 40, \"character\": \"Lieutenant Greitzer\", \"credit_id\": \"52fe4232c3a36847f800b5c1\", \"gender\": 2, \"id\": 1224149, \"name\": \"David Meunier\", \"order\": 26}, {\"cast_id\": 49, \"character\": \"Hadras\", \"credit_id\": \"56d1871c92514174680010cf\", \"gender\": 2, \"id\": 429401, \"name\": \"Ho-Kwan Tse\", \"order\": 27}, {\"cast_id\": 56, \"character\": \"Clacker\", \"credit_id\": \"57e28d4b92514125710055cb\", \"gender\": 0, \"id\": 1123, \"name\": \"Andy Beckwith\", \"order\": 28}, {\"cast_id\": 51, \"character\": \"Penrod\", \"credit_id\": \"56ec8c14c3a3682260003c53\", \"gender\": 2, \"id\": 1056117, \"name\": \"Peter Donald Badalamenti II\", \"order\": 29}, {\"cast_id\": 61, \"character\": \"Cotton\\'s Parrot (voice)\", \"credit_id\": \"57e28dcc9251412463005678\", \"gender\": 2, \"id\": 21700, \"name\": \"Christopher S. Capp\", \"order\": 30}, {\"cast_id\": 65, \"character\": \"Captain Teague\", \"credit_id\": \"58bc2a37c3a368663003740b\", \"gender\": 2, \"id\": 1430, \"name\": \"Keith Richards\", \"order\": 31}, {\"cast_id\": 66, \"character\": \"Captain Jocard\", \"credit_id\": \"58bc2a8e925141609e03a179\", \"gender\": 2, \"id\": 2603, \"name\": \"Hakeem Kae-Kazim\", \"order\": 32}, {\"cast_id\": 67, \"character\": \"Captain Ammand\", \"credit_id\": \"58e2a21ac3a36872af00f9c2\", \"gender\": 0, \"id\": 70577, \"name\": \"Ghassan Massoud\", \"order\": 33}]'"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df.loc[:,'cast'][1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "998cd452",
   "metadata": {},
   "outputs": [],
   "source": [
    "import ast\n",
    "'''Converts dictionary to lists of lists'''\n",
    "def convert2(obj):\n",
    "    L=[]\n",
    "    counter=0\n",
    "    for i in ast.literal_eval(obj):\n",
    "        if counter<4:  #to select first 4 characters and names only\n",
    "#             L.append(i['name']+' : '+i['character'])\n",
    "              L.append(i['name']+' '+i['character'])\n",
    "              counter+=1\n",
    "        else:\n",
    "            break\n",
    "    return L    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "d7ddeef9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Rajan\\AppData\\Local\\Temp\\ipykernel_15052\\1302294160.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",
      "  movies_df['cast'] = movies_df['cast'].apply(convert2)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0       [Sam Worthington Jake Sully, Zoe Saldana Neyti...\n",
       "1       [Johnny Depp Captain Jack Sparrow, Orlando Blo...\n",
       "2       [Daniel Craig James Bond, Christoph Waltz Blof...\n",
       "3       [Christian Bale Bruce Wayne / Batman, Michael ...\n",
       "4       [Taylor Kitsch John Carter, Lynn Collins Dejah...\n",
       "                              ...                        \n",
       "4804    [Carlos Gallardo El Mariachi, Jaime de Hoyos B...\n",
       "4805    [Edward Burns Buzzy, Kerry Bishé Linda, Marsha...\n",
       "4806    [Eric Mabius Oliver O’Toole, Kristin Booth Sha...\n",
       "4807    [Daniel Henney Sam, Eliza Coupe Amanda, Bill P...\n",
       "4808    [Drew Barrymore Herself, Brian Herzlinger Hims...\n",
       "Name: cast, Length: 4806, dtype: object"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df['cast'] = movies_df['cast'].apply(convert2)\n",
    "movies_df['cast']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "199ac64e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Sam Worthington Jake Sully',\n",
       " 'Zoe Saldana Neytiri',\n",
       " 'Sigourney Weaver Dr. Grace Augustine',\n",
       " 'Stephen Lang Col. Quaritch']"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df['cast'][0] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "4f6d0922",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>id</th>\n",
       "      <th>title</th>\n",
       "      <th>overview</th>\n",
       "      <th>budget</th>\n",
       "      <th>genres</th>\n",
       "      <th>keywords</th>\n",
       "      <th>cast</th>\n",
       "      <th>runtime</th>\n",
       "      <th>revenue</th>\n",
       "      <th>crew</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19995</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>In the 22nd century, a paraplegic Marine is di...</td>\n",
       "      <td>237000000</td>\n",
       "      <td>[Action, Adventure, Fantasy, Science Fiction]</td>\n",
       "      <td>[culture clash, future, space war, space colon...</td>\n",
       "      <td>[Sam Worthington Jake Sully, Zoe Saldana Neyti...</td>\n",
       "      <td>162.0</td>\n",
       "      <td>2787965087</td>\n",
       "      <td>[{\"credit_id\": \"52fe48009251416c750aca23\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>285</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>Captain Barbossa, long believed to be dead, ha...</td>\n",
       "      <td>300000000</td>\n",
       "      <td>[Adventure, Fantasy, Action]</td>\n",
       "      <td>[ocean, drug abuse, exotic island, east india ...</td>\n",
       "      <td>[Johnny Depp Captain Jack Sparrow, Orlando Blo...</td>\n",
       "      <td>169.0</td>\n",
       "      <td>961000000</td>\n",
       "      <td>[{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>206647</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>A cryptic message from Bond’s past sends him o...</td>\n",
       "      <td>245000000</td>\n",
       "      <td>[Action, Adventure, Crime]</td>\n",
       "      <td>[spy, based on novel, secret agent, sequel, mi...</td>\n",
       "      <td>[Daniel Craig James Bond, Christoph Waltz Blof...</td>\n",
       "      <td>148.0</td>\n",
       "      <td>880674609</td>\n",
       "      <td>[{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>49026</td>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>Following the death of District Attorney Harve...</td>\n",
       "      <td>250000000</td>\n",
       "      <td>[Action, Crime, Drama, Thriller]</td>\n",
       "      <td>[dc comics, crime fighter, terrorist, secret i...</td>\n",
       "      <td>[Christian Bale Bruce Wayne / Batman, Michael ...</td>\n",
       "      <td>165.0</td>\n",
       "      <td>1084939099</td>\n",
       "      <td>[{\"credit_id\": \"52fe4781c3a36847f81398c3\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>49529</td>\n",
       "      <td>John Carter</td>\n",
       "      <td>John Carter is a war-weary, former military ca...</td>\n",
       "      <td>260000000</td>\n",
       "      <td>[Action, Adventure, Science Fiction]</td>\n",
       "      <td>[based on novel, mars, medallion, space travel...</td>\n",
       "      <td>[Taylor Kitsch John Carter, Lynn Collins Dejah...</td>\n",
       "      <td>132.0</td>\n",
       "      <td>284139100</td>\n",
       "      <td>[{\"credit_id\": \"52fe479ac3a36847f813eaa3\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4804</th>\n",
       "      <td>9367</td>\n",
       "      <td>El Mariachi</td>\n",
       "      <td>El Mariachi just wants to play his guitar and ...</td>\n",
       "      <td>220000</td>\n",
       "      <td>[Action, Crime, Thriller]</td>\n",
       "      <td>[united states–mexico barrier, legs, arms, pap...</td>\n",
       "      <td>[Carlos Gallardo El Mariachi, Jaime de Hoyos B...</td>\n",
       "      <td>81.0</td>\n",
       "      <td>2040920</td>\n",
       "      <td>[{\"credit_id\": \"52fe44eec3a36847f80b280b\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4805</th>\n",
       "      <td>72766</td>\n",
       "      <td>Newlyweds</td>\n",
       "      <td>A newlywed couple's honeymoon is upended by th...</td>\n",
       "      <td>9000</td>\n",
       "      <td>[Comedy, Romance]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[Edward Burns Buzzy, Kerry Bishé Linda, Marsha...</td>\n",
       "      <td>85.0</td>\n",
       "      <td>0</td>\n",
       "      <td>[{\"credit_id\": \"52fe487dc3a368484e0fb013\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4806</th>\n",
       "      <td>231617</td>\n",
       "      <td>Signed, Sealed, Delivered</td>\n",
       "      <td>\"Signed, Sealed, Delivered\" introduces a dedic...</td>\n",
       "      <td>0</td>\n",
       "      <td>[Comedy, Drama, Romance, TV Movie]</td>\n",
       "      <td>[date, love at first sight, narration, investi...</td>\n",
       "      <td>[Eric Mabius Oliver O’Toole, Kristin Booth Sha...</td>\n",
       "      <td>120.0</td>\n",
       "      <td>0</td>\n",
       "      <td>[{\"credit_id\": \"52fe4df3c3a36847f8275ecf\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4807</th>\n",
       "      <td>126186</td>\n",
       "      <td>Shanghai Calling</td>\n",
       "      <td>When ambitious New York attorney Sam is sent t...</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[Daniel Henney Sam, Eliza Coupe Amanda, Bill P...</td>\n",
       "      <td>98.0</td>\n",
       "      <td>0</td>\n",
       "      <td>[{\"credit_id\": \"52fe4ad9c3a368484e16a36b\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4808</th>\n",
       "      <td>25975</td>\n",
       "      <td>My Date with Drew</td>\n",
       "      <td>Ever since the second grade when he first saw ...</td>\n",
       "      <td>0</td>\n",
       "      <td>[Documentary]</td>\n",
       "      <td>[obsession, camcorder, crush, dream girl]</td>\n",
       "      <td>[Drew Barrymore Herself, Brian Herzlinger Hims...</td>\n",
       "      <td>90.0</td>\n",
       "      <td>0</td>\n",
       "      <td>[{\"credit_id\": \"58ce021b9251415a390165d9\", \"de...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4806 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id                                     title  \\\n",
       "0      19995                                    Avatar   \n",
       "1        285  Pirates of the Caribbean: At World's End   \n",
       "2     206647                                   Spectre   \n",
       "3      49026                     The Dark Knight Rises   \n",
       "4      49529                               John Carter   \n",
       "...      ...                                       ...   \n",
       "4804    9367                               El Mariachi   \n",
       "4805   72766                                 Newlyweds   \n",
       "4806  231617                 Signed, Sealed, Delivered   \n",
       "4807  126186                          Shanghai Calling   \n",
       "4808   25975                         My Date with Drew   \n",
       "\n",
       "                                               overview     budget  \\\n",
       "0     In the 22nd century, a paraplegic Marine is di...  237000000   \n",
       "1     Captain Barbossa, long believed to be dead, ha...  300000000   \n",
       "2     A cryptic message from Bond’s past sends him o...  245000000   \n",
       "3     Following the death of District Attorney Harve...  250000000   \n",
       "4     John Carter is a war-weary, former military ca...  260000000   \n",
       "...                                                 ...        ...   \n",
       "4804  El Mariachi just wants to play his guitar and ...     220000   \n",
       "4805  A newlywed couple's honeymoon is upended by th...       9000   \n",
       "4806  \"Signed, Sealed, Delivered\" introduces a dedic...          0   \n",
       "4807  When ambitious New York attorney Sam is sent t...          0   \n",
       "4808  Ever since the second grade when he first saw ...          0   \n",
       "\n",
       "                                             genres  \\\n",
       "0     [Action, Adventure, Fantasy, Science Fiction]   \n",
       "1                      [Adventure, Fantasy, Action]   \n",
       "2                        [Action, Adventure, Crime]   \n",
       "3                  [Action, Crime, Drama, Thriller]   \n",
       "4              [Action, Adventure, Science Fiction]   \n",
       "...                                             ...   \n",
       "4804                      [Action, Crime, Thriller]   \n",
       "4805                              [Comedy, Romance]   \n",
       "4806             [Comedy, Drama, Romance, TV Movie]   \n",
       "4807                                             []   \n",
       "4808                                  [Documentary]   \n",
       "\n",
       "                                               keywords  \\\n",
       "0     [culture clash, future, space war, space colon...   \n",
       "1     [ocean, drug abuse, exotic island, east india ...   \n",
       "2     [spy, based on novel, secret agent, sequel, mi...   \n",
       "3     [dc comics, crime fighter, terrorist, secret i...   \n",
       "4     [based on novel, mars, medallion, space travel...   \n",
       "...                                                 ...   \n",
       "4804  [united states–mexico barrier, legs, arms, pap...   \n",
       "4805                                                 []   \n",
       "4806  [date, love at first sight, narration, investi...   \n",
       "4807                                                 []   \n",
       "4808          [obsession, camcorder, crush, dream girl]   \n",
       "\n",
       "                                                   cast  runtime     revenue  \\\n",
       "0     [Sam Worthington Jake Sully, Zoe Saldana Neyti...    162.0  2787965087   \n",
       "1     [Johnny Depp Captain Jack Sparrow, Orlando Blo...    169.0   961000000   \n",
       "2     [Daniel Craig James Bond, Christoph Waltz Blof...    148.0   880674609   \n",
       "3     [Christian Bale Bruce Wayne / Batman, Michael ...    165.0  1084939099   \n",
       "4     [Taylor Kitsch John Carter, Lynn Collins Dejah...    132.0   284139100   \n",
       "...                                                 ...      ...         ...   \n",
       "4804  [Carlos Gallardo El Mariachi, Jaime de Hoyos B...     81.0     2040920   \n",
       "4805  [Edward Burns Buzzy, Kerry Bishé Linda, Marsha...     85.0           0   \n",
       "4806  [Eric Mabius Oliver O’Toole, Kristin Booth Sha...    120.0           0   \n",
       "4807  [Daniel Henney Sam, Eliza Coupe Amanda, Bill P...     98.0           0   \n",
       "4808  [Drew Barrymore Herself, Brian Herzlinger Hims...     90.0           0   \n",
       "\n",
       "                                                   crew  \n",
       "0     [{\"credit_id\": \"52fe48009251416c750aca23\", \"de...  \n",
       "1     [{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...  \n",
       "2     [{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...  \n",
       "3     [{\"credit_id\": \"52fe4781c3a36847f81398c3\", \"de...  \n",
       "4     [{\"credit_id\": \"52fe479ac3a36847f813eaa3\", \"de...  \n",
       "...                                                 ...  \n",
       "4804  [{\"credit_id\": \"52fe44eec3a36847f80b280b\", \"de...  \n",
       "4805  [{\"credit_id\": \"52fe487dc3a368484e0fb013\", \"de...  \n",
       "4806  [{\"credit_id\": \"52fe4df3c3a36847f8275ecf\", \"de...  \n",
       "4807  [{\"credit_id\": \"52fe4ad9c3a368484e16a36b\", \"de...  \n",
       "4808  [{\"credit_id\": \"58ce021b9251415a390165d9\", \"de...  \n",
       "\n",
       "[4806 rows x 10 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "bb563500",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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{\"credit_id\": \"54959f07c3a3680fc60027f9\", \"department\": \"Camera\", \"gender\": 2, \"id\": 1401806, \"job\": \"Still Photographer\", \"name\": \"Mark Fellman\"}, {\"credit_id\": \"54959f47c3a3681153002774\", \"department\": \"Lighting\", \"gender\": 0, \"id\": 1401807, \"job\": \"Lighting Technician\", \"name\": \"Scott Sprague\"}, {\"credit_id\": \"54959f8cc3a36831b8001df2\", \"department\": \"Visual Effects\", \"gender\": 0, \"id\": 1401808, \"job\": \"Animation Director\", \"name\": \"Jeremy Hollobon\"}, {\"credit_id\": \"54959fa0c3a36831b8001dfb\", \"department\": \"Visual Effects\", \"gender\": 0, \"id\": 1401809, \"job\": \"Animation Director\", \"name\": \"Orlando Meunier\"}, {\"credit_id\": \"54959fb6c3a3686af3003f54\", \"department\": \"Visual Effects\", \"gender\": 0, \"id\": 1401810, \"job\": \"Animation Director\", \"name\": \"Taisuke Tanimura\"}, {\"credit_id\": \"54959fd2c3a36831b8001e02\", \"department\": \"Costume & Make-Up\", \"gender\": 0, \"id\": 1401812, \"job\": \"Set Costumer\", \"name\": \"Lilia Mishel Acevedo\"}, {\"credit_id\": \"54959ff9c3a3686ae300440c\", \"department\": \"Costume & Make-Up\", \"gender\": 0, \"id\": 1401814, \"job\": \"Set Costumer\", \"name\": \"Alejandro M. Hernandez\"}, {\"credit_id\": \"5495a0ddc3a3686ae10046fe\", \"department\": \"Editing\", \"gender\": 0, \"id\": 1401815, \"job\": \"Digital Intermediate\", \"name\": \"Marvin Hall\"}, {\"credit_id\": \"5495a1f7c3a3686ae3004443\", \"department\": \"Production\", \"gender\": 0, \"id\": 1401816, \"job\": \"Publicist\", \"name\": \"Judy Alley\"}, {\"credit_id\": \"5592b29fc3a36869d100002f\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1418381, \"job\": \"CG Supervisor\", \"name\": \"Mike Perry\"}, {\"credit_id\": \"5592b23a9251415df8001081\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1426854, \"job\": \"CG Supervisor\", \"name\": \"Andrew Morley\"}, {\"credit_id\": \"55491e1192514104c40002d8\", \"department\": \"Art\", \"gender\": 0, \"id\": 1438901, \"job\": \"Conceptual Design\", \"name\": \"Seth Engstrom\"}, {\"credit_id\": \"5525d5809251417276002b06\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1447362, \"job\": \"Visual Effects Art Director\", \"name\": \"Eric Oliver\"}, {\"credit_id\": \"554427ca925141586500312a\", \"department\": \"Visual Effects\", \"gender\": 0, \"id\": 1447503, \"job\": \"Modeling\", \"name\": \"Matsune Suzuki\"}, {\"credit_id\": \"551906889251415aab001c88\", \"department\": \"Art\", \"gender\": 0, \"id\": 1447524, \"job\": \"Art Department Manager\", \"name\": \"Paul Tobin\"}, {\"credit_id\": \"5592af8492514152cc0010de\", \"department\": \"Costume & Make-Up\", \"gender\": 0, \"id\": 1452643, \"job\": \"Hairstylist\", \"name\": \"Roxane Griffin\"}, {\"credit_id\": \"553d3c109251415852001318\", \"department\": \"Lighting\", \"gender\": 0, \"id\": 1453938, \"job\": \"Lighting Artist\", \"name\": \"Arun Ram-Mohan\"}, {\"credit_id\": \"5592af4692514152d5001355\", \"department\": \"Costume & Make-Up\", \"gender\": 0, \"id\": 1457305, \"job\": \"Makeup Artist\", \"name\": \"Georgia Lockhart-Adams\"}, {\"credit_id\": \"5592b2eac3a36877470012a5\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1466035, \"job\": \"CG Supervisor\", \"name\": \"Thrain Shadbolt\"}, {\"credit_id\": \"5592b032c3a36877450015f1\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483220, \"job\": \"CG Supervisor\", \"name\": \"Brad Alexander\"}, {\"credit_id\": \"5592b05592514152d80012f6\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483221, \"job\": \"CG Supervisor\", \"name\": \"Shadi Almassizadeh\"}, {\"credit_id\": \"5592b090c3a36877570010b5\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483222, \"job\": \"CG Supervisor\", \"name\": \"Simon Clutterbuck\"}, {\"credit_id\": \"5592b0dbc3a368774b00112c\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483223, \"job\": \"CG Supervisor\", \"name\": \"Graeme Demmocks\"}, {\"credit_id\": \"5592b0fe92514152db0010c1\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483224, \"job\": \"CG Supervisor\", \"name\": \"Adrian Fernandes\"}, {\"credit_id\": \"5592b11f9251415df8001059\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483225, \"job\": \"CG Supervisor\", \"name\": \"Mitch Gates\"}, {\"credit_id\": \"5592b15dc3a3687745001645\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483226, \"job\": \"CG Supervisor\", \"name\": \"Jerry Kung\"}, {\"credit_id\": \"5592b18e925141645a0004ae\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483227, \"job\": \"CG Supervisor\", \"name\": \"Andy Lomas\"}, {\"credit_id\": \"5592b1bfc3a368775d0010e7\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483228, \"job\": \"CG Supervisor\", \"name\": \"Sebastian Marino\"}, {\"credit_id\": \"5592b2049251415df8001078\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483229, \"job\": \"CG Supervisor\", \"name\": \"Matthias Menz\"}, {\"credit_id\": \"5592b27b92514152d800136a\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483230, \"job\": \"CG Supervisor\", \"name\": \"Sergei Nevshupov\"}, {\"credit_id\": \"5592b2c3c3a36869e800003c\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483231, \"job\": \"CG Supervisor\", \"name\": \"Philippe Rebours\"}, {\"credit_id\": \"5592b317c3a36877470012af\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483232, \"job\": \"CG Supervisor\", \"name\": \"Michael Takarangi\"}, {\"credit_id\": \"5592b345c3a36877470012bb\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483233, \"job\": \"CG Supervisor\", \"name\": \"David Weitzberg\"}, {\"credit_id\": \"5592b37cc3a368775100113b\", \"department\": \"Crew\", \"gender\": 0, \"id\": 1483234, \"job\": \"CG Supervisor\", \"name\": \"Ben White\"}, {\"credit_id\": \"573c8e2f9251413f5d000094\", \"department\": \"Crew\", \"gender\": 1, \"id\": 1621932, \"job\": \"Stunts\", \"name\": \"Min Windle\"}]'"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df['crew'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "c93b7ee0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def fetch_director(obj):\n",
    "    L=[]\n",
    "    for i in ast.literal_eval(obj):\n",
    "        if i['job']  == 'Director':\n",
    "            L.append(i['name'])\n",
    "            break\n",
    "    return L"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "d606a1b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0           [James Cameron]\n",
       "1          [Gore Verbinski]\n",
       "2              [Sam Mendes]\n",
       "3       [Christopher Nolan]\n",
       "4          [Andrew Stanton]\n",
       "               ...         \n",
       "4804     [Robert Rodriguez]\n",
       "4805         [Edward Burns]\n",
       "4806          [Scott Smith]\n",
       "4807          [Daniel Hsia]\n",
       "4808     [Brian Herzlinger]\n",
       "Name: crew, Length: 4806, dtype: object"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df['crew'].apply(fetch_director)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "729252c3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Rajan\\AppData\\Local\\Temp\\ipykernel_15052\\1727772831.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",
      "  movies_df['crew'] = movies_df['crew'].apply(fetch_director)\n"
     ]
    }
   ],
   "source": [
    "movies_df['crew'] = movies_df['crew'].apply(fetch_director)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "cfb1d7e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>id</th>\n",
       "      <th>title</th>\n",
       "      <th>overview</th>\n",
       "      <th>budget</th>\n",
       "      <th>genres</th>\n",
       "      <th>keywords</th>\n",
       "      <th>cast</th>\n",
       "      <th>runtime</th>\n",
       "      <th>revenue</th>\n",
       "      <th>crew</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19995</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>In the 22nd century, a paraplegic Marine is di...</td>\n",
       "      <td>237000000</td>\n",
       "      <td>[Action, Adventure, Fantasy, Science Fiction]</td>\n",
       "      <td>[culture clash, future, space war, space colon...</td>\n",
       "      <td>[Sam Worthington Jake Sully, Zoe Saldana Neyti...</td>\n",
       "      <td>162.0</td>\n",
       "      <td>2787965087</td>\n",
       "      <td>[James Cameron]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>285</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>Captain Barbossa, long believed to be dead, ha...</td>\n",
       "      <td>300000000</td>\n",
       "      <td>[Adventure, Fantasy, Action]</td>\n",
       "      <td>[ocean, drug abuse, exotic island, east india ...</td>\n",
       "      <td>[Johnny Depp Captain Jack Sparrow, Orlando Blo...</td>\n",
       "      <td>169.0</td>\n",
       "      <td>961000000</td>\n",
       "      <td>[Gore Verbinski]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>206647</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>A cryptic message from Bond’s past sends him o...</td>\n",
       "      <td>245000000</td>\n",
       "      <td>[Action, Adventure, Crime]</td>\n",
       "      <td>[spy, based on novel, secret agent, sequel, mi...</td>\n",
       "      <td>[Daniel Craig James Bond, Christoph Waltz Blof...</td>\n",
       "      <td>148.0</td>\n",
       "      <td>880674609</td>\n",
       "      <td>[Sam Mendes]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>49026</td>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>Following the death of District Attorney Harve...</td>\n",
       "      <td>250000000</td>\n",
       "      <td>[Action, Crime, Drama, Thriller]</td>\n",
       "      <td>[dc comics, crime fighter, terrorist, secret i...</td>\n",
       "      <td>[Christian Bale Bruce Wayne / Batman, Michael ...</td>\n",
       "      <td>165.0</td>\n",
       "      <td>1084939099</td>\n",
       "      <td>[Christopher Nolan]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>49529</td>\n",
       "      <td>John Carter</td>\n",
       "      <td>John Carter is a war-weary, former military ca...</td>\n",
       "      <td>260000000</td>\n",
       "      <td>[Action, Adventure, Science Fiction]</td>\n",
       "      <td>[based on novel, mars, medallion, space travel...</td>\n",
       "      <td>[Taylor Kitsch John Carter, Lynn Collins Dejah...</td>\n",
       "      <td>132.0</td>\n",
       "      <td>284139100</td>\n",
       "      <td>[Andrew Stanton]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4804</th>\n",
       "      <td>9367</td>\n",
       "      <td>El Mariachi</td>\n",
       "      <td>El Mariachi just wants to play his guitar and ...</td>\n",
       "      <td>220000</td>\n",
       "      <td>[Action, Crime, Thriller]</td>\n",
       "      <td>[united states–mexico barrier, legs, arms, pap...</td>\n",
       "      <td>[Carlos Gallardo El Mariachi, Jaime de Hoyos B...</td>\n",
       "      <td>81.0</td>\n",
       "      <td>2040920</td>\n",
       "      <td>[Robert Rodriguez]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4805</th>\n",
       "      <td>72766</td>\n",
       "      <td>Newlyweds</td>\n",
       "      <td>A newlywed couple's honeymoon is upended by th...</td>\n",
       "      <td>9000</td>\n",
       "      <td>[Comedy, Romance]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[Edward Burns Buzzy, Kerry Bishé Linda, Marsha...</td>\n",
       "      <td>85.0</td>\n",
       "      <td>0</td>\n",
       "      <td>[Edward Burns]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4806</th>\n",
       "      <td>231617</td>\n",
       "      <td>Signed, Sealed, Delivered</td>\n",
       "      <td>\"Signed, Sealed, Delivered\" introduces a dedic...</td>\n",
       "      <td>0</td>\n",
       "      <td>[Comedy, Drama, Romance, TV Movie]</td>\n",
       "      <td>[date, love at first sight, narration, investi...</td>\n",
       "      <td>[Eric Mabius Oliver O’Toole, Kristin Booth Sha...</td>\n",
       "      <td>120.0</td>\n",
       "      <td>0</td>\n",
       "      <td>[Scott Smith]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4807</th>\n",
       "      <td>126186</td>\n",
       "      <td>Shanghai Calling</td>\n",
       "      <td>When ambitious New York attorney Sam is sent t...</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[Daniel Henney Sam, Eliza Coupe Amanda, Bill P...</td>\n",
       "      <td>98.0</td>\n",
       "      <td>0</td>\n",
       "      <td>[Daniel Hsia]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4808</th>\n",
       "      <td>25975</td>\n",
       "      <td>My Date with Drew</td>\n",
       "      <td>Ever since the second grade when he first saw ...</td>\n",
       "      <td>0</td>\n",
       "      <td>[Documentary]</td>\n",
       "      <td>[obsession, camcorder, crush, dream girl]</td>\n",
       "      <td>[Drew Barrymore Herself, Brian Herzlinger Hims...</td>\n",
       "      <td>90.0</td>\n",
       "      <td>0</td>\n",
       "      <td>[Brian Herzlinger]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4806 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id                                     title  \\\n",
       "0      19995                                    Avatar   \n",
       "1        285  Pirates of the Caribbean: At World's End   \n",
       "2     206647                                   Spectre   \n",
       "3      49026                     The Dark Knight Rises   \n",
       "4      49529                               John Carter   \n",
       "...      ...                                       ...   \n",
       "4804    9367                               El Mariachi   \n",
       "4805   72766                                 Newlyweds   \n",
       "4806  231617                 Signed, Sealed, Delivered   \n",
       "4807  126186                          Shanghai Calling   \n",
       "4808   25975                         My Date with Drew   \n",
       "\n",
       "                                               overview     budget  \\\n",
       "0     In the 22nd century, a paraplegic Marine is di...  237000000   \n",
       "1     Captain Barbossa, long believed to be dead, ha...  300000000   \n",
       "2     A cryptic message from Bond’s past sends him o...  245000000   \n",
       "3     Following the death of District Attorney Harve...  250000000   \n",
       "4     John Carter is a war-weary, former military ca...  260000000   \n",
       "...                                                 ...        ...   \n",
       "4804  El Mariachi just wants to play his guitar and ...     220000   \n",
       "4805  A newlywed couple's honeymoon is upended by th...       9000   \n",
       "4806  \"Signed, Sealed, Delivered\" introduces a dedic...          0   \n",
       "4807  When ambitious New York attorney Sam is sent t...          0   \n",
       "4808  Ever since the second grade when he first saw ...          0   \n",
       "\n",
       "                                             genres  \\\n",
       "0     [Action, Adventure, Fantasy, Science Fiction]   \n",
       "1                      [Adventure, Fantasy, Action]   \n",
       "2                        [Action, Adventure, Crime]   \n",
       "3                  [Action, Crime, Drama, Thriller]   \n",
       "4              [Action, Adventure, Science Fiction]   \n",
       "...                                             ...   \n",
       "4804                      [Action, Crime, Thriller]   \n",
       "4805                              [Comedy, Romance]   \n",
       "4806             [Comedy, Drama, Romance, TV Movie]   \n",
       "4807                                             []   \n",
       "4808                                  [Documentary]   \n",
       "\n",
       "                                               keywords  \\\n",
       "0     [culture clash, future, space war, space colon...   \n",
       "1     [ocean, drug abuse, exotic island, east india ...   \n",
       "2     [spy, based on novel, secret agent, sequel, mi...   \n",
       "3     [dc comics, crime fighter, terrorist, secret i...   \n",
       "4     [based on novel, mars, medallion, space travel...   \n",
       "...                                                 ...   \n",
       "4804  [united states–mexico barrier, legs, arms, pap...   \n",
       "4805                                                 []   \n",
       "4806  [date, love at first sight, narration, investi...   \n",
       "4807                                                 []   \n",
       "4808          [obsession, camcorder, crush, dream girl]   \n",
       "\n",
       "                                                   cast  runtime     revenue  \\\n",
       "0     [Sam Worthington Jake Sully, Zoe Saldana Neyti...    162.0  2787965087   \n",
       "1     [Johnny Depp Captain Jack Sparrow, Orlando Blo...    169.0   961000000   \n",
       "2     [Daniel Craig James Bond, Christoph Waltz Blof...    148.0   880674609   \n",
       "3     [Christian Bale Bruce Wayne / Batman, Michael ...    165.0  1084939099   \n",
       "4     [Taylor Kitsch John Carter, Lynn Collins Dejah...    132.0   284139100   \n",
       "...                                                 ...      ...         ...   \n",
       "4804  [Carlos Gallardo El Mariachi, Jaime de Hoyos B...     81.0     2040920   \n",
       "4805  [Edward Burns Buzzy, Kerry Bishé Linda, Marsha...     85.0           0   \n",
       "4806  [Eric Mabius Oliver O’Toole, Kristin Booth Sha...    120.0           0   \n",
       "4807  [Daniel Henney Sam, Eliza Coupe Amanda, Bill P...     98.0           0   \n",
       "4808  [Drew Barrymore Herself, Brian Herzlinger Hims...     90.0           0   \n",
       "\n",
       "                     crew  \n",
       "0         [James Cameron]  \n",
       "1        [Gore Verbinski]  \n",
       "2            [Sam Mendes]  \n",
       "3     [Christopher Nolan]  \n",
       "4        [Andrew Stanton]  \n",
       "...                   ...  \n",
       "4804   [Robert Rodriguez]  \n",
       "4805       [Edward Burns]  \n",
       "4806        [Scott Smith]  \n",
       "4807        [Daniel Hsia]  \n",
       "4808   [Brian Herzlinger]  \n",
       "\n",
       "[4806 rows x 10 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "836d55f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       [In, the, 22nd, century,, a, paraplegic, Marin...\n",
       "1       [Captain, Barbossa,, long, believed, to, be, d...\n",
       "2       [A, cryptic, message, from, Bond’s, past, send...\n",
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       "                              ...                        \n",
       "4804    [El, Mariachi, just, wants, to, play, his, gui...\n",
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       "4807    [When, ambitious, New, York, attorney, Sam, is...\n",
       "4808    [Ever, since, the, second, grade, when, he, fi...\n",
       "Name: overview, Length: 4806, dtype: object"
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     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "movies_df['overview'].apply(lambda x:x.split())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "370856de",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Rajan\\AppData\\Local\\Temp\\ipykernel_15052\\110895886.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",
      "  movies_df['overview'] = movies_df['overview'].apply(lambda x:x.split())\n"
     ]
    }
   ],
   "source": [
    "movies_df['overview'] = movies_df['overview'].apply(lambda x:x.split())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "ef7de1f4",
   "metadata": {},
   "outputs": [
    {
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       "          id                                     title  \\\n",
       "0      19995                                    Avatar   \n",
       "1        285  Pirates of the Caribbean: At World's End   \n",
       "2     206647                                   Spectre   \n",
       "3      49026                     The Dark Knight Rises   \n",
       "4      49529                               John Carter   \n",
       "...      ...                                       ...   \n",
       "4804    9367                               El Mariachi   \n",
       "4805   72766                                 Newlyweds   \n",
       "4806  231617                 Signed, Sealed, Delivered   \n",
       "4807  126186                          Shanghai Calling   \n",
       "4808   25975                         My Date with Drew   \n",
       "\n",
       "                                               overview     budget  \\\n",
       "0     [In, the, 22nd, century,, a, paraplegic, Marin...  237000000   \n",
       "1     [Captain, Barbossa,, long, believed, to, be, d...  300000000   \n",
       "2     [A, cryptic, message, from, Bond’s, past, send...  245000000   \n",
       "3     [Following, the, death, of, District, Attorney...  250000000   \n",
       "4     [John, Carter, is, a, war-weary,, former, mili...  260000000   \n",
       "...                                                 ...        ...   \n",
       "4804  [El, Mariachi, just, wants, to, play, his, gui...     220000   \n",
       "4805  [A, newlywed, couple's, honeymoon, is, upended...       9000   \n",
       "4806  [\"Signed,, Sealed,, Delivered\", introduces, a,...          0   \n",
       "4807  [When, ambitious, New, York, attorney, Sam, is...          0   \n",
       "4808  [Ever, since, the, second, grade, when, he, fi...          0   \n",
       "\n",
       "                                             genres  \\\n",
       "0     [Action, Adventure, Fantasy, Science Fiction]   \n",
       "1                      [Adventure, Fantasy, Action]   \n",
       "2                        [Action, Adventure, Crime]   \n",
       "3                  [Action, Crime, Drama, Thriller]   \n",
       "4              [Action, Adventure, Science Fiction]   \n",
       "...                                             ...   \n",
       "4804                      [Action, Crime, Thriller]   \n",
       "4805                              [Comedy, Romance]   \n",
       "4806             [Comedy, Drama, Romance, TV Movie]   \n",
       "4807                                             []   \n",
       "4808                                  [Documentary]   \n",
       "\n",
       "                                               keywords  \\\n",
       "0     [culture clash, future, space war, space colon...   \n",
       "1     [ocean, drug abuse, exotic island, east india ...   \n",
       "2     [spy, based on novel, secret agent, sequel, mi...   \n",
       "3     [dc comics, crime fighter, terrorist, secret i...   \n",
       "4     [based on novel, mars, medallion, space travel...   \n",
       "...                                                 ...   \n",
       "4804  [united states–mexico barrier, legs, arms, pap...   \n",
       "4805                                                 []   \n",
       "4806  [date, love at first sight, narration, investi...   \n",
       "4807                                                 []   \n",
       "4808          [obsession, camcorder, crush, dream girl]   \n",
       "\n",
       "                                                   cast  runtime     revenue  \\\n",
       "0     [Sam Worthington Jake Sully, Zoe Saldana Neyti...    162.0  2787965087   \n",
       "1     [Johnny Depp Captain Jack Sparrow, Orlando Blo...    169.0   961000000   \n",
       "2     [Daniel Craig James Bond, Christoph Waltz Blof...    148.0   880674609   \n",
       "3     [Christian Bale Bruce Wayne / Batman, Michael ...    165.0  1084939099   \n",
       "4     [Taylor Kitsch John Carter, Lynn Collins Dejah...    132.0   284139100   \n",
       "...                                                 ...      ...         ...   \n",
       "4804  [Carlos Gallardo El Mariachi, Jaime de Hoyos B...     81.0     2040920   \n",
       "4805  [Edward Burns Buzzy, Kerry Bishé Linda, Marsha...     85.0           0   \n",
       "4806  [Eric Mabius Oliver O’Toole, Kristin Booth Sha...    120.0           0   \n",
       "4807  [Daniel Henney Sam, Eliza Coupe Amanda, Bill P...     98.0           0   \n",
       "4808  [Drew Barrymore Herself, Brian Herzlinger Hims...     90.0           0   \n",
       "\n",
       "                     crew  \n",
       "0         [James Cameron]  \n",
       "1        [Gore Verbinski]  \n",
       "2            [Sam Mendes]  \n",
       "3     [Christopher Nolan]  \n",
       "4        [Andrew Stanton]  \n",
       "...                   ...  \n",
       "4804   [Robert Rodriguez]  \n",
       "4805       [Edward Burns]  \n",
       "4806        [Scott Smith]  \n",
       "4807        [Daniel Hsia]  \n",
       "4808   [Brian Herzlinger]  \n",
       "\n",
       "[4806 rows x 10 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "f93fccf0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Rajan\\AppData\\Local\\Temp\\ipykernel_15052\\2109951910.py:2: 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",
      "  movies_df['tags'] = movies_df['genres'] + movies_df['keywords'] + movies_df['cast'] + movies_df['crew'] + movies_df['overview']\n"
     ]
    }
   ],
   "source": [
    "''' Merging columns together'''\n",
    "movies_df['tags'] = movies_df['genres'] + movies_df['keywords'] + movies_df['cast'] + movies_df['crew'] + movies_df['overview']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "d4f262d0",
   "metadata": {},
   "outputs": [
    {
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       "      <td>[Edward Burns]</td>\n",
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       "    <tr>\n",
       "      <th>4806</th>\n",
       "      <td>231617</td>\n",
       "      <td>Signed, Sealed, Delivered</td>\n",
       "      <td>[\"Signed,, Sealed,, Delivered\", introduces, a,...</td>\n",
       "      <td>0</td>\n",
       "      <td>[Comedy, Drama, Romance, TV Movie]</td>\n",
       "      <td>[date, love at first sight, narration, investi...</td>\n",
       "      <td>[Eric Mabius Oliver O’Toole, Kristin Booth Sha...</td>\n",
       "      <td>120.0</td>\n",
       "      <td>0</td>\n",
       "      <td>[Scott Smith]</td>\n",
       "      <td>[Comedy, Drama, Romance, TV Movie, date, love ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4807</th>\n",
       "      <td>126186</td>\n",
       "      <td>Shanghai Calling</td>\n",
       "      <td>[When, ambitious, New, York, attorney, Sam, is...</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[Daniel Henney Sam, Eliza Coupe Amanda, Bill P...</td>\n",
       "      <td>98.0</td>\n",
       "      <td>0</td>\n",
       "      <td>[Daniel Hsia]</td>\n",
       "      <td>[Daniel Henney Sam, Eliza Coupe Amanda, Bill P...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4808</th>\n",
       "      <td>25975</td>\n",
       "      <td>My Date with Drew</td>\n",
       "      <td>[Ever, since, the, second, grade, when, he, fi...</td>\n",
       "      <td>0</td>\n",
       "      <td>[Documentary]</td>\n",
       "      <td>[obsession, camcorder, crush, dream girl]</td>\n",
       "      <td>[Drew Barrymore Herself, Brian Herzlinger Hims...</td>\n",
       "      <td>90.0</td>\n",
       "      <td>0</td>\n",
       "      <td>[Brian Herzlinger]</td>\n",
       "      <td>[Documentary, obsession, camcorder, crush, dre...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4806 rows × 11 columns</p>\n",
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      ],
      "text/plain": [
       "          id                                     title  \\\n",
       "0      19995                                    Avatar   \n",
       "1        285  Pirates of the Caribbean: At World's End   \n",
       "2     206647                                   Spectre   \n",
       "3      49026                     The Dark Knight Rises   \n",
       "4      49529                               John Carter   \n",
       "...      ...                                       ...   \n",
       "4804    9367                               El Mariachi   \n",
       "4805   72766                                 Newlyweds   \n",
       "4806  231617                 Signed, Sealed, Delivered   \n",
       "4807  126186                          Shanghai Calling   \n",
       "4808   25975                         My Date with Drew   \n",
       "\n",
       "                                               overview     budget  \\\n",
       "0     [In, the, 22nd, century,, a, paraplegic, Marin...  237000000   \n",
       "1     [Captain, Barbossa,, long, believed, to, be, d...  300000000   \n",
       "2     [A, cryptic, message, from, Bond’s, past, send...  245000000   \n",
       "3     [Following, the, death, of, District, Attorney...  250000000   \n",
       "4     [John, Carter, is, a, war-weary,, former, mili...  260000000   \n",
       "...                                                 ...        ...   \n",
       "4804  [El, Mariachi, just, wants, to, play, his, gui...     220000   \n",
       "4805  [A, newlywed, couple's, honeymoon, is, upended...       9000   \n",
       "4806  [\"Signed,, Sealed,, Delivered\", introduces, a,...          0   \n",
       "4807  [When, ambitious, New, York, attorney, Sam, is...          0   \n",
       "4808  [Ever, since, the, second, grade, when, he, fi...          0   \n",
       "\n",
       "                                             genres  \\\n",
       "0     [Action, Adventure, Fantasy, Science Fiction]   \n",
       "1                      [Adventure, Fantasy, Action]   \n",
       "2                        [Action, Adventure, Crime]   \n",
       "3                  [Action, Crime, Drama, Thriller]   \n",
       "4              [Action, Adventure, Science Fiction]   \n",
       "...                                             ...   \n",
       "4804                      [Action, Crime, Thriller]   \n",
       "4805                              [Comedy, Romance]   \n",
       "4806             [Comedy, Drama, Romance, TV Movie]   \n",
       "4807                                             []   \n",
       "4808                                  [Documentary]   \n",
       "\n",
       "                                               keywords  \\\n",
       "0     [culture clash, future, space war, space colon...   \n",
       "1     [ocean, drug abuse, exotic island, east india ...   \n",
       "2     [spy, based on novel, secret agent, sequel, mi...   \n",
       "3     [dc comics, crime fighter, terrorist, secret i...   \n",
       "4     [based on novel, mars, medallion, space travel...   \n",
       "...                                                 ...   \n",
       "4804  [united states–mexico barrier, legs, arms, pap...   \n",
       "4805                                                 []   \n",
       "4806  [date, love at first sight, narration, investi...   \n",
       "4807                                                 []   \n",
       "4808          [obsession, camcorder, crush, dream girl]   \n",
       "\n",
       "                                                   cast  runtime     revenue  \\\n",
       "0     [Sam Worthington Jake Sully, Zoe Saldana Neyti...    162.0  2787965087   \n",
       "1     [Johnny Depp Captain Jack Sparrow, Orlando Blo...    169.0   961000000   \n",
       "2     [Daniel Craig James Bond, Christoph Waltz Blof...    148.0   880674609   \n",
       "3     [Christian Bale Bruce Wayne / Batman, Michael ...    165.0  1084939099   \n",
       "4     [Taylor Kitsch John Carter, Lynn Collins Dejah...    132.0   284139100   \n",
       "...                                                 ...      ...         ...   \n",
       "4804  [Carlos Gallardo El Mariachi, Jaime de Hoyos B...     81.0     2040920   \n",
       "4805  [Edward Burns Buzzy, Kerry Bishé Linda, Marsha...     85.0           0   \n",
       "4806  [Eric Mabius Oliver O’Toole, Kristin Booth Sha...    120.0           0   \n",
       "4807  [Daniel Henney Sam, Eliza Coupe Amanda, Bill P...     98.0           0   \n",
       "4808  [Drew Barrymore Herself, Brian Herzlinger Hims...     90.0           0   \n",
       "\n",
       "                     crew                                               tags  \n",
       "0         [James Cameron]  [Action, Adventure, Fantasy, Science Fiction, ...  \n",
       "1        [Gore Verbinski]  [Adventure, Fantasy, Action, ocean, drug abuse...  \n",
       "2            [Sam Mendes]  [Action, Adventure, Crime, spy, based on novel...  \n",
       "3     [Christopher Nolan]  [Action, Crime, Drama, Thriller, dc comics, cr...  \n",
       "4        [Andrew Stanton]  [Action, Adventure, Science Fiction, based on ...  \n",
       "...                   ...                                                ...  \n",
       "4804   [Robert Rodriguez]  [Action, Crime, Thriller, united states–mexico...  \n",
       "4805       [Edward Burns]  [Comedy, Romance, Edward Burns Buzzy, Kerry Bi...  \n",
       "4806        [Scott Smith]  [Comedy, Drama, Romance, TV Movie, date, love ...  \n",
       "4807        [Daniel Hsia]  [Daniel Henney Sam, Eliza Coupe Amanda, Bill P...  \n",
       "4808   [Brian Herzlinger]  [Documentary, obsession, camcorder, crush, dre...  \n",
       "\n",
       "[4806 rows x 11 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "044b2df0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0</td>\n",
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       "      <th>4807</th>\n",
       "      <td>126186</td>\n",
       "      <td>Shanghai Calling</td>\n",
       "      <td>0</td>\n",
       "      <td>98.0</td>\n",
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      "text/plain": [
       "          id                                     title     budget  runtime  \\\n",
       "0      19995                                    Avatar  237000000    162.0   \n",
       "1        285  Pirates of the Caribbean: At World's End  300000000    169.0   \n",
       "2     206647                                   Spectre  245000000    148.0   \n",
       "3      49026                     The Dark Knight Rises  250000000    165.0   \n",
       "4      49529                               John Carter  260000000    132.0   \n",
       "...      ...                                       ...        ...      ...   \n",
       "4804    9367                               El Mariachi     220000     81.0   \n",
       "4805   72766                                 Newlyweds       9000     85.0   \n",
       "4806  231617                 Signed, Sealed, Delivered          0    120.0   \n",
       "4807  126186                          Shanghai Calling          0     98.0   \n",
       "4808   25975                         My Date with Drew          0     90.0   \n",
       "\n",
       "         revenue                                               tags  \n",
       "0     2787965087  [Action, Adventure, Fantasy, Science Fiction, ...  \n",
       "1      961000000  [Adventure, Fantasy, Action, ocean, drug abuse...  \n",
       "2      880674609  [Action, Adventure, Crime, spy, based on novel...  \n",
       "3     1084939099  [Action, Crime, Drama, Thriller, dc comics, cr...  \n",
       "4      284139100  [Action, Adventure, Science Fiction, based on ...  \n",
       "...          ...                                                ...  \n",
       "4804     2040920  [Action, Crime, Thriller, united states–mexico...  \n",
       "4805           0  [Comedy, Romance, Edward Burns Buzzy, Kerry Bi...  \n",
       "4806           0  [Comedy, Drama, Romance, TV Movie, date, love ...  \n",
       "4807           0  [Daniel Henney Sam, Eliza Coupe Amanda, Bill P...  \n",
       "4808           0  [Documentary, obsession, camcorder, crush, dre...  \n",
       "\n",
       "[4806 rows x 6 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "''' Extracting columns we need '''\n",
    "new_df = movies_df[['id', 'title', 'budget', 'runtime', 'revenue', 'tags']]\n",
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "185681ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Rajan\\AppData\\Local\\Temp\\ipykernel_15052\\2742978520.py:2: 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",
      "  new_df['tags'] = new_df['tags'].apply(lambda x:[i.replace(\" \",\"\") for i in x])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0       [Action, Adventure, Fantasy, ScienceFiction, c...\n",
       "1       [Adventure, Fantasy, Action, ocean, drugabuse,...\n",
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       "                              ...                        \n",
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       "4807    [DanielHenneySam, ElizaCoupeAmanda, BillPaxton...\n",
       "4808    [Documentary, obsession, camcorder, crush, dre...\n",
       "Name: tags, Length: 4806, dtype: object"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''Removing space between strings in 'tags' column'''\n",
    "new_df['tags'] = new_df['tags'].apply(lambda x:[i.replace(\" \",\"\") for i in x])\n",
    "new_df['tags']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "fa779871",
   "metadata": {},
   "outputs": [
    {
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       "          id                                     title     budget  runtime  \\\n",
       "0      19995                                    Avatar  237000000    162.0   \n",
       "1        285  Pirates of the Caribbean: At World's End  300000000    169.0   \n",
       "2     206647                                   Spectre  245000000    148.0   \n",
       "3      49026                     The Dark Knight Rises  250000000    165.0   \n",
       "4      49529                               John Carter  260000000    132.0   \n",
       "...      ...                                       ...        ...      ...   \n",
       "4804    9367                               El Mariachi     220000     81.0   \n",
       "4805   72766                                 Newlyweds       9000     85.0   \n",
       "4806  231617                 Signed, Sealed, Delivered          0    120.0   \n",
       "4807  126186                          Shanghai Calling          0     98.0   \n",
       "4808   25975                         My Date with Drew          0     90.0   \n",
       "\n",
       "         revenue                                               tags  \n",
       "0     2787965087  [Action, Adventure, Fantasy, ScienceFiction, c...  \n",
       "1      961000000  [Adventure, Fantasy, Action, ocean, drugabuse,...  \n",
       "2      880674609  [Action, Adventure, Crime, spy, basedonnovel, ...  \n",
       "3     1084939099  [Action, Crime, Drama, Thriller, dccomics, cri...  \n",
       "4      284139100  [Action, Adventure, ScienceFiction, basedonnov...  \n",
       "...          ...                                                ...  \n",
       "4804     2040920  [Action, Crime, Thriller, unitedstates–mexicob...  \n",
       "4805           0  [Comedy, Romance, EdwardBurnsBuzzy, KerryBishé...  \n",
       "4806           0  [Comedy, Drama, Romance, TVMovie, date, loveat...  \n",
       "4807           0  [DanielHenneySam, ElizaCoupeAmanda, BillPaxton...  \n",
       "4808           0  [Documentary, obsession, camcorder, crush, dre...  \n",
       "\n",
       "[4806 rows x 6 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "c313a9fa",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Rajan\\AppData\\Local\\Temp\\ipykernel_15052\\3977848256.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",
      "  new_df['tags'] = new_df['tags'].apply(lambda x:\" \".join(x))\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0       Action Adventure Fantasy ScienceFiction cultur...\n",
       "1       Adventure Fantasy Action ocean drugabuse exoti...\n",
       "2       Action Adventure Crime spy basedonnovel secret...\n",
       "3       Action Crime Drama Thriller dccomics crimefigh...\n",
       "4       Action Adventure ScienceFiction basedonnovel m...\n",
       "                              ...                        \n",
       "4804    Action Crime Thriller unitedstates–mexicobarri...\n",
       "4805    Comedy Romance EdwardBurnsBuzzy KerryBishéLind...\n",
       "4806    Comedy Drama Romance TVMovie date loveatfirsts...\n",
       "4807    DanielHenneySam ElizaCoupeAmanda BillPaxtonDon...\n",
       "4808    Documentary obsession camcorder crush dreamgir...\n",
       "Name: tags, Length: 4806, dtype: object"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df['tags'] = new_df['tags'].apply(lambda x:\" \".join(x))\n",
    "new_df['tags']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2630f1d0",
   "metadata": {},
   "source": [
    "## Stemming(Truncating words to their origin words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "00180988",
   "metadata": {},
   "outputs": [],
   "source": [
    "import nltk\n",
    "from nltk.stem.porter import PorterStemmer\n",
    "ps = PorterStemmer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "67b08c30",
   "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 samworthingtonjakesully zoesaldananeytiri sigourneyweaverdr.graceaugustine stephenlangcol.quaritch 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": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ps.stem(\"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 samworthingtonjakesully zoesaldananeytiri sigourneyweaverdr.graceaugustine stephenlangcol.quaritch 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.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "b3dfa579",
   "metadata": {},
   "outputs": [],
   "source": [
    "def stem(text):\n",
    "    L=[]\n",
    "    for i in text.split():\n",
    "        L.append(ps.stem(i)) \n",
    "    return \" \".join(L)     "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "dfcbb18e",
   "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",
       "4804    action crime thriller unitedstates–mexicobarri...\n",
       "4805    comedi romanc edwardburnsbuzzi kerrybishélinda...\n",
       "4806    comedi drama romanc tvmovi date loveatfirstsig...\n",
       "4807    danielhenneysam elizacoupeamanda billpaxtondon...\n",
       "4808    documentari obsess camcord crush dreamgirl dre...\n",
       "Name: tags, Length: 4806, dtype: object"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df['tags'].apply(stem)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "af76977f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Rajan\\AppData\\Local\\Temp\\ipykernel_15052\\3213734980.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",
      "  new_df['tags'] = new_df['tags'].apply(stem)\n"
     ]
    }
   ],
   "source": [
    "new_df['tags'] = new_df['tags'].apply(stem)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "3a5f55d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'action adventur fantasi sciencefict cultureclash futur spacewar spacecoloni societi spacetravel futurist romanc space alien tribe alienplanet cgi marin soldier battl loveaffair antiwar powerrel mindandsoul 3d samworthingtonjakesulli zoesaldananeytiri sigourneyweaverdr.graceaugustin stephenlangcol.quaritch jamescameron in the 22nd century, a parapleg marin is dispatch to the moon pandora on a uniqu mission, but becom torn between follow order and protect an alien civilization.'"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df['tags'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "906d5fc8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Rajan\\AppData\\Local\\Temp\\ipykernel_15052\\3982020389.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",
      "  new_df['tags'] = new_df['tags'].apply(lambda x:x.lower())\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'action adventur fantasi sciencefict cultureclash futur spacewar spacecoloni societi spacetravel futurist romanc space alien tribe alienplanet cgi marin soldier battl loveaffair antiwar powerrel mindandsoul 3d samworthingtonjakesulli zoesaldananeytiri sigourneyweaverdr.graceaugustin stephenlangcol.quaritch jamescameron in the 22nd century, a parapleg marin is dispatch to the moon pandora on a uniqu mission, but becom torn between follow order and protect an alien civilization.'"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df['tags'] = new_df['tags'].apply(lambda x:x.lower())\n",
    "new_df['tags'][0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a9871b4",
   "metadata": {},
   "source": [
    "## Vectorizing tags"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "c9f2c72f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "cv = CountVectorizer(max_features=5000, stop_words='english')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "eed73d69",
   "metadata": {},
   "outputs": [],
   "source": [
    "vectors = cv.fit_transform(new_df['tags']).toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "9548d65d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       ...,\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0]], dtype=int64)"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "f3106598",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['000', '007', '10', ..., 'zombies', 'zone', 'zoo'], dtype=object)"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cv.get_feature_names_out()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce8c3425",
   "metadata": {},
   "source": [
    "### We need to find distance between similar words but we can't use euclidean distance or any other distance measure because we are dealing with multi-dimensional space and normal distance are'nt reliable in multi-dim space. So, we will use cosine angle between two vectors to find distance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "7c8f5cb0",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics.pairwise import cosine_similarity"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c25d10b5",
   "metadata": {},
   "source": [
    "### Distance of every vector to each other and themself. Which means how much one movie is related to other, in this case, the amount every movie is related to each other."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "ff57efa8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.        , 0.08718573, 0.09004503, ..., 0.04516388, 0.        ,\n",
       "        0.        ],\n",
       "       [0.08718573, 1.        , 0.06454972, ..., 0.02428215, 0.        ,\n",
       "        0.02727724],\n",
       "       [0.09004503, 0.06454972, 1.        , ..., 0.02507849, 0.        ,\n",
       "        0.        ],\n",
       "       ...,\n",
       "       [0.04516388, 0.02428215, 0.02507849, ..., 1.        , 0.03924588,\n",
       "        0.04239039],\n",
       "       [0.        , 0.        , 0.        , ..., 0.03924588, 1.        ,\n",
       "        0.08817334],\n",
       "       [0.        , 0.02727724, 0.        , ..., 0.04239039, 0.08817334,\n",
       "        1.        ]])"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "similarity = cosine_similarity(vectors)\n",
    "similarity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "056af554",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4806, 4806)"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cosine_similarity(vectors).shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "127bd00a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                                         Avatar\n",
       "1       Pirates of the Caribbean: At World's End\n",
       "2                                        Spectre\n",
       "3                          The Dark Knight Rises\n",
       "4                                    John Carter\n",
       "                          ...                   \n",
       "4804                                 El Mariachi\n",
       "4805                                   Newlyweds\n",
       "4806                   Signed, Sealed, Delivered\n",
       "4807                            Shanghai Calling\n",
       "4808                           My Date with Drew\n",
       "Name: title, Length: 4806, dtype: object"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df['title']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "670f9785",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>budget</th>\n",
       "      <th>runtime</th>\n",
       "      <th>revenue</th>\n",
       "      <th>tags</th>\n",
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       "  </thead>\n",
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       "      <td>2787965087</td>\n",
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       "      id   title     budget  runtime     revenue  \\\n",
       "0  19995  Avatar  237000000    162.0  2787965087   \n",
       "\n",
       "                                                tags  \n",
       "0  action adventur fantasi sciencefict culturecla...  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df[new_df['title'] == \"Avatar\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "64167bd4",
   "metadata": {},
   "outputs": [
    {
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       "0"
      ]
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     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "new_df[new_df['title'] == \"Avatar\"].index[0]"
   ]
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  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "2633858e",
   "metadata": {},
   "outputs": [
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       "1887"
      ]
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     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df[new_df['title'] == \"The Shawshank Redemption\"].index[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "e1de511e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       " ...]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(similarity[0],reverse=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "1645b33a",
   "metadata": {},
   "outputs": [
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       " (981, 0.04604092555161308),\n",
       " (982, 0.021402925123634755),\n",
       " (983, 0.0),\n",
       " (984, 0.06003002251876642),\n",
       " (985, 0.03271662128033808),\n",
       " (986, 0.0),\n",
       " (987, 0.05723638070321425),\n",
       " (988, 0.10269923319261937),\n",
       " (989, 0.06213697660012),\n",
       " (990, 0.0),\n",
       " (991, 0.03504998186163908),\n",
       " (992, 0.041757384532966166),\n",
       " (993, 0.0644825880219161),\n",
       " (994, 0.0),\n",
       " (995, 0.07974522228289),\n",
       " (996, 0.05723638070321425),\n",
       " (997, 0.09394227846020416),\n",
       " (998, 0.06213697660012),\n",
       " (999, 0.0),\n",
       " ...]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#using enumerate so we don't lose index positions of movie distances\n",
    "list(enumerate(similarity[0])) \n",
    "#the distance between the first movie is one because it's being compared with itself"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "276bf480",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       " (1854, 0.06105625108726635),\n",
       " ...]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#List of all movies that are closest to the first [0] movie\n",
    "sorted(list(enumerate(similarity[0])),reverse=True, key=lambda x:x[1]) #sort according to the second number"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "4d229f94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(1216, 0.28102505044048826),\n",
       " (539, 0.2657423679108717),\n",
       " (507, 0.26130213378560535),\n",
       " (3730, 0.25732511773283273),\n",
       " (61, 0.25112360116696136)]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Top 5 movies that are most closesly related to the first movie\n",
    "sorted(list(enumerate(similarity[0])),reverse=True, key=lambda x:x[1])[1:6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "925b6cbd",
   "metadata": {},
   "outputs": [],
   "source": [
    "def recommend(movie):\n",
    "    movie_index = new_df[new_df['title'] == movie].index[0]\n",
    "    distances = similarity[movie_index]\n",
    "    movies_list = sorted(list(enumerate(distances)),reverse=True, key=lambda x:x[1])[1:6]\n",
    "    \n",
    "    for i in movies_list:\n",
    "#         print(new_df.iloc[i[0]].title, i[0] )\n",
    "        print(new_df.iloc[i[0]].title)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "2bd72bc8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Aliens vs Predator: Requiem\n",
      "Titan A.E.\n",
      "Independence Day\n",
      "Falcon Rising\n",
      "Jupiter Ascending\n"
     ]
    }
   ],
   "source": [
    "recommend('Avatar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "d7aae0a8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Aliens vs Predator: Requiem\n",
      "Titan A.E.\n",
      "Independence Day\n",
      "Falcon Rising\n"
     ]
    }
   ],
   "source": [
    "print(new_df.iloc[1216].title)\n",
    "print(new_df.iloc[539].title)\n",
    "print(new_df.iloc[507].title)\n",
    "print(new_df.iloc[3730].title)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "efdb9ab2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prison\n",
      "Buffalo '66\n",
      "The Truman Show\n",
      "1982\n",
      "Flying By\n"
     ]
    }
   ],
   "source": [
    "recommend(\"The Shawshank Redemption\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "c1ba965e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Juliet and Alfa Romeo\n",
      "What's Eating Gilbert Grape\n",
      "The Legend of Hercules\n",
      "Cyrus\n",
      "At First Sight\n"
     ]
    }
   ],
   "source": [
    "recommend(\"Forrest Gump\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "6d576ab0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "pickle.dump(new_df,open('movies.pkl','wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "1185312f",
   "metadata": {},
   "outputs": [],
   "source": [
    "pickle.dump(new_df.to_dict(),open('movies_dict.pkl','wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "9bc2f6b3",
   "metadata": {},
   "outputs": [],
   "source": [
    "pickle.dump(similarity,open('similarity.pkl','wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c42b0fd3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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