python project(recommender system).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import numpy as np \n",
    "df1=pd.read_csv('tmdb_5000_credits.csv')\n",
    "df2=pd.read_csv('tmdb_5000_movies.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<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",
       "      <td>0</td>\n",
       "      <td>19995</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>[{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...</td>\n",
       "      <td>[{\"credit_id\": \"52fe48009251416c750aca23\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>285</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>[{\"cast_id\": 4, \"character\": \"Captain Jack Spa...</td>\n",
       "      <td>[{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>206647</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>[{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...</td>\n",
       "      <td>[{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>49026</td>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>[{\"cast_id\": 2, \"character\": \"Bruce Wayne / Ba...</td>\n",
       "      <td>[{\"credit_id\": \"52fe4781c3a36847f81398c3\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>49529</td>\n",
       "      <td>John Carter</td>\n",
       "      <td>[{\"cast_id\": 5, \"character\": \"John Carter\", \"c...</td>\n",
       "      <td>[{\"credit_id\": \"52fe479ac3a36847f813eaa3\", \"de...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   movie_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",
       "                                                cast  \\\n",
       "0  [{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...   \n",
       "1  [{\"cast_id\": 4, \"character\": \"Captain Jack Spa...   \n",
       "2  [{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...   \n",
       "3  [{\"cast_id\": 2, \"character\": \"Bruce Wayne / Ba...   \n",
       "4  [{\"cast_id\": 5, \"character\": \"John Carter\", \"c...   \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": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4803, 4)\n"
     ]
    }
   ],
   "source": [
    "print(df1.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>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",
       "      <td>0</td>\n",
       "      <td>237000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
       "      <td>http://www.avatarmovie.com/</td>\n",
       "      <td>19995</td>\n",
       "      <td>[{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...</td>\n",
       "      <td>en</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>In the 22nd century, a paraplegic Marine is di...</td>\n",
       "      <td>150.437577</td>\n",
       "      <td>[{\"name\": \"Ingenious Film Partners\", \"id\": 289...</td>\n",
       "      <td>[{\"iso_3166_1\": \"US\", \"name\": \"United States o...</td>\n",
       "      <td>2009-12-10</td>\n",
       "      <td>2787965087</td>\n",
       "      <td>162.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...</td>\n",
       "      <td>Released</td>\n",
       "      <td>Enter the World of Pandora.</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>7.2</td>\n",
       "      <td>11800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>300000000</td>\n",
       "      <td>[{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...</td>\n",
       "      <td>http://disney.go.com/disneypictures/pirates/</td>\n",
       "      <td>285</td>\n",
       "      <td>[{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...</td>\n",
       "      <td>en</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>139.082615</td>\n",
       "      <td>[{\"name\": \"Walt Disney Pictures\", \"id\": 2}, {\"...</td>\n",
       "      <td>[{\"iso_3166_1\": \"US\", \"name\": \"United States o...</td>\n",
       "      <td>2007-05-19</td>\n",
       "      <td>961000000</td>\n",
       "      <td>169.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>At the end of the world, the adventure begins.</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>6.9</td>\n",
       "      <td>4500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>245000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
       "      <td>http://www.sonypictures.com/movies/spectre/</td>\n",
       "      <td>206647</td>\n",
       "      <td>[{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...</td>\n",
       "      <td>en</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>A cryptic message from Bond’s past sends him o...</td>\n",
       "      <td>107.376788</td>\n",
       "      <td>[{\"name\": \"Columbia Pictures\", \"id\": 5}, {\"nam...</td>\n",
       "      <td>[{\"iso_3166_1\": \"GB\", \"name\": \"United Kingdom\"...</td>\n",
       "      <td>2015-10-26</td>\n",
       "      <td>880674609</td>\n",
       "      <td>148.0</td>\n",
       "      <td>[{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"},...</td>\n",
       "      <td>Released</td>\n",
       "      <td>A Plan No One Escapes</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>6.3</td>\n",
       "      <td>4466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>250000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam...</td>\n",
       "      <td>http://www.thedarkknightrises.com/</td>\n",
       "      <td>49026</td>\n",
       "      <td>[{\"id\": 849, \"name\": \"dc comics\"}, {\"id\": 853,...</td>\n",
       "      <td>en</td>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>Following the death of District Attorney Harve...</td>\n",
       "      <td>112.312950</td>\n",
       "      <td>[{\"name\": \"Legendary Pictures\", \"id\": 923}, {\"...</td>\n",
       "      <td>[{\"iso_3166_1\": \"US\", \"name\": \"United States o...</td>\n",
       "      <td>2012-07-16</td>\n",
       "      <td>1084939099</td>\n",
       "      <td>165.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>The Legend Ends</td>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>7.6</td>\n",
       "      <td>9106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>260000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
       "      <td>http://movies.disney.com/john-carter</td>\n",
       "      <td>49529</td>\n",
       "      <td>[{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...</td>\n",
       "      <td>en</td>\n",
       "      <td>John Carter</td>\n",
       "      <td>John Carter is a war-weary, former military ca...</td>\n",
       "      <td>43.926995</td>\n",
       "      <td>[{\"name\": \"Walt Disney Pictures\", \"id\": 2}]</td>\n",
       "      <td>[{\"iso_3166_1\": \"US\", \"name\": \"United States o...</td>\n",
       "      <td>2012-03-07</td>\n",
       "      <td>284139100</td>\n",
       "      <td>132.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>Lost in our world, found in another.</td>\n",
       "      <td>John Carter</td>\n",
       "      <td>6.1</td>\n",
       "      <td>2124</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      budget                                             genres  \\\n",
       "0  237000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
       "1  300000000  [{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...   \n",
       "2  245000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
       "3  250000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam...   \n",
       "4  260000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
       "\n",
       "                                       homepage      id  \\\n",
       "0                   http://www.avatarmovie.com/   19995   \n",
       "1  http://disney.go.com/disneypictures/pirates/     285   \n",
       "2   http://www.sonypictures.com/movies/spectre/  206647   \n",
       "3            http://www.thedarkknightrises.com/   49026   \n",
       "4          http://movies.disney.com/john-carter   49529   \n",
       "\n",
       "                                            keywords original_language  \\\n",
       "0  [{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...                en   \n",
       "1  [{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...                en   \n",
       "2  [{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...                en   \n",
       "3  [{\"id\": 849, \"name\": \"dc comics\"}, {\"id\": 853,...                en   \n",
       "4  [{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...                en   \n",
       "\n",
       "                             original_title  \\\n",
       "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",
       "                                            overview  popularity  \\\n",
       "0  In the 22nd century, a paraplegic Marine is di...  150.437577   \n",
       "1  Captain Barbossa, long believed to be dead, ha...  139.082615   \n",
       "2  A cryptic message from Bond’s past sends him o...  107.376788   \n",
       "3  Following the death of District Attorney Harve...  112.312950   \n",
       "4  John Carter is a war-weary, former military ca...   43.926995   \n",
       "\n",
       "                                production_companies  \\\n",
       "0  [{\"name\": \"Ingenious Film Partners\", \"id\": 289...   \n",
       "1  [{\"name\": \"Walt Disney Pictures\", \"id\": 2}, {\"...   \n",
       "2  [{\"name\": \"Columbia Pictures\", \"id\": 5}, {\"nam...   \n",
       "3  [{\"name\": \"Legendary Pictures\", \"id\": 923}, {\"...   \n",
       "4        [{\"name\": \"Walt Disney Pictures\", \"id\": 2}]   \n",
       "\n",
       "                                production_countries release_date     revenue  \\\n",
       "0  [{\"iso_3166_1\": \"US\", \"name\": \"United States o...   2009-12-10  2787965087   \n",
       "1  [{\"iso_3166_1\": \"US\", \"name\": \"United States o...   2007-05-19   961000000   \n",
       "2  [{\"iso_3166_1\": \"GB\", \"name\": \"United Kingdom\"...   2015-10-26   880674609   \n",
       "3  [{\"iso_3166_1\": \"US\", \"name\": \"United States o...   2012-07-16  1084939099   \n",
       "4  [{\"iso_3166_1\": \"US\", \"name\": \"United States o...   2012-03-07   284139100   \n",
       "\n",
       "   runtime                                   spoken_languages    status  \\\n",
       "0    162.0  [{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...  Released   \n",
       "1    169.0           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
       "2    148.0  [{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"},...  Released   \n",
       "3    165.0           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
       "4    132.0           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
       "\n",
       "                                          tagline  \\\n",
       "0                     Enter the World of Pandora.   \n",
       "1  At the end of the world, the adventure begins.   \n",
       "2                           A Plan No One Escapes   \n",
       "3                                 The Legend Ends   \n",
       "4            Lost in our world, found in another.   \n",
       "\n",
       "                                      title  vote_average  vote_count  \n",
       "0                                    Avatar           7.2       11800  \n",
       "1  Pirates of the Caribbean: At World's End           6.9        4500  \n",
       "2                                   Spectre           6.3        4466  \n",
       "3                     The Dark Knight Rises           7.6        9106  \n",
       "4                               John Carter           6.1        2124  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.head()\n",
    "#print(df2.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4803, 20)\n"
     ]
    }
   ],
   "source": [
    "print(df2.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1.columns = ['id','tittle','cast','crew']\n",
    "df2= df2.merge(df1,on='id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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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>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>tittle</th>\n",
       "      <th>cast</th>\n",
       "      <th>crew</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>237000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
       "      <td>http://www.avatarmovie.com/</td>\n",
       "      <td>19995</td>\n",
       "      <td>[{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...</td>\n",
       "      <td>en</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>In the 22nd century, a paraplegic Marine is di...</td>\n",
       "      <td>150.437577</td>\n",
       "      <td>[{\"name\": \"Ingenious Film Partners\", \"id\": 289...</td>\n",
       "      <td>...</td>\n",
       "      <td>162.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...</td>\n",
       "      <td>Released</td>\n",
       "      <td>Enter the World of Pandora.</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>7.2</td>\n",
       "      <td>11800</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>[{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...</td>\n",
       "      <td>[{\"credit_id\": \"52fe48009251416c750aca23\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>300000000</td>\n",
       "      <td>[{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...</td>\n",
       "      <td>http://disney.go.com/disneypictures/pirates/</td>\n",
       "      <td>285</td>\n",
       "      <td>[{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...</td>\n",
       "      <td>en</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>139.082615</td>\n",
       "      <td>[{\"name\": \"Walt Disney Pictures\", \"id\": 2}, {\"...</td>\n",
       "      <td>...</td>\n",
       "      <td>169.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>At the end of the world, the adventure begins.</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>6.9</td>\n",
       "      <td>4500</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>[{\"cast_id\": 4, \"character\": \"Captain Jack Spa...</td>\n",
       "      <td>[{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>245000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
       "      <td>http://www.sonypictures.com/movies/spectre/</td>\n",
       "      <td>206647</td>\n",
       "      <td>[{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...</td>\n",
       "      <td>en</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>A cryptic message from Bond’s past sends him o...</td>\n",
       "      <td>107.376788</td>\n",
       "      <td>[{\"name\": \"Columbia Pictures\", \"id\": 5}, {\"nam...</td>\n",
       "      <td>...</td>\n",
       "      <td>148.0</td>\n",
       "      <td>[{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"},...</td>\n",
       "      <td>Released</td>\n",
       "      <td>A Plan No One Escapes</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>6.3</td>\n",
       "      <td>4466</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>[{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...</td>\n",
       "      <td>[{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      budget                                             genres  \\\n",
       "0  237000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
       "1  300000000  [{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...   \n",
       "2  245000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
       "\n",
       "                                       homepage      id  \\\n",
       "0                   http://www.avatarmovie.com/   19995   \n",
       "1  http://disney.go.com/disneypictures/pirates/     285   \n",
       "2   http://www.sonypictures.com/movies/spectre/  206647   \n",
       "\n",
       "                                            keywords original_language  \\\n",
       "0  [{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...                en   \n",
       "1  [{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...                en   \n",
       "2  [{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...                en   \n",
       "\n",
       "                             original_title  \\\n",
       "0                                    Avatar   \n",
       "1  Pirates of the Caribbean: At World's End   \n",
       "2                                   Spectre   \n",
       "\n",
       "                                            overview  popularity  \\\n",
       "0  In the 22nd century, a paraplegic Marine is di...  150.437577   \n",
       "1  Captain Barbossa, long believed to be dead, ha...  139.082615   \n",
       "2  A cryptic message from Bond’s past sends him o...  107.376788   \n",
       "\n",
       "                                production_companies  ... runtime  \\\n",
       "0  [{\"name\": \"Ingenious Film Partners\", \"id\": 289...  ...   162.0   \n",
       "1  [{\"name\": \"Walt Disney Pictures\", \"id\": 2}, {\"...  ...   169.0   \n",
       "2  [{\"name\": \"Columbia Pictures\", \"id\": 5}, {\"nam...  ...   148.0   \n",
       "\n",
       "                                    spoken_languages    status  \\\n",
       "0  [{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...  Released   \n",
       "1           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
       "2  [{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"},...  Released   \n",
       "\n",
       "                                          tagline  \\\n",
       "0                     Enter the World of Pandora.   \n",
       "1  At the end of the world, the adventure begins.   \n",
       "2                           A Plan No One Escapes   \n",
       "\n",
       "                                      title vote_average vote_count  \\\n",
       "0                                    Avatar          7.2      11800   \n",
       "1  Pirates of the Caribbean: At World's End          6.9       4500   \n",
       "2                                   Spectre          6.3       4466   \n",
       "\n",
       "                                     tittle  \\\n",
       "0                                    Avatar   \n",
       "1  Pirates of the Caribbean: At World's End   \n",
       "2                                   Spectre   \n",
       "\n",
       "                                                cast  \\\n",
       "0  [{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...   \n",
       "1  [{\"cast_id\": 4, \"character\": \"Captain Jack Spa...   \n",
       "2  [{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...   \n",
       "\n",
       "                                                crew  \n",
       "0  [{\"credit_id\": \"52fe48009251416c750aca23\", \"de...  \n",
       "1  [{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...  \n",
       "2  [{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...  \n",
       "\n",
       "[3 rows x 23 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4803, 23)\n"
     ]
    }
   ],
   "source": [
    "print(df2.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.092171559442011"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "C= df2['vote_average'].mean()\n",
    "C"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "m= df2['vote_count'].quantile(0.9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1838.4000000000015"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>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>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>tittle</th>\n",
       "      <th>cast</th>\n",
       "      <th>crew</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>237000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
       "      <td>http://www.avatarmovie.com/</td>\n",
       "      <td>19995</td>\n",
       "      <td>[{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...</td>\n",
       "      <td>en</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>In the 22nd century, a paraplegic Marine is di...</td>\n",
       "      <td>150.437577</td>\n",
       "      <td>[{\"name\": \"Ingenious Film Partners\", \"id\": 289...</td>\n",
       "      <td>...</td>\n",
       "      <td>162.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...</td>\n",
       "      <td>Released</td>\n",
       "      <td>Enter the World of Pandora.</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>7.2</td>\n",
       "      <td>11800</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>[{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...</td>\n",
       "      <td>[{\"credit_id\": \"52fe48009251416c750aca23\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>300000000</td>\n",
       "      <td>[{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...</td>\n",
       "      <td>http://disney.go.com/disneypictures/pirates/</td>\n",
       "      <td>285</td>\n",
       "      <td>[{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...</td>\n",
       "      <td>en</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>139.082615</td>\n",
       "      <td>[{\"name\": \"Walt Disney Pictures\", \"id\": 2}, {\"...</td>\n",
       "      <td>...</td>\n",
       "      <td>169.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>At the end of the world, the adventure begins.</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>6.9</td>\n",
       "      <td>4500</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>[{\"cast_id\": 4, \"character\": \"Captain Jack Spa...</td>\n",
       "      <td>[{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>245000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
       "      <td>http://www.sonypictures.com/movies/spectre/</td>\n",
       "      <td>206647</td>\n",
       "      <td>[{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...</td>\n",
       "      <td>en</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>A cryptic message from Bond’s past sends him o...</td>\n",
       "      <td>107.376788</td>\n",
       "      <td>[{\"name\": \"Columbia Pictures\", \"id\": 5}, {\"nam...</td>\n",
       "      <td>...</td>\n",
       "      <td>148.0</td>\n",
       "      <td>[{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"},...</td>\n",
       "      <td>Released</td>\n",
       "      <td>A Plan No One Escapes</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>6.3</td>\n",
       "      <td>4466</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>[{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...</td>\n",
       "      <td>[{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      budget                                             genres  \\\n",
       "0  237000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
       "1  300000000  [{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...   \n",
       "2  245000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
       "\n",
       "                                       homepage      id  \\\n",
       "0                   http://www.avatarmovie.com/   19995   \n",
       "1  http://disney.go.com/disneypictures/pirates/     285   \n",
       "2   http://www.sonypictures.com/movies/spectre/  206647   \n",
       "\n",
       "                                            keywords original_language  \\\n",
       "0  [{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...                en   \n",
       "1  [{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...                en   \n",
       "2  [{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...                en   \n",
       "\n",
       "                             original_title  \\\n",
       "0                                    Avatar   \n",
       "1  Pirates of the Caribbean: At World's End   \n",
       "2                                   Spectre   \n",
       "\n",
       "                                            overview  popularity  \\\n",
       "0  In the 22nd century, a paraplegic Marine is di...  150.437577   \n",
       "1  Captain Barbossa, long believed to be dead, ha...  139.082615   \n",
       "2  A cryptic message from Bond’s past sends him o...  107.376788   \n",
       "\n",
       "                                production_companies  ... runtime  \\\n",
       "0  [{\"name\": \"Ingenious Film Partners\", \"id\": 289...  ...   162.0   \n",
       "1  [{\"name\": \"Walt Disney Pictures\", \"id\": 2}, {\"...  ...   169.0   \n",
       "2  [{\"name\": \"Columbia Pictures\", \"id\": 5}, {\"nam...  ...   148.0   \n",
       "\n",
       "                                    spoken_languages    status  \\\n",
       "0  [{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...  Released   \n",
       "1           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
       "2  [{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"},...  Released   \n",
       "\n",
       "                                          tagline  \\\n",
       "0                     Enter the World of Pandora.   \n",
       "1  At the end of the world, the adventure begins.   \n",
       "2                           A Plan No One Escapes   \n",
       "\n",
       "                                      title vote_average vote_count  \\\n",
       "0                                    Avatar          7.2      11800   \n",
       "1  Pirates of the Caribbean: At World's End          6.9       4500   \n",
       "2                                   Spectre          6.3       4466   \n",
       "\n",
       "                                     tittle  \\\n",
       "0                                    Avatar   \n",
       "1  Pirates of the Caribbean: At World's End   \n",
       "2                                   Spectre   \n",
       "\n",
       "                                                cast  \\\n",
       "0  [{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...   \n",
       "1  [{\"cast_id\": 4, \"character\": \"Captain Jack Spa...   \n",
       "2  [{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...   \n",
       "\n",
       "                                                crew  \n",
       "0  [{\"credit_id\": \"52fe48009251416c750aca23\", \"de...  \n",
       "1  [{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...  \n",
       "2  [{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...  \n",
       "\n",
       "[3 rows x 23 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q_movies = df2.copy().loc[df2['vote_count'] >= m]\n",
    "q_movies.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(481, 23)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q_movies.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def weighted_rating(x, m=m, C=C):\n",
    "    v = x['vote_count']\n",
    "    R = x['vote_average']\n",
    "    # Calculation based on the IMDB formula\n",
    "    return (v/(v+m) * R) + (m/(m+v) * C)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\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>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",
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       "      <th>...</th>\n",
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       "      <th>crew</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>237000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
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       "      <td>19995</td>\n",
       "      <td>[{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...</td>\n",
       "      <td>en</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>In the 22nd century, a paraplegic Marine is di...</td>\n",
       "      <td>150.437577</td>\n",
       "      <td>[{\"name\": \"Ingenious Film Partners\", \"id\": 289...</td>\n",
       "      <td>...</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...</td>\n",
       "      <td>Released</td>\n",
       "      <td>Enter the World of Pandora.</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>7.2</td>\n",
       "      <td>11800</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>[{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...</td>\n",
       "      <td>[{\"credit_id\": \"52fe48009251416c750aca23\", \"de...</td>\n",
       "      <td>7.050669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>300000000</td>\n",
       "      <td>[{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...</td>\n",
       "      <td>http://disney.go.com/disneypictures/pirates/</td>\n",
       "      <td>285</td>\n",
       "      <td>[{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...</td>\n",
       "      <td>en</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>139.082615</td>\n",
       "      <td>[{\"name\": \"Walt Disney Pictures\", \"id\": 2}, {\"...</td>\n",
       "      <td>...</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>At the end of the world, the adventure begins.</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>6.9</td>\n",
       "      <td>4500</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>[{\"cast_id\": 4, \"character\": \"Captain Jack Spa...</td>\n",
       "      <td>[{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...</td>\n",
       "      <td>6.665696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>245000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
       "      <td>http://www.sonypictures.com/movies/spectre/</td>\n",
       "      <td>206647</td>\n",
       "      <td>[{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...</td>\n",
       "      <td>en</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>A cryptic message from Bond’s past sends him o...</td>\n",
       "      <td>107.376788</td>\n",
       "      <td>[{\"name\": \"Columbia Pictures\", \"id\": 5}, {\"nam...</td>\n",
       "      <td>...</td>\n",
       "      <td>[{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"},...</td>\n",
       "      <td>Released</td>\n",
       "      <td>A Plan No One Escapes</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>6.3</td>\n",
       "      <td>4466</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>[{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...</td>\n",
       "      <td>[{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...</td>\n",
       "      <td>6.239396</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      budget                                             genres  \\\n",
       "0  237000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
       "1  300000000  [{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...   \n",
       "2  245000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
       "\n",
       "                                       homepage      id  \\\n",
       "0                   http://www.avatarmovie.com/   19995   \n",
       "1  http://disney.go.com/disneypictures/pirates/     285   \n",
       "2   http://www.sonypictures.com/movies/spectre/  206647   \n",
       "\n",
       "                                            keywords original_language  \\\n",
       "0  [{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...                en   \n",
       "1  [{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...                en   \n",
       "2  [{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...                en   \n",
       "\n",
       "                             original_title  \\\n",
       "0                                    Avatar   \n",
       "1  Pirates of the Caribbean: At World's End   \n",
       "2                                   Spectre   \n",
       "\n",
       "                                            overview  popularity  \\\n",
       "0  In the 22nd century, a paraplegic Marine is di...  150.437577   \n",
       "1  Captain Barbossa, long believed to be dead, ha...  139.082615   \n",
       "2  A cryptic message from Bond’s past sends him o...  107.376788   \n",
       "\n",
       "                                production_companies  ...  \\\n",
       "0  [{\"name\": \"Ingenious Film Partners\", \"id\": 289...  ...   \n",
       "1  [{\"name\": \"Walt Disney Pictures\", \"id\": 2}, {\"...  ...   \n",
       "2  [{\"name\": \"Columbia Pictures\", \"id\": 5}, {\"nam...  ...   \n",
       "\n",
       "                                    spoken_languages    status  \\\n",
       "0  [{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...  Released   \n",
       "1           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
       "2  [{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"},...  Released   \n",
       "\n",
       "                                          tagline  \\\n",
       "0                     Enter the World of Pandora.   \n",
       "1  At the end of the world, the adventure begins.   \n",
       "2                           A Plan No One Escapes   \n",
       "\n",
       "                                      title vote_average vote_count  \\\n",
       "0                                    Avatar          7.2      11800   \n",
       "1  Pirates of the Caribbean: At World's End          6.9       4500   \n",
       "2                                   Spectre          6.3       4466   \n",
       "\n",
       "                                     tittle  \\\n",
       "0                                    Avatar   \n",
       "1  Pirates of the Caribbean: At World's End   \n",
       "2                                   Spectre   \n",
       "\n",
       "                                                cast  \\\n",
       "0  [{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...   \n",
       "1  [{\"cast_id\": 4, \"character\": \"Captain Jack Spa...   \n",
       "2  [{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...   \n",
       "\n",
       "                                                crew     score  \n",
       "0  [{\"credit_id\": \"52fe48009251416c750aca23\", \"de...  7.050669  \n",
       "1  [{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...  6.665696  \n",
       "2  [{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...  6.239396  \n",
       "\n",
       "[3 rows x 24 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Define a new feature 'score' and calculate its value with `weighted_rating()`\n",
    "q_movies['score'] = q_movies.apply(weighted_rating, axis=1)\n",
    "q_movies.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>title</th>\n",
       "      <th>vote_count</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>1881</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>8205</td>\n",
       "      <td>8.5</td>\n",
       "      <td>8.059258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>662</td>\n",
       "      <td>Fight Club</td>\n",
       "      <td>9413</td>\n",
       "      <td>8.3</td>\n",
       "      <td>7.939256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>65</td>\n",
       "      <td>The Dark Knight</td>\n",
       "      <td>12002</td>\n",
       "      <td>8.2</td>\n",
       "      <td>7.920020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3232</td>\n",
       "      <td>Pulp Fiction</td>\n",
       "      <td>8428</td>\n",
       "      <td>8.3</td>\n",
       "      <td>7.904645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>96</td>\n",
       "      <td>Inception</td>\n",
       "      <td>13752</td>\n",
       "      <td>8.1</td>\n",
       "      <td>7.863239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3337</td>\n",
       "      <td>The Godfather</td>\n",
       "      <td>5893</td>\n",
       "      <td>8.4</td>\n",
       "      <td>7.851236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>95</td>\n",
       "      <td>Interstellar</td>\n",
       "      <td>10867</td>\n",
       "      <td>8.1</td>\n",
       "      <td>7.809479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>809</td>\n",
       "      <td>Forrest Gump</td>\n",
       "      <td>7927</td>\n",
       "      <td>8.2</td>\n",
       "      <td>7.803188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>329</td>\n",
       "      <td>The Lord of the Rings: The Return of the King</td>\n",
       "      <td>8064</td>\n",
       "      <td>8.1</td>\n",
       "      <td>7.727243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1990</td>\n",
       "      <td>The Empire Strikes Back</td>\n",
       "      <td>5879</td>\n",
       "      <td>8.2</td>\n",
       "      <td>7.697884</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              title  vote_count  vote_average  \\\n",
       "1881                       The Shawshank Redemption        8205           8.5   \n",
       "662                                      Fight Club        9413           8.3   \n",
       "65                                  The Dark Knight       12002           8.2   \n",
       "3232                                   Pulp Fiction        8428           8.3   \n",
       "96                                        Inception       13752           8.1   \n",
       "3337                                  The Godfather        5893           8.4   \n",
       "95                                     Interstellar       10867           8.1   \n",
       "809                                    Forrest Gump        7927           8.2   \n",
       "329   The Lord of the Rings: The Return of the King        8064           8.1   \n",
       "1990                        The Empire Strikes Back        5879           8.2   \n",
       "\n",
       "         score  \n",
       "1881  8.059258  \n",
       "662   7.939256  \n",
       "65    7.920020  \n",
       "3232  7.904645  \n",
       "96    7.863239  \n",
       "3337  7.851236  \n",
       "95    7.809479  \n",
       "809   7.803188  \n",
       "329   7.727243  \n",
       "1990  7.697884  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Sort movies based on score calculated above\n",
    "q_movies = q_movies.sort_values('score', ascending=False)\n",
    "\n",
    "#Print the top 15 movies\n",
    "q_movies[['title', 'vote_count', 'vote_average', 'score']].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>title</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>3519</td>\n",
       "      <td>Stiff Upper Lips</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4247</td>\n",
       "      <td>Me You and Five Bucks</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4045</td>\n",
       "      <td>Dancer, Texas Pop. 81</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4662</td>\n",
       "      <td>Little Big Top</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3992</td>\n",
       "      <td>Sardaarji</td>\n",
       "      <td>9.5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2386</td>\n",
       "      <td>One Man's Hero</td>\n",
       "      <td>9.3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2970</td>\n",
       "      <td>There Goes My Baby</td>\n",
       "      <td>8.5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1881</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>8.5</td>\n",
       "      <td>8205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2796</td>\n",
       "      <td>The Prisoner of Zenda</td>\n",
       "      <td>8.4</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3337</td>\n",
       "      <td>The Godfather</td>\n",
       "      <td>8.4</td>\n",
       "      <td>5893</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         title  vote_average  vote_count\n",
       "3519          Stiff Upper Lips          10.0           1\n",
       "4247     Me You and Five Bucks          10.0           2\n",
       "4045     Dancer, Texas Pop. 81          10.0           1\n",
       "4662            Little Big Top          10.0           1\n",
       "3992                 Sardaarji           9.5           2\n",
       "2386            One Man's Hero           9.3           2\n",
       "2970        There Goes My Baby           8.5           2\n",
       "1881  The Shawshank Redemption           8.5        8205\n",
       "2796     The Prisoner of Zenda           8.4          11\n",
       "3337             The Godfather           8.4        5893"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2[['title','vote_average','vote_count']].sort_values(\"vote_average\", ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>title</th>\n",
       "      <th>vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>96</td>\n",
       "      <td>Inception</td>\n",
       "      <td>13752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>65</td>\n",
       "      <td>The Dark Knight</td>\n",
       "      <td>12002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>11800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>The Avengers</td>\n",
       "      <td>11776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>788</td>\n",
       "      <td>Deadpool</td>\n",
       "      <td>10995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>95</td>\n",
       "      <td>Interstellar</td>\n",
       "      <td>10867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>287</td>\n",
       "      <td>Django Unchained</td>\n",
       "      <td>10099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>94</td>\n",
       "      <td>Guardians of the Galaxy</td>\n",
       "      <td>9742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>426</td>\n",
       "      <td>The Hunger Games</td>\n",
       "      <td>9455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>127</td>\n",
       "      <td>Mad Max: Fury Road</td>\n",
       "      <td>9427</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       title  vote_count\n",
       "96                 Inception       13752\n",
       "65           The Dark Knight       12002\n",
       "0                     Avatar       11800\n",
       "16              The Avengers       11776\n",
       "788                 Deadpool       10995\n",
       "95              Interstellar       10867\n",
       "287         Django Unchained       10099\n",
       "94   Guardians of the Galaxy        9742\n",
       "426         The Hunger Games        9455\n",
       "127       Mad Max: Fury Road        9427"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2[['title','vote_count']].sort_values(\"vote_count\",ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x00000260E94DD908>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_style('dark')\n",
    "\n",
    "plt.rcParams['patch.force_edgecolor'] = True\n",
    "df2.hist(column='vote_count',bins=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x00000260E9810C48>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2.hist(column='vote_average',bins=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x260e9b4c208>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(x='vote_average', y='vote_count', data=df2, alpha=0.4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pop= df2.sort_values('popularity', ascending=False)\n",
    "\n",
    "plt.figure(figsize=(12,4))\n",
    "\n",
    "plt.barh(pop['title'].head(6),pop['popularity'].head(6), align='center',\n",
    "        color='skyblue')\n",
    "plt.gca().invert_yaxis()\n",
    "plt.xlabel(\"Popularity\")\n",
    "plt.title(\"Popular Movies\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    In the 22nd century, a paraplegic Marine is di...\n",
       "1    Captain Barbossa, long believed to be dead, ha...\n",
       "2    A cryptic message from Bond’s past sends him o...\n",
       "3    Following the death of District Attorney Harve...\n",
       "4    John Carter is a war-weary, former military ca...\n",
       "Name: overview, dtype: object"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2['overview'].head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4803, 20978)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Import TfIdfVectorizer from scikit-learn\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "\n",
    "#Define a TF-IDF Vectorizer Object. Remove all english stop words such as 'the', 'a'\n",
    "tfidf = TfidfVectorizer(stop_words='english')\n",
    "\n",
    "\n",
    "#Replace NaN with an empty string\n",
    "df2['overview'] = df2['overview'].fillna('')\n",
    "\n",
    "#Construct the required TF-IDF matrix by fitting and transforming the data\n",
    "tfidf_matrix = tfidf.fit_transform(df2['overview'])\n",
    "\n",
    "#Output the shape of tfidf_matrix\n",
    "tfidf_matrix.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import linear_kernel\n",
    "from sklearn.metrics.pairwise import linear_kernel\n",
    "\n",
    "# Compute the cosine similarity matrix\n",
    "cosine_sim = linear_kernel(tfidf_matrix, tfidf_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Construct a reverse map of indices and movie titles\n",
    "indices = pd.Series(df2.index, index=df2['title']).drop_duplicates()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function that takes in movie title as input and outputs most similar movies\n",
    "def get_recommendations(title, cosine_sim=cosine_sim):\n",
    "    # Get the index of the movie that matches the title\n",
    "    idx =indices[title]\n",
    "\n",
    "    # Get the pairwsie similarity scores of all movies with that movie\n",
    "    sim_scores = list(enumerate(cosine_sim[idx]))\n",
    "\n",
    "    # Sort the movies based on the similarity scores\n",
    "    sim_scores = sorted(sim_scores, key=lambda x: x[1], reverse=True)\n",
    "\n",
    "    # Get the scores of the 10 most similar movies\n",
    "    sim_scores = sim_scores[1:11]\n",
    "\n",
    "    # Get the movie indices\n",
    "    movie_indices = [i[0] for i in sim_scores]\n",
    "\n",
    "    # Return the top 10 most similar movies\n",
    "    return df2['title'].iloc[movie_indices]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "65                              The Dark Knight\n",
       "299                              Batman Forever\n",
       "428                              Batman Returns\n",
       "1359                                     Batman\n",
       "3854    Batman: The Dark Knight Returns, Part 2\n",
       "119                               Batman Begins\n",
       "2507                                  Slow Burn\n",
       "9            Batman v Superman: Dawn of Justice\n",
       "1181                                        JFK\n",
       "210                              Batman & Robin\n",
       "Name: title, dtype: object"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_recommendations('The Dark Knight Rises')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7               Avengers: Age of Ultron\n",
       "3144                            Plastic\n",
       "1715                            Timecop\n",
       "4124                 This Thing of Ours\n",
       "3311              Thank You for Smoking\n",
       "3033                      The Corruptor\n",
       "588     Wall Street: Money Never Sleeps\n",
       "2136         Team America: World Police\n",
       "1468                       The Fountain\n",
       "1286                        Snowpiercer\n",
       "Name: title, dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_recommendations('The Avengers')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Parse the stringified features into their corresponding python objects\n",
    "from ast import literal_eval\n",
    "\n",
    "features = ['cast', 'crew', 'keywords', 'genres']\n",
    "for feature in features:\n",
    "    df2[feature] = df2[feature].apply(literal_eval)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'credit_id': '52fe4232c3a36847f800b579',\n",
       "  'department': 'Camera',\n",
       "  'gender': 2,\n",
       "  'id': 120,\n",
       "  'job': 'Director of Photography',\n",
       "  'name': 'Dariusz Wolski'},\n",
       " {'credit_id': '52fe4232c3a36847f800b4fd',\n",
       "  'department': 'Directing',\n",
       "  'gender': 2,\n",
       "  'id': 1704,\n",
       "  'job': 'Director',\n",
       "  'name': 'Gore Verbinski'},\n",
       " {'credit_id': '52fe4232c3a36847f800b54f',\n",
       "  'department': 'Production',\n",
       "  'gender': 2,\n",
       "  'id': 770,\n",
       "  'job': 'Producer',\n",
       "  'name': 'Jerry Bruckheimer'},\n",
       " {'credit_id': '52fe4232c3a36847f800b503',\n",
       "  'department': 'Writing',\n",
       "  'gender': 2,\n",
       "  'id': 1705,\n",
       "  'job': 'Screenplay',\n",
       "  'name': 'Ted Elliott'},\n",
       " {'credit_id': '52fe4232c3a36847f800b509',\n",
       "  'department': 'Writing',\n",
       "  'gender': 2,\n",
       "  'id': 1706,\n",
       "  'job': 'Screenplay',\n",
       "  'name': 'Terry Rossio'},\n",
       " {'credit_id': '52fe4232c3a36847f800b57f',\n",
       "  'department': 'Editing',\n",
       "  'gender': 0,\n",
       "  'id': 1721,\n",
       "  'job': 'Editor',\n",
       "  'name': 'Stephen E. Rivkin'},\n",
       " {'credit_id': '52fe4232c3a36847f800b585',\n",
       "  'department': 'Editing',\n",
       "  'gender': 2,\n",
       "  'id': 1722,\n",
       "  'job': 'Editor',\n",
       "  'name': 'Craig Wood'},\n",
       " {'credit_id': '52fe4232c3a36847f800b573',\n",
       "  'department': 'Sound',\n",
       "  'gender': 2,\n",
       "  'id': 947,\n",
       "  'job': 'Original Music Composer',\n",
       "  'name': 'Hans Zimmer'},\n",
       " {'credit_id': '52fe4232c3a36847f800b555',\n",
       "  'department': 'Production',\n",
       "  'gender': 2,\n",
       "  'id': 2444,\n",
       "  'job': 'Executive Producer',\n",
       "  'name': 'Mike Stenson'},\n",
       " {'credit_id': '52fe4232c3a36847f800b561',\n",
       "  'department': 'Production',\n",
       "  'gender': 2,\n",
       "  'id': 2445,\n",
       "  'job': 'Producer',\n",
       "  'name': 'Eric McLeod'},\n",
       " {'credit_id': '52fe4232c3a36847f800b55b',\n",
       "  'department': 'Production',\n",
       "  'gender': 2,\n",
       "  'id': 2446,\n",
       "  'job': 'Producer',\n",
       "  'name': 'Chad Oman'},\n",
       " {'credit_id': '52fe4232c3a36847f800b567',\n",
       "  'department': 'Production',\n",
       "  'gender': 0,\n",
       "  'id': 2447,\n",
       "  'job': 'Producer',\n",
       "  'name': 'Peter Kohn'},\n",
       " {'credit_id': '52fe4232c3a36847f800b56d',\n",
       "  'department': 'Production',\n",
       "  'gender': 0,\n",
       "  'id': 2448,\n",
       "  'job': 'Producer',\n",
       "  'name': 'Pat Sandston'},\n",
       " {'credit_id': '52fe4232c3a36847f800b58b',\n",
       "  'department': 'Production',\n",
       "  'gender': 1,\n",
       "  'id': 2215,\n",
       "  'job': 'Casting',\n",
       "  'name': 'Denise Chamian'},\n",
       " {'credit_id': '52fe4232c3a36847f800b597',\n",
       "  'department': 'Art',\n",
       "  'gender': 2,\n",
       "  'id': 1226,\n",
       "  'job': 'Production Design',\n",
       "  'name': 'Rick Heinrichs'},\n",
       " {'credit_id': '52fe4232c3a36847f800b59d',\n",
       "  'department': 'Art',\n",
       "  'gender': 2,\n",
       "  'id': 553,\n",
       "  'job': 'Art Direction',\n",
       "  'name': 'John Dexter'},\n",
       " {'credit_id': '52fe4232c3a36847f800b591',\n",
       "  'department': 'Production',\n",
       "  'gender': 1,\n",
       "  'id': 3311,\n",
       "  'job': 'Casting',\n",
       "  'name': 'Priscilla John'},\n",
       " {'credit_id': '52fe4232c3a36847f800b5a3',\n",
       "  'department': 'Art',\n",
       "  'gender': 1,\n",
       "  'id': 4032,\n",
       "  'job': 'Set Decoration',\n",
       "  'name': 'Cheryl Carasik'},\n",
       " {'credit_id': '52fe4232c3a36847f800b5a9',\n",
       "  'department': 'Costume & Make-Up',\n",
       "  'gender': 0,\n",
       "  'id': 4033,\n",
       "  'job': 'Costume Design',\n",
       "  'name': 'Liz Dann'},\n",
       " {'credit_id': '52fe4232c3a36847f800b5af',\n",
       "  'department': 'Costume & Make-Up',\n",
       "  'gender': 1,\n",
       "  'id': 4034,\n",
       "  'job': 'Costume Design',\n",
       "  'name': 'Penny Rose'},\n",
       " {'credit_id': '56427ce8c3a3686a53000d8b',\n",
       "  'department': 'Sound',\n",
       "  'gender': 2,\n",
       "  'id': 5132,\n",
       "  'job': 'Music Supervisor',\n",
       "  'name': 'Bob Badami'},\n",
       " {'credit_id': '55993c15c3a36855db002f33',\n",
       "  'department': 'Art',\n",
       "  'gender': 2,\n",
       "  'id': 146439,\n",
       "  'job': 'Conceptual Design',\n",
       "  'name': 'James Ward Byrkit'},\n",
       " {'credit_id': '52fe4232c3a36847f800b5b9',\n",
       "  'department': 'Costume & Make-Up',\n",
       "  'gender': 1,\n",
       "  'id': 406204,\n",
       "  'job': 'Makeup Department Head',\n",
       "  'name': 'Ve Neill'},\n",
       " {'credit_id': '56e47f7892514132690017bd',\n",
       "  'department': 'Crew',\n",
       "  'gender': 2,\n",
       "  'id': 1259516,\n",
       "  'job': 'Stunts',\n",
       "  'name': 'John Dixon'},\n",
       " {'credit_id': '5740be639251416597000849',\n",
       "  'department': 'Crew',\n",
       "  'gender': 0,\n",
       "  'id': 1336716,\n",
       "  'job': 'CGI Supervisor',\n",
       "  'name': 'Dottie Starling'},\n",
       " {'credit_id': '56427c639251412fc8000dc1',\n",
       "  'department': 'Directing',\n",
       "  'gender': 1,\n",
       "  'id': 1344278,\n",
       "  'job': 'Script Supervisor',\n",
       "  'name': 'Pamela Alch'},\n",
       " {'credit_id': '57083101c3a3681d320004e6',\n",
       "  'department': 'Crew',\n",
       "  'gender': 0,\n",
       "  'id': 1368867,\n",
       "  'job': 'Special Effects Coordinator',\n",
       "  'name': 'Allen Hall'},\n",
       " {'credit_id': '56427d5ec3a3686a62000d4a',\n",
       "  'department': 'Sound',\n",
       "  'gender': 0,\n",
       "  'id': 1368884,\n",
       "  'job': 'Music Editor',\n",
       "  'name': 'Melissa Muik'},\n",
       " {'credit_id': '56427c7b9251412fd4000e07',\n",
       "  'department': 'Directing',\n",
       "  'gender': 1,\n",
       "  'id': 1395290,\n",
       "  'job': 'Script Supervisor',\n",
       "  'name': 'Sharron Reynolds'},\n",
       " {'credit_id': '56427d2bc3a3686a53000d9b',\n",
       "  'department': 'Sound',\n",
       "  'gender': 0,\n",
       "  'id': 1399327,\n",
       "  'job': 'Music Editor',\n",
       "  'name': 'Barbara McDermott'},\n",
       " {'credit_id': '56427cb4c3a3686a53000d87',\n",
       "  'department': 'Directing',\n",
       "  'gender': 1,\n",
       "  'id': 1400738,\n",
       "  'job': 'Script Supervisor',\n",
       "  'name': 'Karen Golden'},\n",
       " {'credit_id': '56427d169251412fd4000e23',\n",
       "  'department': 'Sound',\n",
       "  'gender': 0,\n",
       "  'id': 1534197,\n",
       "  'job': 'Music Editor',\n",
       "  'name': 'Katie Greathouse'}]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.loc[1,'crew']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the director's name from the crew feature. If director is not listed, return NaN\n",
    "def get_director(x):\n",
    "    for i in x:\n",
    "        if i['job'] == 'Director':\n",
    "            return i['name']\n",
    "    return np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Returns the list top 3 elements or entire list; whichever is more.\n",
    "def get_list(x):\n",
    "    if isinstance(x, list):\n",
    "        names = [i['name'] for i in x]\n",
    "        #Check if more than 3 elements exist. If yes, return only first three. If no, return entire list.\n",
    "        if len(names) > 3:\n",
    "            names = names[:3]\n",
    "        return names\n",
    "\n",
    "    #Return empty list in case of missing/malformed data\n",
    "    return []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define new director, cast, genres and keywords features that are in a suitable form.\n",
    "df2['director'] = df2['crew'].apply(get_director)\n",
    "\n",
    "features = ['cast', 'keywords', 'genres']\n",
    "for feature in features:\n",
    "    df2[feature] = df2[feature].apply(get_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>title</th>\n",
       "      <th>cast</th>\n",
       "      <th>director</th>\n",
       "      <th>keywords</th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>[Sam Worthington, Zoe Saldana, Sigourney Weaver]</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>[culture clash, future, space war]</td>\n",
       "      <td>[Action, Adventure, Fantasy]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>[Johnny Depp, Orlando Bloom, Keira Knightley]</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "      <td>[ocean, drug abuse, exotic island]</td>\n",
       "      <td>[Adventure, Fantasy, Action]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>[Daniel Craig, Christoph Waltz, Léa Seydoux]</td>\n",
       "      <td>Sam Mendes</td>\n",
       "      <td>[spy, based on novel, secret agent]</td>\n",
       "      <td>[Action, Adventure, Crime]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      title  \\\n",
       "0                                    Avatar   \n",
       "1  Pirates of the Caribbean: At World's End   \n",
       "2                                   Spectre   \n",
       "\n",
       "                                               cast        director  \\\n",
       "0  [Sam Worthington, Zoe Saldana, Sigourney Weaver]   James Cameron   \n",
       "1     [Johnny Depp, Orlando Bloom, Keira Knightley]  Gore Verbinski   \n",
       "2      [Daniel Craig, Christoph Waltz, Léa Seydoux]      Sam Mendes   \n",
       "\n",
       "                              keywords                        genres  \n",
       "0   [culture clash, future, space war]  [Action, Adventure, Fantasy]  \n",
       "1   [ocean, drug abuse, exotic island]  [Adventure, Fantasy, Action]  \n",
       "2  [spy, based on novel, secret agent]    [Action, Adventure, Crime]  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Print the new features of the first 3 films\n",
    "df2[['title', 'cast', 'director', 'keywords', 'genres']].head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to convert all strings to lower case and strip names of spaces\n",
    "def clean_data(x):\n",
    "    if isinstance(x, list):\n",
    "        return [str.lower(i.replace(\" \", \"\")) for i in x]\n",
    "    else:\n",
    "        #Check if director exists. If not, return empty string\n",
    "        if isinstance(x, str):\n",
    "            return str.lower(x.replace(\" \", \"\"))\n",
    "        else:\n",
    "            return ''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Apply clean_data function to your features.\n",
    "features = ['cast', 'keywords', 'director', 'genres']\n",
    "\n",
    "for feature in features:\n",
    "    df2[feature] = df2[feature].apply(clean_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>cast</th>\n",
       "      <th>keywords</th>\n",
       "      <th>director</th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>[samworthington, zoesaldana, sigourneyweaver]</td>\n",
       "      <td>[cultureclash, future, spacewar]</td>\n",
       "      <td>jamescameron</td>\n",
       "      <td>[action, adventure, fantasy]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>[johnnydepp, orlandobloom, keiraknightley]</td>\n",
       "      <td>[ocean, drugabuse, exoticisland]</td>\n",
       "      <td>goreverbinski</td>\n",
       "      <td>[adventure, fantasy, action]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            cast  \\\n",
       "0  [samworthington, zoesaldana, sigourneyweaver]   \n",
       "1     [johnnydepp, orlandobloom, keiraknightley]   \n",
       "\n",
       "                           keywords       director  \\\n",
       "0  [cultureclash, future, spacewar]   jamescameron   \n",
       "1  [ocean, drugabuse, exoticisland]  goreverbinski   \n",
       "\n",
       "                         genres  \n",
       "0  [action, adventure, fantasy]  \n",
       "1  [adventure, fantasy, action]  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2[features].head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    cultureclash future spacewar samworthington zo...\n",
       "1    ocean drugabuse exoticisland johnnydepp orland...\n",
       "Name: soup, dtype: object"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def create_soup(x):\n",
    "    return ' '.join(x['keywords']) + ' ' + ' '.join(x['cast']) + ' ' + x['director'] + ' ' + ' '.join(x['genres'])\n",
    "df2['soup'] = df2.apply(create_soup, axis=1)\n",
    "df2['soup'].head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import CountVectorizer and create the count matrix\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "\n",
    "count = CountVectorizer(stop_words='english')\n",
    "count_matrix = count.fit_transform(df2['soup'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compute the Cosine Similarity matrix based on the count_matrix\n",
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "\n",
    "cosine_sim2 = cosine_similarity(count_matrix, count_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reset index of our main DataFrame and construct reverse mapping as before\n",
    "df2 = df2.reset_index()\n",
    "indices = pd.Series(df2.index, index=df2['title'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "65               The Dark Knight\n",
       "119                Batman Begins\n",
       "4638    Amidst the Devil's Wings\n",
       "1196                The Prestige\n",
       "3073           Romeo Is Bleeding\n",
       "3326              Black November\n",
       "1503                      Takers\n",
       "1986                      Faster\n",
       "303                     Catwoman\n",
       "747               Gangster Squad\n",
       "Name: title, dtype: object"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_recommendations('The Dark Knight Rises', cosine_sim2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function that takes in movie title as input and outputs most similar movies\n",
    "def get_recommendations_gui(title, cosine_sim=cosine_sim):\n",
    "    # Get the index of the movie that matches the title\n",
    "    idx =indices[title]\n",
    "\n",
    "    # Get the pairwsie similarity scores of all movies with that movie\n",
    "    sim_scores = list(enumerate(cosine_sim[idx]))\n",
    "\n",
    "    # Sort the movies based on the similarity scores\n",
    "    sim_scores = sorted(sim_scores, key=lambda x: x[1], reverse=True)\n",
    "\n",
    "    # Get the scores of the 10 most similar movies\n",
    "    sim_scores = sim_scores[1:11]\n",
    "\n",
    "    # Get the movie indices\n",
    "    movie_indices = [i[0] for i in sim_scores]\n",
    "\n",
    "    l = list(df2['title'].iloc[movie_indices])\n",
    "    #l = list(df2['title'].head(10))\n",
    "    \n",
    "    for i in range(len(l)):\n",
    "        l[i] = l[i]+'\\n'\n",
    "        \n",
    "    # Return the top 10 most similar movies\n",
    "    return l"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "def validate(flag):\n",
    "    while(True):\n",
    "        #flag = input(\"Enter a movie name to get recommendations or 0 to exit\")\n",
    "        #print(flag)\n",
    "        if(flag == '0'):\n",
    "            break\n",
    "        else:\n",
    "            l=list(df2['title'])\n",
    "           # print(df2['title'].head(3))\n",
    "            #print(\"aefafe\")\n",
    "            #print(l)\n",
    "            #flag=str(flag)\n",
    "           # print(flag in l)\n",
    "            if (flag in l):\n",
    "                #print(\"pp\")\n",
    "                l = (get_recommendations_gui(flag, cosine_sim2))\n",
    "                return l\n",
    "               # print(\"pp\")\n",
    "            else:\n",
    "                return \"Not a correct Movie name\"\n",
    "            #print(\"aefafe\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tkinter import *\n",
    "from tkinter import messagebox\n",
    "\n",
    "root = Tk()\n",
    "root.configure(bg='#060809')\n",
    "#2f2f2b   ff7129    ec4d37   1d1b1b\n",
    "#060809-black   #434343-grey   #ee682a-orange\n",
    "#root.geometry('600x400')\n",
    "root.title('Movie Recommender System')\n",
    "\n",
    "#Entry of a movie name\n",
    "recommend = Entry(root , width=50)\n",
    "recommend.grid(row = 1 , column = 1 , padx=20 , pady= 20)\n",
    "\n",
    "#Label for movie\n",
    "Label(root , text=\"MOVIE RECOMMENDER\" ,bg = \"#060809\" , fg=\"#ee682a\").grid(row = 0 , column = 0 ,columnspan = 2, padx=20 , pady= 20)\n",
    "recommend_label = Label(root , text=\"Please enter a movie name\" ,bg = \"#060809\" , fg=\"#ee682a\").grid(row = 1 , column = 0 , padx=20 , pady= 20)\n",
    "count = 0\n",
    "\n",
    "def submit(flag):\n",
    "    global count\n",
    "    \n",
    "    if(count!=0):\n",
    "        global new_window\n",
    "        new_window.destroy()\n",
    "    flag = flag.strip('\\n')\n",
    "    #print(flag.strip('\\n'))\n",
    "    l = validate(flag)\n",
    "    #t = Text(new_window)\n",
    "    \n",
    "    if(type(l) == list):\n",
    "        new_window = Toplevel()\n",
    "        new_window.configure(bg='#060809')\n",
    "        count+=1\n",
    "        #new_window.geometry('300x800')\n",
    "        Label(new_window, text = \"Movie related to \"+flag ,bg = \"#ee682a\").grid(row = 0 ,column = 0)\n",
    "        btn = [None]*len(l)\n",
    "        j = 1\n",
    "        for i in l:\n",
    "            #btn[i] = Button(new_window , text=l[i] , command=lambda: [submit(l[j]) , new_window.destroy]).grid(row = i , column = 0 , padx=10 , pady=10 , sticky=\"ew\")\n",
    "            \n",
    "            button = Button(new_window, text=i, command=lambda x=i: submit(x), bg=\"#434343\" , fg=\"#ee682a\")\n",
    "            button.grid(row = j , column = 0 , padx=10 , pady=10 , sticky=\"ew\")\n",
    "            j+=1\n",
    "        Button(new_window , text=\"EXIT\" , command=new_window.destroy, bg=\"#434343\" , fg=\"#ee682a\").grid(row = len(l)+1 , column = 0 , ipadx = 20 ,pady=20)\n",
    "    else:\n",
    "        a = messagebox.showinfo(\"Message\",\"PLease enter a correct movie name\")\n",
    "        return\n",
    "    #Label(new_window , text=get_recommendations_gui(print(l), cosine_sim2)).grid(row = 0 , column = 0)\n",
    "    #Button(new_window , text=\"Close window\" , command=new_window.destroy).pack()\n",
    "\n",
    "count = 0\n",
    "recommend_submit = Button(root, text=\"Submit\" , command =lambda : submit(recommend.get()) , bg=\"#434343\" , fg=\"#ee682a\").grid(row = 2 , column = 0 ,columnspan=2 , padx = 20 , pady = 10)\n",
    "exit = Button(root, text=\"EXIT\" , command = root.destroy, bg=\"#434343\" , fg=\"#ee682a\").grid(row = 3 , column = 0 ,columnspan=2 , ipadx = 10 , pady = 10)\n",
    "root.mainloop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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