Recommender.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <center> Movie Recommendation System"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is a movie recommendation system, that is trained on a dataset from <a href=\"https://www.themoviedb.org/\" target=\"_new\">The Movie Database (TMDb)</a> <br/>\n",
    "Let's explore the Dataset!    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4803, 4)\n",
      "(4803, 20)\n"
     ]
    }
   ],
   "source": [
    "# Reading the data\n",
    "df1 = pd.read_csv(\"tmdb_5000_credits.csv\")\n",
    "df2 = pd.read_csv(\"tmdb_5000_movies.csv\")\n",
    "print(df1.shape)\n",
    "print(df2.shape)\n",
    "\n",
    "# We have 4803 different movies in our database!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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>0</th>\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",
       "      <th>1</th>\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",
       "      <th>2</th>\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",
       "      <th>3</th>\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",
       "      <th>4</th>\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",
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      "text/plain": [
       "   movie_id                                     title  \\\n",
       "0     19995                                    Avatar   \n",
       "1       285  Pirates of the Caribbean: At World's End   \n",
       "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": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      <th>0</th>\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",
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       "      <td>162.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...</td>\n",
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       "      <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",
       "      <th>1</th>\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",
       "      <th>2</th>\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",
       "      <th>3</th>\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",
       "      <th>4</th>\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",
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      "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  "
      ]
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     "execution_count": 5,
     "metadata": {},
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   "source": [
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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       "      <td>The Dark Knight Rises</td>\n",
       "      <td>7.6</td>\n",
       "      <td>9106</td>\n",
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       "      budget                                             genres  \\\n",
       "3  250000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam...   \n",
       "\n",
       "                             homepage     id  \\\n",
       "3  http://www.thedarkknightrises.com/  49026   \n",
       "\n",
       "                                            keywords original_language  \\\n",
       "3  [{\"id\": 849, \"name\": \"dc comics\"}, {\"id\": 853,...                en   \n",
       "\n",
       "          original_title                                           overview  \\\n",
       "3  The Dark Knight Rises  Following the death of District Attorney Harve...   \n",
       "\n",
       "   popularity                               production_companies  \\\n",
       "3   112.31295  [{\"name\": \"Legendary Pictures\", \"id\": 923}, {\"...   \n",
       "\n",
       "                                production_countries release_date     revenue  \\\n",
       "3  [{\"iso_3166_1\": \"US\", \"name\": \"United States o...   2012-07-16  1084939099   \n",
       "\n",
       "   runtime                          spoken_languages    status  \\\n",
       "3    165.0  [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
       "\n",
       "           tagline                  title  vote_average  vote_count  \n",
       "3  The Legend Ends  The Dark Knight Rises           7.6        9106  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.loc[df2['id']== 49026]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The two datasets are linked via the Movie_ID Key, so we'll merge the two, and work with the merged dataset only!\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Joining the two DataFrames \n",
    "df1.rename(columns = {'movie_id' : 'id' , 'title':'title_1'}, inplace= True) \n",
    "df2 = df2.merge(df1, on ='id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>...</th>\n",
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       "      <th>status</th>\n",
       "      <th>tagline</th>\n",
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       "      <th>vote_count</th>\n",
       "      <th>title_1</th>\n",
       "      <th>cast</th>\n",
       "      <th>crew</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\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",
       "      <th>1</th>\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",
       "      <th>2</th>\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",
       "    <tr>\n",
       "      <th>3</th>\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>...</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",
       "      <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",
       "      <th>4</th>\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>...</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",
       "      <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",
       "<p>5 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",
       "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  ... 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",
       "3  [{\"name\": \"Legendary Pictures\", \"id\": 923}, {\"...  ...   165.0   \n",
       "4        [{\"name\": \"Walt Disney Pictures\", \"id\": 2}]  ...   132.0   \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",
       "3           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
       "4           [{\"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   \n",
       "\n",
       "                                    title_1  \\\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",
       "                                                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...  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We need to figure out a scoring method for the movies before filtering, as all movies have different no.of votes, and ratings can't be compared directly. <br/>\n",
    "Using IMDB's Weighted Rating : WR = (v/v+m)*R  + (m/v+m)*C <br/>\n",
    "where:<br/>\n",
    "    v = no.of votes <br/>\n",
    "    m = minimum votes required to be listed<br/>\n",
    "    R = Avg. rating<br/>\n",
    "    C = mean votes across the entire report<br/>"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# v = vote_count\n",
    "# R = vote_average\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.76084222668461"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_votes = df2['vote_count'].sum()\n",
    "total_ratings = (df2['vote_count']*df2['vote_average']).sum()\n",
    "c =  total_ratings/total_votes\n",
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "957.6000000000004"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#We'll use 85th percentile as the cutoff for the minimum no.of votes required\n",
    "m = df2['vote_count'].quantile(0.80)\n",
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(961, 23)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Moving forward, we'll only consider the movies having a minimumn of 957 votes!\n",
    "#Filtering out the movies based on this criterion\n",
    "fil_mov = df2.copy().loc[df2['vote_count']>=m]\n",
    "fil_mov.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# So, out of 4803, we are left with 961 movies! That's just 20% of the dataset!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def weighted_rat(df, m = m, C =c):\n",
    "    v = df['vote_count']\n",
    "    r = df['vote_average']\n",
    "    \n",
    "    x = ((v/(v+m))*r) + ((m/(m+v))*C)\n",
    "    \n",
    "    return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "fil_mov['weighted_rat'] = fil_mov.apply(weighted_rat, axis= 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <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",
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       "      <th>production_companies</th>\n",
       "      <th>...</th>\n",
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       "      <th>status</th>\n",
       "      <th>tagline</th>\n",
       "      <th>title</th>\n",
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       "      <th>title_1</th>\n",
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       "      <th>weighted_rat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\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>[{\"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>7.167036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\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>6.875583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\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>6.381367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\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>...</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",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>[{\"cast_id\": 2, \"character\": \"Bruce Wayne / Ba...</td>\n",
       "      <td>[{\"credit_id\": \"52fe4781c3a36847f81398c3\", \"de...</td>\n",
       "      <td>7.520150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\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>...</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",
       "      <td>John Carter</td>\n",
       "      <td>[{\"cast_id\": 5, \"character\": \"John Carter\", \"c...</td>\n",
       "      <td>[{\"credit_id\": \"52fe479ac3a36847f813eaa3\", \"de...</td>\n",
       "      <td>6.305355</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 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",
       "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",
       "                                    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",
       "3           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
       "4           [{\"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   \n",
       "\n",
       "                                    title_1  \\\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",
       "                                                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  weighted_rat  \n",
       "0  [{\"credit_id\": \"52fe48009251416c750aca23\", \"de...      7.167036  \n",
       "1  [{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...      6.875583  \n",
       "2  [{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...      6.381367  \n",
       "3  [{\"credit_id\": \"52fe4781c3a36847f81398c3\", \"de...      7.520150  \n",
       "4  [{\"credit_id\": \"52fe479ac3a36847f813eaa3\", \"de...      6.305355  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fil_mov.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are many different types of recommendation systems for movies, based on features, and based on the user preferences. For this, we'll be working on the following 3 types of recommendation systems!<br /> \n",
    "1: Demographic Filtering. This will recommend same movies to the audience with similar demographics <br /> \n",
    "2: Content Based Filtering. This will recommend movies based on the content that you like, watch, etc.<br />\n",
    "3: Collaborative Filtering. This will provide a better recommendation, and will recommend movies that people with similar interests watch (similar actors, directors, etc)\n",
    "\n",
    "\n",
    "## Demographic Filtering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>weighted_rat</th>\n",
       "      <th>vote_count</th>\n",
       "      <th>vote_average</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1881</th>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>8.318237</td>\n",
       "      <td>8205</td>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3337</th>\n",
       "      <td>The Godfather</td>\n",
       "      <td>8.170873</td>\n",
       "      <td>5893</td>\n",
       "      <td>8.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>662</th>\n",
       "      <td>Fight Club</td>\n",
       "      <td>8.157877</td>\n",
       "      <td>9413</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3232</th>\n",
       "      <td>Pulp Fiction</td>\n",
       "      <td>8.142962</td>\n",
       "      <td>8428</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>The Dark Knight</td>\n",
       "      <td>8.093659</td>\n",
       "      <td>12002</td>\n",
       "      <td>8.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>809</th>\n",
       "      <td>Forrest Gump</td>\n",
       "      <td>8.044885</td>\n",
       "      <td>7927</td>\n",
       "      <td>8.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1818</th>\n",
       "      <td>Schindler's List</td>\n",
       "      <td>8.021201</td>\n",
       "      <td>4329</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3865</th>\n",
       "      <td>Whiplash</td>\n",
       "      <td>8.017189</td>\n",
       "      <td>4254</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>Inception</td>\n",
       "      <td>8.012820</td>\n",
       "      <td>13752</td>\n",
       "      <td>8.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990</th>\n",
       "      <td>The Empire Strikes Back</td>\n",
       "      <td>7.998418</td>\n",
       "      <td>5879</td>\n",
       "      <td>8.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         title  weighted_rat  vote_count  vote_average\n",
       "1881  The Shawshank Redemption      8.318237        8205           8.5\n",
       "3337             The Godfather      8.170873        5893           8.4\n",
       "662                 Fight Club      8.157877        9413           8.3\n",
       "3232              Pulp Fiction      8.142962        8428           8.3\n",
       "65             The Dark Knight      8.093659       12002           8.2\n",
       "809               Forrest Gump      8.044885        7927           8.2\n",
       "1818          Schindler's List      8.021201        4329           8.3\n",
       "3865                  Whiplash      8.017189        4254           8.3\n",
       "96                   Inception      8.012820       13752           8.1\n",
       "1990   The Empire Strikes Back      7.998418        5879           8.2"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Now we can sort the DataFrame on this metric\n",
    "fil_mov = fil_mov.sort_values('weighted_rat', ascending =False)\n",
    "fil_mov[['title', 'weighted_rat', 'vote_count', 'vote_average']].head(10)\n",
    "\n",
    "# The following is recommending the popular movies currently. Similar to Netflix's top 10 in the Country ranking!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Popularity based Sorting\n",
    "pop_mov = df2.sort_values('popularity', ascending = False)\n",
    "plt.figure(figsize = (15, 6))\n",
    "p = sns.barplot(y = 'popularity',x ='title' , data =pop_mov.head(10))\n",
    "plt.xticks(rotation= 25)\n",
    "plt.title(\"Top 10 Movies rated by Popularity\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above movies are general and do not depend on a User's interests! <br/>\n",
    "Now, we'll move to a better rating, that is based on the content that the user likes!\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Content Based Rating"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "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": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2['overview'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "#We can find similarity scores for plots of movies \n",
    "from sklearn.feature_extraction.text import TfidfVectorizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "tfidf =TfidfVectorizer(stop_words = 'english')\n",
    "df2['overview'] = df2['overview'].fillna('')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4803, 20978)"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tfidf_m = tfidf.fit_transform(df2['overview'])\n",
    "\n",
    "tfidf_m.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics.pairwise import linear_kernel\n",
    "\n",
    "#Computing cosine similarity\n",
    "cos_sim = linear_kernel(tfidf_m, tfidf_m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "mov_idx = pd.Series(df2.index , index = df2['title']).drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ax = list(enumerate(cos_sim[23]))\n",
    "# ax = sorted(ax, key = lambda x: x[1], reverse = True)\n",
    "# ax[1:11]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "def recom_cos_sim (title, cos_sim = cos_sim):\n",
    "    idx = mov_idx[title]\n",
    "    \n",
    "    #Getting similarity score of all the movies with the movie in consideration\n",
    "    sim_scr = list(enumerate(cos_sim[idx]))\n",
    "    sim_scr = sorted(sim_scr, key = lambda x: x[1], reverse = True)\n",
    "    sim_scr = sim_scr[1:11] #The top most score will be for the movie with itself.\n",
    "    movie_idx = [i[0] for i in sim_scr]\n",
    "    \n",
    "    return (df2['title'].iloc[movie_idx])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above function will recommend 10 movies based on the movie that the user likes! "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "506                           Despicable Me 2\n",
      "221                           Stuart Little 2\n",
      "1218                           The Guilt Trip\n",
      "2511                               Home Alone\n",
      "3944                                  Freeway\n",
      "2892                        Darling Companion\n",
      "505     The League of Extraordinary Gentlemen\n",
      "3188                          Velvet Goldmine\n",
      "1733                        The Spy Next Door\n",
      "70                             Wild Wild West\n",
      "Name: title, dtype: object\n"
     ]
    }
   ],
   "source": [
    "a =recom_cos_sim('Minions')\n",
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1218                                 The Guilt Trip\n",
       "418     Cats & Dogs 2 : The Revenge of Kitty Galore\n",
       "2276                               The Painted Veil\n",
       "1007                                  Anna Karenina\n",
       "4403                                 The Jimmy Show\n",
       "3492                  The First Great Train Robbery\n",
       "263                     Around the World in 80 Days\n",
       "1750         Star Trek VI: The Undiscovered Country\n",
       "2987                               The Mighty Ducks\n",
       "4349                                 Love Me Tender\n",
       "Name: title, dtype: object"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recom_cos_sim(\"Wild Wild West\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Genre, Credit, Keyword based Recommender:"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# The metadata we'll use now is:\n",
    "1: Top 4 actors\n",
    "2: Director\n",
    "3: Related Genres\n",
    "4: Movie Plot Keywords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We have to extract the first 2 from the cast, crew and keywords\n",
    "from ast import literal_eval\n",
    "features = [ 'cast', 'crew', 'keywords', 'genres']\n",
    "df_feat = df2.copy()\n",
    "for feature in features:\n",
    "    df_feat[feature] = df_feat[feature].apply(literal_eval)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\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>...</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>title_1</th>\n",
       "      <th>cast</th>\n",
       "      <th>crew</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\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",
       "      <th>1</th>\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",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 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",
       "\n",
       "                                       homepage     id  \\\n",
       "0                   http://www.avatarmovie.com/  19995   \n",
       "1  http://disney.go.com/disneypictures/pirates/    285   \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",
       "\n",
       "                             original_title  \\\n",
       "0                                    Avatar   \n",
       "1  Pirates of the Caribbean: At World's End   \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",
       "\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",
       "\n",
       "                                    spoken_languages    status  \\\n",
       "0  [{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...  Released   \n",
       "1           [{\"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",
       "\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",
       "\n",
       "                                    title_1  \\\n",
       "0                                    Avatar   \n",
       "1  Pirates of the Caribbean: At World's End   \n",
       "\n",
       "                                                cast  \\\n",
       "0  [{'cast_id': 242, 'character': 'Jake Sully', '...   \n",
       "1  [{'cast_id': 4, 'character': 'Captain Jack Spa...   \n",
       "\n",
       "                                                crew  \n",
       "0  [{'credit_id': '52fe48009251416c750aca23', 'de...  \n",
       "1  [{'credit_id': '52fe4232c3a36847f800b579', 'de...  \n",
       "\n",
       "[2 rows x 23 columns]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_feat.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We'll get the required information from the columns.\n",
    "def direct_name(df_x):\n",
    "    for i in df_x:\n",
    "        if i['job'] == 'Director':\n",
    "            return i['name']\n",
    "    return np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_list(df_x):\n",
    "    if isinstance(df_x, list):\n",
    "        name = [i['name'] for i in df_x]\n",
    "        \n",
    "        if len(name)>4:\n",
    "            name = name[:4]\n",
    "        return name\n",
    "    return []\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_feat['director'] = df_feat['crew'].apply(direct_name)\n",
    "\n",
    "feat_list = ['cast' , 'keywords' , 'genres']\n",
    "\n",
    "for feats in feat_list:\n",
    "    df_feat[feats] = df_feat[feats].apply(get_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_feat.loc[1 , 'genres']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
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       "      <th>production_companies</th>\n",
       "      <th>...</th>\n",
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       "      <th>director</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>237000000</td>\n",
       "      <td>[Action, Adventure, Fantasy, Science Fiction]</td>\n",
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       "      <td>19995</td>\n",
       "      <td>[culture clash, future, space war, space colony]</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",
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       "      <td>11800</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>[Sam Worthington, Zoe Saldana, Sigourney Weave...</td>\n",
       "      <td>[{'credit_id': '52fe48009251416c750aca23', 'de...</td>\n",
       "      <td>James Cameron</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>300000000</td>\n",
       "      <td>[Adventure, Fantasy, Action]</td>\n",
       "      <td>http://disney.go.com/disneypictures/pirates/</td>\n",
       "      <td>285</td>\n",
       "      <td>[ocean, drug abuse, exotic island, east india ...</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>[Johnny Depp, Orlando Bloom, Keira Knightley, ...</td>\n",
       "      <td>[{'credit_id': '52fe4232c3a36847f800b579', 'de...</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      budget                                         genres  \\\n",
       "0  237000000  [Action, Adventure, Fantasy, Science Fiction]   \n",
       "1  300000000                   [Adventure, Fantasy, Action]   \n",
       "\n",
       "                                       homepage     id  \\\n",
       "0                   http://www.avatarmovie.com/  19995   \n",
       "1  http://disney.go.com/disneypictures/pirates/    285   \n",
       "\n",
       "                                            keywords original_language  \\\n",
       "0   [culture clash, future, space war, space colony]                en   \n",
       "1  [ocean, drug abuse, exotic island, east india ...                en   \n",
       "\n",
       "                             original_title  \\\n",
       "0                                    Avatar   \n",
       "1  Pirates of the Caribbean: At World's End   \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",
       "\n",
       "                                production_companies  ...  \\\n",
       "0  [{\"name\": \"Ingenious Film Partners\", \"id\": 289...  ...   \n",
       "1  [{\"name\": \"Walt Disney Pictures\", \"id\": 2}, {\"...  ...   \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",
       "\n",
       "                                          tagline  \\\n",
       "0                     Enter the World of Pandora.   \n",
       "1  At the end of the world, the adventure begins.   \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",
       "\n",
       "                                    title_1  \\\n",
       "0                                    Avatar   \n",
       "1  Pirates of the Caribbean: At World's End   \n",
       "\n",
       "                                                cast  \\\n",
       "0  [Sam Worthington, Zoe Saldana, Sigourney Weave...   \n",
       "1  [Johnny Depp, Orlando Bloom, Keira Knightley, ...   \n",
       "\n",
       "                                                crew        director  \n",
       "0  [{'credit_id': '52fe48009251416c750aca23', 'de...   James Cameron  \n",
       "1  [{'credit_id': '52fe4232c3a36847f800b579', 'de...  Gore Verbinski  \n",
       "\n",
       "[2 rows x 24 columns]"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_feat.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "feat_list.append('title')\n",
    "feat_list.append('director')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cast</th>\n",
       "      <th>keywords</th>\n",
       "      <th>genres</th>\n",
       "      <th>title</th>\n",
       "      <th>director</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[Sam Worthington, Zoe Saldana, Sigourney Weave...</td>\n",
       "      <td>[culture clash, future, space war, space colony]</td>\n",
       "      <td>[Action, Adventure, Fantasy, Science Fiction]</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>James Cameron</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[Johnny Depp, Orlando Bloom, Keira Knightley, ...</td>\n",
       "      <td>[ocean, drug abuse, exotic island, east india ...</td>\n",
       "      <td>[Adventure, Fantasy, Action]</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[Daniel Craig, Christoph Waltz, Léa Seydoux, R...</td>\n",
       "      <td>[spy, based on novel, secret agent, sequel]</td>\n",
       "      <td>[Action, Adventure, Crime]</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>Sam Mendes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[Christian Bale, Michael Caine, Gary Oldman, A...</td>\n",
       "      <td>[dc comics, crime fighter, terrorist, secret i...</td>\n",
       "      <td>[Action, Crime, Drama, Thriller]</td>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[Taylor Kitsch, Lynn Collins, Samantha Morton,...</td>\n",
       "      <td>[based on novel, mars, medallion, space travel]</td>\n",
       "      <td>[Action, Adventure, Science Fiction]</td>\n",
       "      <td>John Carter</td>\n",
       "      <td>Andrew Stanton</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                cast  \\\n",
       "0  [Sam Worthington, Zoe Saldana, Sigourney Weave...   \n",
       "1  [Johnny Depp, Orlando Bloom, Keira Knightley, ...   \n",
       "2  [Daniel Craig, Christoph Waltz, Léa Seydoux, R...   \n",
       "3  [Christian Bale, Michael Caine, Gary Oldman, A...   \n",
       "4  [Taylor Kitsch, Lynn Collins, Samantha Morton,...   \n",
       "\n",
       "                                            keywords  \\\n",
       "0   [culture clash, future, space war, space colony]   \n",
       "1  [ocean, drug abuse, exotic island, east india ...   \n",
       "2        [spy, based on novel, secret agent, sequel]   \n",
       "3  [dc comics, crime fighter, terrorist, secret i...   \n",
       "4    [based on novel, mars, medallion, space travel]   \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",
       "                                      title           director  \n",
       "0                                    Avatar      James Cameron  \n",
       "1  Pirates of the Caribbean: At World's End     Gore Verbinski  \n",
       "2                                   Spectre         Sam Mendes  \n",
       "3                     The Dark Knight Rises  Christopher Nolan  \n",
       "4                               John Carter     Andrew Stanton  "
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_feat[feat_list].head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Converting the Names to Lowercase and removing space"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "def lower_case(strs):\n",
    "    if isinstance(strs, list):\n",
    "        return[str.lower(i.replace(\" \", \"\")) for i in strs]\n",
    "    else:\n",
    "        if isinstance(strs, str):\n",
    "            return str.lower(strs.replace(\" \", \"\"))\n",
    "        else:\n",
    "            return \"\"\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "for features in feat_list:\n",
    "    df_feat[features] = df_feat[features].apply(lower_case)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let's combine the features to create meta-data\n",
    "def combine_feats(x):\n",
    "    return ' '.join(x['keywords']) + ' ' + ' '.join(x['cast']) + ' ' + x['director'] + ' ' + ' '.join(x['genres'])\n",
    "df_feat['metadata'] = df_feat.apply(combine_feats, axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "\n",
    "count = CountVectorizer(stop_words = 'english')\n",
    "count_matrix = count.fit_transform(df_feat['metadata'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "cos_sim2 = cosine_similarity(count_matrix, count_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_feat = df_feat.reset_index()\n",
    "indices = pd.Series(df_feat.index, index =df_feat['title'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "258                                          The Smurfs 2\n",
       "66                                                     Up\n",
       "2114                                 Return to Never Land\n",
       "3403    Alpha and Omega: The Legend of the Saw Tooth Cave\n",
       "565                                               Shrek 2\n",
       "899                                                 Shrek\n",
       "1426                                              Valiant\n",
       "1695                                              Aladdin\n",
       "40                                                 Cars 2\n",
       "77                                             Inside Out\n",
       "Name: title, dtype: object"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recom_cos_sim('The Smurfs', cos_sim2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now, the user is recommended 10 movies based on the Movies Top 4 actors, Director, Related Genres and Movie Plot Keywords"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Collaborative Filtering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Implementing Singular Value Decomposition\n",
    "# SVD is a dimensionality reduction technique that decomposes a matrix into three matrices, the first is users' latent factors, \n",
    "# the second is a diagonal matrix, that represents the strength of each latent factor, and the third contains the latent factors of the items.\n",
    "#Since the above data doesn't have user Information, whihc is required for the Collaborative Filtering, we'll use the \n",
    "\n",
    "\n",
    "from surprise import Reader, Dataset, SVD\n",
    "from surprise.model_selection import cross_validate\n",
    "from surprise.model_selection import KFold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "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>userId</th>\n",
       "      <th>movieId</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1260759144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1029</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1260759179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1061</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1260759182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1129</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1260759185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1172</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1260759205</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   userId  movieId  rating   timestamp\n",
       "0       1       31     2.5  1260759144\n",
       "1       1     1029     3.0  1260759179\n",
       "2       1     1061     3.0  1260759182\n",
       "3       1     1129     2.0  1260759185\n",
       "4       1     1172     4.0  1260759205"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reader = Reader()\n",
    "ratings =pd.read_csv('ratings_small.csv')\n",
    "ratings.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 671 unique users in the dataset.\n"
     ]
    }
   ],
   "source": [
    "print(\"There are {} unique users in the dataset.\" .format(len(ratings.userId.unique())))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<generator object KFold.split at 0x0000025F98FD4EC8>"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "kf = KFold(n_splits=5)\n",
    "data = Dataset.load_from_df(ratings[['userId', 'movieId', 'rating' ]], reader)\n",
    "\n",
    "kf.split(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "svd = SVD()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Evaluating RMSE, MAE of algorithm SVD on 5 split(s).\n",
      "\n",
      "                  Fold 1  Fold 2  Fold 3  Fold 4  Fold 5  Mean    Std     \n",
      "RMSE (testset)    0.8886  0.8931  0.9063  0.8964  0.8984  0.8966  0.0059  \n",
      "MAE (testset)     0.6839  0.6885  0.6988  0.6900  0.6939  0.6910  0.0050  \n",
      "Fit time          5.67    5.68    5.48    6.09    6.01    5.78    0.23    \n",
      "Test time         0.18    0.15    0.27    0.18    0.17    0.19    0.04    \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'test_rmse': array([0.88864937, 0.89308049, 0.90631513, 0.89642428, 0.89835741]),\n",
       " 'test_mae': array([0.68392486, 0.68852226, 0.69878865, 0.68995505, 0.69394652]),\n",
       " 'fit_time': (5.665408372879028,\n",
       "  5.682655572891235,\n",
       "  5.480091094970703,\n",
       "  6.0860278606414795,\n",
       "  6.007667303085327),\n",
       " 'test_time': (0.1759958267211914,\n",
       "  0.1479966640472412,\n",
       "  0.27299976348876953,\n",
       "  0.1770017147064209,\n",
       "  0.16500639915466309)}"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cross_validate(svd, data, measures = ['rmse', 'mae'], verbose = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [],
   "source": [
    "trainset = data.build_full_trainset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [],
   "source": [
    "svd.fit(trainset);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [],
   "source": [
    "#The following gives the ratings for User ID \n",
    "\n",
    "#ratings[ratings['userId']==4].sort_values('movieId')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The predicted Rating of Movie: 1, for User 30, is: 2.79\n"
     ]
    }
   ],
   "source": [
    "#Let's see what's the predicted rating for User 1 for movie 20 is:\n",
    "# The following will predict the movie ratings based on the SVD.\n",
    "UserID = 1\n",
    "MovieID = 30\n",
    "\n",
    "a = svd.predict(UserID, MovieID)\n",
    "print(\"The predicted Rating of Movie: {}, for User {}, is: {}\".format(a.uid, a.iid, format(a.est, '.2f')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [],
   "source": [
    "#This is a Collaborative Filtering based result, however, there's room for more work, and I'll update the files once I get the chance to work on it!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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