ContentBased_Recommender.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "263f2d75-7df2-47a9-8241-60c0bf12bf78",
   "metadata": {},
   "source": [
    "# Content based Recommender System\n",
    "In this project I will build a **Content Based Recommender System**. Here I will use ***Cosine Similarity*** for searching/filtering similar content in terms of the user inputs.\n",
    "\n",
    "I want to based on the data related to the movies people watched in the past and recommend similar movies based on the features *Plot, genre, director, etc...*.\n",
    "\n",
    "For example: If we search for *Titanic* movie, similar movies should be present at the Recommended movies section."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "01e9d410-b405-43db-b86b-a815d3eeb36c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "from sklearn.feature_extraction.text import CountVectorizer # Document Term Frequency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "55130cb2-f186-4beb-a010-65fd77b886da",
   "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>Unnamed: 0</th>\n",
       "      <th>Title</th>\n",
       "      <th>Year</th>\n",
       "      <th>Rated</th>\n",
       "      <th>Released</th>\n",
       "      <th>Runtime</th>\n",
       "      <th>Genre</th>\n",
       "      <th>Director</th>\n",
       "      <th>Writer</th>\n",
       "      <th>Actors</th>\n",
       "      <th>Plot</th>\n",
       "      <th>Language</th>\n",
       "      <th>Country</th>\n",
       "      <th>Awards</th>\n",
       "      <th>Poster</th>\n",
       "      <th>Ratings.Source</th>\n",
       "      <th>Ratings.Value</th>\n",
       "      <th>Metascore</th>\n",
       "      <th>imdbRating</th>\n",
       "      <th>imdbVotes</th>\n",
       "      <th>imdbID</th>\n",
       "      <th>Type</th>\n",
       "      <th>tomatoMeter</th>\n",
       "      <th>tomatoImage</th>\n",
       "      <th>tomatoRating</th>\n",
       "      <th>tomatoReviews</th>\n",
       "      <th>tomatoFresh</th>\n",
       "      <th>tomatoRotten</th>\n",
       "      <th>tomatoConsensus</th>\n",
       "      <th>tomatoUserMeter</th>\n",
       "      <th>tomatoUserRating</th>\n",
       "      <th>tomatoUserReviews</th>\n",
       "      <th>tomatoURL</th>\n",
       "      <th>DVD</th>\n",
       "      <th>BoxOffice</th>\n",
       "      <th>Production</th>\n",
       "      <th>Website</th>\n",
       "      <th>Response</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>1994</td>\n",
       "      <td>R</td>\n",
       "      <td>14 Oct 1994</td>\n",
       "      <td>142 min</td>\n",
       "      <td>Crime, Drama</td>\n",
       "      <td>Frank Darabont</td>\n",
       "      <td>Stephen King (short story \"Rita Hayworth and S...</td>\n",
       "      <td>Tim Robbins, Morgan Freeman, Bob Gunton, Willi...</td>\n",
       "      <td>Two imprisoned men bond over a number of years...</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>Nominated for 7 Oscars. Another 19 wins &amp; 30 n...</td>\n",
       "      <td>https://images-na.ssl-images-amazon.com/images...</td>\n",
       "      <td>Internet Movie Database</td>\n",
       "      <td>9.3/10</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9.3</td>\n",
       "      <td>1,825,626</td>\n",
       "      <td>tt0111161</td>\n",
       "      <td>movie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.rottentomatoes.com/m/shawshank_rede...</td>\n",
       "      <td>27 Jan 1998</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Columbia Pictures</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>The Godfather</td>\n",
       "      <td>1972</td>\n",
       "      <td>R</td>\n",
       "      <td>24 Mar 1972</td>\n",
       "      <td>175 min</td>\n",
       "      <td>Crime, Drama</td>\n",
       "      <td>Francis Ford Coppola</td>\n",
       "      <td>Mario Puzo (screenplay), Francis Ford Coppola ...</td>\n",
       "      <td>Marlon Brando, Al Pacino, James Caan, Richard ...</td>\n",
       "      <td>The aging patriarch of an organized crime dyna...</td>\n",
       "      <td>English, Italian, Latin</td>\n",
       "      <td>USA</td>\n",
       "      <td>Won 3 Oscars. Another 23 wins &amp; 27 nominations.</td>\n",
       "      <td>https://images-na.ssl-images-amazon.com/images...</td>\n",
       "      <td>Internet Movie Database</td>\n",
       "      <td>9.2/10</td>\n",
       "      <td>100.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>1,243,444</td>\n",
       "      <td>tt0068646</td>\n",
       "      <td>movie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.rottentomatoes.com/m/godfather/</td>\n",
       "      <td>09 Oct 2001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Paramount Pictures</td>\n",
       "      <td>http://www.thegodfather.com</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>The Godfather: Part II</td>\n",
       "      <td>1974</td>\n",
       "      <td>R</td>\n",
       "      <td>20 Dec 1974</td>\n",
       "      <td>202 min</td>\n",
       "      <td>Crime, Drama</td>\n",
       "      <td>Francis Ford Coppola</td>\n",
       "      <td>Francis Ford Coppola (screenplay), Mario Puzo ...</td>\n",
       "      <td>Al Pacino, Robert Duvall, Diane Keaton, Robert...</td>\n",
       "      <td>The early life and career of Vito Corleone in ...</td>\n",
       "      <td>English, Italian, Spanish, Latin, Sicilian</td>\n",
       "      <td>USA</td>\n",
       "      <td>Won 6 Oscars. Another 10 wins &amp; 20 nominations.</td>\n",
       "      <td>https://images-na.ssl-images-amazon.com/images...</td>\n",
       "      <td>Internet Movie Database</td>\n",
       "      <td>9.0/10</td>\n",
       "      <td>85.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>856,870</td>\n",
       "      <td>tt0071562</td>\n",
       "      <td>movie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.rottentomatoes.com/m/godfather_part...</td>\n",
       "      <td>24 May 2005</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Paramount Pictures</td>\n",
       "      <td>http://www.thegodfather.com/</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>The Dark Knight</td>\n",
       "      <td>2008</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>18 Jul 2008</td>\n",
       "      <td>152 min</td>\n",
       "      <td>Action, Crime, Drama</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "      <td>Jonathan Nolan (screenplay), Christopher Nolan...</td>\n",
       "      <td>Christian Bale, Heath Ledger, Aaron Eckhart, M...</td>\n",
       "      <td>When the menace known as the Joker emerges fro...</td>\n",
       "      <td>English, Mandarin</td>\n",
       "      <td>USA, UK</td>\n",
       "      <td>Won 2 Oscars. Another 151 wins &amp; 153 nominations.</td>\n",
       "      <td>https://images-na.ssl-images-amazon.com/images...</td>\n",
       "      <td>Internet Movie Database</td>\n",
       "      <td>9.0/10</td>\n",
       "      <td>82.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1,802,351</td>\n",
       "      <td>tt0468569</td>\n",
       "      <td>movie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.rottentomatoes.com/m/the_dark_knight/</td>\n",
       "      <td>09 Dec 2008</td>\n",
       "      <td>$533,316,061</td>\n",
       "      <td>Warner Bros. Pictures/Legendary</td>\n",
       "      <td>http://thedarkknight.warnerbros.com/</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>12 Angry Men</td>\n",
       "      <td>1957</td>\n",
       "      <td>APPROVED</td>\n",
       "      <td>01 Apr 1957</td>\n",
       "      <td>96 min</td>\n",
       "      <td>Crime, Drama</td>\n",
       "      <td>Sidney Lumet</td>\n",
       "      <td>Reginald Rose (story), Reginald Rose (screenplay)</td>\n",
       "      <td>Martin Balsam, John Fiedler, Lee J. Cobb, E.G....</td>\n",
       "      <td>A jury holdout attempts to prevent a miscarria...</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>Nominated for 3 Oscars. Another 16 wins &amp; 8 no...</td>\n",
       "      <td>https://images-na.ssl-images-amazon.com/images...</td>\n",
       "      <td>Internet Movie Database</td>\n",
       "      <td>8.9/10</td>\n",
       "      <td>96.0</td>\n",
       "      <td>8.9</td>\n",
       "      <td>494,215</td>\n",
       "      <td>tt0050083</td>\n",
       "      <td>movie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.rottentomatoes.com/m/1000013-12_ang...</td>\n",
       "      <td>06 Mar 2001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Criterion Collection</td>\n",
       "      <td>http://www.criterion.com/films/27871-12-angry-men</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0                     Title  Year     Rated     Released  Runtime  \\\n",
       "0           1  The Shawshank Redemption  1994         R  14 Oct 1994  142 min   \n",
       "1           2             The Godfather  1972         R  24 Mar 1972  175 min   \n",
       "2           3    The Godfather: Part II  1974         R  20 Dec 1974  202 min   \n",
       "3           4           The Dark Knight  2008     PG-13  18 Jul 2008  152 min   \n",
       "4           5              12 Angry Men  1957  APPROVED  01 Apr 1957   96 min   \n",
       "\n",
       "                  Genre              Director  \\\n",
       "0          Crime, Drama        Frank Darabont   \n",
       "1          Crime, Drama  Francis Ford Coppola   \n",
       "2          Crime, Drama  Francis Ford Coppola   \n",
       "3  Action, Crime, Drama     Christopher Nolan   \n",
       "4          Crime, Drama          Sidney Lumet   \n",
       "\n",
       "                                              Writer  \\\n",
       "0  Stephen King (short story \"Rita Hayworth and S...   \n",
       "1  Mario Puzo (screenplay), Francis Ford Coppola ...   \n",
       "2  Francis Ford Coppola (screenplay), Mario Puzo ...   \n",
       "3  Jonathan Nolan (screenplay), Christopher Nolan...   \n",
       "4  Reginald Rose (story), Reginald Rose (screenplay)   \n",
       "\n",
       "                                              Actors  \\\n",
       "0  Tim Robbins, Morgan Freeman, Bob Gunton, Willi...   \n",
       "1  Marlon Brando, Al Pacino, James Caan, Richard ...   \n",
       "2  Al Pacino, Robert Duvall, Diane Keaton, Robert...   \n",
       "3  Christian Bale, Heath Ledger, Aaron Eckhart, M...   \n",
       "4  Martin Balsam, John Fiedler, Lee J. Cobb, E.G....   \n",
       "\n",
       "                                                Plot  \\\n",
       "0  Two imprisoned men bond over a number of years...   \n",
       "1  The aging patriarch of an organized crime dyna...   \n",
       "2  The early life and career of Vito Corleone in ...   \n",
       "3  When the menace known as the Joker emerges fro...   \n",
       "4  A jury holdout attempts to prevent a miscarria...   \n",
       "\n",
       "                                     Language  Country  \\\n",
       "0                                     English      USA   \n",
       "1                     English, Italian, Latin      USA   \n",
       "2  English, Italian, Spanish, Latin, Sicilian      USA   \n",
       "3                           English, Mandarin  USA, UK   \n",
       "4                                     English      USA   \n",
       "\n",
       "                                              Awards  \\\n",
       "0  Nominated for 7 Oscars. Another 19 wins & 30 n...   \n",
       "1    Won 3 Oscars. Another 23 wins & 27 nominations.   \n",
       "2    Won 6 Oscars. Another 10 wins & 20 nominations.   \n",
       "3  Won 2 Oscars. Another 151 wins & 153 nominations.   \n",
       "4  Nominated for 3 Oscars. Another 16 wins & 8 no...   \n",
       "\n",
       "                                              Poster           Ratings.Source  \\\n",
       "0  https://images-na.ssl-images-amazon.com/images...  Internet Movie Database   \n",
       "1  https://images-na.ssl-images-amazon.com/images...  Internet Movie Database   \n",
       "2  https://images-na.ssl-images-amazon.com/images...  Internet Movie Database   \n",
       "3  https://images-na.ssl-images-amazon.com/images...  Internet Movie Database   \n",
       "4  https://images-na.ssl-images-amazon.com/images...  Internet Movie Database   \n",
       "\n",
       "  Ratings.Value  Metascore  imdbRating  imdbVotes     imdbID   Type  \\\n",
       "0        9.3/10       80.0         9.3  1,825,626  tt0111161  movie   \n",
       "1        9.2/10      100.0         9.2  1,243,444  tt0068646  movie   \n",
       "2        9.0/10       85.0         9.0    856,870  tt0071562  movie   \n",
       "3        9.0/10       82.0         9.0  1,802,351  tt0468569  movie   \n",
       "4        8.9/10       96.0         8.9    494,215  tt0050083  movie   \n",
       "\n",
       "   tomatoMeter  tomatoImage  tomatoRating  tomatoReviews  tomatoFresh  \\\n",
       "0          NaN          NaN           NaN            NaN          NaN   \n",
       "1          NaN          NaN           NaN            NaN          NaN   \n",
       "2          NaN          NaN           NaN            NaN          NaN   \n",
       "3          NaN          NaN           NaN            NaN          NaN   \n",
       "4          NaN          NaN           NaN            NaN          NaN   \n",
       "\n",
       "   tomatoRotten  tomatoConsensus  tomatoUserMeter  tomatoUserRating  \\\n",
       "0           NaN              NaN              NaN               NaN   \n",
       "1           NaN              NaN              NaN               NaN   \n",
       "2           NaN              NaN              NaN               NaN   \n",
       "3           NaN              NaN              NaN               NaN   \n",
       "4           NaN              NaN              NaN               NaN   \n",
       "\n",
       "   tomatoUserReviews                                          tomatoURL  \\\n",
       "0                NaN  http://www.rottentomatoes.com/m/shawshank_rede...   \n",
       "1                NaN         http://www.rottentomatoes.com/m/godfather/   \n",
       "2                NaN  http://www.rottentomatoes.com/m/godfather_part...   \n",
       "3                NaN   http://www.rottentomatoes.com/m/the_dark_knight/   \n",
       "4                NaN  http://www.rottentomatoes.com/m/1000013-12_ang...   \n",
       "\n",
       "           DVD     BoxOffice                       Production  \\\n",
       "0  27 Jan 1998           NaN                Columbia Pictures   \n",
       "1  09 Oct 2001           NaN               Paramount Pictures   \n",
       "2  24 May 2005           NaN               Paramount Pictures   \n",
       "3  09 Dec 2008  $533,316,061  Warner Bros. Pictures/Legendary   \n",
       "4  06 Mar 2001           NaN             Criterion Collection   \n",
       "\n",
       "                                             Website  Response  \n",
       "0                                                NaN      True  \n",
       "1                        http://www.thegodfather.com      True  \n",
       "2                       http://www.thegodfather.com/      True  \n",
       "3               http://thedarkknight.warnerbros.com/      True  \n",
       "4  http://www.criterion.com/films/27871-12-angry-men      True  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('display.max_columns', 100)\n",
    "df = pd.read_csv('https://query.data.world/s/uikepcpffyo2nhig52xxeevdialfl7')\n",
    "#df = pd.read_csv('movie_data.csv') # if above url does not worling, uncomment this line, comment above and run again\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4be9a52c-34c0-43a9-b988-44d2b549633c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(250, 38)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1ae8405-9875-4ec1-87b0-05e9ab76b240",
   "metadata": {},
   "source": [
    "We can see that above dataset has 38 features. We do not need all of them in this particular task. So, let's select the features we need and update our original dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ba152881-bb8f-47af-a84d-898b11a01dcd",
   "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>Genre</th>\n",
       "      <th>Director</th>\n",
       "      <th>Actors</th>\n",
       "      <th>Plot</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>Crime, Drama</td>\n",
       "      <td>Frank Darabont</td>\n",
       "      <td>Tim Robbins, Morgan Freeman, Bob Gunton, Willi...</td>\n",
       "      <td>Two imprisoned men bond over a number of years...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>The Godfather</td>\n",
       "      <td>Crime, Drama</td>\n",
       "      <td>Francis Ford Coppola</td>\n",
       "      <td>Marlon Brando, Al Pacino, James Caan, Richard ...</td>\n",
       "      <td>The aging patriarch of an organized crime dyna...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Godfather: Part II</td>\n",
       "      <td>Crime, Drama</td>\n",
       "      <td>Francis Ford Coppola</td>\n",
       "      <td>Al Pacino, Robert Duvall, Diane Keaton, Robert...</td>\n",
       "      <td>The early life and career of Vito Corleone in ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>The Dark Knight</td>\n",
       "      <td>Action, Crime, Drama</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "      <td>Christian Bale, Heath Ledger, Aaron Eckhart, M...</td>\n",
       "      <td>When the menace known as the Joker emerges fro...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12 Angry Men</td>\n",
       "      <td>Crime, Drama</td>\n",
       "      <td>Sidney Lumet</td>\n",
       "      <td>Martin Balsam, John Fiedler, Lee J. Cobb, E.G....</td>\n",
       "      <td>A jury holdout attempts to prevent a miscarria...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Title                 Genre              Director  \\\n",
       "0  The Shawshank Redemption          Crime, Drama        Frank Darabont   \n",
       "1             The Godfather          Crime, Drama  Francis Ford Coppola   \n",
       "2    The Godfather: Part II          Crime, Drama  Francis Ford Coppola   \n",
       "3           The Dark Knight  Action, Crime, Drama     Christopher Nolan   \n",
       "4              12 Angry Men          Crime, Drama          Sidney Lumet   \n",
       "\n",
       "                                              Actors  \\\n",
       "0  Tim Robbins, Morgan Freeman, Bob Gunton, Willi...   \n",
       "1  Marlon Brando, Al Pacino, James Caan, Richard ...   \n",
       "2  Al Pacino, Robert Duvall, Diane Keaton, Robert...   \n",
       "3  Christian Bale, Heath Ledger, Aaron Eckhart, M...   \n",
       "4  Martin Balsam, John Fiedler, Lee J. Cobb, E.G....   \n",
       "\n",
       "                                                Plot  \n",
       "0  Two imprisoned men bond over a number of years...  \n",
       "1  The aging patriarch of an organized crime dyna...  \n",
       "2  The early life and career of Vito Corleone in ...  \n",
       "3  When the menace known as the Joker emerges fro...  \n",
       "4  A jury holdout attempts to prevent a miscarria...  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df[['Title','Genre','Director','Actors','Plot']]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0adc8c9a-884a-4e14-b9c6-18bca172547c",
   "metadata": {},
   "source": [
    "### Some data preparation...\n",
    "Using Pythons' *map* function with the help of *Lambda function*\n",
    "1. *Genre* and *Actors* columns, they consists of comma separated values. We need to separate them in terms of using them effectively in our searching/filtering algorithm. Convert them to lowercase to avoid duplicates. ***(Python is case sensitive)*** -> `'robin' == 'Robin' # outputs False`\n",
    "2. *Director* names also be separated using space in between."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b3621c83-9334-4b9c-b77f-0402e08aacb3",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Actors'] = df['Actors'].map(lambda x: x.lower().split(','))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8fe31575-90da-429b-a869-92337a54d4e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      [tim robbins,  morgan freeman,  bob gunton,  w...\n",
       "1      [marlon brando,  al pacino,  james caan,  rich...\n",
       "2      [al pacino,  robert duvall,  diane keaton,  ro...\n",
       "3      [christian bale,  heath ledger,  aaron eckhart...\n",
       "4      [martin balsam,  john fiedler,  lee j. cobb,  ...\n",
       "                             ...                        \n",
       "245    [ray milland,  jane wyman,  phillip terry,  ho...\n",
       "246    [brie larson,  john gallagher jr.,  stephanie ...\n",
       "247    [cary grant,  rosalind russell,  ralph bellamy...\n",
       "248    [sissy spacek,  jane galloway heitz,  joseph a...\n",
       "249    [dev patel,  saurabh shukla,  anil kapoor,  ra...\n",
       "Name: Actors, Length: 250, dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Actors']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "25059eb7-2698-41ea-8f05-e495ee831b15",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Genre'] = df['Genre'].map(lambda x: x.lower().split(','))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b9476990-6fc1-4bdd-a032-2b4608b88c77",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                 [crime,  drama]\n",
       "1                 [crime,  drama]\n",
       "2                 [crime,  drama]\n",
       "3        [action,  crime,  drama]\n",
       "4                 [crime,  drama]\n",
       "                  ...            \n",
       "245           [drama,  film-noir]\n",
       "246                       [drama]\n",
       "247    [comedy,  drama,  romance]\n",
       "248           [biography,  drama]\n",
       "249                       [drama]\n",
       "Name: Genre, Length: 250, dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Genre']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a561191c-ced9-4ef1-99cb-affb9d7f7137",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Director'] = df['Director'].map(lambda x: x.lower().split(' '))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "88d3fb69-d2a8-4e3e-933c-634fb3251521",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                      [frank, darabont]\n",
       "1               [francis, ford, coppola]\n",
       "2               [francis, ford, coppola]\n",
       "3                   [christopher, nolan]\n",
       "4                        [sidney, lumet]\n",
       "                     ...                \n",
       "245                      [billy, wilder]\n",
       "246            [destin, daniel, cretton]\n",
       "247                      [howard, hawks]\n",
       "248                       [david, lynch]\n",
       "249    [danny, boyle,, loveleen, tandan]\n",
       "Name: Director, Length: 250, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Director']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db3984e9-4983-4bf4-8e03-dca681d931d0",
   "metadata": {},
   "source": [
    "In this step I *Join* each *Actors* names and *Director* names as a single string. Then they are not treated as two seprate words."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c7db06e8-2cbd-4868-9ea5-37366f2e3d76",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Actors'] = df.apply(\n",
    "    lambda row: [x.replace(' ', '') for x in row['Actors']],\n",
    "    axis=1\n",
    ")\n",
    "\n",
    "df['Director'] = df.apply(\n",
    "    lambda row: ''.join(row['Director']),\n",
    "    axis=1\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0c58ae0f-0ae8-4016-a78b-85aed36f672c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      [timrobbins, morganfreeman, bobgunton, william...\n",
       "1      [marlonbrando, alpacino, jamescaan, richards.c...\n",
       "2      [alpacino, robertduvall, dianekeaton, robertde...\n",
       "3      [christianbale, heathledger, aaroneckhart, mic...\n",
       "4      [martinbalsam, johnfiedler, leej.cobb, e.g.mar...\n",
       "                             ...                        \n",
       "245    [raymilland, janewyman, phillipterry, howardda...\n",
       "246    [brielarson, johngallagherjr., stephaniebeatri...\n",
       "247    [carygrant, rosalindrussell, ralphbellamy, gen...\n",
       "248    [sissyspacek, janegallowayheitz, josepha.carpe...\n",
       "249     [devpatel, saurabhshukla, anilkapoor, rajzutshi]\n",
       "Name: Actors, Length: 250, dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Actors']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "42fa882d-3bc8-4403-b31b-54cf3a37b16a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                  frankdarabont\n",
       "1             francisfordcoppola\n",
       "2             francisfordcoppola\n",
       "3               christophernolan\n",
       "4                    sidneylumet\n",
       "                 ...            \n",
       "245                  billywilder\n",
       "246          destindanielcretton\n",
       "247                  howardhawks\n",
       "248                   davidlynch\n",
       "249    dannyboyle,loveleentandan\n",
       "Name: Director, Length: 250, dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Director']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4badc86b-7127-4faf-b09d-2f9acf07d608",
   "metadata": {},
   "source": [
    "I use *rake_nltk* **Naturel Language Toolkit** library for continue this work.\n",
    "\n",
    "Let's install it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "cda37ece-df2a-46cc-a1a3-44fc575867b8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: rake_nltk in c:\\users\\navilog\\anaconda3\\lib\\site-packages (1.0.6)\n",
      "Requirement already satisfied: nltk<4.0.0,>=3.6.2 in c:\\users\\navilog\\anaconda3\\lib\\site-packages (from rake_nltk) (3.7)\n",
      "Requirement already satisfied: tqdm in c:\\users\\navilog\\anaconda3\\lib\\site-packages (from nltk<4.0.0,>=3.6.2->rake_nltk) (4.64.1)\n",
      "Requirement already satisfied: joblib in c:\\users\\navilog\\anaconda3\\lib\\site-packages (from nltk<4.0.0,>=3.6.2->rake_nltk) (1.1.1)\n",
      "Requirement already satisfied: regex>=2021.8.3 in c:\\users\\navilog\\anaconda3\\lib\\site-packages (from nltk<4.0.0,>=3.6.2->rake_nltk) (2022.7.9)\n",
      "Requirement already satisfied: click in c:\\users\\navilog\\anaconda3\\lib\\site-packages (from nltk<4.0.0,>=3.6.2->rake_nltk) (8.0.4)\n",
      "Requirement already satisfied: colorama in c:\\users\\navilog\\anaconda3\\lib\\site-packages (from click->nltk<4.0.0,>=3.6.2->rake_nltk) (0.4.6)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: Ignoring invalid distribution -ensorflow-intel (c:\\users\\navilog\\anaconda3\\lib\\site-packages)\n",
      "WARNING: Ignoring invalid distribution -ensorflow-intel (c:\\users\\navilog\\anaconda3\\lib\\site-packages)\n",
      "WARNING: Ignoring invalid distribution -ensorflow-intel (c:\\users\\navilog\\anaconda3\\lib\\site-packages)\n",
      "WARNING: Ignoring invalid distribution -ensorflow-intel (c:\\users\\navilog\\anaconda3\\lib\\site-packages)\n",
      "WARNING: Ignoring invalid distribution -ensorflow-intel (c:\\users\\navilog\\anaconda3\\lib\\site-packages)\n",
      "WARNING: Ignoring invalid distribution -ensorflow-intel (c:\\users\\navilog\\anaconda3\\lib\\site-packages)\n"
     ]
    }
   ],
   "source": [
    "!pip install rake_nltk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0b91c5ac-72eb-48bd-b84a-75addb18ac8a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     C:\\Users\\navilog\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n",
      "[nltk_data] Downloading package punkt to\n",
      "[nltk_data]     C:\\Users\\navilog\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package punkt is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import rake_nltk\n",
    "from rake_nltk import Rake # for extracting significant keywords in the entire text\n",
    "import nltk\n",
    "nltk.download('stopwords')\n",
    "nltk.download('punkt')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d468281-2943-4449-a5f1-639aa9760f9c",
   "metadata": {},
   "source": [
    "### ***Rake()***\n",
    "*Rake()* is used to extract keywords from a large text like *Plot* in our case. Let's use *Rake* now...\n",
    "\n",
    "And I store the *Keywords* in a new column called *Key_words*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "02b9b5e6-e259-42a2-98ac-885a2bb2f862",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      [two, imprisoned, men, bond, number, years, fi...\n",
       "1      [aging, patriarch, organized, crime, dynasty, ...\n",
       "2      [early, life, career, vito, corleone, 1920s, n...\n",
       "3      [menace, known, joker, emerges, mysterious, pa...\n",
       "4      [jury, holdout, attempts, prevent, miscarriage...\n",
       "                             ...                        \n",
       "245    [desperate, life, chronic, alcoholic, followed...\n",
       "246    [20, something, supervising, staff, member, re...\n",
       "247    [newspaper, editor, uses, every, trick, book, ...\n",
       "248    [old, man, makes, long, journey, lawn, mover, ...\n",
       "249    [mumbai, teen, reflects, upbringing, slums, ac...\n",
       "Name: Key_words, Length: 250, dtype: object"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Key_words']=\"\" # initializing the new column\n",
    "\n",
    "for index, row in df.iterrows():\n",
    "    plot = row['Plot']\n",
    "    \n",
    "    # instantiating Rake\n",
    "    # by default it uses English stopwords from NLTK and discard all punctuations and characters\n",
    "    r = Rake()\n",
    "    \n",
    "    # extracting the words by passing the text\n",
    "    r.extract_keywords_from_text(plot)\n",
    "    \n",
    "    # preparing a dictionary with keywords and their scores\n",
    "    keyword_dict_score = r.get_word_degrees()\n",
    "    \n",
    "    # assign keywords to the new column\n",
    "    row['Key_words'] = list(keyword_dict_score.keys())\n",
    "    \n",
    "df['Key_words']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "3b040c6f-3250-4ee8-8667-37d9a9f37397",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now we don't need Plot column\n",
    "df.drop('Plot', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f541bb20-36f1-453b-810e-4df8dc2ce1a9",
   "metadata": {},
   "source": [
    "#### Keywords and scores...\n",
    "As an example, these are the keywords extrated from last movie in the dataset and their scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7edc8299-ad2b-484b-ae61-6601817f58f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "defaultdict(<function rake_nltk.rake.Rake._build_word_co_occurance_graph.<locals>.<lambda>()>,\n",
       "            {'mumbai': 3,\n",
       "             'teen': 3,\n",
       "             'reflects': 3,\n",
       "             'upbringing': 1,\n",
       "             'slums': 1,\n",
       "             'accused': 1,\n",
       "             'cheating': 1,\n",
       "             'indian': 2,\n",
       "             'version': 2,\n",
       "             'wants': 1,\n",
       "             'millionaire': 2,\n",
       "             '?\"': 2})"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "keyword_dict_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d838774e-d16f-403d-8385-cf1905293555",
   "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>Genre</th>\n",
       "      <th>Director</th>\n",
       "      <th>Actors</th>\n",
       "      <th>Key_words</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>Slumdog Millionaire</td>\n",
       "      <td>[drama]</td>\n",
       "      <td>dannyboyle,loveleentandan</td>\n",
       "      <td>[devpatel, saurabhshukla, anilkapoor, rajzutshi]</td>\n",
       "      <td>[mumbai, teen, reflects, upbringing, slums, ac...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Title    Genre                   Director  \\\n",
       "249  Slumdog Millionaire  [drama]  dannyboyle,loveleentandan   \n",
       "\n",
       "                                               Actors  \\\n",
       "249  [devpatel, saurabhshukla, anilkapoor, rajzutshi]   \n",
       "\n",
       "                                             Key_words  \n",
       "249  [mumbai, teen, reflects, upbringing, slums, ac...  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acd5698a-06cb-456d-9ca2-0bb7814a06e8",
   "metadata": {},
   "source": [
    "#### Set the *Title* as the index\n",
    "Setting the *Title* as the index will ease identifying records instead of numerical index."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "90db4367-1b5d-403f-a4ff-075688f96522",
   "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>Genre</th>\n",
       "      <th>Director</th>\n",
       "      <th>Actors</th>\n",
       "      <th>Key_words</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>The Shawshank Redemption</th>\n",
       "      <td>[crime,  drama]</td>\n",
       "      <td>frankdarabont</td>\n",
       "      <td>[timrobbins, morganfreeman, bobgunton, william...</td>\n",
       "      <td>[two, imprisoned, men, bond, number, years, fi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Godfather</th>\n",
       "      <td>[crime,  drama]</td>\n",
       "      <td>francisfordcoppola</td>\n",
       "      <td>[marlonbrando, alpacino, jamescaan, richards.c...</td>\n",
       "      <td>[aging, patriarch, organized, crime, dynasty, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Godfather: Part II</th>\n",
       "      <td>[crime,  drama]</td>\n",
       "      <td>francisfordcoppola</td>\n",
       "      <td>[alpacino, robertduvall, dianekeaton, robertde...</td>\n",
       "      <td>[early, life, career, vito, corleone, 1920s, n...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Dark Knight</th>\n",
       "      <td>[action,  crime,  drama]</td>\n",
       "      <td>christophernolan</td>\n",
       "      <td>[christianbale, heathledger, aaroneckhart, mic...</td>\n",
       "      <td>[menace, known, joker, emerges, mysterious, pa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12 Angry Men</th>\n",
       "      <td>[crime,  drama]</td>\n",
       "      <td>sidneylumet</td>\n",
       "      <td>[martinbalsam, johnfiedler, leej.cobb, e.g.mar...</td>\n",
       "      <td>[jury, holdout, attempts, prevent, miscarriage...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             Genre            Director  \\\n",
       "Title                                                                    \n",
       "The Shawshank Redemption           [crime,  drama]       frankdarabont   \n",
       "The Godfather                      [crime,  drama]  francisfordcoppola   \n",
       "The Godfather: Part II             [crime,  drama]  francisfordcoppola   \n",
       "The Dark Knight           [action,  crime,  drama]    christophernolan   \n",
       "12 Angry Men                       [crime,  drama]         sidneylumet   \n",
       "\n",
       "                                                                     Actors  \\\n",
       "Title                                                                         \n",
       "The Shawshank Redemption  [timrobbins, morganfreeman, bobgunton, william...   \n",
       "The Godfather             [marlonbrando, alpacino, jamescaan, richards.c...   \n",
       "The Godfather: Part II    [alpacino, robertduvall, dianekeaton, robertde...   \n",
       "The Dark Knight           [christianbale, heathledger, aaroneckhart, mic...   \n",
       "12 Angry Men              [martinbalsam, johnfiedler, leej.cobb, e.g.mar...   \n",
       "\n",
       "                                                                  Key_words  \n",
       "Title                                                                        \n",
       "The Shawshank Redemption  [two, imprisoned, men, bond, number, years, fi...  \n",
       "The Godfather             [aging, patriarch, organized, crime, dynasty, ...  \n",
       "The Godfather: Part II    [early, life, career, vito, corleone, 1920s, n...  \n",
       "The Dark Knight           [menace, known, joker, emerges, mysterious, pa...  \n",
       "12 Angry Men              [jury, holdout, attempts, prevent, miscarriage...  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.set_index('Title', inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23f4c31a-1c77-452e-94c6-5af0fff56e5b",
   "metadata": {},
   "source": [
    "### Now we create a column called *bag_of_words*\n",
    "*bag_of_words* is used to store all the terms we prepared and keywrods we extracted in one place.\n",
    "\n",
    "*i.e.* use in *Term Frequency Matrix*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "399844d2-fc3e-41f9-bd50-ec1e2a7e5f08",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['bag_of_words'] = ''\n",
    "\n",
    "columns = df.columns\n",
    "\n",
    "def bag_of_words_row(row):\n",
    "    words = ''\n",
    "    for col in columns:\n",
    "        if col == 'Director':\n",
    "            words += row[col] + ' '\n",
    "        else:\n",
    "            words += ' '.join(row[col]) + ' '\n",
    "    \n",
    "    return words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b2f6bb0e-72ec-4d69-b40e-0da7965691a6",
   "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>Genre</th>\n",
       "      <th>Director</th>\n",
       "      <th>Actors</th>\n",
       "      <th>Key_words</th>\n",
       "      <th>bag_of_words</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>The Shawshank Redemption</th>\n",
       "      <td>[crime,  drama]</td>\n",
       "      <td>frankdarabont</td>\n",
       "      <td>[timrobbins, morganfreeman, bobgunton, william...</td>\n",
       "      <td>[two, imprisoned, men, bond, number, years, fi...</td>\n",
       "      <td>crime  drama frankdarabont timrobbins morganfr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Godfather</th>\n",
       "      <td>[crime,  drama]</td>\n",
       "      <td>francisfordcoppola</td>\n",
       "      <td>[marlonbrando, alpacino, jamescaan, richards.c...</td>\n",
       "      <td>[aging, patriarch, organized, crime, dynasty, ...</td>\n",
       "      <td>crime  drama francisfordcoppola marlonbrando a...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Godfather: Part II</th>\n",
       "      <td>[crime,  drama]</td>\n",
       "      <td>francisfordcoppola</td>\n",
       "      <td>[alpacino, robertduvall, dianekeaton, robertde...</td>\n",
       "      <td>[early, life, career, vito, corleone, 1920s, n...</td>\n",
       "      <td>crime  drama francisfordcoppola alpacino rober...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Dark Knight</th>\n",
       "      <td>[action,  crime,  drama]</td>\n",
       "      <td>christophernolan</td>\n",
       "      <td>[christianbale, heathledger, aaroneckhart, mic...</td>\n",
       "      <td>[menace, known, joker, emerges, mysterious, pa...</td>\n",
       "      <td>action  crime  drama christophernolan christia...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12 Angry Men</th>\n",
       "      <td>[crime,  drama]</td>\n",
       "      <td>sidneylumet</td>\n",
       "      <td>[martinbalsam, johnfiedler, leej.cobb, e.g.mar...</td>\n",
       "      <td>[jury, holdout, attempts, prevent, miscarriage...</td>\n",
       "      <td>crime  drama sidneylumet martinbalsam johnfied...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             Genre            Director  \\\n",
       "Title                                                                    \n",
       "The Shawshank Redemption           [crime,  drama]       frankdarabont   \n",
       "The Godfather                      [crime,  drama]  francisfordcoppola   \n",
       "The Godfather: Part II             [crime,  drama]  francisfordcoppola   \n",
       "The Dark Knight           [action,  crime,  drama]    christophernolan   \n",
       "12 Angry Men                       [crime,  drama]         sidneylumet   \n",
       "\n",
       "                                                                     Actors  \\\n",
       "Title                                                                         \n",
       "The Shawshank Redemption  [timrobbins, morganfreeman, bobgunton, william...   \n",
       "The Godfather             [marlonbrando, alpacino, jamescaan, richards.c...   \n",
       "The Godfather: Part II    [alpacino, robertduvall, dianekeaton, robertde...   \n",
       "The Dark Knight           [christianbale, heathledger, aaroneckhart, mic...   \n",
       "12 Angry Men              [martinbalsam, johnfiedler, leej.cobb, e.g.mar...   \n",
       "\n",
       "                                                                  Key_words  \\\n",
       "Title                                                                         \n",
       "The Shawshank Redemption  [two, imprisoned, men, bond, number, years, fi...   \n",
       "The Godfather             [aging, patriarch, organized, crime, dynasty, ...   \n",
       "The Godfather: Part II    [early, life, career, vito, corleone, 1920s, n...   \n",
       "The Dark Knight           [menace, known, joker, emerges, mysterious, pa...   \n",
       "12 Angry Men              [jury, holdout, attempts, prevent, miscarriage...   \n",
       "\n",
       "                                                               bag_of_words  \n",
       "Title                                                                        \n",
       "The Shawshank Redemption  crime  drama frankdarabont timrobbins morganfr...  \n",
       "The Godfather             crime  drama francisfordcoppola marlonbrando a...  \n",
       "The Godfather: Part II    crime  drama francisfordcoppola alpacino rober...  \n",
       "The Dark Knight           action  crime  drama christophernolan christia...  \n",
       "12 Angry Men              crime  drama sidneylumet martinbalsam johnfied...  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "df['bag_of_words'] = df.apply(\n",
    "    lambda row: bag_of_words_row(row),\n",
    "    axis=1\n",
    ")\n",
    "\n",
    "df.head()        "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "825e0caa-42f7-4478-bf08-97e16fe99baf",
   "metadata": {},
   "source": [
    "#### Now we only need the *Index* column and *bag_of_words* column\n",
    "*bag_for_words* has everything we need. Let's drop others"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "1f357bab-a272-4f79-bd05-827a41a5c71c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop([col for col in columns if col != 'bag_of_words'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c654af56-c82d-42ac-940a-f409b301f88c",
   "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>bag_of_words</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Title</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>The Shawshank Redemption</th>\n",
       "      <td>crime  drama frankdarabont timrobbins morganfr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Godfather</th>\n",
       "      <td>crime  drama francisfordcoppola marlonbrando a...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Godfather: Part II</th>\n",
       "      <td>crime  drama francisfordcoppola alpacino rober...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Dark Knight</th>\n",
       "      <td>action  crime  drama christophernolan christia...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12 Angry Men</th>\n",
       "      <td>crime  drama sidneylumet martinbalsam johnfied...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                               bag_of_words\n",
       "Title                                                                      \n",
       "The Shawshank Redemption  crime  drama frankdarabont timrobbins morganfr...\n",
       "The Godfather             crime  drama francisfordcoppola marlonbrando a...\n",
       "The Godfather: Part II    crime  drama francisfordcoppola alpacino rober...\n",
       "The Dark Knight           action  crime  drama christophernolan christia...\n",
       "12 Angry Men              crime  drama sidneylumet martinbalsam johnfied..."
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d17b04a6-cabd-4ad7-b21b-f653ffca2e1c",
   "metadata": {},
   "source": [
    "### CountVectorizer()\n",
    "*CountVetorizer()* pick all the unique words in each *bag_of_words* and count their frequency. Basically it converts the text into ***lowercase*** and ***word-level tokenization***."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "0c9357e0-7111-4bf2-b214-9c5f209fd14c",
   "metadata": {},
   "outputs": [],
   "source": [
    "count_vector = CountVectorizer()\n",
    "count_matrix = count_vector.fit_transform(df['bag_of_words'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a58a8b6d-a186-4ea7-8230-e98ff27a877a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<250x3176 sparse matrix of type '<class 'numpy.int64'>'\n",
       "\twith 5601 stored elements in Compressed Sparse Row format>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count_matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d01fb8a-3939-413d-846c-e9dba6cd2649",
   "metadata": {},
   "source": [
    "#### Let's see what's inside..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "52e60213-b0b1-4948-a24e-0a286e1165f3",
   "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>000</th>\n",
       "      <th>10</th>\n",
       "      <th>100</th>\n",
       "      <th>12</th>\n",
       "      <th>17</th>\n",
       "      <th>1820s</th>\n",
       "      <th>18th</th>\n",
       "      <th>1900</th>\n",
       "      <th>1920s</th>\n",
       "      <th>1936</th>\n",
       "      <th>1940s</th>\n",
       "      <th>1941</th>\n",
       "      <th>1948</th>\n",
       "      <th>1950s</th>\n",
       "      <th>1951</th>\n",
       "      <th>1954</th>\n",
       "      <th>1960s</th>\n",
       "      <th>1970s</th>\n",
       "      <th>1972</th>\n",
       "      <th>1979</th>\n",
       "      <th>1980</th>\n",
       "      <th>1984</th>\n",
       "      <th>19th</th>\n",
       "      <th>20</th>\n",
       "      <th>2029</th>\n",
       "      <th>24</th>\n",
       "      <th>25</th>\n",
       "      <th>30</th>\n",
       "      <th>40</th>\n",
       "      <th>7th</th>\n",
       "      <th>9000</th>\n",
       "      <th>aaroneckhart</th>\n",
       "      <th>abagnale</th>\n",
       "      <th>abandoned</th>\n",
       "      <th>abandons</th>\n",
       "      <th>abducted</th>\n",
       "      <th>abhishekbharate</th>\n",
       "      <th>ability</th>\n",
       "      <th>able</th>\n",
       "      <th>abrams</th>\n",
       "      <th>accelerated</th>\n",
       "      <th>accept</th>\n",
       "      <th>accepted</th>\n",
       "      <th>accepts</th>\n",
       "      <th>accident</th>\n",
       "      <th>accidentally</th>\n",
       "      <th>according</th>\n",
       "      <th>account</th>\n",
       "      <th>accumulates</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>...</th>\n",
       "      <th>winter</th>\n",
       "      <th>wiped</th>\n",
       "      <th>wiser</th>\n",
       "      <th>within</th>\n",
       "      <th>without</th>\n",
       "      <th>witness</th>\n",
       "      <th>witnessing</th>\n",
       "      <th>wits</th>\n",
       "      <th>wizard</th>\n",
       "      <th>wolfgang</th>\n",
       "      <th>woman</th>\n",
       "      <th>womb</th>\n",
       "      <th>women</th>\n",
       "      <th>woody</th>\n",
       "      <th>woodyallen</th>\n",
       "      <th>woodyharrelson</th>\n",
       "      <th>wookiee</th>\n",
       "      <th>work</th>\n",
       "      <th>worker</th>\n",
       "      <th>workforce</th>\n",
       "      <th>working</th>\n",
       "      <th>works</th>\n",
       "      <th>world</th>\n",
       "      <th>wormhole</th>\n",
       "      <th>worship</th>\n",
       "      <th>worshipper</th>\n",
       "      <th>worth</th>\n",
       "      <th>worthy</th>\n",
       "      <th>would</th>\n",
       "      <th>wreak</th>\n",
       "      <th>wreaks</th>\n",
       "      <th>wrentz</th>\n",
       "      <th>write</th>\n",
       "      <th>writer</th>\n",
       "      <th>wrong</th>\n",
       "      <th>wwii</th>\n",
       "      <th>xolanimali</th>\n",
       "      <th>year</th>\n",
       "      <th>years</th>\n",
       "      <th>yet</th>\n",
       "      <th>yoda</th>\n",
       "      <th>york</th>\n",
       "      <th>young</th>\n",
       "      <th>younger</th>\n",
       "      <th>youngest</th>\n",
       "      <th>yuppie</th>\n",
       "      <th>zachgrenier</th>\n",
       "      <th>zero</th>\n",
       "      <th>zoesaldana</th>\n",
       "      <th>zubrowka</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 3176 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   000  10  100  12  17  1820s  18th  1900  1920s  1936  1940s  1941  1948  \\\n",
       "0    0   0    0   0   0      0     0     0      0     0      0     0     0   \n",
       "1    0   0    0   0   0      0     0     0      0     0      0     0     0   \n",
       "2    0   0    0   0   0      0     0     0      1     0      0     0     0   \n",
       "3    0   0    0   0   0      0     0     0      0     0      0     0     0   \n",
       "4    0   0    0   0   0      0     0     0      0     0      0     0     0   \n",
       "\n",
       "   1950s  1951  1954  1960s  1970s  1972  1979  1980  1984  19th  20  2029  \\\n",
       "0      0     0     0      0      0     0     0     0     0     0   0     0   \n",
       "1      0     0     0      0      0     0     0     0     0     0   0     0   \n",
       "2      0     0     0      0      0     0     0     0     0     0   0     0   \n",
       "3      0     0     0      0      0     0     0     0     0     0   0     0   \n",
       "4      0     0     0      0      0     0     0     0     0     0   0     0   \n",
       "\n",
       "   24  25  30  40  7th  9000  aaroneckhart  abagnale  abandoned  abandons  \\\n",
       "0   0   0   0   0    0     0             0         0          0         0   \n",
       "1   0   0   0   0    0     0             0         0          0         0   \n",
       "2   0   0   0   0    0     0             0         0          0         0   \n",
       "3   0   0   0   0    0     0             1         0          0         0   \n",
       "4   0   0   0   0    0     0             0         0          0         0   \n",
       "\n",
       "   abducted  abhishekbharate  ability  able  abrams  accelerated  accept  \\\n",
       "0         0                0        0     0       0            0       0   \n",
       "1         0                0        0     0       0            0       0   \n",
       "2         0                0        0     0       0            0       0   \n",
       "3         0                0        1     0       0            0       1   \n",
       "4         0                0        0     0       0            0       0   \n",
       "\n",
       "   accepted  accepts  accident  accidentally  according  account  accumulates  \\\n",
       "0         0        0         0             0          0        0            0   \n",
       "1         0        0         0             0          0        0            0   \n",
       "2         0        0         0             0          0        0            0   \n",
       "3         0        0         0             0          0        0            0   \n",
       "4         0        0         0             0          0        0            0   \n",
       "\n",
       "   accuracy  ...  winter  wiped  wiser  within  without  witness  witnessing  \\\n",
       "0         0  ...       0      0      0       0        0        0           0   \n",
       "1         0  ...       0      0      0       0        0        0           0   \n",
       "2         0  ...       0      0      0       0        0        0           0   \n",
       "3         0  ...       0      0      0       0        0        0           0   \n",
       "4         0  ...       0      0      0       0        0        0           0   \n",
       "\n",
       "   wits  wizard  wolfgang  woman  womb  women  woody  woodyallen  \\\n",
       "0     0       0         0      0     0      0      0           0   \n",
       "1     0       0         0      0     0      0      0           0   \n",
       "2     0       0         0      0     0      0      0           0   \n",
       "3     0       0         0      0     0      0      0           0   \n",
       "4     0       0         0      0     0      0      0           0   \n",
       "\n",
       "   woodyharrelson  wookiee  work  worker  workforce  working  works  world  \\\n",
       "0               0        0     0       0          0        0      0      0   \n",
       "1               0        0     0       0          0        0      0      0   \n",
       "2               0        0     0       0          0        0      0      0   \n",
       "3               0        0     0       0          0        0      0      0   \n",
       "4               0        0     0       0          0        0      0      0   \n",
       "\n",
       "   wormhole  worship  worshipper  worth  worthy  would  wreak  wreaks  wrentz  \\\n",
       "0         0        0           0      0       0      0      0       0       0   \n",
       "1         0        0           0      0       0      0      0       0       0   \n",
       "2         0        0           0      0       0      0      0       0       0   \n",
       "3         0        0           0      0       0      0      0       1       0   \n",
       "4         0        0           0      0       0      0      0       0       0   \n",
       "\n",
       "   write  writer  wrong  wwii  xolanimali  year  years  yet  yoda  york  \\\n",
       "0      0       0      0     0           0     0      1    0     0     0   \n",
       "1      0       0      0     0           0     0      0    0     0     0   \n",
       "2      0       0      0     0           0     0      0    0     0     1   \n",
       "3      0       0      0     0           0     0      0    0     0     0   \n",
       "4      0       0      0     0           0     0      0    0     0     0   \n",
       "\n",
       "   young  younger  youngest  yuppie  zachgrenier  zero  zoesaldana  zubrowka  \n",
       "0      0        0         0       0            0     0           0         0  \n",
       "1      0        0         0       0            0     0           0         0  \n",
       "2      0        0         0       0            0     0           0         0  \n",
       "3      0        0         0       0            0     0           0         0  \n",
       "4      0        0         0       0            0     0           0         0  \n",
       "\n",
       "[5 rows x 3176 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cv = pd.DataFrame(data=count_matrix.toarray(), columns=count_vector.get_feature_names_out())\n",
    "df_cv.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "9987a6e8-7574-4028-bfcf-d962f328be7b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(250, 3176)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cv.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a5f5689-1aa3-4244-9cab-36b4bce7ecef",
   "metadata": {},
   "source": [
    "### Generate the *Cosine Similarity Matrix*\n",
    "Since we have the *Term Frequency Matrix* now we can create the *Cosine Similarity Matrix* as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "2956b710-e91f-4964-ad54-527476228007",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.        , 0.14638501, 0.1315587 , ..., 0.05      , 0.05      ,\n",
       "        0.05270463],\n",
       "       [0.14638501, 1.        , 0.34236839, ..., 0.048795  , 0.048795  ,\n",
       "        0.05143445],\n",
       "       [0.1315587 , 0.34236839, 1.        , ..., 0.0438529 , 0.0438529 ,\n",
       "        0.04622502],\n",
       "       ...,\n",
       "       [0.05      , 0.048795  , 0.0438529 , ..., 1.        , 0.05      ,\n",
       "        0.05270463],\n",
       "       [0.05      , 0.048795  , 0.0438529 , ..., 0.05      , 1.        ,\n",
       "        0.05270463],\n",
       "       [0.05270463, 0.05143445, 0.04622502, ..., 0.05270463, 0.05270463,\n",
       "        1.        ]])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cosine_sim = cosine_similarity(count_matrix, count_matrix)\n",
    "cosine_sim"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b982e12-d4cc-48af-bc8d-043d78739111",
   "metadata": {},
   "source": [
    "### Implementation of *Recommender* function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "f71fee9c-e3cb-4d32-8f29-a751a9027e23",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      The Shawshank Redemption\n",
       "1                 The Godfather\n",
       "2        The Godfather: Part II\n",
       "3               The Dark Knight\n",
       "4                  12 Angry Men\n",
       "                 ...           \n",
       "245            The Lost Weekend\n",
       "246               Short Term 12\n",
       "247             His Girl Friday\n",
       "248          The Straight Story\n",
       "249         Slumdog Millionaire\n",
       "Name: Title, Length: 250, dtype: object"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# take indeces (Movie Titles) of our DataFrame and create a Pandas Series out of it\n",
    "indeces = pd.Series(df.index)\n",
    "indeces"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20104edf-f692-473b-8286-92fed6114cc5",
   "metadata": {},
   "source": [
    "Above series of titles are indexed similar to the *cosine_sim* matrix. So, we can map those indexes and reach relevant cosine similarities easily."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "eb30d14d-a977-40c6-970b-bff795f4e7ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "245"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "indeces[indeces == 'The Lost Weekend'].index[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "be2e3795-aa62-4373-9256-53863b61e5d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "def recommender(title, cosine_sim=cosine_sim):\n",
    "    recommendations = []\n",
    "    \n",
    "    # get relevant indeces\n",
    "    search_idx = indeces[indeces == title].index[0]\n",
    "    \n",
    "    # get relevant cosine similarity list and sort them\n",
    "    similarities = pd.Series(cosine_sim[search_idx]).sort_values(ascending=False)\n",
    "    \n",
    "    # get top 10 matches (indexes)\n",
    "    # use these indexes again to retrieve Movie titles\n",
    "    top_10_matches = list(similarities.iloc[1:11].index)\n",
    "    print(top_10_matches)\n",
    "    \n",
    "    # store best matched movie names\n",
    "    for i in top_10_matches:\n",
    "        recommendations.append(indeces[i])\n",
    "        \n",
    "    return recommendations\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "1345eb26-da3e-49cc-a860-0206a364922e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[7, 226, 18, 15, 151, 1, 212, 29, 110, 54]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['Pulp Fiction',\n",
       " 'Rope',\n",
       " 'Se7en',\n",
       " 'Goodfellas',\n",
       " 'Butch Cassidy and the Sundance Kid',\n",
       " 'The Godfather',\n",
       " 'Papillon',\n",
       " 'The Green Mile',\n",
       " 'Casino',\n",
       " 'Once Upon a Time in America']"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recommender('The Shawshank Redemption')"
   ]
  },
  {
   "attachments": {
    "a18e1b23-df2e-4e22-bed4-78eb70c459d1.jpg": {
     "image/jpeg": "/9j/4RtJRXhpZgAATU0AKgAAAAgABwESAAMAAAABAAEAAAEaAAUAAAABAAAAYgEbAAUAAAABAAAA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\n"
    }
   },
   "cell_type": "markdown",
   "id": "a22f74b2-9f4e-4789-9f82-68920ca680c5",
   "metadata": {},
   "source": [
    "## **Netflix** recommendations\n",
    "Based on previously watched movies, Netflix recommends list of movies as follows.\n",
    "![netflix_recommender.jpg](attachment:a18e1b23-df2e-4e22-bed4-78eb70c459d1.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0691d464-7af4-47b2-a6aa-6dcf204a7e01",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}