Movie_Recommendation_System.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Libraries Required"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import warnings\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "from sklearn.metrics.pairwise import cosine_similarity"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filtering Based Method\n",
    "In this method, we filter out the movies based on there rating by different users.\n",
    "Then we sort the movies in descending order of there correlation with the name of the movie which is being entered."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Having a look at the data and removing the values which are of no use."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "warnings.filterwarnings(\"ignore\", category=RuntimeWarning) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "Movies = pd.read_csv('Datasets/movies.csv')\n",
    "Ratings = pd.read_csv('Datasets/ratings.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>movieId</th>\n",
       "      <th>title</th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>Adventure|Animation|Children|Comedy|Fantasy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Jumanji (1995)</td>\n",
       "      <td>Adventure|Children|Fantasy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Grumpier Old Men (1995)</td>\n",
       "      <td>Comedy|Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Waiting to Exhale (1995)</td>\n",
       "      <td>Comedy|Drama|Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Father of the Bride Part II (1995)</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   movieId                               title  \\\n",
       "0        1                    Toy Story (1995)   \n",
       "1        2                      Jumanji (1995)   \n",
       "2        3             Grumpier Old Men (1995)   \n",
       "3        4            Waiting to Exhale (1995)   \n",
       "4        5  Father of the Bride Part II (1995)   \n",
       "\n",
       "                                        genres  \n",
       "0  Adventure|Animation|Children|Comedy|Fantasy  \n",
       "1                   Adventure|Children|Fantasy  \n",
       "2                               Comedy|Romance  \n",
       "3                         Comedy|Drama|Romance  \n",
       "4                                       Comedy  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Movies.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
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       "  <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",
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      "text/plain": [
       "   userId  movieId  rating  timestamp\n",
       "0       1        1     4.0  964982703\n",
       "1       1        3     4.0  964981247\n",
       "2       1        6     4.0  964982224\n",
       "3       1       47     5.0  964983815\n",
       "4       1       50     5.0  964982931"
      ]
     },
     "execution_count": 27,
     "metadata": {},
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    }
   ],
   "source": [
    "Ratings.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.merge(Movies,Ratings, on = 'movieId')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "vv = df['title'].value_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
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       "      <th>0</th>\n",
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       "      <td>Toy Story (1995)</td>\n",
       "      <td>Adventure|Animation|Children|Comedy|Fantasy</td>\n",
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       "      <td>Toy Story (1995)</td>\n",
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       "      <td>4.5</td>\n",
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      "text/plain": [
       "   movieId             title                                       genres  \\\n",
       "0        1  Toy Story (1995)  Adventure|Animation|Children|Comedy|Fantasy   \n",
       "1        1  Toy Story (1995)  Adventure|Animation|Children|Comedy|Fantasy   \n",
       "2        1  Toy Story (1995)  Adventure|Animation|Children|Comedy|Fantasy   \n",
       "3        1  Toy Story (1995)  Adventure|Animation|Children|Comedy|Fantasy   \n",
       "4        1  Toy Story (1995)  Adventure|Animation|Children|Comedy|Fantasy   \n",
       "\n",
       "   userId  rating   timestamp  \n",
       "0       1     4.0   964982703  \n",
       "1       5     4.0   847434962  \n",
       "2       7     4.5  1106635946  \n",
       "3      15     2.5  1510577970  \n",
       "4      17     4.5  1305696483  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Lower_case_converter(title):\n",
    "    return title.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['title'] = df['title'].apply(Lower_case_converter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
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       "      <th>movieId</th>\n",
       "      <th>title</th>\n",
       "      <th>genres</th>\n",
       "      <th>userId</th>\n",
       "      <th>rating</th>\n",
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      ],
      "text/plain": [
       "   movieId             title                                       genres  \\\n",
       "0        1  toy story (1995)  Adventure|Animation|Children|Comedy|Fantasy   \n",
       "1        1  toy story (1995)  Adventure|Animation|Children|Comedy|Fantasy   \n",
       "2        1  toy story (1995)  Adventure|Animation|Children|Comedy|Fantasy   \n",
       "3        1  toy story (1995)  Adventure|Animation|Children|Comedy|Fantasy   \n",
       "4        1  toy story (1995)  Adventure|Animation|Children|Comedy|Fantasy   \n",
       "\n",
       "   userId  rating   timestamp  \n",
       "0       1     4.0   964982703  \n",
       "1       5     4.0   847434962  \n",
       "2       7     4.5  1106635946  \n",
       "3      15     2.5  1510577970  \n",
       "4      17     4.5  1305696483  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['title'] = df['title'].str.replace(r\"\\s*\\(.*\\)\",\"\") #removing year from the front of the movie name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "group = df.groupby('title')['rating'].mean().sort_values(ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title\n",
       "forrest gump                 329\n",
       "shawshank redemption, the    317\n",
       "pulp fiction                 307\n",
       "silence of the lambs, the    279\n",
       "matrix, the                  278\n",
       "                            ... \n",
       "hatchet ii                     1\n",
       "hatchet                        1\n",
       "hatari!                        1\n",
       "harvey girls, the              1\n",
       "à nous la liberté              1\n",
       "Name: rating, Length: 9396, dtype: int64"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('title')['rating'].count().sort_values(ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "Newdf = pd.DataFrame(df.groupby('title')['rating'].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "Newdf['NumOfRating'] = df.groupby('title')['rating'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
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       "      <td>3.666667</td>\n",
       "      <td>42</td>\n",
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       "      <th>'71</th>\n",
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       "    <tr>\n",
       "      <th>'burbs, the</th>\n",
       "      <td>3.176471</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>'hellboy': the seeds of creation</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>'night mother</th>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
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       "      <th>zoom</th>\n",
       "      <td>2.500000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zootopia</th>\n",
       "      <td>3.890625</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zulu</th>\n",
       "      <td>3.500000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>¡three amigos!</th>\n",
       "      <td>3.134615</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>à nous la liberté</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9396 rows × 2 columns</p>\n",
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      ],
      "text/plain": [
       "                                    rating  NumOfRating\n",
       "title                                                  \n",
       "                                  3.666667           42\n",
       "'71                               4.000000            1\n",
       "'burbs, the                       3.176471           17\n",
       "'hellboy': the seeds of creation  4.000000            1\n",
       "'night mother                     3.000000            1\n",
       "...                                    ...          ...\n",
       "zoom                              2.500000            2\n",
       "zootopia                          3.890625           32\n",
       "zulu                              3.500000            5\n",
       "¡three amigos!                    3.134615           26\n",
       "à nous la liberté                 1.000000            1\n",
       "\n",
       "[9396 rows x 2 columns]"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
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    "Newdf"
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  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "Movie_Title = df.pivot_table(index = 'userId', columns = 'title', values = 'rating')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
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       "<p>610 rows × 9396 columns</p>\n",
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      ],
      "text/plain": [
       "title        '71  'burbs, the  'hellboy': the seeds of creation  \\\n",
       "userId                                                            \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",
       "5       NaN  NaN          NaN                               NaN   \n",
       "...     ...  ...          ...                               ...   \n",
       "606     NaN  NaN          NaN                               NaN   \n",
       "607     NaN  NaN          NaN                               NaN   \n",
       "608     NaN  NaN          NaN                               NaN   \n",
       "609     NaN  NaN          NaN                               NaN   \n",
       "610     3.5  4.0          NaN                               NaN   \n",
       "\n",
       "title   'night mother  'round midnight  'salem's lot  'til there was you  \\\n",
       "userId                                                                     \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",
       "5                 NaN              NaN           NaN                 NaN   \n",
       "...               ...              ...           ...                 ...   \n",
       "606               NaN              NaN           NaN                 NaN   \n",
       "607               NaN              NaN           NaN                 NaN   \n",
       "608               NaN              NaN           NaN                 NaN   \n",
       "609               NaN              NaN           NaN                 NaN   \n",
       "610               NaN              NaN           NaN                 NaN   \n",
       "\n",
       "title   'tis the season for love  *batteries not included  ...  zone 39  \\\n",
       "userId                                                     ...            \n",
       "1                            NaN                      NaN  ...      NaN   \n",
       "2                            NaN                      NaN  ...      NaN   \n",
       "3                            NaN                      NaN  ...      NaN   \n",
       "4                            NaN                      NaN  ...      NaN   \n",
       "5                            NaN                      NaN  ...      NaN   \n",
       "...                          ...                      ...  ...      ...   \n",
       "606                          NaN                      NaN  ...      NaN   \n",
       "607                          NaN                      NaN  ...      NaN   \n",
       "608                          NaN                      NaN  ...      NaN   \n",
       "609                          NaN                      NaN  ...      NaN   \n",
       "610                          NaN                      NaN  ...      NaN   \n",
       "\n",
       "title   zone, the  zookeeper  zoolander  zoolander 2  zoom  zootopia  zulu  \\\n",
       "userId                                                                       \n",
       "1             NaN        NaN        NaN          NaN   NaN       NaN   NaN   \n",
       "2             NaN        NaN        NaN          NaN   NaN       NaN   NaN   \n",
       "3             NaN        NaN        NaN          NaN   NaN       NaN   NaN   \n",
       "4             NaN        NaN        NaN          NaN   NaN       NaN   NaN   \n",
       "5             NaN        NaN        NaN          NaN   NaN       NaN   NaN   \n",
       "...           ...        ...        ...          ...   ...       ...   ...   \n",
       "606           NaN        NaN        NaN          NaN   NaN       NaN   NaN   \n",
       "607           NaN        NaN        NaN          NaN   NaN       NaN   NaN   \n",
       "608           NaN        NaN        3.0          NaN   NaN       NaN   NaN   \n",
       "609           NaN        NaN        NaN          NaN   NaN       NaN   NaN   \n",
       "610           NaN        NaN        4.0          NaN   NaN       4.0   NaN   \n",
       "\n",
       "title   ¡three amigos!  à nous la liberté  \n",
       "userId                                     \n",
       "1                  4.0                NaN  \n",
       "2                  NaN                NaN  \n",
       "3                  NaN                NaN  \n",
       "4                  NaN                NaN  \n",
       "5                  NaN                NaN  \n",
       "...                ...                ...  \n",
       "606                NaN                NaN  \n",
       "607                NaN                NaN  \n",
       "608                NaN                NaN  \n",
       "609                NaN                NaN  \n",
       "610                NaN                NaN  \n",
       "\n",
       "[610 rows x 9396 columns]"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Movie_Title"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "userId\n",
       "1      4.0\n",
       "2      NaN\n",
       "3      NaN\n",
       "4      NaN\n",
       "5      4.0\n",
       "      ... \n",
       "606    2.5\n",
       "607    4.0\n",
       "608    2.5\n",
       "609    3.0\n",
       "610    5.0\n",
       "Name: toy story, Length: 610, dtype: float64"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Movie_Title['toy story']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is the main part where the recommended movies are being generated."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Rec():\n",
    "    MovieName = input(\"Enter Movie Name: \").lower()\n",
    "    try:\n",
    "        user_ratings = Movie_Title[MovieName]\n",
    "        similar_movies = Movie_Title.corrwith(user_ratings)\n",
    "        corr_movie = pd.DataFrame(similar_movies, columns = ['Correlation'])\n",
    "        corr_movie.dropna(inplace = True)\n",
    "        corr_movie = corr_movie.join(Newdf['NumOfRating'])\n",
    "        sugg = corr_movie[corr_movie['NumOfRating']>100].sort_values(['Correlation'], ascending = False)\n",
    "        top_5 = sugg[:10].index\n",
    "        print(\"Similar Movies:\")\n",
    "        for i in top_5:\n",
    "            print(i)\n",
    "    except:\n",
    "        print('No suggestions')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter Movie Name: toy story\n",
      "Similar Movies:\n",
      "toy story\n",
      "incredibles, the\n",
      "finding nemo\n",
      "aladdin\n",
      "monsters, inc.\n",
      "mrs. doubtfire\n",
      "amelie\n",
      "american pie\n",
      "die hard: with a vengeance\n",
      "e.t. the extra-terrestrial\n"
     ]
    }
   ],
   "source": [
    "Rec()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " ## Content Based Method\n",
    " In this method, we recommend movies based on the similarity.\n",
    " The movies with the most similar content to the movie entered are being displayed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "Moviedata = pd.read_csv('Datasets/data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4803, 24)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Moviedata.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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       "      <td>Sam Worthington Zoe Saldana Sigourney Weaver S...</td>\n",
       "      <td>[{'name': 'Stephen E. Rivkin', 'gender': 0, 'd...</td>\n",
       "      <td>James Cameron</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\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 trad...</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>...</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>Johnny Depp Orlando Bloom Keira Knightley Stel...</td>\n",
       "      <td>[{'name': 'Dariusz Wolski', 'gender': 2, 'depa...</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>245000000</td>\n",
       "      <td>Action Adventure Crime</td>\n",
       "      <td>http://www.sonypictures.com/movies/spectre/</td>\n",
       "      <td>206647</td>\n",
       "      <td>spy based on novel secret agent sequel mi6</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>...</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>Daniel Craig Christoph Waltz L\\u00e9a Seydoux ...</td>\n",
       "      <td>[{'name': 'Thomas Newman', 'gender': 2, 'depar...</td>\n",
       "      <td>Sam Mendes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>250000000</td>\n",
       "      <td>Action Crime Drama Thriller</td>\n",
       "      <td>http://www.thedarkknightrises.com/</td>\n",
       "      <td>49026</td>\n",
       "      <td>dc comics crime fighter terrorist secret ident...</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>...</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>Christian Bale Michael Caine Gary Oldman Anne ...</td>\n",
       "      <td>[{'name': 'Hans Zimmer', 'gender': 2, 'departm...</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>260000000</td>\n",
       "      <td>Action Adventure Science Fiction</td>\n",
       "      <td>http://movies.disney.com/john-carter</td>\n",
       "      <td>49529</td>\n",
       "      <td>based on novel mars medallion space travel pri...</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>...</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>Taylor Kitsch Lynn Collins Samantha Morton Wil...</td>\n",
       "      <td>[{'name': 'Andrew Stanton', 'gender': 2, 'depa...</td>\n",
       "      <td>Andrew Stanton</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   index     budget                                    genres  \\\n",
       "0      0  237000000  Action Adventure Fantasy Science Fiction   \n",
       "1      1  300000000                  Adventure Fantasy Action   \n",
       "2      2  245000000                    Action Adventure Crime   \n",
       "3      3  250000000               Action Crime Drama Thriller   \n",
       "4      4  260000000          Action Adventure Science Fiction   \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  culture clash future space war space colony so...                en   \n",
       "1  ocean drug abuse exotic island east india trad...                en   \n",
       "2         spy based on novel secret agent sequel mi6                en   \n",
       "3  dc comics crime fighter terrorist secret ident...                en   \n",
       "4  based on novel mars medallion space travel pri...                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  ... runtime  \\\n",
       "0  In the 22nd century, a paraplegic Marine is di...  150.437577  ...   162.0   \n",
       "1  Captain Barbossa, long believed to be dead, ha...  139.082615  ...   169.0   \n",
       "2  A cryptic message from Bond’s past sends him o...  107.376788  ...   148.0   \n",
       "3  Following the death of District Attorney Harve...  112.312950  ...   165.0   \n",
       "4  John Carter is a war-weary, former military ca...   43.926995  ...   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",
       "                                                cast  \\\n",
       "0  Sam Worthington Zoe Saldana Sigourney Weaver S...   \n",
       "1  Johnny Depp Orlando Bloom Keira Knightley Stel...   \n",
       "2  Daniel Craig Christoph Waltz L\\u00e9a Seydoux ...   \n",
       "3  Christian Bale Michael Caine Gary Oldman Anne ...   \n",
       "4  Taylor Kitsch Lynn Collins Samantha Morton Wil...   \n",
       "\n",
       "                                                crew           director  \n",
       "0  [{'name': 'Stephen E. Rivkin', 'gender': 0, 'd...      James Cameron  \n",
       "1  [{'name': 'Dariusz Wolski', 'gender': 2, 'depa...     Gore Verbinski  \n",
       "2  [{'name': 'Thomas Newman', 'gender': 2, 'depar...         Sam Mendes  \n",
       "3  [{'name': 'Hans Zimmer', 'gender': 2, 'departm...  Christopher Nolan  \n",
       "4  [{'name': 'Andrew Stanton', 'gender': 2, 'depa...     Andrew Stanton  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Moviedata.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['index', 'budget', 'genres', 'homepage', 'id', 'keywords',\n",
       "       'original_language', 'original_title', 'overview', 'popularity',\n",
       "       'production_companies', 'production_countries', 'release_date',\n",
       "       'revenue', 'runtime', 'spoken_languages', 'status', 'tagline', 'title',\n",
       "       'vote_average', 'vote_count', 'cast', 'crew', 'director'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Moviedata.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4803 entries, 0 to 4802\n",
      "Data columns (total 24 columns):\n",
      " #   Column                Non-Null Count  Dtype  \n",
      "---  ------                --------------  -----  \n",
      " 0   index                 4803 non-null   int64  \n",
      " 1   budget                4803 non-null   int64  \n",
      " 2   genres                4775 non-null   object \n",
      " 3   homepage              1712 non-null   object \n",
      " 4   id                    4803 non-null   int64  \n",
      " 5   keywords              4391 non-null   object \n",
      " 6   original_language     4803 non-null   object \n",
      " 7   original_title        4803 non-null   object \n",
      " 8   overview              4800 non-null   object \n",
      " 9   popularity            4803 non-null   float64\n",
      " 10  production_companies  4803 non-null   object \n",
      " 11  production_countries  4803 non-null   object \n",
      " 12  release_date          4802 non-null   object \n",
      " 13  revenue               4803 non-null   int64  \n",
      " 14  runtime               4801 non-null   float64\n",
      " 15  spoken_languages      4803 non-null   object \n",
      " 16  status                4803 non-null   object \n",
      " 17  tagline               3959 non-null   object \n",
      " 18  title                 4803 non-null   object \n",
      " 19  vote_average          4803 non-null   float64\n",
      " 20  vote_count            4803 non-null   int64  \n",
      " 21  cast                  4760 non-null   object \n",
      " 22  crew                  4803 non-null   object \n",
      " 23  director              4773 non-null   object \n",
      "dtypes: float64(3), int64(5), object(16)\n",
      "memory usage: 900.7+ KB\n"
     ]
    }
   ],
   "source": [
    "Moviedata.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "features = ['genres', 'keywords', 'cast', 'director']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in features:\n",
    "    Moviedata[i] = Moviedata[i].fillna(\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def CreateContent(row):\n",
    "    content = \"\"\n",
    "    for i in features:\n",
    "        content += row[i]\n",
    "        content += \" \"\n",
    "    return content    \n",
    "\n",
    "def LowerCase(title):\n",
    "    return title.lower()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "Moviedata['original_title'] = Moviedata['original_title'].apply(LowerCase)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "Moviedata['movie_content'] = Moviedata.apply(CreateContent, axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       Action Adventure Fantasy Science Fiction cultu...\n",
       "1       Adventure Fantasy Action ocean drug abuse exot...\n",
       "2       Action Adventure Crime spy based on novel secr...\n",
       "3       Action Crime Drama Thriller dc comics crime fi...\n",
       "4       Action Adventure Science Fiction based on nove...\n",
       "                              ...                        \n",
       "4798    Action Crime Thriller united states\\u2013mexic...\n",
       "4799    Comedy Romance  Edward Burns Kerry Bish\\u00e9 ...\n",
       "4800    Comedy Drama Romance TV Movie date love at fir...\n",
       "4801      Daniel Henney Eliza Coupe Bill Paxton Alan R...\n",
       "4802    Documentary obsession camcorder crush dream gi...\n",
       "Name: movie_content, Length: 4803, dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Moviedata['movie_content']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                                         avatar\n",
       "1       pirates of the caribbean: at world's end\n",
       "2                                        spectre\n",
       "3                          the dark knight rises\n",
       "4                                    john carter\n",
       "                          ...                   \n",
       "4798                                 el mariachi\n",
       "4799                                   newlyweds\n",
       "4800                   signed, sealed, delivered\n",
       "4801                            shanghai calling\n",
       "4802                           my date with drew\n",
       "Name: original_title, Length: 4803, dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Moviedata['original_title']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "cv = CountVectorizer()\n",
    "count = cv.fit_transform(Moviedata['movie_content'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4803, 14845)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count.toarray().shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['11',\n",
       " '15th',\n",
       " '17th',\n",
       " '18th',\n",
       " '1910s',\n",
       " '1917',\n",
       " '1920s',\n",
       " '1930s',\n",
       " '1950s',\n",
       " '1960s',\n",
       " '1970s',\n",
       " '1980s',\n",
       " '1990s',\n",
       " '1992',\n",
       " '1995',\n",
       " '19th',\n",
       " '2001',\n",
       " '2002',\n",
       " '3d',\n",
       " '40',\n",
       " '50',\n",
       " '51',\n",
       " '60s',\n",
       " '66',\n",
       " 'aaliyah',\n",
       " 'aamir',\n",
       " 'aaran',\n",
       " 'aarniokoski',\n",
       " 'aaron',\n",
       " 'aasheekaa',\n",
       " 'aasif',\n",
       " 'abai',\n",
       " 'abandoned',\n",
       " 'abascal',\n",
       " 'abbas',\n",
       " 'abbass',\n",
       " 'abbey',\n",
       " 'abbie',\n",
       " 'abbott',\n",
       " 'abdalla',\n",
       " 'abdoo',\n",
       " 'abduction',\n",
       " 'abdul',\n",
       " 'abdulayev',\n",
       " 'abdullah',\n",
       " 'abe',\n",
       " 'abel',\n",
       " 'abell',\n",
       " 'abercrombie',\n",
       " 'abernathy',\n",
       " 'abhinay',\n",
       " 'abhishek',\n",
       " 'abi',\n",
       " 'abigail',\n",
       " 'abiteboul',\n",
       " 'abkarian',\n",
       " 'able',\n",
       " 'abo',\n",
       " 'abraham',\n",
       " 'abrahams',\n",
       " 'abrahamson',\n",
       " 'abrams',\n",
       " 'abramsohn',\n",
       " 'abroad',\n",
       " 'abu',\n",
       " 'abuse',\n",
       " 'abusive',\n",
       " 'academy',\n",
       " 'accent',\n",
       " 'accepting',\n",
       " 'accident',\n",
       " 'accidental',\n",
       " 'accountant',\n",
       " 'accusal',\n",
       " 'accusations',\n",
       " 'accused',\n",
       " 'ace',\n",
       " 'acharya',\n",
       " 'achrekar',\n",
       " 'acinapura',\n",
       " 'acker',\n",
       " 'ackland',\n",
       " 'ackles',\n",
       " 'ackman',\n",
       " 'acovone',\n",
       " 'acres',\n",
       " 'action',\n",
       " 'activism',\n",
       " 'activist',\n",
       " 'actor',\n",
       " 'actors',\n",
       " 'actress',\n",
       " 'ad',\n",
       " 'ada',\n",
       " 'adam',\n",
       " 'adams',\n",
       " 'adamson',\n",
       " 'adaptation',\n",
       " 'adar',\n",
       " 'addict',\n",
       " 'addicted',\n",
       " 'addiction',\n",
       " 'addison',\n",
       " 'addy',\n",
       " 'adeel',\n",
       " 'adel',\n",
       " 'adelaide',\n",
       " 'adele',\n",
       " 'adelman',\n",
       " 'adelstein',\n",
       " 'adetuyi',\n",
       " 'adewale',\n",
       " 'adil',\n",
       " 'adilah',\n",
       " 'adilet',\n",
       " 'aditya',\n",
       " 'adjani',\n",
       " 'adkins',\n",
       " 'adler',\n",
       " 'adlon',\n",
       " 'admiration',\n",
       " 'admissions',\n",
       " 'adolescence',\n",
       " 'adolf',\n",
       " 'adolfo',\n",
       " 'adolph',\n",
       " 'adolphe',\n",
       " 'adomian',\n",
       " 'adoption',\n",
       " 'adoptive',\n",
       " 'ador',\n",
       " 'adoti',\n",
       " 'adri',\n",
       " 'adrian',\n",
       " 'adriana',\n",
       " 'adrianne',\n",
       " 'adriano',\n",
       " 'adrien',\n",
       " 'adrienne',\n",
       " 'adsit',\n",
       " 'adult',\n",
       " 'adultery',\n",
       " 'advancement',\n",
       " 'advani',\n",
       " 'adventure',\n",
       " 'adversary',\n",
       " 'advertising',\n",
       " 'advice',\n",
       " 'ae',\n",
       " 'aerial',\n",
       " 'aerobics',\n",
       " 'afable',\n",
       " 'affair',\n",
       " 'affairs',\n",
       " 'affection',\n",
       " 'affion',\n",
       " 'affleck',\n",
       " 'afghanistan',\n",
       " 'africa',\n",
       " 'african',\n",
       " 'after',\n",
       " 'aftercreditsstinger',\n",
       " 'afterlife',\n",
       " 'against',\n",
       " 'agapova',\n",
       " 'agar',\n",
       " 'agata',\n",
       " 'agbaje',\n",
       " 'age',\n",
       " 'agee',\n",
       " 'agency',\n",
       " 'agent',\n",
       " 'ages',\n",
       " 'aggeliki',\n",
       " 'aggression',\n",
       " 'aghdashloo',\n",
       " 'aging',\n",
       " 'agnes',\n",
       " 'agnieszka',\n",
       " 'agnihotri',\n",
       " 'agniya',\n",
       " 'agostino',\n",
       " 'agosto',\n",
       " 'agrelo',\n",
       " 'agresti',\n",
       " 'agriculture',\n",
       " 'agrippina',\n",
       " 'agron',\n",
       " 'aguilar',\n",
       " 'aguilera',\n",
       " 'aguirre',\n",
       " 'agust',\n",
       " 'agustin',\n",
       " 'agutter',\n",
       " 'ah',\n",
       " 'ahmad',\n",
       " 'ahmed',\n",
       " 'ahn',\n",
       " 'ahna',\n",
       " 'ahnaise',\n",
       " 'ahney',\n",
       " 'ahr',\n",
       " 'aid',\n",
       " 'aidan',\n",
       " 'aiden',\n",
       " 'aidman',\n",
       " 'aids',\n",
       " 'aiello',\n",
       " 'aierra',\n",
       " 'aiken',\n",
       " 'aimee',\n",
       " 'air',\n",
       " 'aires',\n",
       " 'airlie',\n",
       " 'airplane',\n",
       " 'airport',\n",
       " 'aisha',\n",
       " 'aishwarya',\n",
       " 'aislinn',\n",
       " 'aitana',\n",
       " 'aj',\n",
       " 'aja',\n",
       " 'ajay',\n",
       " 'akar',\n",
       " 'akeel',\n",
       " 'akerstream',\n",
       " 'akhtar',\n",
       " 'aki',\n",
       " 'akihiro',\n",
       " 'akiko',\n",
       " 'akil',\n",
       " 'akin',\n",
       " 'akinnuoye',\n",
       " 'akins',\n",
       " 'akinshina',\n",
       " 'akira',\n",
       " 'akiva',\n",
       " 'akkad',\n",
       " 'akon',\n",
       " 'akosua',\n",
       " 'aksel',\n",
       " 'akshay',\n",
       " 'akshaye',\n",
       " 'akurati',\n",
       " 'al',\n",
       " 'alabama',\n",
       " 'alaimo',\n",
       " 'alain',\n",
       " 'alaistair',\n",
       " 'alakina',\n",
       " 'alamo',\n",
       " 'alamsyah',\n",
       " 'alan',\n",
       " 'alanna',\n",
       " 'alarm',\n",
       " 'alaska',\n",
       " 'alastair',\n",
       " 'alazraqui',\n",
       " 'alba',\n",
       " 'alban',\n",
       " 'albarn',\n",
       " 'albert',\n",
       " 'alberti',\n",
       " 'alberto',\n",
       " 'albertson',\n",
       " 'albrizzi',\n",
       " 'alcarazu',\n",
       " 'alcatraz',\n",
       " 'alch',\n",
       " 'alcohol',\n",
       " 'alcoholic',\n",
       " 'alcoholism',\n",
       " 'alda',\n",
       " 'alden',\n",
       " 'aldis',\n",
       " 'aldo',\n",
       " 'aldrin',\n",
       " 'aleandro',\n",
       " 'alec',\n",
       " 'aleisha',\n",
       " 'alejandro',\n",
       " 'aleksa',\n",
       " 'aleksandr',\n",
       " 'aleksandrova',\n",
       " 'aleksey',\n",
       " 'aleksia',\n",
       " 'aleong',\n",
       " 'ales',\n",
       " 'alessandro',\n",
       " 'alessi',\n",
       " 'alex',\n",
       " 'alexa',\n",
       " 'alexander',\n",
       " 'alexandra',\n",
       " 'alexandre',\n",
       " 'alexandru',\n",
       " 'alexi',\n",
       " 'alexia',\n",
       " 'alexie',\n",
       " 'alexis',\n",
       " 'alexz',\n",
       " 'alf',\n",
       " 'alfano',\n",
       " 'alfie',\n",
       " 'alfonso',\n",
       " 'alford',\n",
       " 'alfre',\n",
       " 'alfred',\n",
       " 'alfredson',\n",
       " 'algar',\n",
       " 'algrant',\n",
       " 'ali',\n",
       " 'alia',\n",
       " 'alianak',\n",
       " 'alibi',\n",
       " 'alice',\n",
       " 'alicia',\n",
       " 'alicja',\n",
       " 'alien',\n",
       " 'alike',\n",
       " 'aliou',\n",
       " 'alisa',\n",
       " 'alisha',\n",
       " 'alison',\n",
       " 'alistair',\n",
       " 'alister',\n",
       " 'alive',\n",
       " 'aliya',\n",
       " 'all',\n",
       " 'alladin',\n",
       " 'allan',\n",
       " 'allcroft',\n",
       " 'allegory',\n",
       " 'allegra',\n",
       " 'allen',\n",
       " 'allergy',\n",
       " 'allers',\n",
       " 'alley',\n",
       " 'allie',\n",
       " 'allied',\n",
       " 'alligator',\n",
       " 'allison',\n",
       " 'allix',\n",
       " 'allman',\n",
       " 'allred',\n",
       " 'ally',\n",
       " 'allyson',\n",
       " 'almani',\n",
       " 'almeida',\n",
       " 'almod',\n",
       " 'almond',\n",
       " 'almonte',\n",
       " 'almstead',\n",
       " 'aloma',\n",
       " 'alon',\n",
       " 'alone',\n",
       " 'alonna',\n",
       " 'alonso',\n",
       " 'alpay',\n",
       " 'alpert',\n",
       " 'alphonso',\n",
       " 'alston',\n",
       " 'altagracia',\n",
       " 'altamura',\n",
       " 'alter',\n",
       " 'alterman',\n",
       " 'alternate',\n",
       " 'alternative',\n",
       " 'altieri',\n",
       " 'altman',\n",
       " 'alun',\n",
       " 'alvarado',\n",
       " 'alvarez',\n",
       " 'alvaro',\n",
       " 'alvart',\n",
       " 'aly',\n",
       " 'alycia',\n",
       " 'alyn',\n",
       " 'alyson',\n",
       " 'alyssa',\n",
       " 'alzheimer',\n",
       " 'am',\n",
       " 'amalric',\n",
       " 'amami',\n",
       " 'amancaya',\n",
       " 'amanda',\n",
       " 'amandes',\n",
       " 'amara',\n",
       " 'amario',\n",
       " 'amaro',\n",
       " 'amaru',\n",
       " 'amat',\n",
       " 'amata',\n",
       " 'amateur',\n",
       " 'amaury',\n",
       " 'amaya',\n",
       " 'amazon',\n",
       " 'ambassador',\n",
       " 'amber',\n",
       " 'ambiguity',\n",
       " 'ambition',\n",
       " 'ambrose',\n",
       " 'ambulance',\n",
       " 'ambush',\n",
       " 'ameche',\n",
       " 'amedori',\n",
       " 'ameen',\n",
       " 'amelia',\n",
       " 'amell',\n",
       " 'amen',\n",
       " 'amendola',\n",
       " 'amer',\n",
       " 'america',\n",
       " 'american',\n",
       " 'ami',\n",
       " 'amidou',\n",
       " 'amie',\n",
       " 'amiel',\n",
       " 'amighetti',\n",
       " 'amila',\n",
       " 'amin',\n",
       " 'amir',\n",
       " 'amish',\n",
       " 'amitabh',\n",
       " 'aml',\n",
       " 'amnesia',\n",
       " 'amore',\n",
       " 'amorim',\n",
       " 'amos',\n",
       " 'amr',\n",
       " 'amrish',\n",
       " 'amrutlal',\n",
       " 'amsterdam',\n",
       " 'amurri',\n",
       " 'amusement',\n",
       " 'amy',\n",
       " 'an',\n",
       " 'ana',\n",
       " 'anaconda',\n",
       " 'analeigh',\n",
       " 'analeine',\n",
       " 'analingus',\n",
       " 'anamaria',\n",
       " 'anand',\n",
       " 'anas',\n",
       " 'anatoli',\n",
       " 'anatoliy',\n",
       " 'anaya',\n",
       " 'ancient',\n",
       " 'and',\n",
       " 'andelin',\n",
       " 'anden',\n",
       " 'anders',\n",
       " 'andersen',\n",
       " 'anderson',\n",
       " 'andersson',\n",
       " 'andie',\n",
       " 'andr',\n",
       " 'andrade',\n",
       " 'andre',\n",
       " 'andrea',\n",
       " 'andreasyan',\n",
       " 'andree',\n",
       " 'andrei',\n",
       " 'andress',\n",
       " 'andrew',\n",
       " 'andrews',\n",
       " 'andrey',\n",
       " 'andrieu',\n",
       " 'android',\n",
       " 'andrucha',\n",
       " 'andrzej',\n",
       " 'andrzejewski',\n",
       " 'andy',\n",
       " 'aneurin',\n",
       " 'anfanger',\n",
       " 'anfone',\n",
       " 'ang',\n",
       " 'angarano',\n",
       " 'angel',\n",
       " 'angela',\n",
       " 'angeles',\n",
       " 'angelica',\n",
       " 'angeliki',\n",
       " 'angelina',\n",
       " 'angelique',\n",
       " 'angell',\n",
       " 'angelo',\n",
       " 'angie',\n",
       " 'angkor',\n",
       " 'anglade',\n",
       " 'angourie',\n",
       " 'angst',\n",
       " 'angulo',\n",
       " 'angus',\n",
       " 'anh',\n",
       " 'ania',\n",
       " 'anika',\n",
       " 'anil',\n",
       " 'animal',\n",
       " 'animals',\n",
       " 'animated',\n",
       " 'animation',\n",
       " 'aniston',\n",
       " 'anita',\n",
       " 'anjelica',\n",
       " 'anjul',\n",
       " 'anka',\n",
       " 'ankle',\n",
       " 'anmol',\n",
       " 'ann',\n",
       " 'anna',\n",
       " 'annabel',\n",
       " 'annabella',\n",
       " 'annabelle',\n",
       " 'annabeth',\n",
       " 'annable',\n",
       " 'annalee',\n",
       " 'annasophia',\n",
       " 'annaud',\n",
       " 'anne',\n",
       " 'annedore',\n",
       " 'annelyse',\n",
       " 'annette',\n",
       " 'annie',\n",
       " 'annika',\n",
       " 'annis',\n",
       " 'anniversary',\n",
       " 'anno',\n",
       " 'anonymity',\n",
       " 'anonymous',\n",
       " 'another',\n",
       " 'ansah',\n",
       " 'ansari',\n",
       " 'ansel',\n",
       " 'anson',\n",
       " 'anspaugh',\n",
       " 'answering',\n",
       " 'ant',\n",
       " 'antal',\n",
       " 'antarctic',\n",
       " 'antarctica',\n",
       " 'anthology',\n",
       " 'anthony',\n",
       " 'anthropomorphism',\n",
       " 'anti',\n",
       " 'antin',\n",
       " 'antiquary',\n",
       " 'antje',\n",
       " 'antoine',\n",
       " 'anton',\n",
       " 'antonia',\n",
       " 'antonio',\n",
       " 'antony',\n",
       " 'anupam',\n",
       " 'anurag',\n",
       " 'anushka',\n",
       " 'anvar',\n",
       " 'anwar',\n",
       " 'anya',\n",
       " 'aoi',\n",
       " 'aoki',\n",
       " 'aouad',\n",
       " 'apache',\n",
       " 'apartheid',\n",
       " 'apatow',\n",
       " 'ape',\n",
       " 'apocalypse',\n",
       " 'apocalyptic',\n",
       " 'apostle',\n",
       " 'appalachia',\n",
       " 'appearance',\n",
       " 'apple',\n",
       " 'appleby',\n",
       " 'applegate',\n",
       " 'appleman',\n",
       " 'apprentice',\n",
       " 'approach',\n",
       " 'approved',\n",
       " 'apted',\n",
       " 'aquarium',\n",
       " 'aquino',\n",
       " 'arab',\n",
       " 'arabella',\n",
       " 'arabia',\n",
       " 'arabian',\n",
       " 'arag',\n",
       " 'aramaki',\n",
       " 'aranoa',\n",
       " 'arata',\n",
       " 'araujo',\n",
       " 'arbanville',\n",
       " 'arbitrary',\n",
       " 'arby',\n",
       " 'arcade',\n",
       " 'arcand',\n",
       " 'arcelia',\n",
       " 'archaeologist',\n",
       " 'archangel',\n",
       " 'archeology',\n",
       " 'archer',\n",
       " 'archibald',\n",
       " 'archie',\n",
       " 'architect',\n",
       " 'architecture',\n",
       " 'archive',\n",
       " 'arcieri',\n",
       " 'arctic',\n",
       " 'arcy',\n",
       " 'ardant',\n",
       " 'arden',\n",
       " 'arditi',\n",
       " 'ardolino',\n",
       " 'ardova',\n",
       " 'area',\n",
       " 'arena',\n",
       " 'arend',\n",
       " 'arestrup',\n",
       " 'arfi',\n",
       " 'argentina',\n",
       " 'argentine',\n",
       " 'argento',\n",
       " 'argo',\n",
       " 'argos',\n",
       " 'argument',\n",
       " 'ari',\n",
       " 'ariadna',\n",
       " 'ariana',\n",
       " 'arianda',\n",
       " 'arias',\n",
       " 'arie',\n",
       " 'ariel',\n",
       " 'arielle',\n",
       " 'arienzo',\n",
       " 'arif',\n",
       " 'arifin',\n",
       " 'arija',\n",
       " 'aristocrat',\n",
       " 'aristotle',\n",
       " 'ariza',\n",
       " 'arizona',\n",
       " 'arjun',\n",
       " 'ark',\n",
       " 'arkansas',\n",
       " 'arkin',\n",
       " 'arkush',\n",
       " 'arletty',\n",
       " 'arliss',\n",
       " 'arlo',\n",
       " 'arlook',\n",
       " 'arly',\n",
       " 'arm',\n",
       " 'armageddon',\n",
       " 'armand',\n",
       " 'armando',\n",
       " 'armed',\n",
       " 'armend',\n",
       " 'armie',\n",
       " 'armin',\n",
       " 'armisen',\n",
       " 'armitage',\n",
       " 'armored',\n",
       " 'arms',\n",
       " 'armstrong',\n",
       " 'army',\n",
       " 'arnaz',\n",
       " 'arndt',\n",
       " 'arne',\n",
       " 'arnett',\n",
       " 'arnette',\n",
       " 'arnezeder',\n",
       " 'arnie',\n",
       " 'arnold',\n",
       " 'arntz',\n",
       " 'aronofsky',\n",
       " 'around',\n",
       " 'arquette',\n",
       " 'arranged',\n",
       " 'arrest',\n",
       " 'arrindell',\n",
       " 'arrogance',\n",
       " 'arrow',\n",
       " 'arru',\n",
       " 'arshad',\n",
       " 'arsher',\n",
       " 'arsin',\n",
       " 'arson',\n",
       " 'art',\n",
       " 'artell',\n",
       " 'artem',\n",
       " 'artemeva',\n",
       " 'arterton',\n",
       " 'arteta',\n",
       " 'arthouse',\n",
       " 'arthur',\n",
       " 'artial',\n",
       " 'article',\n",
       " 'artie',\n",
       " 'artifact',\n",
       " 'artificial',\n",
       " 'artist',\n",
       " 'arts',\n",
       " 'artura',\n",
       " 'arturo',\n",
       " 'artyom',\n",
       " 'arundathi',\n",
       " 'aryana',\n",
       " 'arzamasova',\n",
       " 'as',\n",
       " 'asa',\n",
       " 'asano',\n",
       " 'asaro',\n",
       " 'asbury',\n",
       " 'asefa',\n",
       " 'aselton',\n",
       " 'asger',\n",
       " 'asghar',\n",
       " 'ash',\n",
       " 'ashanti',\n",
       " 'ashbrook',\n",
       " 'ashby',\n",
       " 'ashcroft',\n",
       " 'ashfield',\n",
       " 'ashish',\n",
       " 'ashleigh',\n",
       " 'ashley',\n",
       " 'ashlyn',\n",
       " 'ashmore',\n",
       " 'ashour',\n",
       " 'ashraf',\n",
       " 'ashton',\n",
       " 'asia',\n",
       " 'asian',\n",
       " 'asim',\n",
       " 'asin',\n",
       " 'askew',\n",
       " 'asner',\n",
       " 'aspen',\n",
       " 'asperger',\n",
       " 'aspinall',\n",
       " 'aspiring',\n",
       " 'assante',\n",
       " 'assassin',\n",
       " 'assassination',\n",
       " 'assault',\n",
       " 'assayas',\n",
       " 'assertion',\n",
       " 'assignment',\n",
       " 'assistant',\n",
       " 'astaire',\n",
       " 'asteroid',\n",
       " 'astin',\n",
       " 'aston',\n",
       " 'astor',\n",
       " 'astrid',\n",
       " 'astro',\n",
       " 'astronaut',\n",
       " 'asylum',\n",
       " 'at',\n",
       " 'atchison',\n",
       " 'atencio',\n",
       " 'atherton',\n",
       " 'athlete',\n",
       " 'atias',\n",
       " 'atis',\n",
       " 'atkin',\n",
       " 'atkins',\n",
       " 'atkinson',\n",
       " 'atlanta',\n",
       " 'atlantic',\n",
       " 'atlantis',\n",
       " 'ato',\n",
       " 'atom',\n",
       " 'atomic',\n",
       " 'atossa',\n",
       " 'attachment',\n",
       " 'attack',\n",
       " 'attal',\n",
       " 'attempt',\n",
       " 'attempted',\n",
       " 'attenborough',\n",
       " 'attic',\n",
       " 'atticus',\n",
       " 'attieh',\n",
       " 'attila',\n",
       " 'attract',\n",
       " 'atwell',\n",
       " 'aubert',\n",
       " 'aubier',\n",
       " 'aubrey',\n",
       " 'auburtin',\n",
       " 'auction',\n",
       " 'auctioneer',\n",
       " 'audi',\n",
       " 'audience',\n",
       " 'audio',\n",
       " 'audition',\n",
       " 'audrey',\n",
       " 'auer',\n",
       " 'auerbach',\n",
       " 'auffarth',\n",
       " 'auger',\n",
       " 'august',\n",
       " 'augusto',\n",
       " 'augustus',\n",
       " 'aumont',\n",
       " 'aundre',\n",
       " 'aune',\n",
       " 'aunjanue',\n",
       " 'aunt',\n",
       " 'auria',\n",
       " 'ausilia',\n",
       " 'austen',\n",
       " 'austin',\n",
       " 'australia',\n",
       " 'australian',\n",
       " 'austria',\n",
       " 'auteuil',\n",
       " 'author',\n",
       " 'authoritarian',\n",
       " 'authority',\n",
       " 'autism',\n",
       " 'auto',\n",
       " 'autobiographical',\n",
       " 'autobiography',\n",
       " 'autocide',\n",
       " 'autograph',\n",
       " 'automobile',\n",
       " 'autonomy',\n",
       " 'autoritian',\n",
       " 'autumn',\n",
       " 'ava',\n",
       " 'avary',\n",
       " 'avery',\n",
       " 'avi',\n",
       " 'aviation',\n",
       " 'avildsen',\n",
       " 'aviles',\n",
       " 'avis',\n",
       " 'avnet',\n",
       " 'avraham',\n",
       " 'award',\n",
       " 'awards',\n",
       " 'awareness',\n",
       " 'awol',\n",
       " 'ax',\n",
       " 'axe',\n",
       " 'axel',\n",
       " 'axton',\n",
       " 'ayala',\n",
       " 'ayalon',\n",
       " 'ayan',\n",
       " 'ayanat',\n",
       " 'ayano',\n",
       " 'ayelet',\n",
       " 'ayer',\n",
       " 'ayesha',\n",
       " 'aykroyd',\n",
       " 'aylesworth',\n",
       " 'aymen',\n",
       " 'ayn',\n",
       " 'ayoade',\n",
       " 'ayush',\n",
       " 'az',\n",
       " 'azabal',\n",
       " 'azami',\n",
       " 'azaria',\n",
       " 'aziz',\n",
       " 'azmi',\n",
       " 'aznavour',\n",
       " 'aztec',\n",
       " 'azuelos',\n",
       " 'azur',\n",
       " 'azura',\n",
       " 'ba',\n",
       " 'baba',\n",
       " 'babak',\n",
       " 'babar',\n",
       " 'babatund',\n",
       " 'babbar',\n",
       " 'babbit',\n",
       " 'babes',\n",
       " 'baboon',\n",
       " 'babou',\n",
       " 'baby',\n",
       " 'babysitter',\n",
       " 'bacall',\n",
       " 'baccarin',\n",
       " 'bach',\n",
       " 'bachar',\n",
       " 'bachchan',\n",
       " 'bache',\n",
       " 'bachelor',\n",
       " 'bachleda',\n",
       " 'bachman',\n",
       " 'bachrach',\n",
       " 'bacic',\n",
       " 'backer',\n",
       " 'background',\n",
       " 'backpacker',\n",
       " 'bacon',\n",
       " 'bad',\n",
       " 'badberg',\n",
       " 'baddeley',\n",
       " 'bader',\n",
       " 'badge',\n",
       " 'badger',\n",
       " 'badgley',\n",
       " 'badham',\n",
       " 'badland',\n",
       " 'badreya',\n",
       " 'badu',\n",
       " 'bae',\n",
       " 'baer',\n",
       " 'baez',\n",
       " 'baeza',\n",
       " 'bag',\n",
       " 'baganov',\n",
       " 'bagby',\n",
       " 'bagdad',\n",
       " 'baghdad',\n",
       " 'bagley',\n",
       " 'baglio',\n",
       " 'bagneris',\n",
       " 'bahamas',\n",
       " 'bahar',\n",
       " 'bahare',\n",
       " 'bahns',\n",
       " 'bahr',\n",
       " 'bai',\n",
       " 'bail',\n",
       " 'bailee',\n",
       " 'bailey',\n",
       " 'baio',\n",
       " 'baird',\n",
       " 'bairley',\n",
       " 'bairstow',\n",
       " 'bajrangi',\n",
       " 'bakaitis',\n",
       " 'baker',\n",
       " 'bakery',\n",
       " 'bakke',\n",
       " 'bakula',\n",
       " 'balaban',\n",
       " 'balaguer',\n",
       " 'balan',\n",
       " 'balance',\n",
       " 'balaski',\n",
       " 'balda',\n",
       " 'baldry',\n",
       " 'baldwin',\n",
       " 'bale',\n",
       " 'bales',\n",
       " 'balfe',\n",
       " 'balfour',\n",
       " 'bali',\n",
       " 'balibar',\n",
       " 'balin',\n",
       " 'balk',\n",
       " 'balkan',\n",
       " 'ball',\n",
       " 'ballantyne',\n",
       " 'ballard',\n",
       " 'ballet',\n",
       " 'balloon',\n",
       " 'ballroom',\n",
       " 'balmer',\n",
       " 'balsam',\n",
       " 'baltasar',\n",
       " 'balthazar',\n",
       " 'baltimore',\n",
       " 'balzen',\n",
       " 'bam',\n",
       " 'ban',\n",
       " 'bana',\n",
       " 'bancroft',\n",
       " 'band',\n",
       " 'bandana',\n",
       " 'banderas',\n",
       " 'bandiero',\n",
       " 'bandit',\n",
       " 'bands',\n",
       " 'banerjee',\n",
       " 'bang',\n",
       " 'bangkok',\n",
       " 'bangladesh',\n",
       " 'banionis',\n",
       " 'banishment',\n",
       " 'bank',\n",
       " 'banker',\n",
       " 'bankes',\n",
       " 'bankol',\n",
       " 'bankrupt',\n",
       " 'banks',\n",
       " 'bannen',\n",
       " 'banner',\n",
       " 'bannister',\n",
       " 'bannon',\n",
       " 'baoqiang',\n",
       " 'baptiste',\n",
       " ...]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cv.get_feature_names()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "row_similarity = cosine_similarity(count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.        , 0.10540926, 0.12038585, ..., 0.        , 0.        ,\n",
       "        0.        ],\n",
       "       [0.10540926, 1.        , 0.0761387 , ..., 0.03651484, 0.        ,\n",
       "        0.        ],\n",
       "       [0.12038585, 0.0761387 , 1.        , ..., 0.        , 0.11145564,\n",
       "        0.        ],\n",
       "       ...,\n",
       "       [0.        , 0.03651484, 0.        , ..., 1.        , 0.        ,\n",
       "        0.04264014],\n",
       "       [0.        , 0.        , 0.11145564, ..., 0.        , 1.        ,\n",
       "        0.        ],\n",
       "       [0.        , 0.        , 0.        , ..., 0.04264014, 0.        ,\n",
       "        1.        ]])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "row_similarity"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The part where the movies to be recommended are selected and displayed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ContentBasedRecomm():\n",
    "    movie_name = input(\"Enter the movie name: \").lower()\n",
    "    try:\n",
    "        m_index = Moviedata[Moviedata['original_title'] == movie_name]['index'].values[0]\n",
    "        similar_word_value = row_similarity[m_index]\n",
    "        pairing_value = list(enumerate(similar_word_value))\n",
    "        similar_movie = sorted(pairing_value, key = lambda x:x[1], reverse = True)\n",
    "        num = 5\n",
    "        print(\"Top 5 Similar Movies..\")\n",
    "        for i in range(num):\n",
    "            index = similar_movie[i][0]\n",
    "            movie = Moviedata[index:index+1]['original_title'].values[0]\n",
    "            print(i+1, movie)    \n",
    "    except IndexError:\n",
    "        print(\"No suggestions..\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter the movie name: spectre\n",
      "Top 5 Similar Movies..\n",
      "1 spectre\n",
      "2 skyfall\n",
      "3 quantum of solace\n",
      "4 the girl with the dragon tattoo\n",
      "5 the hunger games: catching fire\n"
     ]
    }
   ],
   "source": [
    "ContentBasedRecomm()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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