Main.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "17a748ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "777d8c00",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies = pd.read_csv('dataset.csv')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "b3ec45d5",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>genre</th>\n",
       "      <th>original_language</th>\n",
       "      <th>overview</th>\n",
       "      <th>popularity</th>\n",
       "      <th>release_date</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>278</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>Drama,Crime</td>\n",
       "      <td>en</td>\n",
       "      <td>Framed in the 1940s for the double murder of h...</td>\n",
       "      <td>94.075</td>\n",
       "      <td>1994-09-23</td>\n",
       "      <td>8.7</td>\n",
       "      <td>21862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19404</td>\n",
       "      <td>Dilwale Dulhania Le Jayenge</td>\n",
       "      <td>Comedy,Drama,Romance</td>\n",
       "      <td>hi</td>\n",
       "      <td>Raj is a rich, carefree, happy-go-lucky second...</td>\n",
       "      <td>25.408</td>\n",
       "      <td>1995-10-19</td>\n",
       "      <td>8.7</td>\n",
       "      <td>3731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>238</td>\n",
       "      <td>The Godfather</td>\n",
       "      <td>Drama,Crime</td>\n",
       "      <td>en</td>\n",
       "      <td>Spanning the years 1945 to 1955, a chronicle o...</td>\n",
       "      <td>90.585</td>\n",
       "      <td>1972-03-14</td>\n",
       "      <td>8.7</td>\n",
       "      <td>16280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>424</td>\n",
       "      <td>Schindler's List</td>\n",
       "      <td>Drama,History,War</td>\n",
       "      <td>en</td>\n",
       "      <td>The true story of how businessman Oskar Schind...</td>\n",
       "      <td>44.761</td>\n",
       "      <td>1993-12-15</td>\n",
       "      <td>8.6</td>\n",
       "      <td>12959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>240</td>\n",
       "      <td>The Godfather: Part II</td>\n",
       "      <td>Drama,Crime</td>\n",
       "      <td>en</td>\n",
       "      <td>In the continuing saga of the Corleone crime f...</td>\n",
       "      <td>57.749</td>\n",
       "      <td>1974-12-20</td>\n",
       "      <td>8.6</td>\n",
       "      <td>9811</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "      id                        title                 genre original_language  \\\n",
       "0    278     The Shawshank Redemption           Drama,Crime                en   \n",
       "1  19404  Dilwale Dulhania Le Jayenge  Comedy,Drama,Romance                hi   \n",
       "2    238                The Godfather           Drama,Crime                en   \n",
       "3    424             Schindler's List     Drama,History,War                en   \n",
       "4    240       The Godfather: Part II           Drama,Crime                en   \n",
       "\n",
       "                                            overview  popularity release_date  \\\n",
       "0  Framed in the 1940s for the double murder of h...      94.075   1994-09-23   \n",
       "1  Raj is a rich, carefree, happy-go-lucky second...      25.408   1995-10-19   \n",
       "2  Spanning the years 1945 to 1955, a chronicle o...      90.585   1972-03-14   \n",
       "3  The true story of how businessman Oskar Schind...      44.761   1993-12-15   \n",
       "4  In the continuing saga of the Corleone crime f...      57.749   1974-12-20   \n",
       "\n",
       "   vote_average  vote_count  \n",
       "0           8.7       21862  \n",
       "1           8.7        3731  \n",
       "2           8.7       16280  \n",
       "3           8.6       12959  \n",
       "4           8.6        9811  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "f04a6236",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>popularity</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>10000.000000</td>\n",
       "      <td>10000.000000</td>\n",
       "      <td>10000.000000</td>\n",
       "      <td>10000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>161243.505000</td>\n",
       "      <td>34.697267</td>\n",
       "      <td>6.621150</td>\n",
       "      <td>1547.309400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>211422.046043</td>\n",
       "      <td>211.684175</td>\n",
       "      <td>0.766231</td>\n",
       "      <td>2648.295789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>4.600000</td>\n",
       "      <td>200.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>10127.750000</td>\n",
       "      <td>9.154750</td>\n",
       "      <td>6.100000</td>\n",
       "      <td>315.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>30002.500000</td>\n",
       "      <td>13.637500</td>\n",
       "      <td>6.600000</td>\n",
       "      <td>583.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>310133.500000</td>\n",
       "      <td>25.651250</td>\n",
       "      <td>7.200000</td>\n",
       "      <td>1460.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>934761.000000</td>\n",
       "      <td>10436.917000</td>\n",
       "      <td>8.700000</td>\n",
       "      <td>31917.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                  id    popularity  vote_average    vote_count\n",
       "count   10000.000000  10000.000000  10000.000000  10000.000000\n",
       "mean   161243.505000     34.697267      6.621150   1547.309400\n",
       "std    211422.046043    211.684175      0.766231   2648.295789\n",
       "min         5.000000      0.600000      4.600000    200.000000\n",
       "25%     10127.750000      9.154750      6.100000    315.000000\n",
       "50%     30002.500000     13.637500      6.600000    583.500000\n",
       "75%    310133.500000     25.651250      7.200000   1460.000000\n",
       "max    934761.000000  10436.917000      8.700000  31917.000000"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.describe()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "df9c78cf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 10000 entries, 0 to 9999\n",
      "Data columns (total 9 columns):\n",
      " #   Column             Non-Null Count  Dtype  \n",
      "---  ------             --------------  -----  \n",
      " 0   id                 10000 non-null  int64  \n",
      " 1   title              10000 non-null  object \n",
      " 2   genre              9997 non-null   object \n",
      " 3   original_language  10000 non-null  object \n",
      " 4   overview           9987 non-null   object \n",
      " 5   popularity         10000 non-null  float64\n",
      " 6   release_date       10000 non-null  object \n",
      " 7   vote_average       10000 non-null  float64\n",
      " 8   vote_count         10000 non-null  int64  \n",
      "dtypes: float64(2), int64(2), object(5)\n",
      "memory usage: 703.3+ KB\n"
     ]
    }
   ],
   "source": [
    "movies.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "1024b33e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                    0\n",
       "title                 0\n",
       "genre                 3\n",
       "original_language     0\n",
       "overview             13\n",
       "popularity            0\n",
       "release_date          0\n",
       "vote_average          0\n",
       "vote_count            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b548b337",
   "metadata": {},
   "source": [
    "Feature Selection Part"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "780e2cea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'title', 'genre', 'original_language', 'overview', 'popularity',\n",
       "       'release_date', 'vote_average', 'vote_count'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "2f60532f",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies = movies[['id', 'title', 'overview', 'genre']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "a7042fd8",
   "metadata": {},
   "outputs": [
    {
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       "      <th>0</th>\n",
       "      <td>278</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>Framed in the 1940s for the double murder of h...</td>\n",
       "      <td>Drama,Crime</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19404</td>\n",
       "      <td>Dilwale Dulhania Le Jayenge</td>\n",
       "      <td>Raj is a rich, carefree, happy-go-lucky second...</td>\n",
       "      <td>Comedy,Drama,Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>238</td>\n",
       "      <td>The Godfather</td>\n",
       "      <td>Spanning the years 1945 to 1955, a chronicle o...</td>\n",
       "      <td>Drama,Crime</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>424</td>\n",
       "      <td>Schindler's List</td>\n",
       "      <td>The true story of how businessman Oskar Schind...</td>\n",
       "      <td>Drama,History,War</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>240</td>\n",
       "      <td>The Godfather: Part II</td>\n",
       "      <td>In the continuing saga of the Corleone crime f...</td>\n",
       "      <td>Drama,Crime</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9995</th>\n",
       "      <td>10196</td>\n",
       "      <td>The Last Airbender</td>\n",
       "      <td>The story follows the adventures of Aang, a yo...</td>\n",
       "      <td>Action,Adventure,Fantasy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9996</th>\n",
       "      <td>331446</td>\n",
       "      <td>Sharknado 3: Oh Hell No!</td>\n",
       "      <td>The sharks take bite out of the East Coast whe...</td>\n",
       "      <td>Action,TV Movie,Science Fiction,Comedy,Adventure</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9997</th>\n",
       "      <td>13995</td>\n",
       "      <td>Captain America</td>\n",
       "      <td>During World War II, a brave, patriotic Americ...</td>\n",
       "      <td>Action,Science Fiction,War</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9998</th>\n",
       "      <td>2312</td>\n",
       "      <td>In the Name of the King: A Dungeon Siege Tale</td>\n",
       "      <td>A man named Farmer sets out to rescue his kidn...</td>\n",
       "      <td>Adventure,Fantasy,Action,Drama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9999</th>\n",
       "      <td>455957</td>\n",
       "      <td>Domino</td>\n",
       "      <td>Seeking justice for his partner’s murder by an...</td>\n",
       "      <td>Thriller,Action,Crime</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10000 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id                                          title  \\\n",
       "0        278                       The Shawshank Redemption   \n",
       "1      19404                    Dilwale Dulhania Le Jayenge   \n",
       "2        238                                  The Godfather   \n",
       "3        424                               Schindler's List   \n",
       "4        240                         The Godfather: Part II   \n",
       "...      ...                                            ...   \n",
       "9995   10196                             The Last Airbender   \n",
       "9996  331446                       Sharknado 3: Oh Hell No!   \n",
       "9997   13995                                Captain America   \n",
       "9998    2312  In the Name of the King: A Dungeon Siege Tale   \n",
       "9999  455957                                         Domino   \n",
       "\n",
       "                                               overview  \\\n",
       "0     Framed in the 1940s for the double murder of h...   \n",
       "1     Raj is a rich, carefree, happy-go-lucky second...   \n",
       "2     Spanning the years 1945 to 1955, a chronicle o...   \n",
       "3     The true story of how businessman Oskar Schind...   \n",
       "4     In the continuing saga of the Corleone crime f...   \n",
       "...                                                 ...   \n",
       "9995  The story follows the adventures of Aang, a yo...   \n",
       "9996  The sharks take bite out of the East Coast whe...   \n",
       "9997  During World War II, a brave, patriotic Americ...   \n",
       "9998  A man named Farmer sets out to rescue his kidn...   \n",
       "9999  Seeking justice for his partner’s murder by an...   \n",
       "\n",
       "                                                 genre  \n",
       "0                                          Drama,Crime  \n",
       "1                                 Comedy,Drama,Romance  \n",
       "2                                          Drama,Crime  \n",
       "3                                    Drama,History,War  \n",
       "4                                          Drama,Crime  \n",
       "...                                                ...  \n",
       "9995                          Action,Adventure,Fantasy  \n",
       "9996  Action,TV Movie,Science Fiction,Comedy,Adventure  \n",
       "9997                        Action,Science Fiction,War  \n",
       "9998                    Adventure,Fantasy,Action,Drama  \n",
       "9999                             Thriller,Action,Crime  \n",
       "\n",
       "[10000 rows x 4 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "84721153",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies['tags'] = movies['overview']+movies['genre']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "f573cad4",
   "metadata": {},
   "outputs": [
    {
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       "      <th>0</th>\n",
       "      <td>278</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>Framed in the 1940s for the double murder of h...</td>\n",
       "      <td>Drama,Crime</td>\n",
       "      <td>Framed in the 1940s for the double murder of h...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19404</td>\n",
       "      <td>Dilwale Dulhania Le Jayenge</td>\n",
       "      <td>Raj is a rich, carefree, happy-go-lucky second...</td>\n",
       "      <td>Comedy,Drama,Romance</td>\n",
       "      <td>Raj is a rich, carefree, happy-go-lucky second...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>238</td>\n",
       "      <td>The Godfather</td>\n",
       "      <td>Spanning the years 1945 to 1955, a chronicle o...</td>\n",
       "      <td>Drama,Crime</td>\n",
       "      <td>Spanning the years 1945 to 1955, a chronicle o...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>424</td>\n",
       "      <td>Schindler's List</td>\n",
       "      <td>The true story of how businessman Oskar Schind...</td>\n",
       "      <td>Drama,History,War</td>\n",
       "      <td>The true story of how businessman Oskar Schind...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>240</td>\n",
       "      <td>The Godfather: Part II</td>\n",
       "      <td>In the continuing saga of the Corleone crime f...</td>\n",
       "      <td>Drama,Crime</td>\n",
       "      <td>In the continuing saga of the Corleone crime f...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9995</th>\n",
       "      <td>10196</td>\n",
       "      <td>The Last Airbender</td>\n",
       "      <td>The story follows the adventures of Aang, a yo...</td>\n",
       "      <td>Action,Adventure,Fantasy</td>\n",
       "      <td>The story follows the adventures of Aang, a yo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9996</th>\n",
       "      <td>331446</td>\n",
       "      <td>Sharknado 3: Oh Hell No!</td>\n",
       "      <td>The sharks take bite out of the East Coast whe...</td>\n",
       "      <td>Action,TV Movie,Science Fiction,Comedy,Adventure</td>\n",
       "      <td>The sharks take bite out of the East Coast whe...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9997</th>\n",
       "      <td>13995</td>\n",
       "      <td>Captain America</td>\n",
       "      <td>During World War II, a brave, patriotic Americ...</td>\n",
       "      <td>Action,Science Fiction,War</td>\n",
       "      <td>During World War II, a brave, patriotic Americ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9998</th>\n",
       "      <td>2312</td>\n",
       "      <td>In the Name of the King: A Dungeon Siege Tale</td>\n",
       "      <td>A man named Farmer sets out to rescue his kidn...</td>\n",
       "      <td>Adventure,Fantasy,Action,Drama</td>\n",
       "      <td>A man named Farmer sets out to rescue his kidn...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9999</th>\n",
       "      <td>455957</td>\n",
       "      <td>Domino</td>\n",
       "      <td>Seeking justice for his partner’s murder by an...</td>\n",
       "      <td>Thriller,Action,Crime</td>\n",
       "      <td>Seeking justice for his partner’s murder by an...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10000 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id                                          title  \\\n",
       "0        278                       The Shawshank Redemption   \n",
       "1      19404                    Dilwale Dulhania Le Jayenge   \n",
       "2        238                                  The Godfather   \n",
       "3        424                               Schindler's List   \n",
       "4        240                         The Godfather: Part II   \n",
       "...      ...                                            ...   \n",
       "9995   10196                             The Last Airbender   \n",
       "9996  331446                       Sharknado 3: Oh Hell No!   \n",
       "9997   13995                                Captain America   \n",
       "9998    2312  In the Name of the King: A Dungeon Siege Tale   \n",
       "9999  455957                                         Domino   \n",
       "\n",
       "                                               overview  \\\n",
       "0     Framed in the 1940s for the double murder of h...   \n",
       "1     Raj is a rich, carefree, happy-go-lucky second...   \n",
       "2     Spanning the years 1945 to 1955, a chronicle o...   \n",
       "3     The true story of how businessman Oskar Schind...   \n",
       "4     In the continuing saga of the Corleone crime f...   \n",
       "...                                                 ...   \n",
       "9995  The story follows the adventures of Aang, a yo...   \n",
       "9996  The sharks take bite out of the East Coast whe...   \n",
       "9997  During World War II, a brave, patriotic Americ...   \n",
       "9998  A man named Farmer sets out to rescue his kidn...   \n",
       "9999  Seeking justice for his partner’s murder by an...   \n",
       "\n",
       "                                                 genre  \\\n",
       "0                                          Drama,Crime   \n",
       "1                                 Comedy,Drama,Romance   \n",
       "2                                          Drama,Crime   \n",
       "3                                    Drama,History,War   \n",
       "4                                          Drama,Crime   \n",
       "...                                                ...   \n",
       "9995                          Action,Adventure,Fantasy   \n",
       "9996  Action,TV Movie,Science Fiction,Comedy,Adventure   \n",
       "9997                        Action,Science Fiction,War   \n",
       "9998                    Adventure,Fantasy,Action,Drama   \n",
       "9999                             Thriller,Action,Crime   \n",
       "\n",
       "                                                   tags  \n",
       "0     Framed in the 1940s for the double murder of h...  \n",
       "1     Raj is a rich, carefree, happy-go-lucky second...  \n",
       "2     Spanning the years 1945 to 1955, a chronicle o...  \n",
       "3     The true story of how businessman Oskar Schind...  \n",
       "4     In the continuing saga of the Corleone crime f...  \n",
       "...                                                 ...  \n",
       "9995  The story follows the adventures of Aang, a yo...  \n",
       "9996  The sharks take bite out of the East Coast whe...  \n",
       "9997  During World War II, a brave, patriotic Americ...  \n",
       "9998  A man named Farmer sets out to rescue his kidn...  \n",
       "9999  Seeking justice for his partner’s murder by an...  \n",
       "\n",
       "[10000 rows x 5 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "33b9f6a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_data = movies.drop(columns = ['overview', 'genre'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "5dfdef72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>tags</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>278</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>Framed in the 1940s for the double murder of h...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19404</td>\n",
       "      <td>Dilwale Dulhania Le Jayenge</td>\n",
       "      <td>Raj is a rich, carefree, happy-go-lucky second...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>238</td>\n",
       "      <td>The Godfather</td>\n",
       "      <td>Spanning the years 1945 to 1955, a chronicle o...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>424</td>\n",
       "      <td>Schindler's List</td>\n",
       "      <td>The true story of how businessman Oskar Schind...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>240</td>\n",
       "      <td>The Godfather: Part II</td>\n",
       "      <td>In the continuing saga of the Corleone crime f...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9995</th>\n",
       "      <td>10196</td>\n",
       "      <td>The Last Airbender</td>\n",
       "      <td>The story follows the adventures of Aang, a yo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9996</th>\n",
       "      <td>331446</td>\n",
       "      <td>Sharknado 3: Oh Hell No!</td>\n",
       "      <td>The sharks take bite out of the East Coast whe...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9997</th>\n",
       "      <td>13995</td>\n",
       "      <td>Captain America</td>\n",
       "      <td>During World War II, a brave, patriotic Americ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9998</th>\n",
       "      <td>2312</td>\n",
       "      <td>In the Name of the King: A Dungeon Siege Tale</td>\n",
       "      <td>A man named Farmer sets out to rescue his kidn...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9999</th>\n",
       "      <td>455957</td>\n",
       "      <td>Domino</td>\n",
       "      <td>Seeking justice for his partner’s murder by an...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10000 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id                                          title  \\\n",
       "0        278                       The Shawshank Redemption   \n",
       "1      19404                    Dilwale Dulhania Le Jayenge   \n",
       "2        238                                  The Godfather   \n",
       "3        424                               Schindler's List   \n",
       "4        240                         The Godfather: Part II   \n",
       "...      ...                                            ...   \n",
       "9995   10196                             The Last Airbender   \n",
       "9996  331446                       Sharknado 3: Oh Hell No!   \n",
       "9997   13995                                Captain America   \n",
       "9998    2312  In the Name of the King: A Dungeon Siege Tale   \n",
       "9999  455957                                         Domino   \n",
       "\n",
       "                                                   tags  \n",
       "0     Framed in the 1940s for the double murder of h...  \n",
       "1     Raj is a rich, carefree, happy-go-lucky second...  \n",
       "2     Spanning the years 1945 to 1955, a chronicle o...  \n",
       "3     The true story of how businessman Oskar Schind...  \n",
       "4     In the continuing saga of the Corleone crime f...  \n",
       "...                                                 ...  \n",
       "9995  The story follows the adventures of Aang, a yo...  \n",
       "9996  The sharks take bite out of the East Coast whe...  \n",
       "9997  During World War II, a brave, patriotic Americ...  \n",
       "9998  A man named Farmer sets out to rescue his kidn...  \n",
       "9999  Seeking justice for his partner’s murder by an...  \n",
       "\n",
       "[10000 rows x 3 columns]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "083ab406",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import CountVectorizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "0b6a775d",
   "metadata": {},
   "outputs": [],
   "source": [
    "cv = CountVectorizer(max_features = 10000, stop_words = 'english')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "1d1ac2d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-3 {color: black;}#sk-container-id-3 pre{padding: 0;}#sk-container-id-3 div.sk-toggleable {background-color: white;}#sk-container-id-3 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-3 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-3 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-3 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-3 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-3 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-3 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-3 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-3 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-3 div.sk-item {position: relative;z-index: 1;}#sk-container-id-3 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-3 div.sk-item::before, #sk-container-id-3 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-3 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-3 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-3 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-3 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-3 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-3 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-3 div.sk-label-container {text-align: center;}#sk-container-id-3 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-3 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>CountVectorizer(max_features=10000, stop_words=&#x27;english&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">CountVectorizer</label><div class=\"sk-toggleable__content\"><pre>CountVectorizer(max_features=10000, stop_words=&#x27;english&#x27;)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "CountVectorizer(max_features=10000, stop_words='english')"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "1cf3544c",
   "metadata": {},
   "outputs": [],
   "source": [
    "vector = cv.fit_transform(new_data['tags'].values.astype('U')).toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "db293212",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10000, 10000)"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vector.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "c17f0527",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics.pairwise import cosine_similarity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "5f41c8af",
   "metadata": {},
   "outputs": [],
   "source": [
    "similarity=cosine_similarity(vector)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "1cc8d012",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.        , 0.05634362, 0.12888482, ..., 0.07559289, 0.11065667,\n",
       "        0.06388766],\n",
       "       [0.05634362, 1.        , 0.07624929, ..., 0.        , 0.03636965,\n",
       "        0.        ],\n",
       "       [0.12888482, 0.07624929, 1.        , ..., 0.02273314, 0.06655583,\n",
       "        0.08645856],\n",
       "       ...,\n",
       "       [0.07559289, 0.        , 0.02273314, ..., 1.        , 0.03253   ,\n",
       "        0.02817181],\n",
       "       [0.11065667, 0.03636965, 0.06655583, ..., 0.03253   , 1.        ,\n",
       "        0.0412393 ],\n",
       "       [0.06388766, 0.        , 0.08645856, ..., 0.02817181, 0.0412393 ,\n",
       "        1.        ]])"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "similarity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "18eea051",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data[new_data['title']==\"The Godfather\"].index[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "5c0184cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 10000 entries, 0 to 9999\n",
      "Data columns (total 3 columns):\n",
      " #   Column  Non-Null Count  Dtype \n",
      "---  ------  --------------  ----- \n",
      " 0   id      10000 non-null  int64 \n",
      " 1   title   10000 non-null  object\n",
      " 2   tags    9985 non-null   object\n",
      "dtypes: int64(1), object(2)\n",
      "memory usage: 234.5+ KB\n"
     ]
    }
   ],
   "source": [
    "new_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "8574507d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Godfather\n",
      "The Godfather: Part II\n",
      "Blood Ties\n",
      "Joker\n",
      "Bomb City\n"
     ]
    }
   ],
   "source": [
    "distance = sorted(list(enumerate(similarity[2])), reverse = True, key = lambda vector:vector[1])\n",
    "for i in distance[0:5]:\n",
    "    print(new_data.iloc[i[0]].title)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "4da001d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def recommend(movies):\n",
    "    index=new_data[new_data['title']==movies].index[0]\n",
    "    distance = sorted(list(enumerate(similarity[index])), reverse=True, key=lambda vector:vector[1])\n",
    "    for i in distance[0:5]:\n",
    "        print(new_data.iloc[i[0]].title)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "90923b2b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iron Man\n",
      "Iron Man 3\n",
      "Guardians of the Galaxy Vol. 2\n",
      "Avengers: Age of Ultron\n",
      "Star Wars: Episode III - Revenge of the Sith\n"
     ]
    }
   ],
   "source": [
    "recommend(\"Iron Man\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "bcab2696",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "434fbe11",
   "metadata": {},
   "outputs": [],
   "source": [
    "pickle.dump(new_data, open('movies_list.pkl', 'wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "744d3876",
   "metadata": {},
   "outputs": [],
   "source": [
    "pickle.dump(similarity, open('similarity.pkl', 'wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "62176d31",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>tags</th>\n",
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       "      <th>0</th>\n",
       "      <td>278</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>Framed in the 1940s for the double murder of h...</td>\n",
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       "          id                                          title  \\\n",
       "0        278                       The Shawshank Redemption   \n",
       "1      19404                    Dilwale Dulhania Le Jayenge   \n",
       "2        238                                  The Godfather   \n",
       "3        424                               Schindler's List   \n",
       "4        240                         The Godfather: Part II   \n",
       "...      ...                                            ...   \n",
       "9995   10196                             The Last Airbender   \n",
       "9996  331446                       Sharknado 3: Oh Hell No!   \n",
       "9997   13995                                Captain America   \n",
       "9998    2312  In the Name of the King: A Dungeon Siege Tale   \n",
       "9999  455957                                         Domino   \n",
       "\n",
       "                                                   tags  \n",
       "0     Framed in the 1940s for the double murder of h...  \n",
       "1     Raj is a rich, carefree, happy-go-lucky second...  \n",
       "2     Spanning the years 1945 to 1955, a chronicle o...  \n",
       "3     The true story of how businessman Oskar Schind...  \n",
       "4     In the continuing saga of the Corleone crime f...  \n",
       "...                                                 ...  \n",
       "9995  The story follows the adventures of Aang, a yo...  \n",
       "9996  The sharks take bite out of the East Coast whe...  \n",
       "9997  During World War II, a brave, patriotic Americ...  \n",
       "9998  A man named Farmer sets out to rescue his kidn...  \n",
       "9999  Seeking justice for his partner’s murder by an...  \n",
       "\n",
       "[10000 rows x 3 columns]"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pickle.load(open('movies_list.pkl', 'rb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e094627f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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