PRJ Movie Recommendation System .ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "118df513",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "# will be using this library for text vectorization\n",
    "from nltk.stem.porter import PorterStemmer\n",
    "# will be using this library for stemming if you don't already have it installed you will have to install this library\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "47ff33bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir('J:\\\\Training program\\\\Datasets\\\\Project movies recommender') # used the dataset provided by your end\n",
    "# use your own directory where the dataset is their"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5374e901",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>budget</th>\n",
       "      <th>genres</th>\n",
       "      <th>homepage</th>\n",
       "      <th>id</th>\n",
       "      <th>keywords</th>\n",
       "      <th>original_language</th>\n",
       "      <th>original_title</th>\n",
       "      <th>overview</th>\n",
       "      <th>popularity</th>\n",
       "      <th>...</th>\n",
       "      <th>runtime</th>\n",
       "      <th>spoken_languages</th>\n",
       "      <th>status</th>\n",
       "      <th>tagline</th>\n",
       "      <th>title</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>vote_count</th>\n",
       "      <th>cast</th>\n",
       "      <th>crew</th>\n",
       "      <th>director</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>237000000</td>\n",
       "      <td>Action Adventure Fantasy Science Fiction</td>\n",
       "      <td>http://www.avatarmovie.com/</td>\n",
       "      <td>19995</td>\n",
       "      <td>culture clash future space war space colony so...</td>\n",
       "      <td>en</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>In the 22nd century, a paraplegic Marine is di...</td>\n",
       "      <td>150.437577</td>\n",
       "      <td>...</td>\n",
       "      <td>162.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...</td>\n",
       "      <td>Released</td>\n",
       "      <td>Enter the World of Pandora.</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>7.2</td>\n",
       "      <td>11800</td>\n",
       "      <td>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": [
    "df  = pd.read_csv('movies.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5e957832",
   "metadata": {},
   "outputs": [
    {
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       "en    4505\n",
       "fr      70\n",
       "es      32\n",
       "zh      27\n",
       "de      27\n",
       "hi      19\n",
       "ja      16\n",
       "it      14\n",
       "cn      12\n",
       "ru      11\n",
       "ko      11\n",
       "pt       9\n",
       "da       7\n",
       "sv       5\n",
       "nl       4\n",
       "fa       4\n",
       "th       3\n",
       "he       3\n",
       "ta       2\n",
       "cs       2\n",
       "ro       2\n",
       "id       2\n",
       "ar       2\n",
       "vi       1\n",
       "sl       1\n",
       "ps       1\n",
       "no       1\n",
       "ky       1\n",
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       "nb       1\n",
       "tr       1\n",
       "is       1\n",
       "xx       1\n",
       "te       1\n",
       "el       1\n",
       "Name: original_language, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['original_language'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "194096c7",
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4803, 24)\n",
      "########\n",
      "<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",
      "None\n",
      "########\n",
      "index                      0\n",
      "budget                     0\n",
      "genres                    28\n",
      "homepage                3091\n",
      "id                         0\n",
      "keywords                 412\n",
      "original_language          0\n",
      "original_title             0\n",
      "overview                   3\n",
      "popularity                 0\n",
      "production_companies       0\n",
      "production_countries       0\n",
      "release_date               1\n",
      "revenue                    0\n",
      "runtime                    2\n",
      "spoken_languages           0\n",
      "status                     0\n",
      "tagline                  844\n",
      "title                      0\n",
      "vote_average               0\n",
      "vote_count                 0\n",
      "cast                      43\n",
      "crew                       0\n",
      "director                  30\n",
      "dtype: int64\n",
      "########\n",
      "0\n"
     ]
    }
   ],
   "source": [
    "print(df.shape)\n",
    "print('########')\n",
    "print(df.info())\n",
    "print('########')\n",
    "print(df.isnull().sum())\n",
    "print('########')\n",
    "print(df.duplicated().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "048f9992",
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       "      <th>0</th>\n",
       "      <td>Action Adventure Fantasy Science Fiction</td>\n",
       "      <td>19995</td>\n",
       "      <td>culture clash future space war space colony so...</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>In the 22nd century, a paraplegic Marine is di...</td>\n",
       "      <td>Sam Worthington Zoe Saldana Sigourney Weaver S...</td>\n",
       "      <td>James Cameron</td>\n",
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       "      <th>1</th>\n",
       "      <td>Adventure Fantasy Action</td>\n",
       "      <td>285</td>\n",
       "      <td>ocean drug abuse exotic island east india trad...</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>Johnny Depp Orlando Bloom Keira Knightley Stel...</td>\n",
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       "      <td>en</td>\n",
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       "      <td>Action Adventure Crime</td>\n",
       "      <td>206647</td>\n",
       "      <td>spy based on novel secret agent sequel mi6</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>A cryptic message from Bond’s past sends him o...</td>\n",
       "      <td>Daniel Craig Christoph Waltz L\\u00e9a Seydoux ...</td>\n",
       "      <td>Sam Mendes</td>\n",
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       "      <td>Action Crime Drama Thriller</td>\n",
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       "      <td>dc comics crime fighter terrorist secret ident...</td>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>Following the death of District Attorney Harve...</td>\n",
       "      <td>Christian Bale Michael Caine Gary Oldman Anne ...</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Action Adventure Science Fiction</td>\n",
       "      <td>49529</td>\n",
       "      <td>based on novel mars medallion space travel pri...</td>\n",
       "      <td>John Carter</td>\n",
       "      <td>John Carter is a war-weary, former military ca...</td>\n",
       "      <td>Taylor Kitsch Lynn Collins Samantha Morton Wil...</td>\n",
       "      <td>Andrew Stanton</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     genres      id  \\\n",
       "0  Action Adventure Fantasy Science Fiction   19995   \n",
       "1                  Adventure Fantasy Action     285   \n",
       "2                    Action Adventure Crime  206647   \n",
       "3               Action Crime Drama Thriller   49026   \n",
       "4          Action Adventure Science Fiction   49529   \n",
       "\n",
       "                                            keywords  \\\n",
       "0  culture clash future space war space colony so...   \n",
       "1  ocean drug abuse exotic island east india trad...   \n",
       "2         spy based on novel secret agent sequel mi6   \n",
       "3  dc comics crime fighter terrorist secret ident...   \n",
       "4  based on novel mars medallion space travel pri...   \n",
       "\n",
       "                                      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  \\\n",
       "0  In the 22nd century, a paraplegic Marine is di...   \n",
       "1  Captain Barbossa, long believed to be dead, ha...   \n",
       "2  A cryptic message from Bond’s past sends him o...   \n",
       "3  Following the death of District Attorney Harve...   \n",
       "4  John Carter is a war-weary, former military ca...   \n",
       "\n",
       "                                                cast           director  \\\n",
       "0  Sam Worthington Zoe Saldana Sigourney Weaver S...      James Cameron   \n",
       "1  Johnny Depp Orlando Bloom Keira Knightley Stel...     Gore Verbinski   \n",
       "2  Daniel Craig Christoph Waltz L\\u00e9a Seydoux ...         Sam Mendes   \n",
       "3  Christian Bale Michael Caine Gary Oldman Anne ...  Christopher Nolan   \n",
       "4  Taylor Kitsch Lynn Collins Samantha Morton Wil...     Andrew Stanton   \n",
       "\n",
       "  original_language  \n",
       "0                en  \n",
       "1                en  \n",
       "2                en  \n",
       "3                en  \n",
       "4                en  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selected_features = ['genres', 'id', 'keywords', 'title', 'overview', 'cast', 'director', 'original_language']\n",
    "# I am keeping id for making the frontend\n",
    "df = df[selected_features]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6a22606b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4803, 8)\n",
      "########\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4803 entries, 0 to 4802\n",
      "Data columns (total 8 columns):\n",
      " #   Column             Non-Null Count  Dtype \n",
      "---  ------             --------------  ----- \n",
      " 0   genres             4775 non-null   object\n",
      " 1   id                 4803 non-null   int64 \n",
      " 2   keywords           4391 non-null   object\n",
      " 3   title              4803 non-null   object\n",
      " 4   overview           4800 non-null   object\n",
      " 5   cast               4760 non-null   object\n",
      " 6   director           4773 non-null   object\n",
      " 7   original_language  4803 non-null   object\n",
      "dtypes: int64(1), object(7)\n",
      "memory usage: 300.3+ KB\n",
      "None\n",
      "########\n",
      "genres                28\n",
      "id                     0\n",
      "keywords             412\n",
      "title                  0\n",
      "overview               3\n",
      "cast                  43\n",
      "director              30\n",
      "original_language      0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(df.shape)\n",
    "print('########')\n",
    "print(df.info())\n",
    "print('########')\n",
    "print(df.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "66d4c89d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genres               0\n",
      "id                   0\n",
      "keywords             0\n",
      "title                0\n",
      "overview             0\n",
      "cast                 0\n",
      "director             0\n",
      "original_language    0\n",
      "dtype: int64\n",
      "*********************\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4803 entries, 0 to 4802\n",
      "Data columns (total 8 columns):\n",
      " #   Column             Non-Null Count  Dtype \n",
      "---  ------             --------------  ----- \n",
      " 0   genres             4803 non-null   object\n",
      " 1   id                 4803 non-null   int64 \n",
      " 2   keywords           4803 non-null   object\n",
      " 3   title              4803 non-null   object\n",
      " 4   overview           4803 non-null   object\n",
      " 5   cast               4803 non-null   object\n",
      " 6   director           4803 non-null   object\n",
      " 7   original_language  4803 non-null   object\n",
      "dtypes: int64(1), object(7)\n",
      "memory usage: 300.3+ KB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "df.fillna('', inplace=True)\n",
    "print(df.isnull().sum())\n",
    "print('*********************')\n",
    "print(df.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "51098736",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cast</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <td>Sam Worthington Zoe Saldana Sigourney Weaver S...</td>\n",
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       "      <th>2</th>\n",
       "      <td>Daniel Craig Christoph Waltz L\\u00e9a Seydoux ...</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Christian Bale Michael Caine Gary Oldman Anne ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Taylor Kitsch Lynn Collins Samantha Morton Wil...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                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..."
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['cast']].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ee570d8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def cast_selector(cast):\n",
    "    cast_list = cast.split(' ')\n",
    "    misc = []\n",
    "    for i in range(0,10):\n",
    "        misc.append(str(i))\n",
    "    y = []\n",
    "    for i in cast_list:\n",
    "        if cast_list.index(i)%2 == 0:\n",
    "            try:\n",
    "                name = i + cast_list[cast_list.index(i)+1]\n",
    "                for j in misc:\n",
    "                    if j in i or j in cast_list[cast_list.index(i)+1]:\n",
    "                                                break\n",
    "                    else:\n",
    "                        y.append(name)\n",
    "                        break\n",
    "                \n",
    "            except:\n",
    "                break\n",
    "            \n",
    "    return y[0:3]\n",
    "# used to filter and clean cast column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d0102a54",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('max_colwidth', 100)\n",
    "df.cast = df['cast'].apply(cast_selector)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "445f12d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.cast = df['cast'].apply(lambda x: \" \".join(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2948cdbd",
   "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>genres</th>\n",
       "      <th>id</th>\n",
       "      <th>keywords</th>\n",
       "      <th>title</th>\n",
       "      <th>overview</th>\n",
       "      <th>cast</th>\n",
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       "      <th>original_language</th>\n",
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       "    <tr>\n",
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       "      <td>Action Adventure Fantasy Science Fiction</td>\n",
       "      <td>19995</td>\n",
       "      <td>culture clash future space war space colony society</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>In the 22nd century, a paraplegic Marine is dispatched to the moon Pandora on a unique mission, ...</td>\n",
       "      <td>SamWorthington ZoeSaldana SigourneyWeaver</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Adventure Fantasy Action</td>\n",
       "      <td>285</td>\n",
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       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>Captain Barbossa, long believed to be dead, has come back to life and is headed to the edge of t...</td>\n",
       "      <td>JohnnyDepp OrlandoBloom KeiraKnightley</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "      <td>en</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Action Adventure Crime</td>\n",
       "      <td>206647</td>\n",
       "      <td>spy based on novel secret agent sequel mi6</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>A cryptic message from Bond’s past sends him on a trail to uncover a sinister organization. Whil...</td>\n",
       "      <td>DanielCraig ChristophWaltz RalphFiennes</td>\n",
       "      <td>Sam Mendes</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Action Crime Drama Thriller</td>\n",
       "      <td>49026</td>\n",
       "      <td>dc comics crime fighter terrorist secret identity burglar</td>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>Following the death of District Attorney Harvey Dent, Batman assumes responsibility for Dent's c...</td>\n",
       "      <td>ChristianBale MichaelCaine GaryOldman</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Action Adventure Science Fiction</td>\n",
       "      <td>49529</td>\n",
       "      <td>based on novel mars medallion space travel princess</td>\n",
       "      <td>John Carter</td>\n",
       "      <td>John Carter is a war-weary, former military captain who's inexplicably transported to the myster...</td>\n",
       "      <td>TaylorKitsch LynnCollins SamanthaMorton</td>\n",
       "      <td>Andrew Stanton</td>\n",
       "      <td>en</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     genres      id  \\\n",
       "0  Action Adventure Fantasy Science Fiction   19995   \n",
       "1                  Adventure Fantasy Action     285   \n",
       "2                    Action Adventure Crime  206647   \n",
       "3               Action Crime Drama Thriller   49026   \n",
       "4          Action Adventure Science Fiction   49529   \n",
       "\n",
       "                                                                       keywords  \\\n",
       "0                           culture clash future space war space colony society   \n",
       "1  ocean drug abuse exotic island east india trading company love of one's life   \n",
       "2                                    spy based on novel secret agent sequel mi6   \n",
       "3                     dc comics crime fighter terrorist secret identity burglar   \n",
       "4                           based on novel mars medallion space travel princess   \n",
       "\n",
       "                                      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  \\\n",
       "0  In the 22nd century, a paraplegic Marine is dispatched to the moon Pandora on a unique mission, ...   \n",
       "1  Captain Barbossa, long believed to be dead, has come back to life and is headed to the edge of t...   \n",
       "2  A cryptic message from Bond’s past sends him on a trail to uncover a sinister organization. Whil...   \n",
       "3  Following the death of District Attorney Harvey Dent, Batman assumes responsibility for Dent's c...   \n",
       "4  John Carter is a war-weary, former military captain who's inexplicably transported to the myster...   \n",
       "\n",
       "                                        cast           director  \\\n",
       "0  SamWorthington ZoeSaldana SigourneyWeaver      James Cameron   \n",
       "1     JohnnyDepp OrlandoBloom KeiraKnightley     Gore Verbinski   \n",
       "2    DanielCraig ChristophWaltz RalphFiennes         Sam Mendes   \n",
       "3      ChristianBale MichaelCaine GaryOldman  Christopher Nolan   \n",
       "4    TaylorKitsch LynnCollins SamanthaMorton     Andrew Stanton   \n",
       "\n",
       "  original_language  \n",
       "0                en  \n",
       "1                en  \n",
       "2                en  \n",
       "3                en  \n",
       "4                en  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7f9e1e58",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4803 entries, 0 to 4802\n",
      "Data columns (total 8 columns):\n",
      " #   Column             Non-Null Count  Dtype \n",
      "---  ------             --------------  ----- \n",
      " 0   genres             4803 non-null   object\n",
      " 1   id                 4803 non-null   int64 \n",
      " 2   keywords           4803 non-null   object\n",
      " 3   title              4803 non-null   object\n",
      " 4   overview           4803 non-null   object\n",
      " 5   cast               4803 non-null   object\n",
      " 6   director           4803 non-null   object\n",
      " 7   original_language  4803 non-null   object\n",
      "dtypes: int64(1), object(7)\n",
      "memory usage: 300.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2af54f4d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['tags'] = df['genres']+' '+df['keywords']+' '+df['overview']+' '+df['cast']+' '+df['director']+' '+df['original_language']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "846be0d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
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       "      <td>Action Adventure Fantasy Science Fiction culture clash future space war space colony society In ...</td>\n",
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       "      <th>1</th>\n",
       "      <td>285</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>206647</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>Action Adventure Crime spy based on novel secret agent sequel mi6 A cryptic message from Bond’s ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>49026</td>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>Action Crime Drama Thriller dc comics crime fighter terrorist secret identity burglar Following ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>49529</td>\n",
       "      <td>John Carter</td>\n",
       "      <td>Action Adventure Science Fiction based on novel mars medallion space travel princess John Carter...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id                                     title  \\\n",
       "0   19995                                    Avatar   \n",
       "1     285  Pirates of the Caribbean: At World's End   \n",
       "2  206647                                   Spectre   \n",
       "3   49026                     The Dark Knight Rises   \n",
       "4   49529                               John Carter   \n",
       "\n",
       "                                                                                                  tags  \n",
       "0  Action Adventure Fantasy Science Fiction culture clash future space war space colony society In ...  \n",
       "1  Adventure Fantasy Action ocean drug abuse exotic island east india trading company love of one's...  \n",
       "2  Action Adventure Crime spy based on novel secret agent sequel mi6 A cryptic message from Bond’s ...  \n",
       "3  Action Crime Drama Thriller dc comics crime fighter terrorist secret identity burglar Following ...  \n",
       "4  Action Adventure Science Fiction based on novel mars medallion space travel princess John Carter...  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ndf = df.drop(columns=['genres', 'keywords', 'overview', 'cast', 'director', 'original_language'])\n",
    "ndf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1a09dfcc",
   "metadata": {},
   "outputs": [],
   "source": [
    "ps = PorterStemmer()\n",
    "def stem(tag):\n",
    "    new_tag = []\n",
    "    for i in tag.split(' '):\n",
    "        new_tag.append(ps.stem(i))\n",
    "    return ' '.join(new_tag)\n",
    "ndf.tags = ndf['tags'].apply(stem)\n",
    "# stemming all the tags"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "3120d599",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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      ],
      "text/plain": [
       "       id                                     title  \\\n",
       "0   19995                                    Avatar   \n",
       "1     285  Pirates of the Caribbean: At World's End   \n",
       "2  206647                                   Spectre   \n",
       "3   49026                     The Dark Knight Rises   \n",
       "4   49529                               John Carter   \n",
       "\n",
       "                                                                                                  tags  \n",
       "0  action adventur fantasi scienc fiction cultur clash futur space war space coloni societi in the ...  \n",
       "1  adventur fantasi action ocean drug abus exot island east india trade compani love of one' life c...  \n",
       "2  action adventur crime spi base on novel secret agent sequel mi6 a cryptic messag from bond’ past...  \n",
       "3  action crime drama thriller dc comic crime fighter terrorist secret ident burglar follow the dea...  \n",
       "4  action adventur scienc fiction base on novel mar medallion space travel princess john carter is ...  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ndf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c7e641a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "cv = CountVectorizer(stop_words='english', max_features=7000)\n",
    "vtags = cv.fit_transform(df['tags']).toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "684ef54d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4803, 7000)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vtags.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "da9b6113",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4803, 3)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ndf.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "52b5e674",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "# to calculate cosine distance and compare"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "10a33a7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.        , 0.11595421, 0.08119979, ..., 0.02300219, 0.02519763,\n",
       "        0.02300219],\n",
       "       [0.11595421, 1.        , 0.08238526, ..., 0.070014  , 0.0255655 ,\n",
       "        0.023338  ],\n",
       "       [0.08119979, 0.08238526, 1.        , ..., 0.04358136, 0.07161149,\n",
       "        0.02179068],\n",
       "       ...,\n",
       "       [0.02300219, 0.070014  , 0.04358136, ..., 1.        , 0.08114408,\n",
       "        0.05555556],\n",
       "       [0.02519763, 0.0255655 , 0.07161149, ..., 0.08114408, 1.        ,\n",
       "        0.06085806],\n",
       "       [0.02300219, 0.023338  , 0.02179068, ..., 0.05555556, 0.06085806,\n",
       "        1.        ]])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "similarity = cosine_similarity(vtags)\n",
    "similarity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e6538852",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Movies recommended for you are: \n",
      "1. The Boxtrolls\n",
      "2. The Simpsons Movie\n",
      "3. The Adventures of Rocky & Bullwinkle\n",
      "4. Evan Almighty\n",
      "5. When Did You Last See Your Father?\n",
      "6. Super Mario Bros.\n",
      "7. Percy Jackson: Sea of Monsters\n",
      "8. The Beastmaster\n",
      "9. Penguins of Madagascar\n",
      "10. Foodfight!\n"
     ]
    }
   ],
   "source": [
    "def recommend(movie):\n",
    "    index = ndf[ndf['title'] == movie].index[0]\n",
    "    recommedations = sorted(enumerate(similarity[index]), reverse = True, key=lambda x:x[1])[1:11]\n",
    "    l = []\n",
    "    j = 1\n",
    "    print('Movies recommended for you are: ')\n",
    "    for i in recommedations:\n",
    "        print(f\"{j}. {ndf.iloc[i[0], 1]}\")\n",
    "        j += 1\n",
    "recommend('The Lego Movie')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "08f9f472",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Movies recommended for you are: \n",
      "1. Superman II\n",
      "2. Superman IV: The Quest for Peace\n",
      "3. Superman Returns\n",
      "4. Superman III\n",
      "5. Man of Steel\n",
      "6. Batman\n",
      "7. The League of Extraordinary Gentlemen\n",
      "8. The Helix... Loaded\n",
      "9. Suicide Squad\n",
      "10. Flyboys\n"
     ]
    }
   ],
   "source": [
    "# you can recommend using this recommend function and passing the name of movie you like\n",
    "# for example\n",
    "# I am recommending 10 movies\n",
    "recommend('Superman')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d8c23f8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "ndf_dict = ndf.to_dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b36666ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "# for implementing frontend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f0418ea6",
   "metadata": {},
   "outputs": [],
   "source": [
    "pickle.dump(ndf_dict, open('Movies.pkl', 'wb'))\n",
    "pickle.dump(similarity, open('similarity.pkl', 'wb'))"
   ]
  }
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