02_project_system.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b60607f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "\n",
    "from nltk.corpus import stopwords\n",
    "import nltk,re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5945d198",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_pickle(r'C:\\Users\\goura\\Documents\\DS and ML Projects\\8. Projects\\Movie Recommendation System\\processed.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1918c41c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>genres</th>\n",
       "      <th>keywords</th>\n",
       "      <th>overview</th>\n",
       "      <th>cast</th>\n",
       "      <th>crew</th>\n",
       "      <th>combined</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19995</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>[Action, Adventure, Fantasy, ScienceFiction]</td>\n",
       "      <td>[cultureclash, future, spacewar, spacecolony, ...</td>\n",
       "      <td>[In, the, 22nd, century,, a, paraplegic, Marin...</td>\n",
       "      <td>[SamWorthington, ZoeSaldana, SigourneyWeaver, ...</td>\n",
       "      <td>[JamesCameron]</td>\n",
       "      <td>Action Adventure Fantasy ScienceFiction cultur...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>285</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>[Adventure, Fantasy, Action]</td>\n",
       "      <td>[ocean, drugabuse, exoticisland, eastindiatrad...</td>\n",
       "      <td>[Captain, Barbossa,, long, believed, to, be, d...</td>\n",
       "      <td>[JohnnyDepp, OrlandoBloom, KeiraKnightley, Ste...</td>\n",
       "      <td>[GoreVerbinski]</td>\n",
       "      <td>Adventure Fantasy Action ocean drugabuse exoti...</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",
       "\n",
       "                                         genres  \\\n",
       "0  [Action, Adventure, Fantasy, ScienceFiction]   \n",
       "1                  [Adventure, Fantasy, Action]   \n",
       "\n",
       "                                            keywords  \\\n",
       "0  [cultureclash, future, spacewar, spacecolony, ...   \n",
       "1  [ocean, drugabuse, exoticisland, eastindiatrad...   \n",
       "\n",
       "                                            overview  \\\n",
       "0  [In, the, 22nd, century,, a, paraplegic, Marin...   \n",
       "1  [Captain, Barbossa,, long, believed, to, be, d...   \n",
       "\n",
       "                                                cast             crew  \\\n",
       "0  [SamWorthington, ZoeSaldana, SigourneyWeaver, ...   [JamesCameron]   \n",
       "1  [JohnnyDepp, OrlandoBloom, KeiraKnightley, Ste...  [GoreVerbinski]   \n",
       "\n",
       "                                            combined  \n",
       "0  Action Adventure Fantasy ScienceFiction cultur...  \n",
       "1  Adventure Fantasy Action ocean drugabuse exoti...  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()[:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cd8e37b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=df[['id','title','combined']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "941b1142",
   "metadata": {},
   "outputs": [
    {
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       "    }\n",
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       "<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>combined</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19995</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>Action Adventure Fantasy ScienceFiction cultur...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>285</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>Adventure Fantasy Action ocean drugabuse exoti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>206647</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>Action Adventure Crime spy basedonnovel secret...</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 dccomics crimefigh...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>49529</td>\n",
       "      <td>John Carter</td>\n",
       "      <td>Action Adventure ScienceFiction basedonnovel m...</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",
       "                                            combined  \n",
       "0  Action Adventure Fantasy ScienceFiction cultur...  \n",
       "1  Adventure Fantasy Action ocean drugabuse exoti...  \n",
       "2  Action Adventure Crime spy basedonnovel secret...  \n",
       "3  Action Crime Drama Thriller dccomics crimefigh...  \n",
       "4  Action Adventure ScienceFiction basedonnovel m...  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9f0b9c84",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-6-363e68ffcf94>:6: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df.combined[i]=' '.join(words)\n",
      "<ipython-input-6-363e68ffcf94>:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df.combined[i]=df.combined[i].lower()\n"
     ]
    }
   ],
   "source": [
    "'''Stop Words and Other symbols and punctuation should be removed'''\n",
    "for i in range(len(df)):\n",
    "    df.combined[i]=df.combined[i].lower()\n",
    "    words=nltk.word_tokenize(df.combined[i])\n",
    "    words=[re.sub('[^a-zA-Z]',\" \",word) for word in words if word not in stopwords.words('english')]\n",
    "    df.combined[i]=' '.join(words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8d31db21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'adventure fantasy action ocean drugabuse exoticisland eastindiatradingcompany loveofone slife traitor shipwreck strongwoman ship alliance calypso afterlife fighter pirate swashbuckler aftercreditsstinger captain barbossa   long believed dead   come back life headed edge earth turner elizabeth swann   nothing quite seems   johnnydepp orlandobloom keiraknightley stellanskarsg rd goreverbinski'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.combined[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d8eebedd",
   "metadata": {},
   "outputs": [],
   "source": [
    "count_vect=CountVectorizer(max_features=10000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "505c2e95",
   "metadata": {},
   "outputs": [],
   "source": [
    "vector=count_vect.fit_transform(df.combined).toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d90646bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4809, 10000)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vector.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "97d9355c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1.         0.07071068 0.04774099 ... 0.0204765  0.02174427 0.        ]\n",
      " [0.07071068 1.         0.07595545 ... 0.02171861 0.         0.        ]\n",
      " [0.04774099 0.07595545 1.         ... 0.02199529 0.         0.        ]\n",
      " ...\n",
      " [0.0204765  0.02171861 0.02199529 ... 1.         0.06010829 0.03924588]\n",
      " [0.02174427 0.         0.         ... 0.06010829 1.         0.06251357]\n",
      " [0.         0.         0.         ... 0.03924588 0.06251357 1.        ]]\n"
     ]
    }
   ],
   "source": [
    "similarity_score=cosine_similarity(vector)\n",
    "print(similarity_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "fcc18c67",
   "metadata": {},
   "outputs": [],
   "source": [
    "def recommend(movie_user):\n",
    "    movie_index=df[df.title==movie_user].index.values[0]\n",
    "    \n",
    "    similar_movies=pd.DataFrame(\n",
    "        enumerate(similarity_score[movie_index])).drop(0,axis='columns').sort_values(by=1,ascending=False)\n",
    "    \n",
    "    similar_movies['Names']=list(map(\n",
    "        lambda x: str(np.squeeze(df[df.index==x]['title'].values)),similar_movies.index.values))\n",
    "    similar_movies['id']=list(map(\n",
    "        lambda x: int(np.squeeze(df[df.index==x]['id'].values)),similar_movies.index.values))\n",
    "    return similar_movies.Names.values[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "12fd55a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Spider-Man', 'Spider-Man 3', 'Spider-Man 2',\n",
       "       'The Amazing Spider-Man 2', 'The Amazing Spider-Man',\n",
       "       'Arachnophobia', 'Kick-Ass', '21 Jump Street', 'X-Men',\n",
       "       'Small Soldiers'], dtype=object)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recommend('Spider-Man')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "09b6fe86",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ea92df2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "pickle.dump(df,open('movie_list.pkl','wb'))\n",
    "pickle.dump(similarity_score,open('similarity.pkl','wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "22836b5d",
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>combined</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19995</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>action adventure fantasy sciencefiction cultur...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>285</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>adventure fantasy action ocean drugabuse exoti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>206647</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>action adventure crime spy basedonnovel secret...</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 dccomics crimefigh...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>49529</td>\n",
       "      <td>John Carter</td>\n",
       "      <td>action adventure sciencefiction basedonnovel m...</td>\n",
       "    </tr>\n",
       "  </tbody>\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",
       "                                            combined  \n",
       "0  action adventure fantasy sciencefiction cultur...  \n",
       "1  adventure fantasy action ocean drugabuse exoti...  \n",
       "2  action adventure crime spy basedonnovel secret...  \n",
       "3  action crime drama thriller dccomics crimefigh...  \n",
       "4  action adventure sciencefiction basedonnovel m...  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fb6d4605",
   "metadata": {},
   "outputs": [],
   "source": []
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