User_based_RS500.ipynb

{
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   "cell_type": "code",
   "execution_count": 36,
   "id": "846d3599-9386-4aa6-8f89-63629fc62d42",
   "metadata": {},
   "outputs": [],
   "source": [
    "import cupy as cp\n",
    "import numpy as np\n",
    "# import torch\n",
    "import pandas as pd "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6df99b7b-decd-4621-bb6f-67f6101ec32a",
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       "       movieId  no_of_votes  avg_rating  weighted_avg\n",
       "0          318        91082    4.429015   3866.323080\n",
       "1          356        91921    4.052926   3583.770527\n",
       "2          296        87901    4.169975   3522.107094\n",
       "3          593        84078    4.152246   3355.331488\n",
       "4         2571        77960    4.154098   3112.756142\n",
       "...        ...          ...         ...           ...\n",
       "45110   141275            1    5.000000      3.407705\n",
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       "45114   171221            1    5.000000      3.407705\n",
       "\n",
       "[45115 rows x 4 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "popular_data = pd.read_csv(\"popular_movies_by_id.csv\")\n",
    "popular_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7212d40b-0a56-49fb-8106-b6e3e2766e41",
   "metadata": {},
   "outputs": [],
   "source": [
    "ratings = pd.read_csv(\"data/ratings_small.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "844844d4-e3a9-4363-86dc-5f31a4b7e757",
   "metadata": {},
   "outputs": [
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       "        userId  movieId  rating   timestamp\n",
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       "100003     671     6565     3.5  1074784724\n",
       "\n",
       "[100004 rows x 4 columns]"
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     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "ratings"
   ]
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   "execution_count": 15,
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       "movieId  1       2       3       4       5       6       7       8       \\\n",
       "userId                                                                    \n",
       "1           0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
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       "671         5.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "\n",
       "movieId  9       10      ...  161084  161155  161594  161830  161918  161944  \\\n",
       "userId                   ...                                                   \n",
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       "...         ...     ...  ...     ...     ...     ...     ...     ...     ...   \n",
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       "671         0.0     0.0  ...     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "\n",
       "movieId  162376  162542  162672  163949  \n",
       "userId                                   \n",
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       "...         ...     ...     ...     ...  \n",
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       "669         0.0     0.0     0.0     0.0  \n",
       "670         0.0     0.0     0.0     0.0  \n",
       "671         0.0     0.0     0.0     0.0  \n",
       "\n",
       "[671 rows x 9066 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pt = ratings.pivot_table(values=\"rating\",index=\"userId\",columns=\"movieId\",fill_value=0)\n",
    "pt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b2728824-1f76-4d39-9ac7-6f7cd376a848",
   "metadata": {},
   "outputs": [],
   "source": [
    "ratingssss = pd.read_csv(\"data/ratings.csv\",low_memory=True)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6afae4f2-1912-4ded-b12d-d85ebcee933d",
   "metadata": {},
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     "execution_count": 20,
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   "cell_type": "code",
   "execution_count": 21,
   "id": "4dfeef52-be8a-4afd-a594-bb93506936c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "a = ratingssss[\"userId\"].value_counts()"
   ]
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   "cell_type": "code",
   "execution_count": 22,
   "id": "42e20398-98ad-4e6b-8362-2d5cd279c12f",
   "metadata": {},
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    {
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  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "33bc608f-76c3-428b-ace2-7147258e496b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "       172224,\n",
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     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
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    "user_ids_to_filter = a[a>500].index\n",
    "user_ids_to_filter"
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   "cell_type": "code",
   "execution_count": 45,
   "id": "8f60a836-0122-4fc3-9302-eecdc3aa1fe9",
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       "          userId  movieId  rating   timestamp\n",
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     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "filtered_ratings_data  =ratingssss[ratingssss['userId'].isin(user_ids_to_filter)]\n",
    "filtered_ratings_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "3b92fd17-f13e-48af-be5a-683ff4f36eb0",
   "metadata": {},
   "outputs": [
    {
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   "execution_count": 47,
   "id": "afee497f-253e-468c-b41d-d6c3e1a7ca7d",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>4.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>270654</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>270684</th>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>270734</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>270769</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>270887</th>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9452 rows × 43482 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "movieId  1       2       3       4       5       6       7       8       \\\n",
       "userId                                                                    \n",
       "24          4.0     3.0     0.0     0.0     0.0     4.0     0.0     0.0   \n",
       "46          4.5     0.0     3.5     0.0     0.0     3.0     0.0     0.0   \n",
       "120         2.0     2.5     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "132         3.0     0.0     0.0     2.0     0.0     0.0     0.0     0.0   \n",
       "150         4.0     0.0     0.0     0.0     0.0     3.0     0.0     0.0   \n",
       "...         ...     ...     ...     ...     ...     ...     ...     ...   \n",
       "270654      3.0     0.0     0.0     0.0     0.0     3.5     0.0     0.0   \n",
       "270684      4.0     0.0     4.0     0.0     3.0     4.0     0.0     0.0   \n",
       "270734      5.0     3.0     3.0     0.0     0.0     0.0     5.0     0.0   \n",
       "270769      4.0     3.0     1.0     0.0     0.0     3.0     0.0     0.0   \n",
       "270887      5.0     5.0     4.0     0.0     0.0     5.0     0.0     0.0   \n",
       "\n",
       "movieId  9       10      ...  176237  176239  176245  176251  176257  176259  \\\n",
       "userId                   ...                                                   \n",
       "24          0.0     0.0  ...     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "46          0.0     0.0  ...     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "120         0.0     0.0  ...     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "132         0.0     0.0  ...     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "150         0.0     0.0  ...     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "...         ...     ...  ...     ...     ...     ...     ...     ...     ...   \n",
       "270654      0.0     0.0  ...     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "270684      0.0     3.0  ...     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "270734      0.0     0.0  ...     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "270769      0.0     3.0  ...     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "270887      5.0     0.0  ...     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "\n",
       "movieId  176263  176267  176273  176275  \n",
       "userId                                   \n",
       "24          0.0     0.0     0.0     0.0  \n",
       "46          0.0     0.0     0.0     0.0  \n",
       "120         0.0     0.0     0.0     0.0  \n",
       "132         0.0     0.0     0.0     0.0  \n",
       "150         0.0     0.0     0.0     0.0  \n",
       "...         ...     ...     ...     ...  \n",
       "270654      0.0     0.0     0.0     0.0  \n",
       "270684      0.0     0.0     0.0     0.0  \n",
       "270734      0.0     0.0     0.0     0.0  \n",
       "270769      0.0     0.0     0.0     0.0  \n",
       "270887      0.0     0.0     0.0     0.0  \n",
       "\n",
       "[9452 rows x 43482 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pt = filtered_ratings_data.pivot_table(values=\"rating\",index=\"userId\",columns=\"movieId\",fill_value=0)\n",
    "pt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "f1796bd2-a613-49df-82a4-7680d8b352e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics.pairwise import cosine_similarity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "8a10b854-1882-4586-a061-e3fee76ab7bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "simiity = cosine_similarity(pt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "4c41d15d-3477-48a2-8b82-95c6f2100b18",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.        , 0.30337475, 0.38789347, ..., 0.34786152, 0.46536317,\n",
       "        0.17498909],\n",
       "       [0.30337475, 1.        , 0.3007393 , ..., 0.23297621, 0.24537149,\n",
       "        0.25571855],\n",
       "       [0.38789347, 0.3007393 , 1.        , ..., 0.34291125, 0.40786269,\n",
       "        0.17727518],\n",
       "       ...,\n",
       "       [0.34786152, 0.23297621, 0.34291125, ..., 1.        , 0.38705754,\n",
       "        0.16353509],\n",
       "       [0.46536317, 0.24537149, 0.40786269, ..., 0.38705754, 1.        ,\n",
       "        0.14342642],\n",
       "       [0.17498909, 0.25571855, 0.17727518, ..., 0.16353509, 0.14342642,\n",
       "        1.        ]])"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simiity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "5dd26415-3f6b-4b4a-ac12-a1aff9382d55",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0.328777</td>\n",
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       "      <td>0.407863</td>\n",
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       "      <td>0.448727</td>\n",
       "      <td>0.304386</td>\n",
       "      <td>0.378200</td>\n",
       "      <td>0.302055</td>\n",
       "      <td>0.170601</td>\n",
       "      <td>0.323307</td>\n",
       "      <td>0.347403</td>\n",
       "      <td>0.347773</td>\n",
       "      <td>0.423316</td>\n",
       "      <td>0.156580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.467059</td>\n",
       "      <td>0.323457</td>\n",
       "      <td>0.371008</td>\n",
       "      <td>0.393779</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.360487</td>\n",
       "      <td>0.251523</td>\n",
       "      <td>0.333233</td>\n",
       "      <td>0.266147</td>\n",
       "      <td>0.197559</td>\n",
       "      <td>...</td>\n",
       "      <td>0.391590</td>\n",
       "      <td>0.256773</td>\n",
       "      <td>0.355247</td>\n",
       "      <td>0.279500</td>\n",
       "      <td>0.136883</td>\n",
       "      <td>0.294211</td>\n",
       "      <td>0.390681</td>\n",
       "      <td>0.333439</td>\n",
       "      <td>0.423196</td>\n",
       "      <td>0.169814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9447</th>\n",
       "      <td>0.292288</td>\n",
       "      <td>0.199854</td>\n",
       "      <td>0.328777</td>\n",
       "      <td>0.323307</td>\n",
       "      <td>0.294211</td>\n",
       "      <td>0.393562</td>\n",
       "      <td>0.274117</td>\n",
       "      <td>0.233019</td>\n",
       "      <td>0.271341</td>\n",
       "      <td>0.289505</td>\n",
       "      <td>...</td>\n",
       "      <td>0.387641</td>\n",
       "      <td>0.322201</td>\n",
       "      <td>0.246056</td>\n",
       "      <td>0.338130</td>\n",
       "      <td>0.189027</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.219397</td>\n",
       "      <td>0.276599</td>\n",
       "      <td>0.383480</td>\n",
       "      <td>0.175035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9448</th>\n",
       "      <td>0.444702</td>\n",
       "      <td>0.408793</td>\n",
       "      <td>0.318633</td>\n",
       "      <td>0.347403</td>\n",
       "      <td>0.390681</td>\n",
       "      <td>0.340460</td>\n",
       "      <td>0.294290</td>\n",
       "      <td>0.402475</td>\n",
       "      <td>0.270537</td>\n",
       "      <td>0.210733</td>\n",
       "      <td>...</td>\n",
       "      <td>0.389340</td>\n",
       "      <td>0.290467</td>\n",
       "      <td>0.424651</td>\n",
       "      <td>0.231773</td>\n",
       "      <td>0.172908</td>\n",
       "      <td>0.219397</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.319531</td>\n",
       "      <td>0.329426</td>\n",
       "      <td>0.231650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9449</th>\n",
       "      <td>0.347862</td>\n",
       "      <td>0.232976</td>\n",
       "      <td>0.342911</td>\n",
       "      <td>0.347773</td>\n",
       "      <td>0.333439</td>\n",
       "      <td>0.363782</td>\n",
       "      <td>0.201251</td>\n",
       "      <td>0.257747</td>\n",
       "      <td>0.233922</td>\n",
       "      <td>0.256076</td>\n",
       "      <td>...</td>\n",
       "      <td>0.421064</td>\n",
       "      <td>0.223163</td>\n",
       "      <td>0.289597</td>\n",
       "      <td>0.226633</td>\n",
       "      <td>0.126655</td>\n",
       "      <td>0.276599</td>\n",
       "      <td>0.319531</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.387058</td>\n",
       "      <td>0.163535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9450</th>\n",
       "      <td>0.465363</td>\n",
       "      <td>0.245371</td>\n",
       "      <td>0.407863</td>\n",
       "      <td>0.423316</td>\n",
       "      <td>0.423196</td>\n",
       "      <td>0.430351</td>\n",
       "      <td>0.218433</td>\n",
       "      <td>0.294451</td>\n",
       "      <td>0.262459</td>\n",
       "      <td>0.221420</td>\n",
       "      <td>...</td>\n",
       "      <td>0.443485</td>\n",
       "      <td>0.254028</td>\n",
       "      <td>0.328361</td>\n",
       "      <td>0.258580</td>\n",
       "      <td>0.134900</td>\n",
       "      <td>0.383480</td>\n",
       "      <td>0.329426</td>\n",
       "      <td>0.387058</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.143426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9451</th>\n",
       "      <td>0.174989</td>\n",
       "      <td>0.255719</td>\n",
       "      <td>0.177275</td>\n",
       "      <td>0.156580</td>\n",
       "      <td>0.169814</td>\n",
       "      <td>0.145683</td>\n",
       "      <td>0.363367</td>\n",
       "      <td>0.247706</td>\n",
       "      <td>0.268889</td>\n",
       "      <td>0.216790</td>\n",
       "      <td>...</td>\n",
       "      <td>0.209381</td>\n",
       "      <td>0.254178</td>\n",
       "      <td>0.259912</td>\n",
       "      <td>0.156187</td>\n",
       "      <td>0.259384</td>\n",
       "      <td>0.175035</td>\n",
       "      <td>0.231650</td>\n",
       "      <td>0.163535</td>\n",
       "      <td>0.143426</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9452 rows × 9452 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1         2         3         4         5         6     \\\n",
       "0     1.000000  0.303375  0.387893  0.465607  0.467059  0.371757  0.280652   \n",
       "1     0.303375  1.000000  0.300739  0.302647  0.323457  0.276435  0.336402   \n",
       "2     0.387893  0.300739  1.000000  0.428290  0.371008  0.370525  0.338186   \n",
       "3     0.465607  0.302647  0.428290  1.000000  0.393779  0.410667  0.273521   \n",
       "4     0.467059  0.323457  0.371008  0.393779  1.000000  0.360487  0.251523   \n",
       "...        ...       ...       ...       ...       ...       ...       ...   \n",
       "9447  0.292288  0.199854  0.328777  0.323307  0.294211  0.393562  0.274117   \n",
       "9448  0.444702  0.408793  0.318633  0.347403  0.390681  0.340460  0.294290   \n",
       "9449  0.347862  0.232976  0.342911  0.347773  0.333439  0.363782  0.201251   \n",
       "9450  0.465363  0.245371  0.407863  0.423316  0.423196  0.430351  0.218433   \n",
       "9451  0.174989  0.255719  0.177275  0.156580  0.169814  0.145683  0.363367   \n",
       "\n",
       "          7         8         9     ...      9442      9443      9444  \\\n",
       "0     0.310332  0.268996  0.197366  ...  0.424657  0.295061  0.379651   \n",
       "1     0.394324  0.329194  0.274437  ...  0.343309  0.293843  0.399885   \n",
       "2     0.310608  0.320079  0.373059  ...  0.487814  0.354643  0.398110   \n",
       "3     0.328893  0.277101  0.264450  ...  0.448727  0.304386  0.378200   \n",
       "4     0.333233  0.266147  0.197559  ...  0.391590  0.256773  0.355247   \n",
       "...        ...       ...       ...  ...       ...       ...       ...   \n",
       "9447  0.233019  0.271341  0.289505  ...  0.387641  0.322201  0.246056   \n",
       "9448  0.402475  0.270537  0.210733  ...  0.389340  0.290467  0.424651   \n",
       "9449  0.257747  0.233922  0.256076  ...  0.421064  0.223163  0.289597   \n",
       "9450  0.294451  0.262459  0.221420  ...  0.443485  0.254028  0.328361   \n",
       "9451  0.247706  0.268889  0.216790  ...  0.209381  0.254178  0.259912   \n",
       "\n",
       "          9445      9446      9447      9448      9449      9450      9451  \n",
       "0     0.256451  0.152454  0.292288  0.444702  0.347862  0.465363  0.174989  \n",
       "1     0.200290  0.280374  0.199854  0.408793  0.232976  0.245371  0.255719  \n",
       "2     0.339258  0.265313  0.328777  0.318633  0.342911  0.407863  0.177275  \n",
       "3     0.302055  0.170601  0.323307  0.347403  0.347773  0.423316  0.156580  \n",
       "4     0.279500  0.136883  0.294211  0.390681  0.333439  0.423196  0.169814  \n",
       "...        ...       ...       ...       ...       ...       ...       ...  \n",
       "9447  0.338130  0.189027  1.000000  0.219397  0.276599  0.383480  0.175035  \n",
       "9448  0.231773  0.172908  0.219397  1.000000  0.319531  0.329426  0.231650  \n",
       "9449  0.226633  0.126655  0.276599  0.319531  1.000000  0.387058  0.163535  \n",
       "9450  0.258580  0.134900  0.383480  0.329426  0.387058  1.000000  0.143426  \n",
       "9451  0.156187  0.259384  0.175035  0.231650  0.163535  0.143426  1.000000  \n",
       "\n",
       "[9452 rows x 9452 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simiraity_score_df = pd.DataFrame(simiity)\n",
    "simiraity_score_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "405a6de2-a6b4-47a8-9173-0455e027ed9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# treshold value of the similarity between users. If treshold > 0.5, similar users\n",
    "# returns the index of the similar user\n",
    "def similar_users(userid,simiraity_treshold = 0.5):\n",
    "    index = userid - 1\n",
    "    frame = simiraity_score_df[index]\n",
    "    a = frame[frame >= simiraity_treshold]\n",
    "    similar_users = a.index.values + 1 #Because index starts from 0 and our userid starts from 1\n",
    "    return similar_users\n",
    "\n",
    "# returns the movies list seen by the user\n",
    "def user_seen_movies(userid):\n",
    "    movie_list_index =  ratings[ratings[\"userId\"] == userid][\"movieId\"].values\n",
    "    return set(movie_list_index)\n",
    "\n",
    "def seen_movies_by_similar_users(userid):\n",
    "    similar_user_list = similar_users(userid=userid)\n",
    "    movie_list_index = []\n",
    "    for i in similar_user_list:\n",
    "        movie_list_index.extend(ratings[ratings[\"userId\"] == i][\"movieId\"].values)\n",
    "    return set(movie_list_index)\n",
    "\n",
    "\n",
    "def recommendations_based_upon_user(user_id):\n",
    "    user_set = user_seen_movies(userid = user_id)\n",
    "    all_set = seen_movies_by_similar_users(userid=user_id)\n",
    "    set_difference = all_set.difference(user_set)\n",
    "    rec_mov = []\n",
    "    for i in popular_data[\"movieId\"]:\n",
    "        if (i in set_difference):\n",
    "            rec_mov.append(i)\n",
    "    return rec_mov\n",
    "b = recommendations_based_upon_user(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "a9e332c6-aea6-48e7-972f-96dc00824d36",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       " 47148]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "b"
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