Recommendation engine-Final.ipynb

{
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   "cell_type": "markdown",
   "id": "da089183",
   "metadata": {},
   "source": [
    "# Problem statement: Build a recommender system by using cosine simillarties score."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3eb0811c",
   "metadata": {},
   "source": [
    "## A recommendation system : \n",
    "seeks to predict the preference of a user. In simple words, it suggests relevant items to users. Eg: In the case of Netflix which movie to watch, In the case of e-commerce which product to buy, or In the case of kindle which book to read, etc."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b3bad3e",
   "metadata": {},
   "source": [
    "## TYPES OF RECOMMENDATION SYSTEM\n",
    "    1. Content-Based Filtering: Here, relevant items are shown using the previously searched items by the users. The system tries to understand what the user wants and it looks in its database and finally tries to recommend different products that the user wants. \n",
    "    Model doesn’t need data of other users since recommendations are specific to a single user.\n",
    "    The model can Capture the specific Interests of the user and can recommend items that very few other users are interested in.\n",
    "    \n",
    "    2.Collaborative Based Filtering: Recommending the new items to users based on the interest and preference of other similar user. \n",
    "    For eg:- When we shop on Amazon it recommends new products saying “Customer who brought this also brought” \n",
    "    \n",
    "    2A.User-Based Collaborative Filtering: Suppose A purchased grapes, strawberry, watermelon, and orange and B purchased strawberry and watermelon. As A and B are similar users due to 2 similar fruits, B will be recommended Grapes and Orange. \n",
    "    \n",
    "    2B.Item-Based Collaborative Filtering: If watermelon is purchased by A, B, C but grapes are purchased by A & B, then C is being recommended grapes."
   ]
  },
  {
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   "outputs": [],
   "source": [
    "#importing necessary libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from sklearn.metrics import pairwise_distances\n",
    "from scipy.spatial.distance import cosine, correlation "
   ]
  },
  {
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   "execution_count": 2,
   "id": "10dd62c5",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>User.ID</th>\n",
       "      <th>Book.Title</th>\n",
       "      <th>Book.Rating</th>\n",
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      "text/plain": [
       "   Unnamed: 0  User.ID                                         Book.Title  \\\n",
       "0           1   276726                                Classical Mythology   \n",
       "1           2   276729                                       Clara Callan   \n",
       "2           3   276729                               Decision in Normandy   \n",
       "3           4   276736  Flu: The Story of the Great Influenza Pandemic...   \n",
       "4           5   276737                             The Mummies of Urumchi   \n",
       "\n",
       "   Book.Rating  \n",
       "0            5  \n",
       "1            3  \n",
       "2            6  \n",
       "3            8  \n",
       "4            6  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "book = pd.read_csv('book.csv', encoding=\"ISO-8859-1\") \n",
    "book.head() "
   ]
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>userid</th>\n",
       "      <th>title</th>\n",
       "      <th>rating</th>\n",
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       "      <td>Clara Callan</td>\n",
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      "text/plain": [
       "   userid                                              title  rating\n",
       "0  276726                                Classical Mythology       5\n",
       "1  276729                                       Clara Callan       3\n",
       "2  276729                               Decision in Normandy       6\n",
       "3  276736  Flu: The Story of the Great Influenza Pandemic...       8\n",
       "4  276737                             The Mummies of Urumchi       6"
      ]
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   "source": [
    "book = book.drop('Unnamed: 0', axis=1) \n",
    "book = book.rename(columns={'User.ID':'userid' , 'Book.Title':'title' ,'Book.Rating':'rating'} )\n",
    "book.head() "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4e3a95b",
   "metadata": {},
   "source": [
    "## Descriptive Statistics "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8aae3ec8",
   "metadata": {
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     "end_time": "2022-11-10T14:22:02.477807Z",
     "start_time": "2022-11-10T14:22:02.461804Z"
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10000, 3)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "book.shape "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "71212524",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:02.493502Z",
     "start_time": "2022-11-10T14:22:02.477807Z"
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2182"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#number of unique users in the dataset\n",
    "len(book.userid.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d4c92cd6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:02.509497Z",
     "start_time": "2022-11-10T14:22:02.493502Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9659"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#number of unique books in the dataset\n",
    "len(book.title.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7cd8577c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:02.533481Z",
     "start_time": "2022-11-10T14:22:02.509497Z"
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   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 10000 entries, 0 to 9999\n",
      "Data columns (total 3 columns):\n",
      " #   Column  Non-Null Count  Dtype \n",
      "---  ------  --------------  ----- \n",
      " 0   userid  10000 non-null  int64 \n",
      " 1   title   10000 non-null  object\n",
      " 2   rating  10000 non-null  int64 \n",
      "dtypes: int64(2), object(1)\n",
      "memory usage: 234.5+ KB\n"
     ]
    }
   ],
   "source": [
    "book.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a2cb4a6d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:02.549502Z",
     "start_time": "2022-11-10T14:22:02.533481Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    10000.00000\n",
       "mean         7.56630\n",
       "std          1.82152\n",
       "min          1.00000\n",
       "25%          7.00000\n",
       "50%          8.00000\n",
       "75%          9.00000\n",
       "max         10.00000\n",
       "Name: rating, dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "book.rating.describe()\n",
    "#no use of getting mean, median of userids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a6d23e2b",
   "metadata": {
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     "end_time": "2022-11-10T14:22:02.565498Z",
     "start_time": "2022-11-10T14:22:02.549502Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "userid    0\n",
       "title     0\n",
       "rating    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "book.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "856e8e00",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:02.581418Z",
     "start_time": "2022-11-10T14:22:02.565498Z"
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       "      <th></th>\n",
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       "Empty DataFrame\n",
       "Columns: [userid, title, rating]\n",
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   ],
   "source": [
    "book[book.index.duplicated()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "81e62143",
   "metadata": {
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     "end_time": "2022-11-10T14:22:02.613568Z",
     "start_time": "2022-11-10T14:22:02.581418Z"
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title\n",
       " Jason, Madison &amp                                                       8.0\n",
       " Other Stories;Merril;1985;McClelland &amp                                 6.0\n",
       " Repairing PC Drives &amp                                                  4.0\n",
       "'48                                                                        7.0\n",
       "'O Au No Keia: Voices from Hawai'I's Mahu and Transgender Communities      8.0\n",
       "                                                                          ... \n",
       "\\Surely You're Joking, Mr. Feynman!\\: Adventures of a Curious Character    8.0\n",
       "\\Well, there's your problem\\: Cartoons                                     9.0\n",
       "iI Paradiso Degli Orchi                                                    7.0\n",
       "stardust                                                                   5.0\n",
       "Ã?Â?bermorgen.                                                             4.0\n",
       "Name: rating, Length: 9659, dtype: float64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Average rating given to books\n",
    "book.groupby('title')['rating'].agg('mean')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "261a6691",
   "metadata": {
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     "end_time": "2022-11-10T14:22:02.629568Z",
     "start_time": "2022-11-10T14:22:02.613568Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title\n",
       " Jason, Madison &amp                                                       1\n",
       " Other Stories;Merril;1985;McClelland &amp                                 1\n",
       " Repairing PC Drives &amp                                                  1\n",
       "'48                                                                        1\n",
       "'O Au No Keia: Voices from Hawai'I's Mahu and Transgender Communities      1\n",
       "                                                                          ..\n",
       "\\Surely You're Joking, Mr. Feynman!\\: Adventures of a Curious Character    1\n",
       "\\Well, there's your problem\\: Cartoons                                     1\n",
       "iI Paradiso Degli Orchi                                                    1\n",
       "stardust                                                                   1\n",
       "Ã?Â?bermorgen.                                                             1\n",
       "Name: rating, Length: 9659, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Number of times rating given to a book\n",
    "book.groupby('title')['rating'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "863a8b6c",
   "metadata": {
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     "end_time": "2022-11-10T14:22:02.653568Z",
     "start_time": "2022-11-10T14:22:02.629568Z"
    }
   },
   "outputs": [],
   "source": [
    "a = pd.array(book.groupby('title')['rating'].count())\n",
    "b=pd.array(book.groupby('title')['rating'].agg('mean')) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "fa96b856",
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     "end_time": "2022-11-10T14:22:02.685702Z",
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       "      <th>Other Stories;Merril;1985;McClelland &amp;amp</th>\n",
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       "      <td>7.0</td>\n",
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       "      <th>'O Au No Keia: Voices from Hawai'I's Mahu and Transgender Communities</th>\n",
       "      <td>8.0</td>\n",
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       "      <th>\\Surely You're Joking, Mr. Feynman!\\: Adventures of a Curious Character</th>\n",
       "      <td>8.0</td>\n",
       "      <td>1</td>\n",
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       "      <th>\\Well, there's your problem\\: Cartoons</th>\n",
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       "      <th>iI Paradiso Degli Orchi</th>\n",
       "      <td>7.0</td>\n",
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       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
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       "      <th>Ã?Â?bermorgen.</th>\n",
       "      <td>4.0</td>\n",
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       "<p>9659 rows × 2 columns</p>\n",
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      "text/plain": [
       "                                                    Avg_rating  No_times_rated\n",
       "title                                                                         \n",
       " Jason, Madison &amp                                       8.0               1\n",
       " Other Stories;Merril;1985;McClelland &amp                 6.0               1\n",
       " Repairing PC Drives &amp                                  4.0               1\n",
       "'48                                                        7.0               1\n",
       "'O Au No Keia: Voices from Hawai'I's Mahu and T...         8.0               1\n",
       "...                                                        ...             ...\n",
       "\\Surely You're Joking, Mr. Feynman!\\: Adventure...         8.0               1\n",
       "\\Well, there's your problem\\: Cartoons                     9.0               1\n",
       "iI Paradiso Degli Orchi                                    7.0               1\n",
       "stardust                                                   5.0               1\n",
       "Ã?Â?bermorgen.                                             4.0               1\n",
       "\n",
       "[9659 rows x 2 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings = pd.DataFrame(book.groupby('title')['rating'].agg('mean')).iloc[:,1:]\n",
    "ratings['Avg_rating'] = b\n",
    "ratings['No_times_rated'] = a \n",
    "ratings "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "932fd595",
   "metadata": {},
   "source": [
    "# Data Visualisation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "98197bfe",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:02.822106Z",
     "start_time": "2022-11-10T14:22:02.685702Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,6))\n",
    "plt.hist(ratings.No_times_rated)\n",
    "plt.show()\n",
    "\n",
    "# Most of the observations are rated only once"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b785297d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:02.959462Z",
     "start_time": "2022-11-10T14:22:02.822106Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,6))\n",
    "plt.hist(ratings.Avg_rating, bins=50)\n",
    "plt.show()\n",
    "\n",
    "# Most of the ratings are 7, 8, 9, 10"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a844c5d",
   "metadata": {},
   "source": [
    "# Collaborative Recommender System Using Cosine Similarity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "dcab098e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:03.447923Z",
     "start_time": "2022-11-10T14:22:02.959462Z"
    }
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "title    Jason, Madison &amp   Other Stories;Merril;1985;McClelland &amp  \\\n",
       "userid                                                                     \n",
       "8                        0.0                                         0.0   \n",
       "9                        0.0                                         0.0   \n",
       "10                       0.0                                         0.0   \n",
       "12                       0.0                                         0.0   \n",
       "14                       0.0                                         0.0   \n",
       "...                      ...                                         ...   \n",
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       "278849                   0.0                                         0.0   \n",
       "278851                   0.0                                         0.0   \n",
       "278852                   0.0                                         0.0   \n",
       "278854                   0.0                                         0.0   \n",
       "\n",
       "title    Repairing PC Drives &amp  '48  \\\n",
       "userid                                   \n",
       "8                             0.0  0.0   \n",
       "9                             0.0  0.0   \n",
       "10                            0.0  0.0   \n",
       "12                            0.0  0.0   \n",
       "14                            0.0  0.0   \n",
       "...                           ...  ...   \n",
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       "278851                        0.0  0.0   \n",
       "278852                        0.0  0.0   \n",
       "278854                        0.0  0.0   \n",
       "\n",
       "title   'O Au No Keia: Voices from Hawai'I's Mahu and Transgender Communities  \\\n",
       "userid                                                                          \n",
       "8                                                     0.0                       \n",
       "9                                                     0.0                       \n",
       "10                                                    0.0                       \n",
       "12                                                    0.0                       \n",
       "14                                                    0.0                       \n",
       "...                                                   ...                       \n",
       "278846                                                0.0                       \n",
       "278849                                                0.0                       \n",
       "278851                                                0.0                       \n",
       "278852                                                0.0                       \n",
       "278854                                                0.0                       \n",
       "\n",
       "title   ...AND THE HORSE HE RODE IN ON : THE PEOPLE V. KENNETH STARR  \\\n",
       "userid                                                                 \n",
       "8                                                     0.0              \n",
       "9                                                     0.0              \n",
       "10                                                    0.0              \n",
       "12                                                    0.0              \n",
       "14                                                    0.0              \n",
       "...                                                   ...              \n",
       "278846                                                0.0              \n",
       "278849                                                0.0              \n",
       "278851                                                0.0              \n",
       "278852                                                0.0              \n",
       "278854                                                0.0              \n",
       "\n",
       "title   01-01-00: A Novel of the Millennium  \\\n",
       "userid                                        \n",
       "8                                       0.0   \n",
       "9                                       0.0   \n",
       "10                                      0.0   \n",
       "12                                      0.0   \n",
       "14                                      0.0   \n",
       "...                                     ...   \n",
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       "278851                                  0.0   \n",
       "278852                                  0.0   \n",
       "278854                                  0.0   \n",
       "\n",
       "title   1,401 More Things That P*Ss Me Off  10 Commandments Of Dating  \\\n",
       "userid                                                                  \n",
       "8                                      0.0                        0.0   \n",
       "9                                      0.0                        0.0   \n",
       "10                                     0.0                        0.0   \n",
       "12                                     0.0                        0.0   \n",
       "14                                     0.0                        0.0   \n",
       "...                                    ...                        ...   \n",
       "278846                                 0.0                        0.0   \n",
       "278849                                 0.0                        0.0   \n",
       "278851                                 0.0                        0.0   \n",
       "278852                                 0.0                        0.0   \n",
       "278854                                 0.0                        0.0   \n",
       "\n",
       "title   100 Great Fantasy Short, Short Stories  ...  \\\n",
       "userid                                          ...   \n",
       "8                                          0.0  ...   \n",
       "9                                          0.0  ...   \n",
       "10                                         0.0  ...   \n",
       "12                                         0.0  ...   \n",
       "14                                         0.0  ...   \n",
       "...                                        ...  ...   \n",
       "278846                                     0.0  ...   \n",
       "278849                                     0.0  ...   \n",
       "278851                                     0.0  ...   \n",
       "278852                                     0.0  ...   \n",
       "278854                                     0.0  ...   \n",
       "\n",
       "title   Zora Hurston and the Chinaberry Tree (Reading Rainbow Book)  \\\n",
       "userid                                                                \n",
       "8                                                     0.0             \n",
       "9                                                     0.0             \n",
       "10                                                    0.0             \n",
       "12                                                    0.0             \n",
       "14                                                    0.0             \n",
       "...                                                   ...             \n",
       "278846                                                0.0             \n",
       "278849                                                0.0             \n",
       "278851                                                0.0             \n",
       "278852                                                0.0             \n",
       "278854                                                0.0             \n",
       "\n",
       "title   \\Even Monkeys Fall from Trees\\ and Other Japanese Proverbs  \\\n",
       "userid                                                               \n",
       "8                                                     0.0            \n",
       "9                                                     0.0            \n",
       "10                                                    0.0            \n",
       "12                                                    0.0            \n",
       "14                                                    0.0            \n",
       "...                                                   ...            \n",
       "278846                                                0.0            \n",
       "278849                                                0.0            \n",
       "278851                                                0.0            \n",
       "278852                                                0.0            \n",
       "278854                                                0.0            \n",
       "\n",
       "title   \\I Won't Learn from You\\: And Other Thoughts on Creative Maladjustment  \\\n",
       "userid                                                                           \n",
       "8                                                     0.0                        \n",
       "9                                                     0.0                        \n",
       "10                                                    0.0                        \n",
       "12                                                    0.0                        \n",
       "14                                                    0.0                        \n",
       "...                                                   ...                        \n",
       "278846                                                0.0                        \n",
       "278849                                                0.0                        \n",
       "278851                                                0.0                        \n",
       "278852                                                0.0                        \n",
       "278854                                                0.0                        \n",
       "\n",
       "title   \\More More More,\\ Said the Baby  \\O\\ Is for Outlaw  \\\n",
       "userid                                                       \n",
       "8                                   0.0                0.0   \n",
       "9                                   0.0                0.0   \n",
       "10                                  0.0                0.0   \n",
       "12                                  0.0                0.0   \n",
       "14                                  0.0                0.0   \n",
       "...                                 ...                ...   \n",
       "278846                              0.0                0.0   \n",
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       "278851                              0.0                0.0   \n",
       "278852                              0.0                0.0   \n",
       "278854                              0.0                0.0   \n",
       "\n",
       "title   \\Surely You're Joking, Mr. Feynman!\\: Adventures of a Curious Character  \\\n",
       "userid                                                                            \n",
       "8                                                     0.0                         \n",
       "9                                                     0.0                         \n",
       "10                                                    0.0                         \n",
       "12                                                    0.0                         \n",
       "14                                                    0.0                         \n",
       "...                                                   ...                         \n",
       "278846                                                0.0                         \n",
       "278849                                                0.0                         \n",
       "278851                                                0.0                         \n",
       "278852                                                0.0                         \n",
       "278854                                                0.0                         \n",
       "\n",
       "title   \\Well, there's your problem\\: Cartoons  iI Paradiso Degli Orchi  \\\n",
       "userid                                                                    \n",
       "8                                          0.0                      0.0   \n",
       "9                                          0.0                      0.0   \n",
       "10                                         0.0                      0.0   \n",
       "12                                         0.0                      0.0   \n",
       "14                                         0.0                      0.0   \n",
       "...                                        ...                      ...   \n",
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       "\n",
       "title   stardust  Ã?Â?bermorgen.  \n",
       "userid                            \n",
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       "\n",
       "[2182 rows x 9659 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_book_df = book.pivot_table(index='userid' , columns='title', values='rating').fillna(0)\n",
    "user_book_df "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "aa5b5462",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:04.096083Z",
     "start_time": "2022-11-10T14:22:03.447923Z"
    }
   },
   "outputs": [],
   "source": [
    "#Calculating Cosine Similarity between Users\n",
    "user_sim = 1 - pairwise_distances(user_book_df.values,metric='cosine')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "e3e505bc",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:04.128286Z",
     "start_time": "2022-11-10T14:22:04.096083Z"
    }
   },
   "outputs": [
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       "      0     1     2     3     4     5     6     7     8     9     ...  2172  \\\n",
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       "\n",
       "      2173  2174  2175  2176  2177  2178  2179  2180  2181  \n",
       "0      0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0   0.0  \n",
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       "\n",
       "[2182 rows x 2182 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Store the results in a dataframe\n",
    "user_sim_df = pd.DataFrame(user_sim)\n",
    "user_sim_df "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "00da0221",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:04.161261Z",
     "start_time": "2022-11-10T14:22:04.128286Z"
    }
   },
   "outputs": [
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       "\n",
       "        278849  278851  278852  278854  \n",
       "8          0.0     0.0     0.0     0.0  \n",
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       "\n",
       "[2182 rows x 2182 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Set the index and column names to user ids \n",
    "user_sim_df.index = list(user_book_df.index)\n",
    "user_sim_df.columns = list(user_book_df.index)\n",
    "\n",
    "user_sim_df "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b7d74d77",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:04.193881Z",
     "start_time": "2022-11-10T14:22:04.161261Z"
    },
    "scrolled": false
   },
   "outputs": [
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      "text/plain": [
       "        8       9       10      12      14      16      17      19      \\\n",
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       "\n",
       "[2182 rows x 2182 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.fill_diagonal(user_sim, 0)\n",
    "user_sim_df "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "619c2ed3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:29.349030Z",
     "start_time": "2022-11-10T14:22:04.193881Z"
    }
   },
   "outputs": [],
   "source": [
    "#finding users with high similarity between them\n",
    "user = []\n",
    "user1 = []\n",
    "similar = []\n",
    "\n",
    "for cols in user_sim_df.columns:\n",
    "    for rows in user_sim_df.index:\n",
    "        if user_sim_df[cols][rows] > 0.01 :\n",
    "            user.append(cols)\n",
    "            user1.append(rows)\n",
    "            similar.append(user_sim_df[cols][rows])\n",
    "           "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "56e307e5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:29.365656Z",
     "start_time": "2022-11-10T14:22:29.350326Z"
    }
   },
   "outputs": [],
   "source": [
    "similar_users = pd.DataFrame()\n",
    "\n",
    "similar_users['user'] = user\n",
    "similar_users['user1'] = user1\n",
    "similar_users['similarity'] = similar "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c87a53ca",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:29.381942Z",
     "start_time": "2022-11-10T14:22:29.365656Z"
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       "      <th>695</th>\n",
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       "      <td>161373</td>\n",
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       "      <th>696</th>\n",
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       "      <td>276813</td>\n",
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       "       user   user1  similarity\n",
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       "\n",
       "[698 rows x 3 columns]"
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    "similar_users "
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   "id": "bde5ba64",
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     "end_time": "2022-11-10T14:22:29.397857Z",
     "start_time": "2022-11-10T14:22:29.381942Z"
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       "      <td>1348</td>\n",
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      "text/plain": [
       "       user   user1  similarity\n",
       "297    3951  276934    1.000000\n",
       "120    1559    1326    1.000000\n",
       "44      698  161645    1.000000\n",
       "45      705  162063    1.000000\n",
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       "519  277284    2355    1.000000\n",
       "99     1326    1559    1.000000\n",
       "415  162004     933    1.000000\n",
       "620  278161    2070    1.000000\n",
       "195    2355  277284    1.000000\n",
       "633  278206  276850    1.000000\n",
       "299    3952  276934    1.000000\n",
       "427  162063     705    1.000000\n",
       "470  276934    3952    1.000000\n",
       "298    3952    3951    1.000000\n",
       "469  276934    3951    1.000000\n",
       "296    3951    3952    1.000000\n",
       "168    2070  278161    1.000000\n",
       "445  276850  278206    1.000000\n",
       "335  160926    2576    1.000000\n",
       "333  160926    1348    0.752577"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "similar_users.sort_values(by=['similarity'], ascending=False).head(25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "6d8e9798",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:29.421856Z",
     "start_time": "2022-11-10T14:22:29.397857Z"
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   },
   "outputs": [
    {
     "data": {
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       "      <th>userid</th>\n",
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       "      <th>265</th>\n",
       "      <td>276934</td>\n",
       "      <td>The Wind in the Willows</td>\n",
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      "text/plain": [
       "      userid                    title  rating\n",
       "265   276934  The Wind in the Willows      10\n",
       "7792    3951  The Wind in the Willows       7"
      ]
     },
     "execution_count": 26,
     "metadata": {},
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    }
   ],
   "source": [
    "book[(book['userid']==3951) | (book['userid']==276934)] # similarity = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "77768a89",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-10T14:22:29.434885Z",
     "start_time": "2022-11-10T14:22:29.421856Z"
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   },
   "outputs": [
    {
     "data": {
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       "      <th>3915</th>\n",
       "      <td>1348</td>\n",
       "      <td>Fantastic Beasts and Where to Find Them</td>\n",
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       "      <th>3916</th>\n",
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      ],
      "text/plain": [
       "      userid                                    title  rating\n",
       "3915    1348  Fantastic Beasts and Where to Find Them       7\n",
       "3916    1348                                 Stardust       8\n",
       "8350  160926                                 Stardust       8"
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    "book[(book['userid']==160926) | (book['userid']==1348)] #similarity = 0.752577"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "915d4960",
   "metadata": {},
   "source": [
    "### Here, we will recommend 'Fantastic Beasts and Where to Find Them' to userid 160926 since user similar to him/her have watched(liked) it "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e785d66c",
   "metadata": {},
   "source": [
    "# Thank You"
   ]
  }
 ],
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