brs.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 31,
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.metrics.pairwise import cosine_similarity"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Harsh\\AppData\\Local\\Temp\\ipykernel_15092\\1923708693.py:1: DtypeWarning: Columns (3) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  books = pd.read_csv('Books.csv')\n"
     ]
    }
   ],
   "source": [
    "books = pd.read_csv('Books.csv')\n",
    "users = pd.read_csv('Users.csv')\n",
    "ratings = pd.read_csv('Ratings.csv')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "data": {
      "text/plain": "         ISBN                                         Book-Title  \\\n0  0195153448                                Classical Mythology   \n1  0002005018                                       Clara Callan   \n2  0060973129                               Decision in Normandy   \n3  0374157065  Flu: The Story of the Great Influenza Pandemic...   \n4  0393045218                             The Mummies of Urumchi   \n\n            Book-Author Year-Of-Publication                   Publisher  \\\n0    Mark P. O. Morford                2002     Oxford University Press   \n1  Richard Bruce Wright                2001       HarperFlamingo Canada   \n2          Carlo D'Este                1991             HarperPerennial   \n3      Gina Bari Kolata                1999        Farrar Straus Giroux   \n4       E. J. W. Barber                1999  W. W. Norton &amp; Company   \n\n                                         Image-URL-S  \\\n0  http://images.amazon.com/images/P/0195153448.0...   \n1  http://images.amazon.com/images/P/0002005018.0...   \n2  http://images.amazon.com/images/P/0060973129.0...   \n3  http://images.amazon.com/images/P/0374157065.0...   \n4  http://images.amazon.com/images/P/0393045218.0...   \n\n                                         Image-URL-M  \\\n0  http://images.amazon.com/images/P/0195153448.0...   \n1  http://images.amazon.com/images/P/0002005018.0...   \n2  http://images.amazon.com/images/P/0060973129.0...   \n3  http://images.amazon.com/images/P/0374157065.0...   \n4  http://images.amazon.com/images/P/0393045218.0...   \n\n                                         Image-URL-L  \n0  http://images.amazon.com/images/P/0195153448.0...  \n1  http://images.amazon.com/images/P/0002005018.0...  \n2  http://images.amazon.com/images/P/0060973129.0...  \n3  http://images.amazon.com/images/P/0374157065.0...  \n4  http://images.amazon.com/images/P/0393045218.0...  ",
      "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>ISBN</th>\n      <th>Book-Title</th>\n      <th>Book-Author</th>\n      <th>Year-Of-Publication</th>\n      <th>Publisher</th>\n      <th>Image-URL-S</th>\n      <th>Image-URL-M</th>\n      <th>Image-URL-L</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0195153448</td>\n      <td>Classical Mythology</td>\n      <td>Mark P. O. Morford</td>\n      <td>2002</td>\n      <td>Oxford University Press</td>\n      <td>http://images.amazon.com/images/P/0195153448.0...</td>\n      <td>http://images.amazon.com/images/P/0195153448.0...</td>\n      <td>http://images.amazon.com/images/P/0195153448.0...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0002005018</td>\n      <td>Clara Callan</td>\n      <td>Richard Bruce Wright</td>\n      <td>2001</td>\n      <td>HarperFlamingo Canada</td>\n      <td>http://images.amazon.com/images/P/0002005018.0...</td>\n      <td>http://images.amazon.com/images/P/0002005018.0...</td>\n      <td>http://images.amazon.com/images/P/0002005018.0...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0060973129</td>\n      <td>Decision in Normandy</td>\n      <td>Carlo D'Este</td>\n      <td>1991</td>\n      <td>HarperPerennial</td>\n      <td>http://images.amazon.com/images/P/0060973129.0...</td>\n      <td>http://images.amazon.com/images/P/0060973129.0...</td>\n      <td>http://images.amazon.com/images/P/0060973129.0...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0374157065</td>\n      <td>Flu: The Story of the Great Influenza Pandemic...</td>\n      <td>Gina Bari Kolata</td>\n      <td>1999</td>\n      <td>Farrar Straus Giroux</td>\n      <td>http://images.amazon.com/images/P/0374157065.0...</td>\n      <td>http://images.amazon.com/images/P/0374157065.0...</td>\n      <td>http://images.amazon.com/images/P/0374157065.0...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0393045218</td>\n      <td>The Mummies of Urumchi</td>\n      <td>E. J. W. Barber</td>\n      <td>1999</td>\n      <td>W. W. Norton &amp;amp; Company</td>\n      <td>http://images.amazon.com/images/P/0393045218.0...</td>\n      <td>http://images.amazon.com/images/P/0393045218.0...</td>\n      <td>http://images.amazon.com/images/P/0393045218.0...</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "books.head()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [
    {
     "data": {
      "text/plain": "   User-ID                            Location   Age\n0        1                  nyc, new york, usa   NaN\n1        2           stockton, california, usa  18.0\n2        3     moscow, yukon territory, russia   NaN\n3        4           porto, v.n.gaia, portugal  17.0\n4        5  farnborough, hants, united kingdom   NaN",
      "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>User-ID</th>\n      <th>Location</th>\n      <th>Age</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>nyc, new york, usa</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>stockton, california, usa</td>\n      <td>18.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3</td>\n      <td>moscow, yukon territory, russia</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4</td>\n      <td>porto, v.n.gaia, portugal</td>\n      <td>17.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5</td>\n      <td>farnborough, hants, united kingdom</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "users.head()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [
    {
     "data": {
      "text/plain": "   User-ID        ISBN  Book-Rating\n0   276725  034545104X            0\n1   276726  0155061224            5\n2   276727  0446520802            0\n3   276729  052165615X            3\n4   276729  0521795028            6",
      "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>User-ID</th>\n      <th>ISBN</th>\n      <th>Book-Rating</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>276725</td>\n      <td>034545104X</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>276726</td>\n      <td>0155061224</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>276727</td>\n      <td>0446520802</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>276729</td>\n      <td>052165615X</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>276729</td>\n      <td>0521795028</td>\n      <td>6</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings.head()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [
    {
     "data": {
      "text/plain": "ISBN                   0\nBook-Title             0\nBook-Author            1\nYear-Of-Publication    0\nPublisher              2\nImage-URL-S            0\nImage-URL-M            0\nImage-URL-L            3\ndtype: int64"
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "books.isnull().sum()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [
    {
     "data": {
      "text/plain": "User-ID          0\nLocation         0\nAge         110762\ndtype: int64"
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "users.isnull().sum()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [
    {
     "data": {
      "text/plain": "User-ID        0\nISBN           0\nBook-Rating    0\ndtype: int64"
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings.isnull().sum()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [
    {
     "data": {
      "text/plain": "0"
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "books.duplicated().sum()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [
    {
     "data": {
      "text/plain": "0"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "users.duplicated().sum()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "outputs": [
    {
     "data": {
      "text/plain": "0"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings.duplicated().sum()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "outputs": [
    {
     "data": {
      "text/plain": "   User-ID        ISBN  Book-Rating            Book-Title Book-Author  \\\n0   276725  034545104X            0  Flesh Tones: A Novel  M. J. Rose   \n1     2313  034545104X            5  Flesh Tones: A Novel  M. J. Rose   \n2     6543  034545104X            0  Flesh Tones: A Novel  M. J. Rose   \n3     8680  034545104X            5  Flesh Tones: A Novel  M. J. Rose   \n4    10314  034545104X            9  Flesh Tones: A Novel  M. J. Rose   \n\n  Year-Of-Publication         Publisher  \\\n0                2002  Ballantine Books   \n1                2002  Ballantine Books   \n2                2002  Ballantine Books   \n3                2002  Ballantine Books   \n4                2002  Ballantine Books   \n\n                                         Image-URL-S  \\\n0  http://images.amazon.com/images/P/034545104X.0...   \n1  http://images.amazon.com/images/P/034545104X.0...   \n2  http://images.amazon.com/images/P/034545104X.0...   \n3  http://images.amazon.com/images/P/034545104X.0...   \n4  http://images.amazon.com/images/P/034545104X.0...   \n\n                                         Image-URL-M  \\\n0  http://images.amazon.com/images/P/034545104X.0...   \n1  http://images.amazon.com/images/P/034545104X.0...   \n2  http://images.amazon.com/images/P/034545104X.0...   \n3  http://images.amazon.com/images/P/034545104X.0...   \n4  http://images.amazon.com/images/P/034545104X.0...   \n\n                                         Image-URL-L  \n0  http://images.amazon.com/images/P/034545104X.0...  \n1  http://images.amazon.com/images/P/034545104X.0...  \n2  http://images.amazon.com/images/P/034545104X.0...  \n3  http://images.amazon.com/images/P/034545104X.0...  \n4  http://images.amazon.com/images/P/034545104X.0...  ",
      "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>User-ID</th>\n      <th>ISBN</th>\n      <th>Book-Rating</th>\n      <th>Book-Title</th>\n      <th>Book-Author</th>\n      <th>Year-Of-Publication</th>\n      <th>Publisher</th>\n      <th>Image-URL-S</th>\n      <th>Image-URL-M</th>\n      <th>Image-URL-L</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>276725</td>\n      <td>034545104X</td>\n      <td>0</td>\n      <td>Flesh Tones: A Novel</td>\n      <td>M. J. Rose</td>\n      <td>2002</td>\n      <td>Ballantine Books</td>\n      <td>http://images.amazon.com/images/P/034545104X.0...</td>\n      <td>http://images.amazon.com/images/P/034545104X.0...</td>\n      <td>http://images.amazon.com/images/P/034545104X.0...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2313</td>\n      <td>034545104X</td>\n      <td>5</td>\n      <td>Flesh Tones: A Novel</td>\n      <td>M. J. Rose</td>\n      <td>2002</td>\n      <td>Ballantine Books</td>\n      <td>http://images.amazon.com/images/P/034545104X.0...</td>\n      <td>http://images.amazon.com/images/P/034545104X.0...</td>\n      <td>http://images.amazon.com/images/P/034545104X.0...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>6543</td>\n      <td>034545104X</td>\n      <td>0</td>\n      <td>Flesh Tones: A Novel</td>\n      <td>M. J. Rose</td>\n      <td>2002</td>\n      <td>Ballantine Books</td>\n      <td>http://images.amazon.com/images/P/034545104X.0...</td>\n      <td>http://images.amazon.com/images/P/034545104X.0...</td>\n      <td>http://images.amazon.com/images/P/034545104X.0...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>8680</td>\n      <td>034545104X</td>\n      <td>5</td>\n      <td>Flesh Tones: A Novel</td>\n      <td>M. J. Rose</td>\n      <td>2002</td>\n      <td>Ballantine Books</td>\n      <td>http://images.amazon.com/images/P/034545104X.0...</td>\n      <td>http://images.amazon.com/images/P/034545104X.0...</td>\n      <td>http://images.amazon.com/images/P/034545104X.0...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>10314</td>\n      <td>034545104X</td>\n      <td>9</td>\n      <td>Flesh Tones: A Novel</td>\n      <td>M. J. Rose</td>\n      <td>2002</td>\n      <td>Ballantine Books</td>\n      <td>http://images.amazon.com/images/P/034545104X.0...</td>\n      <td>http://images.amazon.com/images/P/034545104X.0...</td>\n      <td>http://images.amazon.com/images/P/034545104X.0...</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''populartiy based recommender system'''\n",
    "ratings_with_name = ratings.merge(books,on='ISBN')\n",
    "ratings_with_name.head()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "outputs": [
    {
     "data": {
      "text/plain": "                                               Book-Title  num_ratings\n0        A Light in the Storm: The Civil War Diary of ...            4\n1                                   Always Have Popsicles            1\n2                    Apple Magic (The Collector's series)            1\n3        Ask Lily (Young Women of Faith: Lily Series, ...            1\n4        Beyond IBM: Leadership Marketing and Finance ...            1\n...                                                   ...          ...\n241066                                      Ã?Â?lpiraten.            2\n241067                     Ã?Â?rger mit Produkt X. Roman.            4\n241068                                Ã?Â?sterlich leben.            1\n241069                              Ã?Â?stlich der Berge.            3\n241070                                  Ã?Â?thique en toc            2\n\n[241071 rows x 2 columns]",
      "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>Book-Title</th>\n      <th>num_ratings</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>A Light in the Storm: The Civil War Diary of ...</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Always Have Popsicles</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Apple Magic (The Collector's series)</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Ask Lily (Young Women of Faith: Lily Series, ...</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Beyond IBM: Leadership Marketing and Finance ...</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>241066</th>\n      <td>Ã?Â?lpiraten.</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>241067</th>\n      <td>Ã?Â?rger mit Produkt X. Roman.</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>241068</th>\n      <td>Ã?Â?sterlich leben.</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>241069</th>\n      <td>Ã?Â?stlich der Berge.</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>241070</th>\n      <td>Ã?Â?thique en toc</td>\n      <td>2</td>\n    </tr>\n  </tbody>\n</table>\n<p>241071 rows × 2 columns</p>\n</div>"
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_rating_df = ratings_with_name.groupby('Book-Title').count()['Book-Rating'].reset_index()\n",
    "num_rating_df.rename(columns={'Book-Rating':'num_ratings'},inplace=True)\n",
    "num_rating_df"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Harsh\\AppData\\Local\\Temp\\ipykernel_15092\\2648976164.py:1: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  avg_rating_df = ratings_with_name.groupby('Book-Title').mean()['Book-Rating'].reset_index()\n"
     ]
    },
    {
     "data": {
      "text/plain": "                                               Book-Title  avg_rating\n0        A Light in the Storm: The Civil War Diary of ...    2.250000\n1                                   Always Have Popsicles    0.000000\n2                    Apple Magic (The Collector's series)    0.000000\n3        Ask Lily (Young Women of Faith: Lily Series, ...    8.000000\n4        Beyond IBM: Leadership Marketing and Finance ...    0.000000\n...                                                   ...         ...\n241066                                      Ã?Â?lpiraten.    0.000000\n241067                     Ã?Â?rger mit Produkt X. Roman.    5.250000\n241068                                Ã?Â?sterlich leben.    7.000000\n241069                              Ã?Â?stlich der Berge.    2.666667\n241070                                  Ã?Â?thique en toc    4.000000\n\n[241071 rows x 2 columns]",
      "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>Book-Title</th>\n      <th>avg_rating</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>A Light in the Storm: The Civil War Diary of ...</td>\n      <td>2.250000</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Always Have Popsicles</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Apple Magic (The Collector's series)</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Ask Lily (Young Women of Faith: Lily Series, ...</td>\n      <td>8.000000</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Beyond IBM: Leadership Marketing and Finance ...</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>241066</th>\n      <td>Ã?Â?lpiraten.</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>241067</th>\n      <td>Ã?Â?rger mit Produkt X. Roman.</td>\n      <td>5.250000</td>\n    </tr>\n    <tr>\n      <th>241068</th>\n      <td>Ã?Â?sterlich leben.</td>\n      <td>7.000000</td>\n    </tr>\n    <tr>\n      <th>241069</th>\n      <td>Ã?Â?stlich der Berge.</td>\n      <td>2.666667</td>\n    </tr>\n    <tr>\n      <th>241070</th>\n      <td>Ã?Â?thique en toc</td>\n      <td>4.000000</td>\n    </tr>\n  </tbody>\n</table>\n<p>241071 rows × 2 columns</p>\n</div>"
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg_rating_df = ratings_with_name.groupby('Book-Title').mean()['Book-Rating'].reset_index()\n",
    "avg_rating_df.rename(columns={'Book-Rating':'avg_rating'},inplace=True)\n",
    "avg_rating_df"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "outputs": [
    {
     "data": {
      "text/plain": "                                               Book-Title  num_ratings  \\\n0        A Light in the Storm: The Civil War Diary of ...            4   \n1                                   Always Have Popsicles            1   \n2                    Apple Magic (The Collector's series)            1   \n3        Ask Lily (Young Women of Faith: Lily Series, ...            1   \n4        Beyond IBM: Leadership Marketing and Finance ...            1   \n...                                                   ...          ...   \n241066                                      Ã?Â?lpiraten.            2   \n241067                     Ã?Â?rger mit Produkt X. Roman.            4   \n241068                                Ã?Â?sterlich leben.            1   \n241069                              Ã?Â?stlich der Berge.            3   \n241070                                  Ã?Â?thique en toc            2   \n\n        avg_rating  \n0         2.250000  \n1         0.000000  \n2         0.000000  \n3         8.000000  \n4         0.000000  \n...            ...  \n241066    0.000000  \n241067    5.250000  \n241068    7.000000  \n241069    2.666667  \n241070    4.000000  \n\n[241071 rows x 3 columns]",
      "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>Book-Title</th>\n      <th>num_ratings</th>\n      <th>avg_rating</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>A Light in the Storm: The Civil War Diary of ...</td>\n      <td>4</td>\n      <td>2.250000</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Always Have Popsicles</td>\n      <td>1</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Apple Magic (The Collector's series)</td>\n      <td>1</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Ask Lily (Young Women of Faith: Lily Series, ...</td>\n      <td>1</td>\n      <td>8.000000</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Beyond IBM: Leadership Marketing and Finance ...</td>\n      <td>1</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>241066</th>\n      <td>Ã?Â?lpiraten.</td>\n      <td>2</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>241067</th>\n      <td>Ã?Â?rger mit Produkt X. Roman.</td>\n      <td>4</td>\n      <td>5.250000</td>\n    </tr>\n    <tr>\n      <th>241068</th>\n      <td>Ã?Â?sterlich leben.</td>\n      <td>1</td>\n      <td>7.000000</td>\n    </tr>\n    <tr>\n      <th>241069</th>\n      <td>Ã?Â?stlich der Berge.</td>\n      <td>3</td>\n      <td>2.666667</td>\n    </tr>\n    <tr>\n      <th>241070</th>\n      <td>Ã?Â?thique en toc</td>\n      <td>2</td>\n      <td>4.000000</td>\n    </tr>\n  </tbody>\n</table>\n<p>241071 rows × 3 columns</p>\n</div>"
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "popular_df = num_rating_df.merge(avg_rating_df,on='Book-Title')\n",
    "popular_df"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "outputs": [],
   "source": [
    "popular_df = popular_df[popular_df['num_ratings']>=250].sort_values('avg_rating',ascending=False).head(50)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "outputs": [],
   "source": [
    "popular_df = popular_df.merge(books,on='Book-Title').drop_duplicates('Book-Title')[['Book-Title','Book-Author','Image-URL-M','num_ratings','avg_rating']]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "outputs": [
    {
     "data": {
      "text/plain": "'http://images.amazon.com/images/P/0439136350.01.MZZZZZZZ.jpg'"
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "popular_df['Image-URL-M'][0]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "outputs": [],
   "source": [
    "'''Collaborative Filtering Based Recommender System'''\n",
    "\n",
    "x = ratings_with_name.groupby('User-ID').count()['Book-Rating'] > 200\n",
    "padhe_likhe_users = x[x].index"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "outputs": [],
   "source": [
    "filtered_rating = ratings_with_name[ratings_with_name['User-ID'].isin(padhe_likhe_users)]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "outputs": [],
   "source": [
    "y = filtered_rating.groupby('Book-Title').count()['Book-Rating']>=50\n",
    "famous_books = y[y].index"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "outputs": [],
   "source": [
    "final_ratings = filtered_rating[filtered_rating['Book-Title'].isin(famous_books)]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "outputs": [],
   "source": [
    "pt = final_ratings.pivot_table(index='Book-Title',columns='User-ID',values='Book-Rating')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "outputs": [
    {
     "data": {
      "text/plain": "User-ID              254     2276    2766    2977    3363    4017    4385    \\\nBook-Title                                                                    \n1984                    9.0     0.0     0.0     0.0     0.0     0.0     0.0   \n1st to Die: A Novel     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n2nd Chance              0.0    10.0     0.0     0.0     0.0     0.0     0.0   \n4 Blondes               0.0     0.0     0.0     0.0     0.0     0.0     0.0   \nA Bend in the Road      0.0     0.0     7.0     0.0     0.0     0.0     0.0   \n\nUser-ID              6251    6323    6543    ...  271705  273979  274004  \\\nBook-Title                                   ...                           \n1984                    0.0     0.0     0.0  ...    10.0     0.0     0.0   \n1st to Die: A Novel     0.0     0.0     9.0  ...     0.0     0.0     0.0   \n2nd Chance              0.0     0.0     0.0  ...     0.0     0.0     0.0   \n4 Blondes               0.0     0.0     0.0  ...     0.0     0.0     0.0   \nA Bend in the Road      0.0     0.0     0.0  ...     0.0     0.0     0.0   \n\nUser-ID              274061  274301  274308  275970  277427  277639  278418  \nBook-Title                                                                   \n1984                    0.0     0.0     0.0     0.0     0.0     0.0     0.0  \n1st to Die: A Novel     0.0     0.0     0.0     0.0     0.0     0.0     0.0  \n2nd Chance              0.0     0.0     0.0     0.0     0.0     0.0     0.0  \n4 Blondes               0.0     0.0     0.0     0.0     0.0     0.0     0.0  \nA Bend in the Road      0.0     0.0     0.0     0.0     0.0     0.0     0.0  \n\n[5 rows x 810 columns]",
      "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>User-ID</th>\n      <th>254</th>\n      <th>2276</th>\n      <th>2766</th>\n      <th>2977</th>\n      <th>3363</th>\n      <th>4017</th>\n      <th>4385</th>\n      <th>6251</th>\n      <th>6323</th>\n      <th>6543</th>\n      <th>...</th>\n      <th>271705</th>\n      <th>273979</th>\n      <th>274004</th>\n      <th>274061</th>\n      <th>274301</th>\n      <th>274308</th>\n      <th>275970</th>\n      <th>277427</th>\n      <th>277639</th>\n      <th>278418</th>\n    </tr>\n    <tr>\n      <th>Book-Title</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1984</th>\n      <td>9.0</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      <td>...</td>\n      <td>10.0</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>1st to Die: A Novel</th>\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>9.0</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>2nd Chance</th>\n      <td>0.0</td>\n      <td>10.0</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>...</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>4 Blondes</th>\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      <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>A Bend in the Road</th>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>7.0</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  </tbody>\n</table>\n<p>5 rows × 810 columns</p>\n</div>"
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pt.fillna(0,inplace=True)\n",
    "pt.head()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "outputs": [
    {
     "data": {
      "text/plain": "array([[1.        , 0.10255025, 0.01220856, ..., 0.12110367, 0.07347567,\n        0.04316046],\n       [0.10255025, 1.        , 0.2364573 , ..., 0.07446129, 0.16773875,\n        0.14263397],\n       [0.01220856, 0.2364573 , 1.        , ..., 0.04558758, 0.04938579,\n        0.10796119],\n       ...,\n       [0.12110367, 0.07446129, 0.04558758, ..., 1.        , 0.07085128,\n        0.0196177 ],\n       [0.07347567, 0.16773875, 0.04938579, ..., 0.07085128, 1.        ,\n        0.10602962],\n       [0.04316046, 0.14263397, 0.10796119, ..., 0.0196177 , 0.10602962,\n        1.        ]])"
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "similarity_scores = cosine_similarity(pt)\n",
    "similarity_scores"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "outputs": [],
   "source": [
    "def recommend(book_name):\n",
    "    # index fetch\n",
    "    index = np.where(pt.index==book_name)[0][0]\n",
    "    similar_items = sorted(list(enumerate(similarity_scores[index])),key=lambda x:x[1],reverse=True)[1:5]\n",
    "\n",
    "    data = []\n",
    "    for i in similar_items:\n",
    "        item = []\n",
    "        temp_df = books[books['Book-Title'] == pt.index[i[0]]]\n",
    "        item.extend(list(temp_df.drop_duplicates('Book-Title')['Book-Title'].values))\n",
    "        item.extend(list(temp_df.drop_duplicates('Book-Title')['Book-Author'].values))\n",
    "        item.extend(list(temp_df.drop_duplicates('Book-Title')['Image-URL-M'].values))\n",
    "\n",
    "        data.append(item)\n",
    "\n",
    "    return data"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "outputs": [
    {
     "data": {
      "text/plain": "[['Animal Farm',\n  'George Orwell',\n  'http://images.amazon.com/images/P/0451526341.01.MZZZZZZZ.jpg'],\n [\"The Handmaid's Tale\",\n  'Margaret Atwood',\n  'http://images.amazon.com/images/P/0449212602.01.MZZZZZZZ.jpg'],\n ['Brave New World',\n  'Aldous Huxley',\n  'http://images.amazon.com/images/P/0060809833.01.MZZZZZZZ.jpg'],\n ['The Vampire Lestat (Vampire Chronicles, Book II)',\n  'ANNE RICE',\n  'http://images.amazon.com/images/P/0345313860.01.MZZZZZZZ.jpg']]"
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recommend('1984')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "outputs": [],
   "source": [
    "import pickle\n",
    "pickle.dump(popular_df,open('popular.pkl','wb'))"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "outputs": [],
   "source": [
    "pickle.dump(pt,open('pt.pkl','wb'))\n",
    "pickle.dump(books,open('books.pkl','wb'))\n",
    "pickle.dump(similarity_scores,open('similarity_scores.pkl','wb'))"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
 "metadata": {
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   "display_name": "Python 3",
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   "name": "python",
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   "pygments_lexer": "ipython2",
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 },
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