BOOK_Recommendation_Using_KNN.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy.sparse import csr_matrix\n",
    "import sklearn\n",
    "from sklearn.decomposition import TruncatedSVD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "b'Skipping line 6452: expected 8 fields, saw 9\\nSkipping line 43667: expected 8 fields, saw 10\\nSkipping line 51751: expected 8 fields, saw 9\\n'\n",
      "b'Skipping line 92038: expected 8 fields, saw 9\\nSkipping line 104319: expected 8 fields, saw 9\\nSkipping line 121768: expected 8 fields, saw 9\\n'\n",
      "b'Skipping line 144058: expected 8 fields, saw 9\\nSkipping line 150789: expected 8 fields, saw 9\\nSkipping line 157128: expected 8 fields, saw 9\\nSkipping line 180189: expected 8 fields, saw 9\\nSkipping line 185738: expected 8 fields, saw 9\\n'\n",
      "b'Skipping line 209388: expected 8 fields, saw 9\\nSkipping line 220626: expected 8 fields, saw 9\\nSkipping line 227933: expected 8 fields, saw 11\\nSkipping line 228957: expected 8 fields, saw 10\\nSkipping line 245933: expected 8 fields, saw 9\\nSkipping line 251296: expected 8 fields, saw 9\\nSkipping line 259941: expected 8 fields, saw 9\\nSkipping line 261529: expected 8 fields, saw 9\\n'\n",
      "c:\\users\\prince_shaks\\appdata\\local\\programs\\python\\python36\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3072: DtypeWarning: Columns (3) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<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>"
      ],
      "text/plain": [
       "         ISBN                                         Book-Title  \\\n",
       "0  0195153448                                Classical Mythology   \n",
       "1  0002005018                                       Clara Callan   \n",
       "2  0060973129                               Decision in Normandy   \n",
       "3  0374157065  Flu: The Story of the Great Influenza Pandemic...   \n",
       "4  0393045218                             The Mummies of Urumchi   \n",
       "\n",
       "            Book-Author Year-Of-Publication                   Publisher  \\\n",
       "0    Mark P. O. Morford                2002     Oxford University Press   \n",
       "1  Richard Bruce Wright                2001       HarperFlamingo Canada   \n",
       "2          Carlo D'Este                1991             HarperPerennial   \n",
       "3      Gina Bari Kolata                1999        Farrar Straus Giroux   \n",
       "4       E. J. W. Barber                1999  W. W. Norton &amp; Company   \n",
       "\n",
       "                                         Image-URL-S  \\\n",
       "0  http://images.amazon.com/images/P/0195153448.0...   \n",
       "1  http://images.amazon.com/images/P/0002005018.0...   \n",
       "2  http://images.amazon.com/images/P/0060973129.0...   \n",
       "3  http://images.amazon.com/images/P/0374157065.0...   \n",
       "4  http://images.amazon.com/images/P/0393045218.0...   \n",
       "\n",
       "                                         Image-URL-M  \\\n",
       "0  http://images.amazon.com/images/P/0195153448.0...   \n",
       "1  http://images.amazon.com/images/P/0002005018.0...   \n",
       "2  http://images.amazon.com/images/P/0060973129.0...   \n",
       "3  http://images.amazon.com/images/P/0374157065.0...   \n",
       "4  http://images.amazon.com/images/P/0393045218.0...   \n",
       "\n",
       "                                         Image-URL-L  \n",
       "0  http://images.amazon.com/images/P/0195153448.0...  \n",
       "1  http://images.amazon.com/images/P/0002005018.0...  \n",
       "2  http://images.amazon.com/images/P/0060973129.0...  \n",
       "3  http://images.amazon.com/images/P/0374157065.0...  \n",
       "4  http://images.amazon.com/images/P/0393045218.0...  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "book = pd.read_csv('BX-Books.csv', sep =';', error_bad_lines = False, encoding = 'latin-1')\n",
    "book.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "book.columns = ['ISBN','Book-Title','Book-Author', 'Year-Of-Publication','Publisher','Image-URL-S','Image-URL-M','Image-URL-L']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <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",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>nyc, new york, usa</td>\n",
       "      <td>NaN</td>\n",
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       "    <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>"
      ],
      "text/plain": [
       "   User-ID                            Location   Age\n",
       "0        1                  nyc, new york, usa   NaN\n",
       "1        2           stockton, california, usa  18.0\n",
       "2        3     moscow, yukon territory, russia   NaN\n",
       "3        4           porto, v.n.gaia, portugal  17.0\n",
       "4        5  farnborough, hants, united kingdom   NaN"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "book_user = pd.read_csv('BX-Users.csv', sep =';', error_bad_lines = False, encoding = 'latin-1')\n",
    "book_user.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "book_user.columns = ['User-ID', 'Location', 'Age']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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",
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      ],
      "text/plain": [
       "   User-ID        ISBN  Book-Rating\n",
       "0   276725  034545104X            0\n",
       "1   276726  0155061224            5\n",
       "2   276727  0446520802            0\n",
       "3   276729  052165615X            3\n",
       "4   276729  0521795028            6"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Rating = pd.read_csv('BX-Book-Ratings.csv', sep =';', error_bad_lines = False, encoding = 'latin-1')\n",
    "Rating.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "Rating.columns = ['User-ID','ISBN','Book-Rating']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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>"
      ],
      "text/plain": [
       "   User-ID        ISBN  Book-Rating            Book-Title Book-Author  \\\n",
       "0   276725  034545104X            0  Flesh Tones: A Novel  M. J. Rose   \n",
       "1     2313  034545104X            5  Flesh Tones: A Novel  M. J. Rose   \n",
       "2     6543  034545104X            0  Flesh Tones: A Novel  M. J. Rose   \n",
       "3     8680  034545104X            5  Flesh Tones: A Novel  M. J. Rose   \n",
       "4    10314  034545104X            9  Flesh Tones: A Novel  M. J. Rose   \n",
       "\n",
       "  Year-Of-Publication         Publisher  \\\n",
       "0                2002  Ballantine Books   \n",
       "1                2002  Ballantine Books   \n",
       "2                2002  Ballantine Books   \n",
       "3                2002  Ballantine Books   \n",
       "4                2002  Ballantine Books   \n",
       "\n",
       "                                         Image-URL-S  \\\n",
       "0  http://images.amazon.com/images/P/034545104X.0...   \n",
       "1  http://images.amazon.com/images/P/034545104X.0...   \n",
       "2  http://images.amazon.com/images/P/034545104X.0...   \n",
       "3  http://images.amazon.com/images/P/034545104X.0...   \n",
       "4  http://images.amazon.com/images/P/034545104X.0...   \n",
       "\n",
       "                                         Image-URL-M  \\\n",
       "0  http://images.amazon.com/images/P/034545104X.0...   \n",
       "1  http://images.amazon.com/images/P/034545104X.0...   \n",
       "2  http://images.amazon.com/images/P/034545104X.0...   \n",
       "3  http://images.amazon.com/images/P/034545104X.0...   \n",
       "4  http://images.amazon.com/images/P/034545104X.0...   \n",
       "\n",
       "                                         Image-URL-L  \n",
       "0  http://images.amazon.com/images/P/034545104X.0...  \n",
       "1  http://images.amazon.com/images/P/034545104X.0...  \n",
       "2  http://images.amazon.com/images/P/034545104X.0...  \n",
       "3  http://images.amazon.com/images/P/034545104X.0...  \n",
       "4  http://images.amazon.com/images/P/034545104X.0...  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#since book and Rating had common column ISBN we can use that\n",
    "Book_Rating = pd.merge(Rating, book, on='ISBN')\n",
    "Book_Rating.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns = ['Book-Author', 'Year-Of-Publication','Publisher','Image-URL-S','Image-URL-M','Image-URL-L']\n",
    "Book_Rating = Book_Rating.drop(columns, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>User-ID</th>\n",
       "      <th>ISBN</th>\n",
       "      <th>Book-Rating</th>\n",
       "      <th>Book-Title</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",
       "    </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",
       "    </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",
       "    </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",
       "    </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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   User-ID        ISBN  Book-Rating            Book-Title\n",
       "0   276725  034545104X            0  Flesh Tones: A Novel\n",
       "1     2313  034545104X            5  Flesh Tones: A Novel\n",
       "2     6543  034545104X            0  Flesh Tones: A Novel\n",
       "3     8680  034545104X            5  Flesh Tones: A Novel\n",
       "4    10314  034545104X            9  Flesh Tones: A Novel"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Book_Rating.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "Book_Rating = Book_Rating.dropna(axis=0, subset = ['Book-Title'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Book-Title</th>\n",
       "      <th>totalRatingCount</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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Book-Title  totalRatingCount\n",
       "0   A Light in the Storm: The Civil War Diary of ...                 4\n",
       "1                              Always Have Popsicles                 1\n",
       "2               Apple Magic (The Collector's series)                 1\n",
       "3   Ask Lily (Young Women of Faith: Lily Series, ...                 1\n",
       "4   Beyond IBM: Leadership Marketing and Finance ...                 1"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "book_ratingCount = (Book_Rating.\n",
    "     groupby(by = ['Book-Title'])['Book-Rating'].\n",
    "     count().\n",
    "     reset_index().\n",
    "     rename(columns = {'Book-Rating': 'totalRatingCount'})\n",
    "     [['Book-Title', 'totalRatingCount']]\n",
    "    )\n",
    "book_ratingCount.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>User-ID</th>\n",
       "      <th>ISBN</th>\n",
       "      <th>Book-Rating</th>\n",
       "      <th>Book-Title</th>\n",
       "      <th>totalRatingCount</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>60</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>60</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>60</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>60</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>60</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   User-ID        ISBN  Book-Rating            Book-Title  totalRatingCount\n",
       "0   276725  034545104X            0  Flesh Tones: A Novel                60\n",
       "1     2313  034545104X            5  Flesh Tones: A Novel                60\n",
       "2     6543  034545104X            0  Flesh Tones: A Novel                60\n",
       "3     8680  034545104X            5  Flesh Tones: A Novel                60\n",
       "4    10314  034545104X            9  Flesh Tones: A Novel                60"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Rating_totalRatingCount = Book_Rating.merge(book_ratingCount, left_on = 'Book-Title', right_on = 'Book-Title', how = 'left')\n",
    "Rating_totalRatingCount.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "count   241071.000\n",
      "mean         4.277\n",
      "std         16.739\n",
      "min          1.000\n",
      "25%          1.000\n",
      "50%          1.000\n",
      "75%          3.000\n",
      "max       2502.000\n",
      "Name: totalRatingCount, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "pd.set_option('display.float_format', lambda x: '%.3f' % x)\n",
    "print(book_ratingCount['totalRatingCount'].describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.900    7.000\n",
      "0.910    8.000\n",
      "0.920    9.000\n",
      "0.930   10.000\n",
      "0.940   11.000\n",
      "0.950   13.000\n",
      "0.960   16.000\n",
      "0.970   20.000\n",
      "0.980   29.000\n",
      "0.990   50.000\n",
      "Name: totalRatingCount, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(book_ratingCount['totalRatingCount'].quantile(np.arange(.9, 1, .01)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>User-ID</th>\n",
       "      <th>ISBN</th>\n",
       "      <th>Book-Rating</th>\n",
       "      <th>Book-Title</th>\n",
       "      <th>totalRatingCount</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>60</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>60</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>60</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>60</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>60</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   User-ID        ISBN  Book-Rating            Book-Title  totalRatingCount\n",
       "0   276725  034545104X            0  Flesh Tones: A Novel                60\n",
       "1     2313  034545104X            5  Flesh Tones: A Novel                60\n",
       "2     6543  034545104X            0  Flesh Tones: A Novel                60\n",
       "3     8680  034545104X            5  Flesh Tones: A Novel                60\n",
       "4    10314  034545104X            9  Flesh Tones: A Novel                60"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Rating_threshold = 50\n",
    "rating_popular_book = Rating_totalRatingCount.query('totalRatingCount >= @Rating_threshold')\n",
    "rating_popular_book.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>User-ID</th>\n",
       "      <th>ISBN</th>\n",
       "      <th>Book-Rating</th>\n",
       "      <th>Book-Title</th>\n",
       "      <th>totalRatingCount</th>\n",
       "      <th>Location</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>60</td>\n",
       "      <td>tyler, texas, usa</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>60</td>\n",
       "      <td>cincinnati, ohio, usa</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>60</td>\n",
       "      <td>strafford, missouri, usa</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>60</td>\n",
       "      <td>st. charles county, missouri, usa</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>60</td>\n",
       "      <td>beaverton, oregon, usa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   User-ID        ISBN  Book-Rating            Book-Title  totalRatingCount  \\\n",
       "0   276725  034545104X            0  Flesh Tones: A Novel                60   \n",
       "1     2313  034545104X            5  Flesh Tones: A Novel                60   \n",
       "2     6543  034545104X            0  Flesh Tones: A Novel                60   \n",
       "3     8680  034545104X            5  Flesh Tones: A Novel                60   \n",
       "4    10314  034545104X            9  Flesh Tones: A Novel                60   \n",
       "\n",
       "                            Location  \n",
       "0                  tyler, texas, usa  \n",
       "1              cincinnati, ohio, usa  \n",
       "2           strafford, missouri, usa  \n",
       "3  st. charles county, missouri, usa  \n",
       "4             beaverton, oregon, usa  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined = rating_popular_book.merge(book_user, left_on = 'User-ID', right_on = 'User-ID', how = 'left')\n",
    "us_india_user_rating = combined[combined['Location'].str.contains(\"usa|india\")]\n",
    "us_india_user_rating=us_india_user_rating.drop('Age', axis=1)\n",
    "us_india_user_rating.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial dataframe shape (225207, 6)\n",
      "New dataframe shape (222702, 6)\n",
      "Removed 2505 rows\n"
     ]
    }
   ],
   "source": [
    "if not us_india_user_rating[us_india_user_rating.duplicated(['User-ID', 'Book-Title'])].empty:\n",
    "    initial_rows = us_india_user_rating.shape[0]\n",
    "\n",
    "    print('Initial dataframe shape {0}'.format(us_india_user_rating.shape))\n",
    "    us_india_user_rating = us_india_user_rating.drop_duplicates(['User-ID', 'Book-Title'])\n",
    "    current_rows = us_india_user_rating.shape[0]\n",
    "    print('New dataframe shape {0}'.format(us_india_user_rating.shape))\n",
    "    print('Removed {0} rows'.format(initial_rows - current_rows))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "us_india_user_rating_pivot = us_india_user_rating.pivot(index = 'Book-Title', columns = 'User-ID', values = 'Book-Rating').fillna(0)\n",
    "us_india_user_rating_matrix = csr_matrix(us_india_user_rating_pivot.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NearestNeighbors(algorithm='brute', metric='cosine')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.neighbors import NearestNeighbors\n",
    "\n",
    "model_knn = NearestNeighbors(metric = 'cosine', algorithm = 'brute')\n",
    "model_knn.fit(us_india_user_rating_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recommendations for The Experiment:\n",
      "\n",
      "1: Dead Famous, with distance of 0.8372742520232713:\n",
      "2: Whisper of Evil (Hooper, Kay. Evil Trilogy.), with distance of 0.8423226260977708:\n",
      "3: Midnight Voices, with distance of 0.8497851914230179:\n",
      "4: Out of This World, with distance of 0.85435041076157:\n",
      "5: The President's Daughter, with distance of 0.8553678811310922:\n"
     ]
    }
   ],
   "source": [
    "\n",
    "query_index = np.random.choice(us_india_user_rating_pivot.shape[0])\n",
    "distances, indices = model_knn.kneighbors(us_india_user_rating_pivot.iloc[query_index, :].values.reshape(1, -1), n_neighbors = 6)\n",
    "\n",
    "for i in range(0, len(distances.flatten())):\n",
    "    if i == 0:\n",
    "        print('Recommendations for {0}:\\n'.format(us_india_user_rating_pivot.index[query_index]))\n",
    "    else:\n",
    "        print('{0}: {1}, with distance of {2}:'.format(i, us_india_user_rating_pivot.index[indices.flatten()[i]], distances.flatten()[i]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "us_india_user_rating_pivot2 = us_india_user_rating.pivot(index = 'User-ID', columns = 'Book-Title', values = 'Book-Rating').fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Book-Title</th>\n",
       "      <th>10 Lb. Penalty</th>\n",
       "      <th>16 Lighthouse Road</th>\n",
       "      <th>1984</th>\n",
       "      <th>1st to Die: A Novel</th>\n",
       "      <th>2010: Odyssey Two</th>\n",
       "      <th>204 Rosewood Lane</th>\n",
       "      <th>2061: Odyssey Three</th>\n",
       "      <th>24 Hours</th>\n",
       "      <th>2nd Chance</th>\n",
       "      <th>3rd Degree</th>\n",
       "      <th>...</th>\n",
       "      <th>YOU BELONG TO ME</th>\n",
       "      <th>Year of Wonders</th>\n",
       "      <th>You Belong To Me</th>\n",
       "      <th>You Shall Know Our Velocity</th>\n",
       "      <th>Young Wives</th>\n",
       "      <th>Zen and the Art of Motorcycle Maintenance: An Inquiry into Values</th>\n",
       "      <th>Zoya</th>\n",
       "      <th>\\O\\\" Is for Outlaw\"</th>\n",
       "      <th>\\Surely You're Joking, Mr. Feynman!\\\": Adventures of a Curious Character\"</th>\n",
       "      <th>stardust</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>User-ID</th>\n",
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      ],
      "text/plain": [
       "Book-Title  10 Lb. Penalty  16 Lighthouse Road  1984  1st to Die: A Novel  \\\n",
       "User-ID                                                                     \n",
       "9                    0.000               0.000 0.000                0.000   \n",
       "14                   0.000               0.000 0.000                0.000   \n",
       "16                   0.000               0.000 0.000                0.000   \n",
       "17                   0.000               0.000 0.000                0.000   \n",
       "23                   0.000               0.000 0.000                0.000   \n",
       "\n",
       "Book-Title  2010: Odyssey Two  204 Rosewood Lane  2061: Odyssey Three  \\\n",
       "User-ID                                                                 \n",
       "9                       0.000              0.000                0.000   \n",
       "14                      0.000              0.000                0.000   \n",
       "16                      0.000              0.000                0.000   \n",
       "17                      0.000              0.000                0.000   \n",
       "23                      0.000              0.000                0.000   \n",
       "\n",
       "Book-Title  24 Hours  2nd Chance  3rd Degree  ...  YOU BELONG TO ME  \\\n",
       "User-ID                                       ...                     \n",
       "9              0.000       0.000       0.000  ...             0.000   \n",
       "14             0.000       0.000       0.000  ...             0.000   \n",
       "16             0.000       0.000       0.000  ...             0.000   \n",
       "17             0.000       0.000       0.000  ...             0.000   \n",
       "23             0.000       0.000       0.000  ...             0.000   \n",
       "\n",
       "Book-Title  Year of Wonders  You Belong To Me  You Shall Know Our Velocity  \\\n",
       "User-ID                                                                      \n",
       "9                     0.000             0.000                        0.000   \n",
       "14                    0.000             0.000                        0.000   \n",
       "16                    0.000             0.000                        0.000   \n",
       "17                    0.000             0.000                        0.000   \n",
       "23                    0.000             0.000                        0.000   \n",
       "\n",
       "Book-Title  Young Wives  \\\n",
       "User-ID                   \n",
       "9                 0.000   \n",
       "14                0.000   \n",
       "16                0.000   \n",
       "17                0.000   \n",
       "23                0.000   \n",
       "\n",
       "Book-Title  Zen and the Art of Motorcycle Maintenance: An Inquiry into Values  \\\n",
       "User-ID                                                                         \n",
       "9                                                       0.000                   \n",
       "14                                                      0.000                   \n",
       "16                                                      0.000                   \n",
       "17                                                      0.000                   \n",
       "23                                                      0.000                   \n",
       "\n",
       "Book-Title  Zoya  \\O\\\" Is for Outlaw\"  \\\n",
       "User-ID                                 \n",
       "9          0.000                0.000   \n",
       "14         0.000                0.000   \n",
       "16         0.000                0.000   \n",
       "17         0.000                0.000   \n",
       "23         0.000                0.000   \n",
       "\n",
       "Book-Title  \\Surely You're Joking, Mr. Feynman!\\\": Adventures of a Curious Character\"  \\\n",
       "User-ID                                                                                 \n",
       "9                                                       0.000                           \n",
       "14                                                      0.000                           \n",
       "16                                                      0.000                           \n",
       "17                                                      0.000                           \n",
       "23                                                      0.000                           \n",
       "\n",
       "Book-Title  stardust  \n",
       "User-ID               \n",
       "9              0.000  \n",
       "14             0.000  \n",
       "16             0.000  \n",
       "17             0.000  \n",
       "23             0.000  \n",
       "\n",
       "[5 rows x 2441 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_india_user_rating_pivot2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(35111, 2441)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_india_user_rating_pivot2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2441, 35111)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = us_india_user_rating_pivot2.values.T\n",
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2441, 12)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SVD = TruncatedSVD(n_components=12, random_state=17)\n",
    "matrix = SVD.fit_transform(X)\n",
    "matrix.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2441, 2441)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\",category =RuntimeWarning)\n",
    "corr = np.corrcoef(matrix)\n",
    "corr.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1905\n"
     ]
    }
   ],
   "source": [
    "us_india_book_title = us_india_user_rating_pivot2.columns\n",
    "us_india_book_list = list(us_india_book_title)\n",
    "coffey_hands = us_india_book_list.index(\"The Green Mile: Coffey's Hands (Green Mile Series)\")\n",
    "print(coffey_hands)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "corr_coffey_hands  = corr[coffey_hands]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Carrie',\n",
       " 'Desperation',\n",
       " 'Dreamcatcher',\n",
       " 'Four Past Midnight',\n",
       " \"Gerald's Game\",\n",
       " 'Hearts In Atlantis : New Fiction',\n",
       " 'Needful Things: The Last Castle Rock Story',\n",
       " 'Rose Madder',\n",
       " 'Skinwalkers (Joe Leaphorn/Jim Chee Novels)',\n",
       " 'Strangers',\n",
       " 'The Bachman Books: Rage, the Long Walk, Roadwork, the Running Man',\n",
       " 'The Dark Half',\n",
       " 'The Dead Zone',\n",
       " 'The Green Mile: Coffey on the Mile (Green Mile Series)',\n",
       " 'The Green Mile: Night Journey (Green Mile Series)',\n",
       " 'The Green Mile: The Complete Serial Novel',\n",
       " 'The Green Mile: The Mouse on the Mile (Green Mile Series)',\n",
       " 'The Two Dead Girls (Green Mile Series)']"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(us_india_book_title[(corr_coffey_hands<1.0) & (corr_coffey_hands>0.9)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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