content_based_filtering.ipynb

{
 "cells": [
  {
   "attachments": {
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     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "2bd0b57b-5487-4920-b73c-ebc810417393",
   "metadata": {},
   "source": [
    "# An Extensive GoodReads Dataset containing 100k books\n",
    "\n",
    "![Unknown-5.png](attachment:8db4b025-8e06-4b03-8b69-905dab35be75.png)\n",
    "\n",
    "**This dataset some of the generally required columns needed to express a book. This study includes a detailed title analysis, author analysis, and content-based recommendation system.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d8ffe556-209d-432f-94bd-0a3cc735c688",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns \n",
    "\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "\n",
    "from PIL import Image\n",
    "from wordcloud import WordCloud, ImageColorGenerator\n",
    "from textblob import Word, TextBlob\n",
    "import nltk\n",
    "from nltk.stem import WordNetLemmatizer\n",
    "from nltk.sentiment import SentimentIntensityAnalyzer\n",
    "from nltk.corpus import stopwords\n",
    "\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.float_format', lambda x: '%.2f' % x)\n",
    "pd.set_option('display.width', 200)\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9784d9dc-6b40-4b0e-ad84-0885f5282b76",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('GoodReads_100k_books.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b4f16b54-1708-4127-ae22-62630308160e",
   "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>author</th>\n",
       "      <th>bookformat</th>\n",
       "      <th>desc</th>\n",
       "      <th>genre</th>\n",
       "      <th>img</th>\n",
       "      <th>isbn</th>\n",
       "      <th>isbn13</th>\n",
       "      <th>link</th>\n",
       "      <th>pages</th>\n",
       "      <th>rating</th>\n",
       "      <th>reviews</th>\n",
       "      <th>title</th>\n",
       "      <th>totalratings</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Laurence M. Hauptman</td>\n",
       "      <td>Hardcover</td>\n",
       "      <td>Reveals that several hundred thousand Indians ...</td>\n",
       "      <td>History,Military History,Civil War,American Hi...</td>\n",
       "      <td>https://i.gr-assets.com/images/S/compressed.ph...</td>\n",
       "      <td>002914180X</td>\n",
       "      <td>9.78E+12</td>\n",
       "      <td>https://goodreads.com/book/show/1001053.Betwee...</td>\n",
       "      <td>0</td>\n",
       "      <td>3.52</td>\n",
       "      <td>5</td>\n",
       "      <td>Between Two Fires: American Indians in the Civ...</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Charlotte Fiell,Emmanuelle Dirix</td>\n",
       "      <td>Paperback</td>\n",
       "      <td>Fashion Sourcebook - 1920s is the first book i...</td>\n",
       "      <td>Couture,Fashion,Historical,Art,Nonfiction</td>\n",
       "      <td>https://i.gr-assets.com/images/S/compressed.ph...</td>\n",
       "      <td>1906863482</td>\n",
       "      <td>9.78E+12</td>\n",
       "      <td>https://goodreads.com/book/show/10010552-fashi...</td>\n",
       "      <td>576</td>\n",
       "      <td>4.51</td>\n",
       "      <td>6</td>\n",
       "      <td>Fashion Sourcebook 1920s</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Andy Anderson</td>\n",
       "      <td>Paperback</td>\n",
       "      <td>The seminal history and analysis of the Hungar...</td>\n",
       "      <td>Politics,History</td>\n",
       "      <td>https://i.gr-assets.com/images/S/compressed.ph...</td>\n",
       "      <td>948984147</td>\n",
       "      <td>9.78E+12</td>\n",
       "      <td>https://goodreads.com/book/show/1001077.Hungar...</td>\n",
       "      <td>124</td>\n",
       "      <td>4.15</td>\n",
       "      <td>2</td>\n",
       "      <td>Hungary 56</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Carlotta R. Anderson</td>\n",
       "      <td>Hardcover</td>\n",
       "      <td>\"All-American Anarchist\" chronicles the life a...</td>\n",
       "      <td>Labor,History</td>\n",
       "      <td>https://i.gr-assets.com/images/S/compressed.ph...</td>\n",
       "      <td>814327079</td>\n",
       "      <td>9.78E+12</td>\n",
       "      <td>https://goodreads.com/book/show/1001079.All_Am...</td>\n",
       "      <td>324</td>\n",
       "      <td>3.83</td>\n",
       "      <td>1</td>\n",
       "      <td>All-American Anarchist: Joseph A. Labadie and ...</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Jean Leveille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Aujourdâ€™hui, lâ€™oiseau nous invite Ã  sa ta...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://i.gr-assets.com/images/S/compressed.ph...</td>\n",
       "      <td>2761920813</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://goodreads.com/book/show/10010880-les-o...</td>\n",
       "      <td>177</td>\n",
       "      <td>4.00</td>\n",
       "      <td>1</td>\n",
       "      <td>Les oiseaux gourmands</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             author bookformat                                               desc                                              genre  \\\n",
       "0              Laurence M. Hauptman  Hardcover  Reveals that several hundred thousand Indians ...  History,Military History,Civil War,American Hi...   \n",
       "1  Charlotte Fiell,Emmanuelle Dirix  Paperback  Fashion Sourcebook - 1920s is the first book i...          Couture,Fashion,Historical,Art,Nonfiction   \n",
       "2                     Andy Anderson  Paperback  The seminal history and analysis of the Hungar...                                   Politics,History   \n",
       "3              Carlotta R. Anderson  Hardcover  \"All-American Anarchist\" chronicles the life a...                                      Labor,History   \n",
       "4                     Jean Leveille        NaN  Aujourdâ€™hui, lâ€™oiseau nous invite Ã  sa ta...                                                NaN   \n",
       "\n",
       "                                                 img        isbn    isbn13                                               link  pages  rating  reviews  \\\n",
       "0  https://i.gr-assets.com/images/S/compressed.ph...  002914180X  9.78E+12  https://goodreads.com/book/show/1001053.Betwee...      0    3.52        5   \n",
       "1  https://i.gr-assets.com/images/S/compressed.ph...  1906863482  9.78E+12  https://goodreads.com/book/show/10010552-fashi...    576    4.51        6   \n",
       "2  https://i.gr-assets.com/images/S/compressed.ph...   948984147  9.78E+12  https://goodreads.com/book/show/1001077.Hungar...    124    4.15        2   \n",
       "3  https://i.gr-assets.com/images/S/compressed.ph...   814327079  9.78E+12  https://goodreads.com/book/show/1001079.All_Am...    324    3.83        1   \n",
       "4  https://i.gr-assets.com/images/S/compressed.ph...  2761920813       NaN  https://goodreads.com/book/show/10010880-les-o...    177    4.00        1   \n",
       "\n",
       "                                               title  totalratings  \n",
       "0  Between Two Fires: American Indians in the Civ...            33  \n",
       "1                           Fashion Sourcebook 1920s            41  \n",
       "2                                         Hungary 56            26  \n",
       "3  All-American Anarchist: Joseph A. Labadie and ...             6  \n",
       "4                              Les oiseaux gourmands             1  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "41de5092-4785-40ba-aeee-8ca00edba0d4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 100000 entries, 0 to 99999\n",
      "Data columns (total 13 columns):\n",
      " #   Column        Non-Null Count   Dtype  \n",
      "---  ------        --------------   -----  \n",
      " 0   author        100000 non-null  object \n",
      " 1   bookformat    96772 non-null   object \n",
      " 2   desc          93228 non-null   object \n",
      " 3   genre         89533 non-null   object \n",
      " 4   img           96955 non-null   object \n",
      " 5   isbn          85518 non-null   object \n",
      " 6   isbn13        88565 non-null   object \n",
      " 7   link          100000 non-null  object \n",
      " 8   pages         100000 non-null  int64  \n",
      " 9   rating        100000 non-null  float64\n",
      " 10  reviews       100000 non-null  int64  \n",
      " 11  title         99999 non-null   object \n",
      " 12  totalratings  100000 non-null  int64  \n",
      "dtypes: float64(1), int64(3), object(9)\n",
      "memory usage: 9.9+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "638d946f-dda0-4be6-8eef-4d155bb4625e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100000, 13)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25442342-876a-4bdb-8252-ff43a9cf70ca",
   "metadata": {},
   "source": [
    "**The dataset contains 100000 observations and 13 columns.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "db6d96b9-69ff-40f7-8ad6-bb7769c3bb44",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "author              0\n",
       "bookformat       3228\n",
       "desc             6772\n",
       "genre           10467\n",
       "img              3045\n",
       "isbn            14482\n",
       "isbn13          11435\n",
       "link                0\n",
       "pages               0\n",
       "rating              0\n",
       "reviews             0\n",
       "title               1\n",
       "totalratings        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cde5d424-0246-4cf3-8b6b-1051304f04d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7752"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['pages'] == 0].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "54490d07-b3e0-4fe4-bfd6-a0411885e4a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['pages'] != 0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "afdb8fde-9d83-4fb8-8012-f0c71176e494",
   "metadata": {},
   "source": [
    "**When we look at the first 5 observations with the head function, it is found that there are books with 0 pages.These observations should be dropped from the dataset.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b5eafc78-fb5f-4cb2-81f3-2e33b1645631",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(['img', 'isbn', 'isbn13', 'link'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "63891b3b-b720-4d7c-8f19-233e63a433ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d1a01805-e4a4-476b-b9ca-0cf3a2a1fb92",
   "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>author</th>\n",
       "      <th>bookformat</th>\n",
       "      <th>desc</th>\n",
       "      <th>genre</th>\n",
       "      <th>pages</th>\n",
       "      <th>rating</th>\n",
       "      <th>reviews</th>\n",
       "      <th>title</th>\n",
       "      <th>totalratings</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Charlotte Fiell,Emmanuelle Dirix</td>\n",
       "      <td>Paperback</td>\n",
       "      <td>Fashion Sourcebook - 1920s is the first book i...</td>\n",
       "      <td>Couture,Fashion,Historical,Art,Nonfiction</td>\n",
       "      <td>576</td>\n",
       "      <td>4.51</td>\n",
       "      <td>6</td>\n",
       "      <td>Fashion Sourcebook 1920s</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Andy Anderson</td>\n",
       "      <td>Paperback</td>\n",
       "      <td>The seminal history and analysis of the Hungar...</td>\n",
       "      <td>Politics,History</td>\n",
       "      <td>124</td>\n",
       "      <td>4.15</td>\n",
       "      <td>2</td>\n",
       "      <td>Hungary 56</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Carlotta R. Anderson</td>\n",
       "      <td>Hardcover</td>\n",
       "      <td>\"All-American Anarchist\" chronicles the life a...</td>\n",
       "      <td>Labor,History</td>\n",
       "      <td>324</td>\n",
       "      <td>3.83</td>\n",
       "      <td>1</td>\n",
       "      <td>All-American Anarchist: Joseph A. Labadie and ...</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Jeffrey Pfeffer</td>\n",
       "      <td>Hardcover</td>\n",
       "      <td>Why is common sense so uncommon when it comes ...</td>\n",
       "      <td>Business,Leadership,Romance,Historical Romance...</td>\n",
       "      <td>368</td>\n",
       "      <td>3.73</td>\n",
       "      <td>7</td>\n",
       "      <td>The Human Equation: Building Profits by Puttin...</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Jeffrey Pfeffer</td>\n",
       "      <td>Paperback</td>\n",
       "      <td>\"Competitive Advantage Through People\" explore...</td>\n",
       "      <td>Business,Leadership,Business,Management,Romanc...</td>\n",
       "      <td>304</td>\n",
       "      <td>3.65</td>\n",
       "      <td>1</td>\n",
       "      <td>Competitive Advantage Through People: Unleashi...</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             author bookformat                                               desc                                              genre  pages  rating  reviews  \\\n",
       "1  Charlotte Fiell,Emmanuelle Dirix  Paperback  Fashion Sourcebook - 1920s is the first book i...          Couture,Fashion,Historical,Art,Nonfiction    576    4.51        6   \n",
       "2                     Andy Anderson  Paperback  The seminal history and analysis of the Hungar...                                   Politics,History    124    4.15        2   \n",
       "3              Carlotta R. Anderson  Hardcover  \"All-American Anarchist\" chronicles the life a...                                      Labor,History    324    3.83        1   \n",
       "5                   Jeffrey Pfeffer  Hardcover  Why is common sense so uncommon when it comes ...  Business,Leadership,Romance,Historical Romance...    368    3.73        7   \n",
       "6                   Jeffrey Pfeffer  Paperback  \"Competitive Advantage Through People\" explore...  Business,Leadership,Business,Management,Romanc...    304    3.65        1   \n",
       "\n",
       "                                               title  totalratings  \n",
       "1                           Fashion Sourcebook 1920s            41  \n",
       "2                                         Hungary 56            26  \n",
       "3  All-American Anarchist: Joseph A. Labadie and ...             6  \n",
       "5  The Human Equation: Building Profits by Puttin...           119  \n",
       "6  Competitive Advantage Through People: Unleashi...            20  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "10517126-72ea-48a9-ac01-bcdd00b65661",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(79754, 9)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "939297fc-7b8d-491b-bcac-aba0440f3ef8",
   "metadata": {},
   "source": [
    "## Title Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e4c50243-459f-493a-b855-392b4e78430e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "77847"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# how many unique titles are there ?\n",
    "\n",
    "df['title'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "52b74b21-a435-443c-ab4a-08f3cf1d4ed1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 8))\n",
    "most_reviewed = df.groupby('title')[['reviews']].sum().sort_values(by='reviews', ascending=False).reset_index()[:20]\n",
    "\n",
    "palette = sns.color_palette('Greens_r', 30)\n",
    "ax = plt.barh(most_reviewed['title'] , most_reviewed['reviews'], color=palette)\n",
    "for p in ax.patches:\n",
    "    width = p.get_width()\n",
    "    plt.text(4500+p.get_width(), p.get_y()+0.6*p.get_height(),\n",
    "             '{:d}'.format(width),\n",
    "             ha='center', va='center', fontsize=9.5)\n",
    "plt.gca().invert_yaxis()\n",
    "plt.title('Top 20 Most Reviewed Books', fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d092d80e-53db-4bca-8777-c3b3a7fc4386",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 8))\n",
    "most_rated = df.groupby('title')[['totalratings']].sum().sort_values(by='totalratings', ascending=False).reset_index()[:20]\n",
    "\n",
    "palette = sns.color_palette('Greens_r', 30)\n",
    "ax = plt.barh(most_rated['title'] , most_rated['totalratings'], color=palette)\n",
    "for p in ax.patches:\n",
    "    width = p.get_width()\n",
    "    plt.text(95000+p.get_width(), p.get_y()+0.6*p.get_height(),\n",
    "             '{:d}'.format(width),\n",
    "             ha='center', va='center', fontsize=9.5)\n",
    "plt.gca().invert_yaxis()\n",
    "plt.title('Top 20 Most Rated Books', fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "927fe658-9862-445f-b096-44c3f9ebd8c1",
   "metadata": {},
   "source": [
    "####  Titles with the highest rating among titles with a total rating count of at least 100k "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "35354ab2-1c64-442c-9c02-9a93a613482d",
   "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>rating</th>\n",
       "      <th>totalratings</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Harry Potter and the Deathly Hallows</th>\n",
       "      <td>4.62</td>\n",
       "      <td>2984351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Harry Potter and the Order of the Phoenix (Harry Potter, #5, Part 1)</th>\n",
       "      <td>4.62</td>\n",
       "      <td>133779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Wise Man's Fear</th>\n",
       "      <td>4.54</td>\n",
       "      <td>456510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Complete Maus</th>\n",
       "      <td>4.53</td>\n",
       "      <td>153660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The House of Hades</th>\n",
       "      <td>4.52</td>\n",
       "      <td>294712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Hunger Games: Official Illustrated Movie Companion</th>\n",
       "      <td>4.52</td>\n",
       "      <td>175110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Redeeming Love</th>\n",
       "      <td>4.50</td>\n",
       "      <td>226121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Green Mile</th>\n",
       "      <td>4.45</td>\n",
       "      <td>261605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Death Note, Vol. 1: Boredom</th>\n",
       "      <td>4.45</td>\n",
       "      <td>209127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A Game of Thrones</th>\n",
       "      <td>4.44</td>\n",
       "      <td>2097707</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    rating  totalratings\n",
       "title                                                                   \n",
       "Harry Potter and the Deathly Hallows                  4.62       2984351\n",
       "Harry Potter and the Order of the Phoenix (Harr...    4.62        133779\n",
       "The Wise Man's Fear                                   4.54        456510\n",
       "The Complete Maus                                     4.53        153660\n",
       "The House of Hades                                    4.52        294712\n",
       "The Hunger Games: Official Illustrated Movie Co...    4.52        175110\n",
       "Redeeming Love                                        4.50        226121\n",
       "The Green Mile                                        4.45        261605\n",
       "Death Note, Vol. 1: Boredom                           4.45        209127\n",
       "A Game of Thrones                                     4.44       2097707"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ = df.groupby('title')[['totalratings']].sum().reset_index()\n",
    "filtered = df_[df_['totalratings'] > 100000].title.values.tolist()\n",
    "\n",
    "df[df['title'].isin(filtered)].groupby('title')[['totalratings', 'rating']]. \\\n",
    "                                agg({'rating':'mean','totalratings':'sum'}).sort_values(by=['rating', 'totalratings'],\n",
    "                                                                                        ascending=[False, False])[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca9247c9-38c3-4a37-b327-30ccc248ab6e",
   "metadata": {},
   "source": [
    "#### Titles with the lowest rating among titles with a total rating count of at least 100k "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d2a4b4dc-638f-4af7-86e6-d52289984a6d",
   "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>rating</th>\n",
       "      <th>totalratings</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>The Casual Vacancy</th>\n",
       "      <td>3.30</td>\n",
       "      <td>313167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Silent Wife</th>\n",
       "      <td>3.32</td>\n",
       "      <td>104078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Scarlet Letter</th>\n",
       "      <td>3.42</td>\n",
       "      <td>733658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Turn of the Screw</th>\n",
       "      <td>3.42</td>\n",
       "      <td>117055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Marriage Plot</th>\n",
       "      <td>3.45</td>\n",
       "      <td>113354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moby-Dick or, the Whale</th>\n",
       "      <td>3.51</td>\n",
       "      <td>493984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Tenth Circle</th>\n",
       "      <td>3.51</td>\n",
       "      <td>122618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Crossed</th>\n",
       "      <td>3.53</td>\n",
       "      <td>224446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Death of a Salesman</th>\n",
       "      <td>3.54</td>\n",
       "      <td>195711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Life After Life</th>\n",
       "      <td>3.54</td>\n",
       "      <td>211483</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         rating  totalratings\n",
       "title                                        \n",
       "The Casual Vacancy         3.30        313167\n",
       "The Silent Wife            3.32        104078\n",
       "The Scarlet Letter         3.42        733658\n",
       "The Turn of the Screw      3.42        117055\n",
       "The Marriage Plot          3.45        113354\n",
       "Moby-Dick or, the Whale    3.51        493984\n",
       "The Tenth Circle           3.51        122618\n",
       "Crossed                    3.53        224446\n",
       "Death of a Salesman        3.54        195711\n",
       "Life After Life            3.54        211483"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['title'].isin(filtered)].groupby('title')[['totalratings', 'rating']]. \\\n",
    "                               agg({'rating':'mean','totalratings':'sum'}).sort_values(by=['rating', 'totalratings'], \n",
    "                                                                                       ascending=[True, False])[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86f4713f-c017-4917-b9ea-f9684efdd62f",
   "metadata": {},
   "source": [
    "### Bookformat Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8a01bc0d-f81a-4841-954d-0d5387fbcb33",
   "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>mean</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bookformat</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Paperback</th>\n",
       "      <td>3.91</td>\n",
       "      <td>44817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hardcover</th>\n",
       "      <td>3.91</td>\n",
       "      <td>22811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ebook</th>\n",
       "      <td>3.80</td>\n",
       "      <td>4116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kindle Edition</th>\n",
       "      <td>3.84</td>\n",
       "      <td>3982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mass Market Paperback</th>\n",
       "      <td>3.82</td>\n",
       "      <td>2752</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       mean  count\n",
       "bookformat                        \n",
       "Paperback              3.91  44817\n",
       "Hardcover              3.91  22811\n",
       "ebook                  3.80   4116\n",
       "Kindle Edition         3.84   3982\n",
       "Mass Market Paperback  3.82   2752"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('bookformat')['rating'].agg({'count', 'mean'}).sort_values(by='count', ascending=False)[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56002fbf-d879-4e44-a854-b261e09948ec",
   "metadata": {},
   "source": [
    "### Pages Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f0dbc168-947f-4143-a862-74c966f51921",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-69.0, 10000.857]        79750\n",
       "(10000.857, 20000.714]        1\n",
       "(20000.714, 30000.571]        1\n",
       "(30000.571, 40000.429]        1\n",
       "(60000.143, 70000.0]          1\n",
       "(40000.429, 50000.286]        0\n",
       "(50000.286, 60000.143]        0\n",
       "Name: pages, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['pages'].value_counts(bins=7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "61d1a3b8-d26e-4d1a-8c54-a877cd4b479f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>author</th>\n",
       "      <th>bookformat</th>\n",
       "      <th>desc</th>\n",
       "      <th>genre</th>\n",
       "      <th>pages</th>\n",
       "      <th>rating</th>\n",
       "      <th>reviews</th>\n",
       "      <th>title</th>\n",
       "      <th>totalratings</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>22871</th>\n",
       "      <td>Charles Dickens</td>\n",
       "      <td>Kindle Edition</td>\n",
       "      <td>* ALL 15 Novels and ALL illustrated with the o...</td>\n",
       "      <td>Classics,Fiction,Literature,Anthologies,Collec...</td>\n",
       "      <td>21723</td>\n",
       "      <td>4.41</td>\n",
       "      <td>22</td>\n",
       "      <td>The Complete Works of Charles Dickens</td>\n",
       "      <td>1488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29938</th>\n",
       "      <td>Phyllis Peterson</td>\n",
       "      <td>Hardcover</td>\n",
       "      <td>Assisting the Traumatized Soul reaches out to ...</td>\n",
       "      <td>Religion,Baha I</td>\n",
       "      <td>70000</td>\n",
       "      <td>4.75</td>\n",
       "      <td>0</td>\n",
       "      <td>Assisting the Traumatized Soul: Healing the Wo...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83512</th>\n",
       "      <td>EncyclopÃ¦dia Britannica</td>\n",
       "      <td>Hardcover</td>\n",
       "      <td>Comprises one Propaedia (outline of knowledge)...</td>\n",
       "      <td>Reference,Reference,Dictionaries,Nonfiction</td>\n",
       "      <td>32000</td>\n",
       "      <td>4.46</td>\n",
       "      <td>16</td>\n",
       "      <td>Encyclopaedia Britannica (Set)</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96255</th>\n",
       "      <td>HonorÃ© de Balzac</td>\n",
       "      <td>Kindle Edition</td>\n",
       "      <td>This comprehensive eBook presents the complete...</td>\n",
       "      <td>Fiction,Classics,Cultural,France,Anthologies,C...</td>\n",
       "      <td>15918</td>\n",
       "      <td>4.30</td>\n",
       "      <td>7</td>\n",
       "      <td>Works of Honore de Balzac</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         author      bookformat                                               desc                                              genre  pages  rating  reviews  \\\n",
       "22871           Charles Dickens  Kindle Edition  * ALL 15 Novels and ALL illustrated with the o...  Classics,Fiction,Literature,Anthologies,Collec...  21723    4.41       22   \n",
       "29938          Phyllis Peterson       Hardcover  Assisting the Traumatized Soul reaches out to ...                                    Religion,Baha I  70000    4.75        0   \n",
       "83512  EncyclopÃ¦dia Britannica       Hardcover  Comprises one Propaedia (outline of knowledge)...        Reference,Reference,Dictionaries,Nonfiction  32000    4.46       16   \n",
       "96255         HonorÃ© de Balzac  Kindle Edition  This comprehensive eBook presents the complete...  Fiction,Classics,Cultural,France,Anthologies,C...  15918    4.30        7   \n",
       "\n",
       "                                                   title  totalratings  \n",
       "22871              The Complete Works of Charles Dickens          1488  \n",
       "29938  Assisting the Traumatized Soul: Healing the Wo...             4  \n",
       "83512                     Encyclopaedia Britannica (Set)            89  \n",
       "96255                          Works of Honore de Balzac           177  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['pages'] > 10000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "7ef7954a-7391-4475-b921-5f293ee2e994",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.loc[df['title'] != 'Assisting the Traumatized Soul: Healing the Wounded Talisman' ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "bc97f60e-ac1c-4a68-b143-49889dfd7c6a",
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>5%</th>\n",
       "      <th>10%</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>90%</th>\n",
       "      <th>95%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>pages</th>\n",
       "      <td>79753.00</td>\n",
       "      <td>279.12</td>\n",
       "      <td>245.03</td>\n",
       "      <td>1.00</td>\n",
       "      <td>40.00</td>\n",
       "      <td>88.00</td>\n",
       "      <td>175.00</td>\n",
       "      <td>256.00</td>\n",
       "      <td>352.00</td>\n",
       "      <td>456.00</td>\n",
       "      <td>563.00</td>\n",
       "      <td>32000.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         count   mean    std  min    5%   10%    25%    50%    75%    90%    95%      max\n",
       "pages 79753.00 279.12 245.03 1.00 40.00 88.00 175.00 256.00 352.00 456.00 563.00 32000.00"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['pages']].describe([.05, .1, .25, .75, .9, .95]).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "f538fbfa-e4d1-4783-9de3-804b5d57424a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18, 6))\n",
    "sns.boxenplot(x=df['pages'], color='Green');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddea04c6-ddcd-40a6-8d74-c77588cae678",
   "metadata": {},
   "source": [
    "**The books with a very high number of pages were examined. The title with the error was dropped from the dataset.**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25f6cfbd-a63b-4429-ba0e-2ffce22d635d",
   "metadata": {},
   "source": [
    "### Genre Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f20c7b98-32d1-4f33-8a8e-d39bc4be1dc1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['genre'] = df['genre'].str.replace('M M', 'MM')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "838ca91d-e18c-453d-98ee-16bf2cc14458",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['genre'] = df['genre'].str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ced5c7e2-3251-480e-819d-85974a82568b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "text = \" \".join(i for i in df['genre'])\n",
    "mask = np.array(Image.open('09d318ee250c1c5bd3bc31ae7e4ed1d1.jpg'))\n",
    "wordcloud = WordCloud(max_font_size=120,\n",
    "                      max_words=75,\n",
    "                      background_color=\"black\",\n",
    "                      collocations=False,\n",
    "                      mask=mask,\n",
    "                      contour_width=1,\n",
    "                      contour_color=\"white\"\n",
    "                      ).generate(text)\n",
    "image_colors = ImageColorGenerator(mask)\n",
    "plt.figure(figsize=(15, 12))\n",
    "plt.imshow(wordcloud.recolor(color_func=image_colors), interpolation=\"bilinear\")\n",
    "plt.axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2c0ad51-f5ed-4b22-87db-3a238b1a9776",
   "metadata": {},
   "source": [
    "### Author Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "6f711514-e655-4228-b29d-43e6754c9f72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "54909"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['author'].nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1204ce96-94dc-493c-b3d9-3b5c3ed8996b",
   "metadata": {},
   "source": [
    "**Due to the fact that some books have more than 1 author, split operations are required in the data set to achieve correct results.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "8e06fef1-0e32-4c98-968c-94f205feb146",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[['a_1', 'a_2', 'a_3', 'a_4', 'a_5', 'a_6']] = df['author'].str.split(',', n=5, expand=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "afcb930d-4292-4b5d-8f2c-eccc56620a31",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.loc[df['a_6'].isnull() == False, 'a_6'] = 'Others'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "52c1ded3-0bd6-4912-9ec1-5acd2ccb647d",
   "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>a_1</th>\n",
       "      <th>a_2</th>\n",
       "      <th>a_3</th>\n",
       "      <th>a_4</th>\n",
       "      <th>a_5</th>\n",
       "      <th>a_6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>Rob Boyle</td>\n",
       "      <td>Brian Cross</td>\n",
       "      <td>J.M. Hardy</td>\n",
       "      <td>Olivia Hill</td>\n",
       "      <td>Ken Horner</td>\n",
       "      <td>Others</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>Richard Pini</td>\n",
       "      <td>Robert Lynn Asprin</td>\n",
       "      <td>Lynn Abbey</td>\n",
       "      <td>Mark C. Perry</td>\n",
       "      <td>C.J. Cherryh</td>\n",
       "      <td>Others</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>Martin H. Greenberg</td>\n",
       "      <td>Neil Gaiman</td>\n",
       "      <td>George R.R. Martin</td>\n",
       "      <td>Lucius Shepard</td>\n",
       "      <td>Robert Sheckley</td>\n",
       "      <td>Others</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>T. Pines</td>\n",
       "      <td>D.E. Athkins</td>\n",
       "      <td>Judith Bauer Stamper</td>\n",
       "      <td>R.L. Stine</td>\n",
       "      <td>Ellen Emerson White</td>\n",
       "      <td>Others</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>Levi Bryant</td>\n",
       "      <td>Nick Srnicek</td>\n",
       "      <td>Martin HÃ¤gglund</td>\n",
       "      <td>Peter Hallward</td>\n",
       "      <td>Graham Harman</td>\n",
       "      <td>Others</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99856</th>\n",
       "      <td>The New Yorker</td>\n",
       "      <td>Haruki Murakami</td>\n",
       "      <td>Calvin Trillin</td>\n",
       "      <td>M.F.K. Fisher</td>\n",
       "      <td>Roald Dahl</td>\n",
       "      <td>Others</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99887</th>\n",
       "      <td>Weldon Burge</td>\n",
       "      <td>Shaun Meeks</td>\n",
       "      <td>Christian A. Larsen</td>\n",
       "      <td>L.L. Soares</td>\n",
       "      <td>Michael Bailey</td>\n",
       "      <td>Others</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99902</th>\n",
       "      <td>Marcio Noguchi</td>\n",
       "      <td>Shuki Kato</td>\n",
       "      <td>Jason Ku</td>\n",
       "      <td>Sebastian Arellano</td>\n",
       "      <td>Won Park</td>\n",
       "      <td>Others</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99929</th>\n",
       "      <td>Will Gompertz</td>\n",
       "      <td>Chloe Aridjis</td>\n",
       "      <td>Lila Azam Zanganeh</td>\n",
       "      <td>Alain de Botton</td>\n",
       "      <td>James Bridle</td>\n",
       "      <td>Others</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99932</th>\n",
       "      <td>Isaac Anderson</td>\n",
       "      <td>Cherril Doty</td>\n",
       "      <td>Samantha Kira Harding</td>\n",
       "      <td>Jennifer McCully</td>\n",
       "      <td>Suzette Rosenthal</td>\n",
       "      <td>Others</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1185 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       a_1                 a_2                    a_3                 a_4                  a_5     a_6\n",
       "75               Rob Boyle         Brian Cross             J.M. Hardy         Olivia Hill           Ken Horner  Others\n",
       "84            Richard Pini  Robert Lynn Asprin             Lynn Abbey       Mark C. Perry         C.J. Cherryh  Others\n",
       "113    Martin H. Greenberg         Neil Gaiman     George R.R. Martin      Lucius Shepard      Robert Sheckley  Others\n",
       "257               T. Pines        D.E. Athkins   Judith Bauer Stamper          R.L. Stine  Ellen Emerson White  Others\n",
       "433            Levi Bryant        Nick Srnicek       Martin HÃ¤gglund      Peter Hallward        Graham Harman  Others\n",
       "...                    ...                 ...                    ...                 ...                  ...     ...\n",
       "99856       The New Yorker     Haruki Murakami         Calvin Trillin       M.F.K. Fisher           Roald Dahl  Others\n",
       "99887         Weldon Burge         Shaun Meeks    Christian A. Larsen         L.L. Soares       Michael Bailey  Others\n",
       "99902       Marcio Noguchi          Shuki Kato               Jason Ku  Sebastian Arellano             Won Park  Others\n",
       "99929        Will Gompertz       Chloe Aridjis     Lila Azam Zanganeh     Alain de Botton         James Bridle  Others\n",
       "99932       Isaac Anderson        Cherril Doty  Samantha Kira Harding    Jennifer McCully    Suzette Rosenthal  Others\n",
       "\n",
       "[1185 rows x 6 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df['a_6'].isnull() == False, 'a_1':]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "0a181cd1-8948-4110-973b-35de35a3ed1b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_authors = pd.concat([df.groupby('a_1')[['reviews', 'totalratings', 'rating']].agg({'reviews':'sum', 'totalratings': 'sum', 'rating' : 'mean'}),\n",
    "                        df.groupby('a_2')[['reviews', 'totalratings', 'rating']].agg({'reviews':'sum', 'totalratings': 'sum', 'rating' : 'mean'}), \n",
    "                        df.groupby('a_3')[['reviews', 'totalratings', 'rating']].agg({'reviews':'sum', 'totalratings': 'sum', 'rating' : 'mean'}),\n",
    "                        df.groupby('a_4')[['reviews', 'totalratings', 'rating']].agg({'reviews':'sum', 'totalratings': 'sum', 'rating' : 'mean'}),\n",
    "                        df.groupby('a_5')[['reviews', 'totalratings', 'rating']].agg({'reviews':'sum', 'totalratings': 'sum', 'rating' : 'mean'})],\n",
    "                        axis=0).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "815dec65-9224-40bc-b852-f2cac084be86",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_authors.rename(columns={'index':'author'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "b004916e-c741-4f7c-bd74-37748e5df862",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "65344"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_authors['author'].nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c8f62d7-c5de-4fa2-a9b5-28ec87ce4dde",
   "metadata": {},
   "source": [
    "**It is seen that the count of authors in the data set has increased.There are also authors with more than 1 book in the data set.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "5c9e82af-4ab0-45c9-8c22-df50741cb7c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "71853"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_authors['author'].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "f2ea9686-7056-4a81-91f1-ea2e6afd6596",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 8))\n",
    "df_author = df_authors.groupby('author')[['reviews']].sum().sort_values(by='reviews', ascending=False).reset_index()[:20]\n",
    "palette = sns.color_palette(\"Greens_r\", 30)\n",
    "ax = plt.barh(df_author['author'] , df_author['reviews'], color=palette)\n",
    "for p in ax.patches:\n",
    "    width = p.get_width()\n",
    "    plt.text(8000+p.get_width(), p.get_y()+0.50*p.get_height(),\n",
    "             '{:d}'.format(width),\n",
    "             ha='center', va='center')\n",
    "plt.gca().invert_yaxis()\n",
    "plt.title('Top 20 Most Reviewed Authors', fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "44405c0a-7a1b-4505-a65c-3f73da226ac3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 8))\n",
    "most_rated_a = df_authors.groupby('author')[['totalratings']].sum().sort_values(by='totalratings', ascending=False).reset_index()[:20]\n",
    "\n",
    "palette = sns.color_palette('Greens_r', 30)\n",
    "ax = plt.barh(most_rated_a['author'] , most_rated_a['totalratings'], color=palette)\n",
    "for p in ax.patches:\n",
    "    width = p.get_width()\n",
    "    plt.text(220000+p.get_width(), p.get_y()+0.6*p.get_height(),\n",
    "             '{:d}'.format(width),\n",
    "             ha='center', va='center', fontsize=9.5)\n",
    "plt.gca().invert_yaxis()\n",
    "plt.title('Top 20 Most Rated Authors', fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2bfa980-7608-40f4-af96-a7b8c23aab53",
   "metadata": {},
   "source": [
    "#### Authors with the highest rating among authors with a total rating count of at least 200k "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "4c1d9f0f-c80f-4654-80b2-00738ece1ff7",
   "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>rating</th>\n",
       "      <th>totalratings</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>author</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Francine Rivers</th>\n",
       "      <td>4.50</td>\n",
       "      <td>226121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hajime Isayama</th>\n",
       "      <td>4.47</td>\n",
       "      <td>240331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pookie Rolf</th>\n",
       "      <td>4.45</td>\n",
       "      <td>271605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bisco Hatori</th>\n",
       "      <td>4.44</td>\n",
       "      <td>250136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Toni Morrison</th>\n",
       "      <td>4.44</td>\n",
       "      <td>404851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R.J. Palacio</th>\n",
       "      <td>4.42</td>\n",
       "      <td>810875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Madeline Miller</th>\n",
       "      <td>4.40</td>\n",
       "      <td>339638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Takeshi Obata</th>\n",
       "      <td>4.37</td>\n",
       "      <td>427606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>J.R.R. Tolkien</th>\n",
       "      <td>4.36</td>\n",
       "      <td>407297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Charlie Adlard</th>\n",
       "      <td>4.34</td>\n",
       "      <td>222860</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 rating  totalratings\n",
       "author                               \n",
       "Francine Rivers    4.50        226121\n",
       "Hajime Isayama     4.47        240331\n",
       "Pookie Rolf        4.45        271605\n",
       "Bisco Hatori       4.44        250136\n",
       "Toni Morrison      4.44        404851\n",
       "R.J. Palacio       4.42        810875\n",
       "Madeline Miller    4.40        339638\n",
       "Takeshi Obata      4.37        427606\n",
       "J.R.R. Tolkien     4.36        407297\n",
       "Charlie Adlard     4.34        222860"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "author_rate = df_authors.groupby('author')[['totalratings']].sum().reset_index()\n",
    "filtered_author = author_rate[author_rate['totalratings'] > 200000].author.values.tolist()\n",
    "\n",
    "df_authors[df_authors['author'].isin(filtered_author)].groupby('author')[['totalratings', 'rating']]. \\\n",
    "                                                     agg({'rating':'mean', 'totalratings':'sum'}).sort_values(by=['rating', 'totalratings'],\n",
    "                                                                                        ascending=[False, False])[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9518639d-d0ae-4e5f-84a0-ac2257daa55a",
   "metadata": {},
   "source": [
    "#### Authors with the lowest rating among authors with a total rating count of at least 200k "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "54fa9fed-689a-460b-8495-31d9a566ad03",
   "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>rating</th>\n",
       "      <th>totalratings</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>author</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Chetan Bhagat</th>\n",
       "      <td>3.08</td>\n",
       "      <td>207299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas E. Connolly</th>\n",
       "      <td>3.42</td>\n",
       "      <td>733658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rockwell Kent</th>\n",
       "      <td>3.51</td>\n",
       "      <td>493984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>John Green</th>\n",
       "      <td>3.52</td>\n",
       "      <td>3828586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arthur  Miller</th>\n",
       "      <td>3.53</td>\n",
       "      <td>535252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Herman Melville</th>\n",
       "      <td>3.53</td>\n",
       "      <td>567104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andrew Delbanco</th>\n",
       "      <td>3.54</td>\n",
       "      <td>494615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christopher Bigsby</th>\n",
       "      <td>3.59</td>\n",
       "      <td>338877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paulo Coelho</th>\n",
       "      <td>3.61</td>\n",
       "      <td>698488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jennifer Weiner</th>\n",
       "      <td>3.63</td>\n",
       "      <td>614656</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    rating  totalratings\n",
       "author                                  \n",
       "Chetan Bhagat         3.08        207299\n",
       "Thomas E. Connolly    3.42        733658\n",
       "Rockwell Kent         3.51        493984\n",
       "John Green            3.52       3828586\n",
       "Arthur  Miller        3.53        535252\n",
       "Herman Melville       3.53        567104\n",
       "Andrew Delbanco       3.54        494615\n",
       "Christopher Bigsby    3.59        338877\n",
       "Paulo Coelho          3.61        698488\n",
       "Jennifer Weiner       3.63        614656"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_authors[df_authors['author'].isin(filtered_author)].groupby('author')[['totalratings', 'rating']]. \\\n",
    "                                                     agg({'rating':'mean', 'totalratings':'sum'}).sort_values(by=['rating', 'totalratings'],\n",
    "                                                                                        ascending=[True, False])[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca7ce3d9-2248-4f21-99bb-5cfabf6fec46",
   "metadata": {},
   "source": [
    "# Content Based Recommendation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "6e790300-a70f-48da-a7ea-1e909407f802",
   "metadata": {},
   "outputs": [],
   "source": [
    "random_books = pd.Series(df['title']).sample(40000, random_state=7).values.tolist()\n",
    "random_books_df = df[df['title'].isin(random_books)].reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "f0779b81-1369-4512-a2b4-11a52e942430",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>author</th>\n",
       "      <th>bookformat</th>\n",
       "      <th>desc</th>\n",
       "      <th>genre</th>\n",
       "      <th>pages</th>\n",
       "      <th>rating</th>\n",
       "      <th>reviews</th>\n",
       "      <th>title</th>\n",
       "      <th>totalratings</th>\n",
       "      <th>a_1</th>\n",
       "      <th>a_2</th>\n",
       "      <th>a_3</th>\n",
       "      <th>a_4</th>\n",
       "      <th>a_5</th>\n",
       "      <th>a_6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Andy Anderson</td>\n",
       "      <td>Paperback</td>\n",
       "      <td>The seminal history and analysis of the Hungar...</td>\n",
       "      <td>politics history</td>\n",
       "      <td>124</td>\n",
       "      <td>4.15</td>\n",
       "      <td>2</td>\n",
       "      <td>Hungary 56</td>\n",
       "      <td>26</td>\n",
       "      <td>Andy Anderson</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Carlotta R. Anderson</td>\n",
       "      <td>Hardcover</td>\n",
       "      <td>\"All-American Anarchist\" chronicles the life a...</td>\n",
       "      <td>labor history</td>\n",
       "      <td>324</td>\n",
       "      <td>3.83</td>\n",
       "      <td>1</td>\n",
       "      <td>All-American Anarchist: Joseph A. Labadie and ...</td>\n",
       "      <td>6</td>\n",
       "      <td>Carlotta R. Anderson</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jeffrey Pfeffer</td>\n",
       "      <td>Hardcover</td>\n",
       "      <td>Why is common sense so uncommon when it comes ...</td>\n",
       "      <td>business leadership romance historical romance...</td>\n",
       "      <td>368</td>\n",
       "      <td>3.73</td>\n",
       "      <td>7</td>\n",
       "      <td>The Human Equation: Building Profits by Puttin...</td>\n",
       "      <td>119</td>\n",
       "      <td>Jeffrey Pfeffer</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jeffrey Pfeffer</td>\n",
       "      <td>Paperback</td>\n",
       "      <td>\"Competitive Advantage Through People\" explore...</td>\n",
       "      <td>business leadership business management romanc...</td>\n",
       "      <td>304</td>\n",
       "      <td>3.65</td>\n",
       "      <td>1</td>\n",
       "      <td>Competitive Advantage Through People: Unleashi...</td>\n",
       "      <td>20</td>\n",
       "      <td>Jeffrey Pfeffer</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Edward Joesting</td>\n",
       "      <td>Paperback</td>\n",
       "      <td>\"Even if you know Hawaiian history you will fi...</td>\n",
       "      <td>history nonfiction</td>\n",
       "      <td>353</td>\n",
       "      <td>3.93</td>\n",
       "      <td>2</td>\n",
       "      <td>Hawaii: An Uncommon History</td>\n",
       "      <td>15</td>\n",
       "      <td>Edward Joesting</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40998</th>\n",
       "      <td>Leonard Verduin</td>\n",
       "      <td>Paperback</td>\n",
       "      <td>The Reformers and Their Stepchildren is a bril...</td>\n",
       "      <td>history church church history religion theolog...</td>\n",
       "      <td>292</td>\n",
       "      <td>4.06</td>\n",
       "      <td>26</td>\n",
       "      <td>The Reformers and Their Stepchildren</td>\n",
       "      <td>135</td>\n",
       "      <td>Leonard Verduin</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40999</th>\n",
       "      <td>John Lescroart</td>\n",
       "      <td>Paperback</td>\n",
       "      <td>\"People\" magazine crowns him \"a master.\" \"The ...</td>\n",
       "      <td>mystery fiction thriller legal thriller thrill...</td>\n",
       "      <td>468</td>\n",
       "      <td>4.03</td>\n",
       "      <td>156</td>\n",
       "      <td>The Oath</td>\n",
       "      <td>3413</td>\n",
       "      <td>John Lescroart</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41000</th>\n",
       "      <td>Philip Hoare</td>\n",
       "      <td>Paperback</td>\n",
       "      <td>A startling new book, his most personal to dat...</td>\n",
       "      <td>nonfiction environment nature travel science a...</td>\n",
       "      <td>350</td>\n",
       "      <td>3.77</td>\n",
       "      <td>74</td>\n",
       "      <td>The Sea Inside</td>\n",
       "      <td>497</td>\n",
       "      <td>Philip Hoare</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41001</th>\n",
       "      <td>Sarah Lean</td>\n",
       "      <td>Paperback</td>\n",
       "      <td>Sometimes when things are broken you can't fix...</td>\n",
       "      <td>animals childrens middle grade animals horses ...</td>\n",
       "      <td>288</td>\n",
       "      <td>3.97</td>\n",
       "      <td>94</td>\n",
       "      <td>A Horse for Angel</td>\n",
       "      <td>535</td>\n",
       "      <td>Sarah Lean</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41002</th>\n",
       "      <td>Marc E. Fitch</td>\n",
       "      <td>ebook</td>\n",
       "      <td>Did you know that interest in UFO research inc...</td>\n",
       "      <td>fantasy paranormal nonfiction</td>\n",
       "      <td>398</td>\n",
       "      <td>3.83</td>\n",
       "      <td>3</td>\n",
       "      <td>Paranormal Nation: Why America Needs Ghosts, U...</td>\n",
       "      <td>12</td>\n",
       "      <td>Marc E. Fitch</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>41003 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     author bookformat                                               desc                                              genre  pages  rating  reviews  \\\n",
       "0             Andy Anderson  Paperback  The seminal history and analysis of the Hungar...                                   politics history    124    4.15        2   \n",
       "1      Carlotta R. Anderson  Hardcover  \"All-American Anarchist\" chronicles the life a...                                      labor history    324    3.83        1   \n",
       "2           Jeffrey Pfeffer  Hardcover  Why is common sense so uncommon when it comes ...  business leadership romance historical romance...    368    3.73        7   \n",
       "3           Jeffrey Pfeffer  Paperback  \"Competitive Advantage Through People\" explore...  business leadership business management romanc...    304    3.65        1   \n",
       "4           Edward Joesting  Paperback  \"Even if you know Hawaiian history you will fi...                                 history nonfiction    353    3.93        2   \n",
       "...                     ...        ...                                                ...                                                ...    ...     ...      ...   \n",
       "40998       Leonard Verduin  Paperback  The Reformers and Their Stepchildren is a bril...  history church church history religion theolog...    292    4.06       26   \n",
       "40999        John Lescroart  Paperback  \"People\" magazine crowns him \"a master.\" \"The ...  mystery fiction thriller legal thriller thrill...    468    4.03      156   \n",
       "41000          Philip Hoare  Paperback  A startling new book, his most personal to dat...  nonfiction environment nature travel science a...    350    3.77       74   \n",
       "41001            Sarah Lean  Paperback  Sometimes when things are broken you can't fix...  animals childrens middle grade animals horses ...    288    3.97       94   \n",
       "41002         Marc E. Fitch      ebook  Did you know that interest in UFO research inc...                      fantasy paranormal nonfiction    398    3.83        3   \n",
       "\n",
       "                                                   title  totalratings                   a_1   a_2   a_3   a_4   a_5   a_6  \n",
       "0                                             Hungary 56            26         Andy Anderson  None  None  None  None  None  \n",
       "1      All-American Anarchist: Joseph A. Labadie and ...             6  Carlotta R. Anderson  None  None  None  None  None  \n",
       "2      The Human Equation: Building Profits by Puttin...           119       Jeffrey Pfeffer  None  None  None  None  None  \n",
       "3      Competitive Advantage Through People: Unleashi...            20       Jeffrey Pfeffer  None  None  None  None  None  \n",
       "4                            Hawaii: An Uncommon History            15       Edward Joesting  None  None  None  None  None  \n",
       "...                                                  ...           ...                   ...   ...   ...   ...   ...   ...  \n",
       "40998               The Reformers and Their Stepchildren           135       Leonard Verduin  None  None  None  None  None  \n",
       "40999                                           The Oath          3413        John Lescroart  None  None  None  None  None  \n",
       "41000                                     The Sea Inside           497          Philip Hoare  None  None  None  None  None  \n",
       "41001                                  A Horse for Angel           535            Sarah Lean  None  None  None  None  None  \n",
       "41002  Paranormal Nation: Why America Needs Ghosts, U...            12         Marc E. Fitch  None  None  None  None  None  \n",
       "\n",
       "[41003 rows x 15 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_books_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "318b1d5e-2bc1-4088-8887-d5c7df00a821",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_books_df['desc'].isnull().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "a64b4280-7c34-4606-ad62-8251d3d2e79f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"Marion Weinstein was one of the first witches to release a Book of Shadows to the public. Here is the revised and updated version of Earth Magic, the author's personal book of magical practice, made available for today's Witches. Based on an indepth study of the many facets of Witchcraft, Earth Magic presents the religion as positive and life-affirming.The book is filled with how-to's of a practical nature, as is traditional in Witchcraft. It is intended to be a springboard, to unlock the reader's psychic Wiccan abilities and guide them into the creation of their own unique and personal work. Every technique is explained in detail, in keeping with Weinstein's proviso that one should never attempt to work any magic unless one understands it fully. The goal is to encourage true Witchcraft expertise and creativity.,The information from the original edition is still available, as well as a treasure trove of new material, some of which has never been seen before. In this thoroughly revised edition, you will learn: ,-- How to set up psychic protection.,-- How to work string and cord magic.,-- Working with the phases of the Moon.,-- Forming and working with your own coven.,-- Visualization in a Witch's mode.,-- Choices of Deity alignments from a wide realm of cultures.,-- Not one, but two methods of Manifestation: Creation Manifestation and Affinity Manifestation.,-- Creating rituals, creating Words of Power, composing one's own spells, use of talismans, candles, pendulums, Witch's Bottles, scrying, oracles, and much more.\""
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_books_df['desc'][12]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "3687a9fa-5cd5-41f2-ba01-f5189c6e73ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "lemmatizer = WordNetLemmatizer()\n",
    "stop_words = set(stopwords.words('english'))\n",
    "VERB_CODES = {'VB', 'VBD', 'VBG', 'VBN', 'VBP', 'VBZ'}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b24732c-4b4c-42fe-9fbc-e702a534089d",
   "metadata": {},
   "source": [
    "#### Applying natural language processing techniques to pre-process the text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "cb320a52-b365-4f57-a6b0-1da7e1146873",
   "metadata": {},
   "outputs": [],
   "source": [
    "def preprocess_sentences(text):\n",
    "    text = text.lower()\n",
    "    temp_sent =[]\n",
    "    words = nltk.word_tokenize(text)\n",
    "    tags = nltk.pos_tag(words)\n",
    "    for i, word in enumerate(words):\n",
    "        if tags[i][1] in VERB_CODES: \n",
    "            lemmatized = lemmatizer.lemmatize(word, 'v')\n",
    "        else:\n",
    "            lemmatized = lemmatizer.lemmatize(word)\n",
    "        if lemmatized not in stop_words and lemmatized.isalpha():\n",
    "            temp_sent.append(lemmatized)\n",
    "          \n",
    "    finalsent = ' '.join(temp_sent)\n",
    "    return finalsent"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e30c7ba-2f6c-4d33-9f8f-8502d1b54e17",
   "metadata": {},
   "source": [
    "**Note** \n",
    "*By using the isalpha function, we specify that we want to use only string characters. It is not a definite truth and it is only based on interpretation. We can also keep numeric characters in the text."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a40e3de2-06ca-46ad-b711-d5f8211993a2",
   "metadata": {},
   "source": [
    "- The text is converted into tokens, Using NLTK word tokenizer.\n",
    "- Using NLTK POS tagger, POS tags of tokens are extracted.\n",
    "- Lemmatization is done by removing inflectional endings of tokens, through NLTK Word-net lemmatizer.\n",
    "- Common words are removed to increase the importance of tokens. From NLTK library, English stop words are downloaded and removed from the text."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "0db3901a-27ca-486e-a909-8b4bcc67144a",
   "metadata": {},
   "outputs": [],
   "source": [
    "random_books_df['desc'] = random_books_df['desc'].apply(preprocess_sentences)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "0445eb5d-b116-43c8-b858-aa9d96d0ebc3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'marion weinstein one first witch release book shadow public revised updated version earth magic author personal book magical practice make available today witch base indepth study many facet witchcraft earth magic present religion positive book fill practical nature traditional witchcraft intend springboard unlock reader psychic wiccan ability guide creation unique personal work every technique explain detail keep weinstein proviso one never attempt work magic unless one understand fully goal encourage true witchcraft expertise information original edition still available well treasure trove new material never see thoroughly revise edition learn set psychic work string cord work phase forming work visualization witch choice deity alignment wide realm one two method manifestation creation manifestation affinity create ritual create word power compose one spell use talisman candle pendulum witch bottle scry oracle much'"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_books_df['desc'][12]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76aa3d76-6728-4b48-bbe8-cb58e09d1022",
   "metadata": {},
   "source": [
    "**Some changes**\n",
    "- Book >> book \n",
    "- Shadows >> shadow \n",
    "- author's >> author\n",
    "- Creating >> create"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "a4fea09e-5974-4449-8780-032b42735c07",
   "metadata": {},
   "outputs": [],
   "source": [
    "tfidf = TfidfVectorizer()\n",
    "tfidf_matrix = tfidf.fit_transform(random_books_df['desc'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "572f9913-a06b-4c40-a66a-bc0f2d635262",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(41003, 143424)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tfidf_matrix.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "ff4c8ebc-ae0e-4a5d-8857-a99df1076b14",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]])"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tfidf_matrix.toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "043f3b77-a6a1-47df-aa7b-fdafac79b25a",
   "metadata": {},
   "outputs": [],
   "source": [
    "cosine_sim = cosine_similarity(tfidf_matrix,\n",
    "                               tfidf_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "c3006c60-4f7f-4d0a-af0a-cef4284f0bb4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(41003, 41003)"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cosine_sim.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "613aa74e-0b48-45e3-bf3b-ae35a27532c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "indices = pd.Series(random_books_df.index, index=random_books_df['title'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "fbaaee8d-4b1a-4bd4-be66-7c38c26745dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "indices = indices[~indices.index.duplicated(keep='last')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "d9168a05-5a1d-4b2e-bdbf-e41fe31db287",
   "metadata": {},
   "outputs": [],
   "source": [
    "def check_book(keyword):\n",
    "    return [title for title in random_books_df.title if keyword in title]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b225f9f-da33-4e82-aed2-d57693cfab90",
   "metadata": {},
   "source": [
    "### 1- Recommendations For The Title 'The Lord of the Rings: The Two Towers: Visual Companion'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "94bef505-f60f-49aa-92b4-d29c4d498455",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Ten Rings: My Championship Seasons',\n",
       " 'Physics on the Fringe: Smoke Rings, Circlons, and Alternative Theories of Everything',\n",
       " \"Witches' Rings\",\n",
       " 'The Rings of Time',\n",
       " 'The Lord of the Rings: The Art of the Fellowship of the Ring',\n",
       " 'Origami Wreaths and Rings',\n",
       " 'Legend of the Five Rings RPG',\n",
       " 'Two Rings: A Story of Love and War',\n",
       " 'The Rings of Haven',\n",
       " 'The Rings of Saturn',\n",
       " 'The Lord of the Rings: The Two Towers: Visual Companion',\n",
       " 'The Lord of the Rings: The Fellowship of the Ring: Visual Companion',\n",
       " 'The Lord of the Rings: Official Movie Guide',\n",
       " 'The Magical Worlds of Lord of the Rings: The Amazing Myths, Legends and Facts Behind the Masterpiece',\n",
       " \"Tolkien's Ordinary Virtues: Exploring the Spiritual Themes of the Lord of the Rings\",\n",
       " 'Keeper of the Rings',\n",
       " 'The Return of the Shadow: The History of The Lord of the Rings, Part One',\n",
       " \"Musashi's Book of Five Rings: The Definitive Interpertation of Miyomoto Musashi's Classic Book of Strategy\"]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "check_book('Rings')[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "cd668edc-f9a4-4bd5-898d-88bf33c6c320",
   "metadata": {},
   "outputs": [],
   "source": [
    "book_index = indices['The Lord of the Rings: The Two Towers: Visual Companion']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "9506a2e7-ad7f-4cd9-b7f1-7c22765c5379",
   "metadata": {},
   "outputs": [],
   "source": [
    "similarity_scores = pd.DataFrame(cosine_sim[book_index],\n",
    "                                 columns=['score'])\n",
    "\n",
    "book_indices = similarity_scores.sort_values('score', ascending=False)[1:11].index"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa5dfe26-fb15-4af9-ba4f-86e07371f5b3",
   "metadata": {},
   "source": [
    "**10 similar titles with The Lord of the Rings: The Two Towers: Visual Companion**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "a5843857-3946-4ec2-9328-7511c1c7ac71",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['The Lord of the Rings: The Fellowship of the Ring: Visual Companion',\n",
       " 'The Return of the Shadow: The History of The Lord of the Rings, Part One',\n",
       " 'The Lord of the Rings: The Art of the Fellowship of the Ring',\n",
       " 'Catnap',\n",
       " 'Gollum: How We Made Movie Magic',\n",
       " 'The Magical Worlds of Lord of the Rings: The Amazing Myths, Legends and Facts Behind the Masterpiece',\n",
       " \"The Hobbit and Philosophy: For When You've Lost Your Dwarves, Your Wizard, and Your Way\",\n",
       " 'The Art of The Hobbit by J.R.R. Tolkien',\n",
       " 'The Lord of the Rings: Official Movie Guide',\n",
       " 'Introduction to Ring Theory']"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_books_df['title'].iloc[book_indices].tolist()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d5bb8ed-d810-4259-a043-18e9543e25ce",
   "metadata": {},
   "source": [
    "### 2- Recommendations For The Title 'Star Trek and History'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "b46e6a97-2a4a-43b7-aae0-bd304f5ca3c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[\"Star Trek: Captain's Log\",\n",
       " 'Beyond Star Trek: From Alien Invasions to the End of Time',\n",
       " \"Star Wars vs. Star Trek: Could the Empire kick the Federation's ass? And other galaxy-shaking enigmas\",\n",
       " 'Computers Of Star Trek',\n",
       " 'Star Trek: The Next Generation - The Gorn Crisis',\n",
       " 'Star Trek: Deep Space Nine Technical Manual',\n",
       " 'Star Trek IV: The Voyage Home',\n",
       " 'The Meaning of Star Trek',\n",
       " 'Star Trek: the manga Volume 2: Kakan ni Shinkou',\n",
       " 'The Best of Trek: From the Magazine for Star Trek Fans',\n",
       " 'Inside Star Trek: The Real Story',\n",
       " 'Star Trek Vault: 40 Years from the Archives',\n",
       " 'Star Trek Book of Opposites',\n",
       " 'Star Trek: The Motion Picture : The Photostory',\n",
       " 'Klingon: Star Trek',\n",
       " \"Chekov's Enterprise: A Personal Journal of the Making of Star Trek, the Motion Picture\",\n",
       " 'The Star Trek Encyclopedia',\n",
       " 'A Brief Guide to Star Trek',\n",
       " 'Star Trek: Strange New Worlds V',\n",
       " 'Star Trek Puzzle Manual']"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "check_book('Star Trek')[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "da5383bb-1f14-423a-a596-fc872008f7a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "book_index = indices[\"Star Trek and History\"]\n",
    "\n",
    "similarity_scores = pd.DataFrame(cosine_sim[book_index],\n",
    "                                 columns=['score'])\n",
    "\n",
    "book_indices = similarity_scores.sort_values('score', ascending=False)[1:11].index"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa81ba05-f806-4bc6-a317-d5359df16250",
   "metadata": {},
   "source": [
    "**10 similar titles with Star Trek and History**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "a2334719-8fec-4fd3-a366-c56105f2d534",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Star Trek: Strange New Worlds V',\n",
       " 'Star Trek FAQ: Everything Left to Know about the First Voyages of the Starship Enterprise Unofficial and Unauthorized',\n",
       " 'Where No One Has Gone Before: A History in Pictures (Star Trek: All)',\n",
       " 'All I Really Need to Know I Learned from Watching Star Trek',\n",
       " 'Star Trek Vault: 40 Years from the Archives',\n",
       " 'Countdown to Darkness',\n",
       " 'Star Trek Classic Quotes: The Next Generation',\n",
       " 'Star Trek: The Next Generation 365',\n",
       " 'The Star Trek Reader I',\n",
       " 'Computers Of Star Trek']"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_books_df['title'].iloc[book_indices].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "f93f920b-9e85-47ac-b08b-f9297512a31b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "check_book('Dorian Gray')[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "13e48d73-8dc7-4df9-85b7-1d9a8ac3c57d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "check_book('When Nietsche Nept')[:20]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1eba829-48fc-4cac-84e6-cf0f9783d3cf",
   "metadata": {},
   "source": [
    "**:(**  I just wanted to search for my favorite books, but the dataset does not include the books."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31e5d91f-f45f-4290-834f-2a954fd7be00",
   "metadata": {},
   "source": [
    "### 3-Recommendations For The Title 'Batman: Gotham Nights #1'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "93c347df-dc4c-4786-b530-fa243b2d0962",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Batman: Impostors',\n",
       " 'Batman: Knight and Squire',\n",
       " 'Batman: Dark Knight of the Round Table Vol. 1',\n",
       " 'Batman: Gotham Noir',\n",
       " 'Batman: Gotham Nights #1',\n",
       " 'Batman: Year 100',\n",
       " \"Year One: Batman/Ra's al Ghul\",\n",
       " 'Batman: Bruce Wayne, Murderer?',\n",
       " 'Batman: Bruce Wayne, Fugitive, Vol. 1',\n",
       " 'Batman: The Long Halloween',\n",
       " 'Batman: Dark Victory',\n",
       " 'Batman: Haunted Knight',\n",
       " 'Batman: Man-Bat',\n",
       " 'Batman: Secrets',\n",
       " 'Batman: Knightfall, Part Two: Who Rules the Night',\n",
       " 'Batman: Hush, Vol. 2',\n",
       " 'Superman/Batman, Vol. 2: Supergirl',\n",
       " 'Superman/Batman, Vol. 4: Vengeance',\n",
       " 'The Batman Handbook',\n",
       " 'Batman: War Crimes']"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "check_book('Batman')[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "91a23afc-2770-402b-aa0c-31f315633d3e",
   "metadata": {},
   "outputs": [],
   "source": [
    "book_index = indices['Batman: Gotham Nights #1']\n",
    "\n",
    "similarity_scores = pd.DataFrame(cosine_sim[book_index],\n",
    "                                 columns=['score'])\n",
    "\n",
    "book_indices = similarity_scores.sort_values('score', ascending=False)[1:11].index"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ff16428-7c26-4b71-8da6-36d2328a623f",
   "metadata": {},
   "source": [
    "**10 similar titles with Batman: Gotham Nights #1**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "6ccd0645-f65a-45e8-9345-b557c7ac3fc3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[\"You Can't Afford the Luxury of a Negative Thought\",\n",
       " 'Batman: Gates of Gotham',\n",
       " 'Batman: The Black Mirror',\n",
       " 'Batman: Year Two: Fear the Reaper',\n",
       " 'Batman: Dark Victory',\n",
       " 'Batman: The Dark Knight - Golden Dawn',\n",
       " 'Batman: Cataclysm',\n",
       " 'Something Out There: Stories',\n",
       " 'Batman: Gotham County Line',\n",
       " 'Batman: Knightfall, Part Two: Who Rules the Night']"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_books_df['title'].iloc[book_indices].tolist()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca09f0dd-634b-428c-a89c-b277f30fbd0f",
   "metadata": {},
   "source": [
    "### 4-Recommendations For The Title 'Neural Darwinism: The Theory Of Neuronal Group Selection'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "135951f9-c3e9-4a03-bb13-372cb7e7236b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['A Field Guide to Earthlings: An Autistic/Asperger View of Neurotypical Behavior',\n",
       " 'The Organization of Behavior: A Neuropsychological Theory',\n",
       " 'The Scientific American Book of Love, Sex and the Brain: The Neuroscience of How, When, Why and Who We Love',\n",
       " 'The Branded Mind: What Neuroscience Really Tells Us about the Puzzle of the Brain and the Brand',\n",
       " 'Decisions, Uncertainty, and the Brain: The Science of Neuroeconomics',\n",
       " 'Introduction to Neurolinguistics',\n",
       " 'Neural Darwinism: The Theory Of Neuronal Group Selection',\n",
       " 'Neurobiology',\n",
       " 'I of the Vortex: From Neurons to Self',\n",
       " \"Soccer Men: Profiles of the Rogues, Geniuses, and Neurotics Who Dominate the World's Most Popular Sport\",\n",
       " 'Neurological  Rehabilitation',\n",
       " 'Left Brain, Right Brain: Perspectives from Cognitive Neuroscience',\n",
       " 'Neurolink',\n",
       " 'Brainfluence: 100 Ways to Persuade and Convince Consumers with Neuromarketing',\n",
       " 'Neurogastronomy: How the Brain Creates Flavor and Why It Matters',\n",
       " 'How to Live with a Neurotic Dog',\n",
       " 'The Quest for Consciousness: A Neurobiological Approach',\n",
       " 'Defining Right and Wrong in Brain Science: Essential Readings in Neuroethics',\n",
       " 'The Neuropsychology of Dreams: A Clinico-Anatomical Study',\n",
       " 'The Brain and the Inner World: An Introduction to the Neuroscience of Subjective Experience']"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "check_book('Neuro')[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "094424be-5eae-4f64-b693-936ace43f003",
   "metadata": {},
   "outputs": [],
   "source": [
    "book_index = indices['Neural Darwinism: The Theory Of Neuronal Group Selection']\n",
    "\n",
    "similarity_scores = pd.DataFrame(cosine_sim[book_index],\n",
    "                                 columns=['score'])\n",
    "\n",
    "book_indices = similarity_scores.sort_values('score', ascending=False)[1:11].index"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd24fb0a-7a32-42ac-8c5a-ca4a1ee2eac0",
   "metadata": {},
   "source": [
    "**10 similar titles with Neural Darwinism: The Theory Of Neuronal Group Selection**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "98ca4b21-a1f7-48ee-8051-70c98d4e4037",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Neurobiology',\n",
       " 'The Philosophy of Human Evolution',\n",
       " 'Modern Operating Systems',\n",
       " 'Beyond the Brain: How Body and Environment Shape Animal and Human Minds',\n",
       " 'Exploring Creation with Biology',\n",
       " 'Principles of Brain Dynamics: Global State Interactions',\n",
       " 'The Synaptic Organization of the Brain',\n",
       " 'How Brains Make Up Their Minds',\n",
       " 'Principles of Human Evolution',\n",
       " 'The Adapted Mind: Evolutionary Psychology and the Generation of Culture']"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_books_df['title'].iloc[book_indices].tolist()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c3730ac-de99-4a4f-a528-e869e40c5ef7",
   "metadata": {},
   "source": [
    "### 5- Recommendations For The Title 'Data Structures and Algorithms in Python'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "0ae99a12-4497-484c-a32f-53abea282f49",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Bushmanders and Bullwinkles: How Politicians Manipulate Electronic Maps and Census Data to Win Elections',\n",
       " 'Handbook of Functional MRI Data Analysis',\n",
       " 'Bayesian Logical Data Analysis for the Physical Sciences: A Comparative Approach with Mathematica Support',\n",
       " 'R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics',\n",
       " 'Linked Data: Evolving the Web Into a Global Data Space',\n",
       " 'Data Structures and Algorithms',\n",
       " 'Readings in Database Systems',\n",
       " 'Access Database Design & Programming',\n",
       " 'Data Structures and the Java Collections Framework',\n",
       " 'The Dinosaur Data Book: The Definitive, Fully Illustrated Encyclopedia Of Dinosaurs',\n",
       " 'Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing',\n",
       " 'A Practical Guide to Designing with Data',\n",
       " \"Big Data Now: Current Perspectives from O'Reilly Radar\",\n",
       " 'Mining of Massive Datasets',\n",
       " 'Big Data: Principles and best practices of scalable realtime data systems',\n",
       " 'What Is Data Science?',\n",
       " 'Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence',\n",
       " 'Hierarchical Linear Models: Applications and Data Analysis Methods',\n",
       " 'Data Structures and Algorithms in Python',\n",
       " 'Data Analysis: A Bayesian Tutorial']"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "check_book('Data')[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "4aaefeb1-9b49-4936-9b6d-7ec716ae6ff2",
   "metadata": {},
   "outputs": [],
   "source": [
    "book_index = indices['Data Structures and Algorithms in Python']\n",
    "\n",
    "similarity_scores = pd.DataFrame(cosine_sim[book_index],\n",
    "                                 columns=['score'])\n",
    "\n",
    "book_indices = similarity_scores.sort_values('score', ascending=False)[1:11].index"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52dc4a70-a050-4393-b986-d521e67b1601",
   "metadata": {},
   "source": [
    "**10 similar titles with Data Structures and Algorithms in Python**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "f6e5d3f6-4f1f-45c1-a136-f16cdd25e3db",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Data Structures and Algorithms',\n",
       " 'Algorithms',\n",
       " 'A Simple Introduction to Data Science',\n",
       " 'Foundations of Multidimensional and Metric Data Structures',\n",
       " \"Big Data Now: Current Perspectives from O'Reilly Radar\",\n",
       " 'What Is Data Science?',\n",
       " 'Python for Data Analysis',\n",
       " 'The Design and Analysis of Computer Algorithms',\n",
       " 'Data Structures and the Java Collections Framework',\n",
       " 'Think Python']"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_books_df['title'].iloc[book_indices].tolist()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43c9047e-eed4-41ce-97c3-c8dca7ee2506",
   "metadata": {},
   "source": [
    "### Final : Preparation of Working Script"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "c2612ab5-78df-4f8b-a808-daa736e23eca",
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_cosine_sim(dataframe, col):\n",
    "    tfidf = TfidfVectorizer()\n",
    "    tfidf_matrix = tfidf.fit_transform(dataframe[col])\n",
    "    cosine_sim = cosine_similarity(tfidf_matrix, tfidf_matrix)\n",
    "    return cosine_sim\n",
    "\n",
    "def recommendation(title, cosine_sim, dataframe):\n",
    "    indices = pd.Series(dataframe.index, index=dataframe['title'])\n",
    "    indices = indices[~indices.index.duplicated(keep='last')]\n",
    "    book_index = indices[title]\n",
    "    similarity_scores = pd.DataFrame(cosine_sim[book_index],\n",
    "                                     columns=[\"score\"])\n",
    "    book_indices = similarity_scores.sort_values(\"score\", ascending=False)[1:11].index\n",
    "    return dataframe['title'].iloc[book_indices]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d5541c4-dcaf-4de4-b04e-b21fb5d0d3c6",
   "metadata": {},
   "source": [
    "## Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6dc3d91-e4f8-49db-9740-c56fc272102f",
   "metadata": {},
   "source": [
    "- We see that one of the advantages of the content-based recommendation system is that the model can capture a user's specific interests.\n",
    "- As we can see in 5 different examples, other series of Batman for Batman or other series of this book for Lord Of The Rings are recommended.As a disadvantage, content-based filtering offers only a small amount of novelty."
   ]
  }
 ],
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