BookRecommendationSystem.ipynb

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  "metadata": {
    "colab": {
      "name": "BookRecommendationSystem.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyOv/IBZ0iydm7ifGq54PJT3",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ria3999/mahine_learning-codes/blob/master/BookRecommendationSystem.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2YndTjG797n5"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xnnaJ6eq-pF9",
        "outputId": "3654a587-8944-488e-9fd8-d50020c0f86a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 141
        }
      },
      "source": [
        "books=pd.read_csv('BX-Books.csv',sep=';',error_bad_lines=False,encoding=\"latin-1\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "b'Skipping line 6452: expected 8 fields, saw 9\\nSkipping line 43667: expected 8 fields, saw 10\\nSkipping line 51751: expected 8 fields, saw 9\\n'\n",
            "b'Skipping line 92038: expected 8 fields, saw 9\\nSkipping line 104319: expected 8 fields, saw 9\\nSkipping line 121768: expected 8 fields, saw 9\\n'\n",
            "b'Skipping line 144058: expected 8 fields, saw 9\\nSkipping line 150789: expected 8 fields, saw 9\\nSkipping line 157128: expected 8 fields, saw 9\\nSkipping line 180189: expected 8 fields, saw 9\\nSkipping line 185738: expected 8 fields, saw 9\\n'\n",
            "b'Skipping line 209388: expected 8 fields, saw 9\\nSkipping line 220626: expected 8 fields, saw 9\\nSkipping line 227933: expected 8 fields, saw 11\\nSkipping line 228957: expected 8 fields, saw 10\\nSkipping line 245933: expected 8 fields, saw 9\\nSkipping line 251296: expected 8 fields, saw 9\\nSkipping line 259941: expected 8 fields, saw 9\\nSkipping line 261529: expected 8 fields, saw 9\\n'\n",
            "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py:2718: DtypeWarning: Columns (3) have mixed types.Specify dtype option on import or set low_memory=False.\n",
            "  interactivity=interactivity, compiler=compiler, result=result)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gf-ZKei_-vb1",
        "outputId": "8469c09a-fcf0-412c-9086-fee3091809f1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 69
        }
      },
      "source": [
        "books.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['ISBN', 'Book-Title', 'Book-Author', 'Year-Of-Publication', 'Publisher',\n",
              "       'Image-URL-S', 'Image-URL-M', 'Image-URL-L'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3UWDXGmLD5oU"
      },
      "source": [
        "users=pd.read_csv('/content/BX-Users.csv',sep=';',error_bad_lines=False,encoding=\"latin-1\")\n",
        "ratings = pd.read_csv('BX-Book-Ratings.csv', sep=';', error_bad_lines=False, encoding=\"latin-1\")\n",
        "ratings.rename(columns = {'Book-Rating':'BookRating'},inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wSp4uGAKG23l",
        "outputId": "5d4b5a47-eb3e-49dd-b45d-c0e8b1c90190",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        }
      },
      "source": [
        "print(books.shape)\n",
        "print(list(books.columns))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(271360, 8)\n",
            "['ISBN', 'Book-Title', 'Book-Author', 'Year-Of-Publication', 'Publisher', 'Image-URL-S', 'Image-URL-M', 'Image-URL-L']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-V94aXjCJXmr",
        "outputId": "99a431f3-2ea6-42f0-cd60-a3907e4aa04e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "source": [
        "print(users.shape)\n",
        "print(list(users.columns))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(278858, 3)\n",
            "['User-ID', 'Location', 'Age']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Uo0gRdCNK3BH"
      },
      "source": [
        "rating_count=pd.DataFrame(ratings.groupby('ISBN')['BookRating'].count())"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6CPSZMGFMESy",
        "outputId": "9f729a34-9daf-48b9-b7aa-1840094fd2f5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 233
        }
      },
      "source": [
        "\n",
        "rating_count.sort_values('BookRating', ascending=False).head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>BookRating</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ISBN</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0971880107</th>\n",
              "      <td>2502</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0316666343</th>\n",
              "      <td>1295</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0385504209</th>\n",
              "      <td>883</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0060928336</th>\n",
              "      <td>732</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0312195516</th>\n",
              "      <td>723</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            BookRating\n",
              "ISBN                  \n",
              "0971880107        2502\n",
              "0316666343        1295\n",
              "0385504209         883\n",
              "0060928336         732\n",
              "0312195516         723"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zTJZfoWnMT8e",
        "outputId": "96281a73-d78d-4c06-adb9-4afe9ef0a650",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        }
      },
      "source": [
        "most_rated_books = pd.DataFrame(['0971880107', '0316666343', '0385504209', '0060928336', '0312195516'], index=np.arange(5), columns = ['ISBN'])\n",
        "most_rated_books_summary = pd.merge(most_rated_books, books, on='ISBN')\n",
        "most_rated_books_summary\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ISBN</th>\n",
              "      <th>Book-Title</th>\n",
              "      <th>Book-Author</th>\n",
              "      <th>Year-Of-Publication</th>\n",
              "      <th>Publisher</th>\n",
              "      <th>Image-URL-S</th>\n",
              "      <th>Image-URL-M</th>\n",
              "      <th>Image-URL-L</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0971880107</td>\n",
              "      <td>Wild Animus</td>\n",
              "      <td>Rich Shapero</td>\n",
              "      <td>2004</td>\n",
              "      <td>Too Far</td>\n",
              "      <td>http://images.amazon.com/images/P/0971880107.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0971880107.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0971880107.0...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0316666343</td>\n",
              "      <td>The Lovely Bones: A Novel</td>\n",
              "      <td>Alice Sebold</td>\n",
              "      <td>2002</td>\n",
              "      <td>Little, Brown</td>\n",
              "      <td>http://images.amazon.com/images/P/0316666343.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0316666343.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0316666343.0...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0385504209</td>\n",
              "      <td>The Da Vinci Code</td>\n",
              "      <td>Dan Brown</td>\n",
              "      <td>2003</td>\n",
              "      <td>Doubleday</td>\n",
              "      <td>http://images.amazon.com/images/P/0385504209.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0385504209.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0385504209.0...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0060928336</td>\n",
              "      <td>Divine Secrets of the Ya-Ya Sisterhood: A Novel</td>\n",
              "      <td>Rebecca Wells</td>\n",
              "      <td>1997</td>\n",
              "      <td>Perennial</td>\n",
              "      <td>http://images.amazon.com/images/P/0060928336.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0060928336.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0060928336.0...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0312195516</td>\n",
              "      <td>The Red Tent (Bestselling Backlist)</td>\n",
              "      <td>Anita Diamant</td>\n",
              "      <td>1998</td>\n",
              "      <td>Picador USA</td>\n",
              "      <td>http://images.amazon.com/images/P/0312195516.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0312195516.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0312195516.0...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         ISBN  ...                                        Image-URL-L\n",
              "0  0971880107  ...  http://images.amazon.com/images/P/0971880107.0...\n",
              "1  0316666343  ...  http://images.amazon.com/images/P/0316666343.0...\n",
              "2  0385504209  ...  http://images.amazon.com/images/P/0385504209.0...\n",
              "3  0060928336  ...  http://images.amazon.com/images/P/0060928336.0...\n",
              "4  0312195516  ...  http://images.amazon.com/images/P/0312195516.0...\n",
              "\n",
              "[5 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2mLOclhjM28a",
        "outputId": "f1580e11-97e9-4a01-ea11-ffee6fe95cc2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 233
        }
      },
      "source": [
        "average_rating = pd.DataFrame(ratings.groupby('ISBN')['BookRating'].mean())\n",
        "average_rating['ratingCount'] = pd.DataFrame(ratings.groupby('ISBN')['BookRating'].count())\n",
        "average_rating.sort_values('ratingCount', ascending=False).head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>BookRating</th>\n",
              "      <th>ratingCount</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ISBN</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0971880107</th>\n",
              "      <td>1.019584</td>\n",
              "      <td>2502</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0316666343</th>\n",
              "      <td>4.468726</td>\n",
              "      <td>1295</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0385504209</th>\n",
              "      <td>4.652322</td>\n",
              "      <td>883</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0060928336</th>\n",
              "      <td>3.448087</td>\n",
              "      <td>732</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0312195516</th>\n",
              "      <td>4.334716</td>\n",
              "      <td>723</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            BookRating  ratingCount\n",
              "ISBN                               \n",
              "0971880107    1.019584         2502\n",
              "0316666343    4.468726         1295\n",
              "0385504209    4.652322          883\n",
              "0060928336    3.448087          732\n",
              "0312195516    4.334716          723"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-F2PsoP2YMYO",
        "outputId": "dc1c1ae5-12b7-4c79-b7fe-bd713ba05ba4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "ratings.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['User-ID', 'ISBN', 'BookRating'], dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Vbq8qEh6Tkxp"
      },
      "source": [
        "counts1 = ratings['User-ID'].value_counts()\n",
        "ratings = ratings[ratings['User-ID'].isin(counts1[counts1 >= 200].index)]\n",
        "counts = ratings['BookRating'].value_counts()\n",
        "ratings = ratings[ratings['BookRating'].isin(counts[counts >= 100].index)]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RdVwf6wCYJKQ",
        "outputId": "86634ded-3ccc-454e-83d2-6b9b548a3361",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 369
        }
      },
      "source": [
        "ratings_pivot = ratings.pivot(index='User-ID', columns='ISBN').BookRating\n",
        "userID = ratings_pivot.index\n",
        "ISBN = ratings_pivot.columns\n",
        "print(ratings_pivot.shape)\n",
        "ratings_pivot.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(905, 207699)\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
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              "      <th>ISBN</th>\n",
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              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 207699 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "ISBN      0330299891   0375404120   0586045007  ...  cn108465  cn113107  Ô½crosoft\n",
              "User-ID                                         ...                               \n",
              "254              NaN          NaN          NaN  ...       NaN       NaN        NaN\n",
              "2276             NaN          NaN          NaN  ...       NaN       NaN        NaN\n",
              "2766             NaN          NaN          NaN  ...       NaN       NaN        NaN\n",
              "2977             NaN          NaN          NaN  ...       NaN       NaN        NaN\n",
              "3363             NaN          NaN          NaN  ...       NaN       NaN        NaN\n",
              "\n",
              "[5 rows x 207699 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yXPa7LvoYlHI"
      },
      "source": [
        "bones_ratings = ratings_pivot['0316666343']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jlVjUQOFYxGu",
        "outputId": "78b52a91-f320-464e-8902-aef6cae2b5cb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 87
        }
      },
      "source": [
        "similar_to_bones = ratings_pivot.corrwith(bones_ratings)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/numpy/lib/function_base.py:2526: RuntimeWarning: Degrees of freedom <= 0 for slice\n",
            "  c = cov(x, y, rowvar)\n",
            "/usr/local/lib/python3.6/dist-packages/numpy/lib/function_base.py:2455: RuntimeWarning: divide by zero encountered in true_divide\n",
            "  c *= np.true_divide(1, fact)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K4nZAGhEY0f-"
      },
      "source": [
        "corr_bones = pd.DataFrame(similar_to_bones, columns=['pearsonR'])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9LIxr2bhZNFN",
        "outputId": "1b62f170-8832-41b5-b145-374a85cb162b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        }
      },
      "source": [
        "corr_bones.dropna(inplace=True)\n",
        "corr_summary = corr_bones.join(average_rating['ratingCount'])\n",
        "corr_summary[corr_summary['ratingCount']>=300].sort_values('pearsonR', ascending=False).head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "\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>pearsonR</th>\n",
              "      <th>ratingCount</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ISBN</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0316666343</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>1295</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0312291639</th>\n",
              "      <td>0.471872</td>\n",
              "      <td>354</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0316601950</th>\n",
              "      <td>0.434248</td>\n",
              "      <td>568</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0446610038</th>\n",
              "      <td>0.429712</td>\n",
              "      <td>391</td>\n",
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              "    <tr>\n",
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              "      <td>585</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0385265700</th>\n",
              "      <td>0.351635</td>\n",
              "      <td>319</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0345342968</th>\n",
              "      <td>0.316922</td>\n",
              "      <td>321</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0060930535</th>\n",
              "      <td>0.309860</td>\n",
              "      <td>494</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0375707972</th>\n",
              "      <td>0.308145</td>\n",
              "      <td>354</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0684872153</th>\n",
              "      <td>0.272480</td>\n",
              "      <td>326</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            pearsonR  ratingCount\n",
              "ISBN                             \n",
              "0316666343  1.000000         1295\n",
              "0312291639  0.471872          354\n",
              "0316601950  0.434248          568\n",
              "0446610038  0.429712          391\n",
              "0446672211  0.421478          585\n",
              "0385265700  0.351635          319\n",
              "0345342968  0.316922          321\n",
              "0060930535  0.309860          494\n",
              "0375707972  0.308145          354\n",
              "0684872153  0.272480          326"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TVC-pOqUZXgp",
        "outputId": "e4963bfa-0155-4a62-f56b-c3aa012ea0f0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 743
        }
      },
      "source": [
        "\n",
        "books_corr_to_bones = pd.DataFrame(['0312291639', '0316601950', '0446610038', '0446672211', '0385265700', '0345342968', '0060930535', '0375707972', '0684872153'], \n",
        "                                  index=np.arange(9), columns=['ISBN'])\n",
        "corr_books = pd.merge(books_corr_to_bones, books, on='ISBN')\n",
        "corr_books"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ISBN</th>\n",
              "      <th>Book-Title</th>\n",
              "      <th>Book-Author</th>\n",
              "      <th>Year-Of-Publication</th>\n",
              "      <th>Publisher</th>\n",
              "      <th>Image-URL-S</th>\n",
              "      <th>Image-URL-M</th>\n",
              "      <th>Image-URL-L</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0312291639</td>\n",
              "      <td>The Nanny Diaries: A Novel</td>\n",
              "      <td>Emma McLaughlin</td>\n",
              "      <td>2003</td>\n",
              "      <td>St. Martin's Griffin</td>\n",
              "      <td>http://images.amazon.com/images/P/0312291639.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0312291639.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0312291639.0...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0316601950</td>\n",
              "      <td>The Pilot's Wife : A Novel</td>\n",
              "      <td>Anita Shreve</td>\n",
              "      <td>1999</td>\n",
              "      <td>Back Bay Books</td>\n",
              "      <td>http://images.amazon.com/images/P/0316601950.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0316601950.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0316601950.0...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0446610038</td>\n",
              "      <td>1st to Die: A Novel</td>\n",
              "      <td>James Patterson</td>\n",
              "      <td>2002</td>\n",
              "      <td>Warner Vision</td>\n",
              "      <td>http://images.amazon.com/images/P/0446610038.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0446610038.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0446610038.0...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0446672211</td>\n",
              "      <td>Where the Heart Is (Oprah's Book Club (Paperba...</td>\n",
              "      <td>Billie Letts</td>\n",
              "      <td>1998</td>\n",
              "      <td>Warner Books</td>\n",
              "      <td>http://images.amazon.com/images/P/0446672211.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0446672211.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0446672211.0...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0385265700</td>\n",
              "      <td>The Book of Ruth (Oprah's Book Club (Paperback))</td>\n",
              "      <td>Jane Hamilton</td>\n",
              "      <td>1990</td>\n",
              "      <td>Anchor</td>\n",
              "      <td>http://images.amazon.com/images/P/0385265700.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0385265700.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0385265700.0...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0345342968</td>\n",
              "      <td>Fahrenheit 451</td>\n",
              "      <td>RAY BRADBURY</td>\n",
              "      <td>1987</td>\n",
              "      <td>Del Rey</td>\n",
              "      <td>http://images.amazon.com/images/P/0345342968.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0345342968.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0345342968.0...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0060930535</td>\n",
              "      <td>The Poisonwood Bible: A Novel</td>\n",
              "      <td>Barbara Kingsolver</td>\n",
              "      <td>1999</td>\n",
              "      <td>Perennial</td>\n",
              "      <td>http://images.amazon.com/images/P/0060930535.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0060930535.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0060930535.0...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>0375707972</td>\n",
              "      <td>The Reader</td>\n",
              "      <td>Bernhard Schlink</td>\n",
              "      <td>1999</td>\n",
              "      <td>Vintage Books USA</td>\n",
              "      <td>http://images.amazon.com/images/P/0375707972.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0375707972.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0375707972.0...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>0684872153</td>\n",
              "      <td>Angela's Ashes (MMP) : A Memoir</td>\n",
              "      <td>Frank McCourt</td>\n",
              "      <td>1999</td>\n",
              "      <td>Scribner</td>\n",
              "      <td>http://images.amazon.com/images/P/0684872153.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0684872153.0...</td>\n",
              "      <td>http://images.amazon.com/images/P/0684872153.0...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         ISBN  ...                                        Image-URL-L\n",
              "0  0312291639  ...  http://images.amazon.com/images/P/0312291639.0...\n",
              "1  0316601950  ...  http://images.amazon.com/images/P/0316601950.0...\n",
              "2  0446610038  ...  http://images.amazon.com/images/P/0446610038.0...\n",
              "3  0446672211  ...  http://images.amazon.com/images/P/0446672211.0...\n",
              "4  0385265700  ...  http://images.amazon.com/images/P/0385265700.0...\n",
              "5  0345342968  ...  http://images.amazon.com/images/P/0345342968.0...\n",
              "6  0060930535  ...  http://images.amazon.com/images/P/0060930535.0...\n",
              "7  0375707972  ...  http://images.amazon.com/images/P/0375707972.0...\n",
              "8  0684872153  ...  http://images.amazon.com/images/P/0684872153.0...\n",
              "\n",
              "[9 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "amaEMxt9lAOf",
        "outputId": "64fb3541-6e5c-4cae-9448-adce25121b12",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 87
        }
      },
      "source": [
        "combine_book_rating.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['User-ID', 'ISBN', 'BookRating', 'Book-Title', 'Book-Author',\n",
              "       'Year-Of-Publication', 'Publisher', 'Image-URL-S', 'Image-URL-M',\n",
              "       'Image-URL-L'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fJ9VzzkpdDIf",
        "outputId": "fcf7ce8e-f639-4e7b-e863-2a55415d5911",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        }
      },
      "source": [
        "combine_book_rating = pd.merge(ratings, books, on='ISBN')\n",
        "columns = ['Year-Of-Publication', 'Publisher', 'Book-Author', 'Image-URL-S', 'Image-URL-M', 'Image-URL-L']\n",
        "combine_book_rating = combine_book_rating.drop(columns, axis=1)\n",
        "combine_book_rating.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "</style>\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>User-ID</th>\n",
              "      <th>ISBN</th>\n",
              "      <th>BookRating</th>\n",
              "      <th>Book-Title</th>\n",
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              "      <th>0</th>\n",
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              "      <td>3363</td>\n",
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              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
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              "      <td>002542730X</td>\n",
              "      <td>0</td>\n",
              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   User-ID  ...                                         Book-Title\n",
              "0   277427  ...  Politically Correct Bedtime Stories: Modern Ta...\n",
              "1     3363  ...  Politically Correct Bedtime Stories: Modern Ta...\n",
              "2    11676  ...  Politically Correct Bedtime Stories: Modern Ta...\n",
              "3    12538  ...  Politically Correct Bedtime Stories: Modern Ta...\n",
              "4    13552  ...  Politically Correct Bedtime Stories: Modern Ta...\n",
              "\n",
              "[5 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FNZBTmkWhIeD",
        "outputId": "ec131fc6-bc02-405f-a028-02e41a64ea8b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        }
      },
      "source": [
        "\n",
        "combine_book_rating = combine_book_rating.dropna(axis = 0, subset = ['Book-Title'])\n",
        "\n",
        "book_ratingCount = (combine_book_rating.\n",
        "     groupby(by = ['Book-Title'])['BookRating'].\n",
        "     count().\n",
        "     reset_index().\n",
        "     rename(columns = {'BookRating': 'totalRatingCount'})\n",
        "     [['Book-Title', 'totalRatingCount']]\n",
        "    )\n",
        "book_ratingCount.head()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Book-Title</th>\n",
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              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A Light in the Storm: The Civil War Diary of ...</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Always Have Popsicles</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
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              "      <th>2</th>\n",
              "      <td>Apple Magic (The Collector's series)</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
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              "      <th>3</th>\n",
              "      <td>Beyond IBM: Leadership Marketing and Finance ...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Clifford Visita El Hospital (Clifford El Gran...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                          Book-Title  totalRatingCount\n",
              "0   A Light in the Storm: The Civil War Diary of ...                 2\n",
              "1                              Always Have Popsicles                 1\n",
              "2               Apple Magic (The Collector's series)                 1\n",
              "3   Beyond IBM: Leadership Marketing and Finance ...                 1\n",
              "4   Clifford Visita El Hospital (Clifford El Gran...                 1"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MzDS1WewhMpR",
        "outputId": "d38e72a4-b173-47e7-b1f2-0745b4f5deec",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        }
      },
      "source": [
        "\n",
        "rating_with_totalRatingCount = combine_book_rating.merge(book_ratingCount, left_on = 'Book-Title', right_on = 'Book-Title', how = 'left')\n",
        "rating_with_totalRatingCount.head()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "      <th></th>\n",
              "      <th>User-ID</th>\n",
              "      <th>ISBN</th>\n",
              "      <th>BookRating</th>\n",
              "      <th>Book-Title</th>\n",
              "      <th>totalRatingCount</th>\n",
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              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>277427</td>\n",
              "      <td>002542730X</td>\n",
              "      <td>10</td>\n",
              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
              "      <td>82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3363</td>\n",
              "      <td>002542730X</td>\n",
              "      <td>0</td>\n",
              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
              "      <td>82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>11676</td>\n",
              "      <td>002542730X</td>\n",
              "      <td>6</td>\n",
              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
              "      <td>82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>12538</td>\n",
              "      <td>002542730X</td>\n",
              "      <td>10</td>\n",
              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
              "      <td>82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>13552</td>\n",
              "      <td>002542730X</td>\n",
              "      <td>0</td>\n",
              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
              "      <td>82</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   User-ID  ... totalRatingCount\n",
              "0   277427  ...               82\n",
              "1     3363  ...               82\n",
              "2    11676  ...               82\n",
              "3    12538  ...               82\n",
              "4    13552  ...               82\n",
              "\n",
              "[5 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YRRjdAjZhQyF",
        "outputId": "d1842d22-baa6-48a5-9314-b60e25494381",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        }
      },
      "source": [
        "pd.set_option('display.float_format', lambda x: '%.3f' % x)\n",
        "print(book_ratingCount['totalRatingCount'].describe())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "count   160576.000\n",
            "mean         3.044\n",
            "std          7.428\n",
            "min          1.000\n",
            "25%          1.000\n",
            "50%          1.000\n",
            "75%          2.000\n",
            "max        365.000\n",
            "Name: totalRatingCount, dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TyXraKJfhTr0",
        "outputId": "4c0ca55f-b962-43ed-92ae-57ddeade21f4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 208
        }
      },
      "source": [
        "print(book_ratingCount['totalRatingCount'].quantile(np.arange(.9, 1, .01)))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0.900    5.000\n",
            "0.910    6.000\n",
            "0.920    7.000\n",
            "0.930    7.000\n",
            "0.940    8.000\n",
            "0.950   10.000\n",
            "0.960   11.000\n",
            "0.970   14.000\n",
            "0.980   19.000\n",
            "0.990   31.000\n",
            "Name: totalRatingCount, dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xEiBAiiihW4v",
        "outputId": "10118e8c-b6b8-43f1-9680-a10f5610e438",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        }
      },
      "source": [
        "popularity_threshold = 50\n",
        "rating_popular_book = rating_with_totalRatingCount.query('totalRatingCount >= @popularity_threshold')\n",
        "rating_popular_book.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>User-ID</th>\n",
              "      <th>ISBN</th>\n",
              "      <th>BookRating</th>\n",
              "      <th>Book-Title</th>\n",
              "      <th>totalRatingCount</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>277427</td>\n",
              "      <td>002542730X</td>\n",
              "      <td>10</td>\n",
              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
              "      <td>82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3363</td>\n",
              "      <td>002542730X</td>\n",
              "      <td>0</td>\n",
              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
              "      <td>82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>11676</td>\n",
              "      <td>002542730X</td>\n",
              "      <td>6</td>\n",
              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
              "      <td>82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>12538</td>\n",
              "      <td>002542730X</td>\n",
              "      <td>10</td>\n",
              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
              "      <td>82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>13552</td>\n",
              "      <td>002542730X</td>\n",
              "      <td>0</td>\n",
              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
              "      <td>82</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   User-ID  ... totalRatingCount\n",
              "0   277427  ...               82\n",
              "1     3363  ...               82\n",
              "2    11676  ...               82\n",
              "3    12538  ...               82\n",
              "4    13552  ...               82\n",
              "\n",
              "[5 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WZZOHNAHhZZa",
        "outputId": "68e39ef4-3701-4e89-e04b-c8e6f6967d0c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "\n",
        "rating_popular_book.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(62149, 5)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nBSQb8OqhZL5",
        "outputId": "b6f2add5-67a2-42c4-e746-ff5210f15755",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        }
      },
      "source": [
        "\n",
        "combined = rating_popular_book.merge(users, left_on = 'User-ID', right_on = 'User-ID', how = 'left')\n",
        "\n",
        "us_canada_user_rating = combined[combined['Location'].str.contains(\"usa|canada\")]\n",
        "us_canada_user_rating=us_canada_user_rating.drop('Age', axis=1)\n",
        "us_canada_user_rating.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>User-ID</th>\n",
              "      <th>ISBN</th>\n",
              "      <th>BookRating</th>\n",
              "      <th>Book-Title</th>\n",
              "      <th>totalRatingCount</th>\n",
              "      <th>Location</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>277427</td>\n",
              "      <td>002542730X</td>\n",
              "      <td>10</td>\n",
              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
              "      <td>82</td>\n",
              "      <td>gilbert, arizona, usa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3363</td>\n",
              "      <td>002542730X</td>\n",
              "      <td>0</td>\n",
              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
              "      <td>82</td>\n",
              "      <td>knoxville, tennessee, usa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>12538</td>\n",
              "      <td>002542730X</td>\n",
              "      <td>10</td>\n",
              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
              "      <td>82</td>\n",
              "      <td>byron, minnesota, usa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>13552</td>\n",
              "      <td>002542730X</td>\n",
              "      <td>0</td>\n",
              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
              "      <td>82</td>\n",
              "      <td>cordova, tennessee, usa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>16795</td>\n",
              "      <td>002542730X</td>\n",
              "      <td>0</td>\n",
              "      <td>Politically Correct Bedtime Stories: Modern Ta...</td>\n",
              "      <td>82</td>\n",
              "      <td>mechanicsville, maryland, usa</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   User-ID        ISBN  ...  totalRatingCount                       Location\n",
              "0   277427  002542730X  ...                82          gilbert, arizona, usa\n",
              "1     3363  002542730X  ...                82      knoxville, tennessee, usa\n",
              "3    12538  002542730X  ...                82          byron, minnesota, usa\n",
              "4    13552  002542730X  ...                82        cordova, tennessee, usa\n",
              "5    16795  002542730X  ...                82  mechanicsville, maryland, usa\n",
              "\n",
              "[5 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NBOsC2EshirY"
      },
      "source": [
        "from scipy.sparse import csr_matrix\n",
        "us_canada_user_rating = us_canada_user_rating.drop_duplicates(['User-ID', 'Book-Title'])\n",
        "us_canada_user_rating_pivot = us_canada_user_rating.pivot(index = 'Book-Title', columns = 'User-ID', values = 'BookRating').fillna(0)\n",
        "us_canada_user_rating_matrix = csr_matrix(us_canada_user_rating_pivot.values)\n",
        "\n",
        "from sklearn.neighbors import NearestNeighbors"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HbSuhUfRhiZs",
        "outputId": "4420002f-63ca-4c89-8741-0dd40bc69989",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 69
        }
      },
      "source": [
        "model_knn = NearestNeighbors(metric = 'cosine', algorithm = 'brute')\n",
        "model_knn.fit(us_canada_user_rating_matrix)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "NearestNeighbors(algorithm='brute', leaf_size=30, metric='cosine',\n",
              "                 metric_params=None, n_jobs=None, n_neighbors=5, p=2,\n",
              "                 radius=1.0)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tZHdIMJ8hmGk",
        "outputId": "02fb08c5-b96b-486a-a9b4-2301b1c8ebcf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "\n",
        "us_canada_user_rating_pivot.iloc[query_index,:].values.reshape(1,-1)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  7.,\n",
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              "         0.,  0.,  0.,  0.,  0.,  0.]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uNhyL1quhoob",
        "outputId": "0334965b-f6ac-469b-8239-5f54a4298261",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "\n",
        "query_index = np.random.choice(us_canada_user_rating_pivot.shape[0])\n",
        "print(query_index)\n",
        "distances, indices = model_knn.kneighbors(us_canada_user_rating_pivot.iloc[query_index,:].values.reshape(1, -1), n_neighbors = 6)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "402\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D83yDjw7hrv8",
        "outputId": "0905cd4f-43a1-4b4a-d15e-2960cf46f48a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "us_canada_user_rating_pivot.index[query_index]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'Presumed Innocent'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "axrNRQSBhuzm",
        "outputId": "37aade55-1650-46bb-f88a-cc104ab27ddc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 139
        }
      },
      "source": [
        "for i in range(0, len(distances.flatten())):\n",
        "    if i == 0:\n",
        "        print('Recommendations for {0}:\\n'.format(us_canada_user_rating_pivot.index[query_index]))\n",
        "    else:\n",
        "        print('{0}: {1}, with distance of {2}:'.format(i, us_canada_user_rating_pivot.index[indices.flatten()[i]], distances.flatten()[i]))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Recommendations for Presumed Innocent:\n",
            "\n",
            "1: Oryx and Crake, with distance of 0.7084195625674329:\n",
            "2: Silent Witness, with distance of 0.7356952787054876:\n",
            "3: The Cardinal of the Kremlin (Jack Ryan Novels), with distance of 0.7370175626768729:\n",
            "4: A Civil Action, with distance of 0.763779929807967:\n",
            "5: The Brethren, with distance of 0.7657645320388977:\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PXpVogpykeo1"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}