Movie_Recommendation_System.ipynb

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    "colab": {
      "name": "Movie Recommendation Syste.ipynb",
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      "authorship_tag": "ABX9TyO+gfvzNDpKVvrbIADxcBpW",
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      "name": "python3",
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      "name": "python"
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/github/parker1021/Machine-Learning/blob/main/Movie_Recommendation_System.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ewjaIFFQVI0W"
      },
      "source": [
        "### **Importing the Libraries and Data**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0winJqo2PNeY"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from scipy.sparse import csr_matrix\n",
        "from sklearn.neighbors import NearestNeighbors\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "movies = pd.read_csv(\"movies.csv\")\n",
        "ratings = pd.read_csv(\"ratings.csv\")"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 203
        },
        "id": "Jr_yK8m-SBvL",
        "outputId": "d501bcbc-e1fb-415d-d126-0ab52aaf0671"
      },
      "source": [
        "movies.head()"
      ],
      "execution_count": 6,
      "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>movieId</th>\n",
              "      <th>title</th>\n",
              "      <th>genres</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Toy Story (1995)</td>\n",
              "      <td>Adventure|Animation|Children|Comedy|Fantasy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>Jumanji (1995)</td>\n",
              "      <td>Adventure|Children|Fantasy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Grumpier Old Men (1995)</td>\n",
              "      <td>Comedy|Romance</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Waiting to Exhale (1995)</td>\n",
              "      <td>Comedy|Drama|Romance</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Father of the Bride Part II (1995)</td>\n",
              "      <td>Comedy</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   movieId  ...                                       genres\n",
              "0        1  ...  Adventure|Animation|Children|Comedy|Fantasy\n",
              "1        2  ...                   Adventure|Children|Fantasy\n",
              "2        3  ...                               Comedy|Romance\n",
              "3        4  ...                         Comedy|Drama|Romance\n",
              "4        5  ...                                       Comedy\n",
              "\n",
              "[5 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
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          "height": 203
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        "id": "Y1R8NaOaSCBu",
        "outputId": "024e012f-cfd0-4437-e0e7-f7eb28474848"
      },
      "source": [
        "ratings.head()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>userId</th>\n",
              "      <th>movieId</th>\n",
              "      <th>rating</th>\n",
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            "text/plain": [
              "   userId  movieId  rating  timestamp\n",
              "0       1        1     4.0  964982703\n",
              "1       1        3     4.0  964981247\n",
              "2       1        6     4.0  964982224\n",
              "3       1       47     5.0  964983815\n",
              "4       1       50     5.0  964982931"
            ]
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          "execution_count": 7
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        },
        "id": "FtopkEp4SCEk",
        "outputId": "246a4fd8-0d99-4f22-a6d6-e11e0a13f1e3"
      },
      "source": [
        "final_dataset = ratings.pivot(index='movieId',columns='userId',values='rating')\n",
        "final_dataset.head()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 610 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "userId   1    2    3    4    5    6    7    ...  604  605  606  607  608  609  610\n",
              "movieId                                     ...                                   \n",
              "1        4.0  NaN  NaN  NaN  4.0  NaN  4.5  ...  3.0  4.0  2.5  4.0  2.5  3.0  5.0\n",
              "2        NaN  NaN  NaN  NaN  NaN  4.0  NaN  ...  5.0  3.5  NaN  NaN  2.0  NaN  NaN\n",
              "3        4.0  NaN  NaN  NaN  NaN  5.0  NaN  ...  NaN  NaN  NaN  NaN  2.0  NaN  NaN\n",
              "4        NaN  NaN  NaN  NaN  NaN  3.0  NaN  ...  NaN  NaN  NaN  NaN  NaN  NaN  NaN\n",
              "5        NaN  NaN  NaN  NaN  NaN  5.0  NaN  ...  3.0  NaN  NaN  NaN  NaN  NaN  NaN\n",
              "\n",
              "[5 rows x 610 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "8CQiyx8TSCHY",
        "outputId": "0a845e8e-0d99-4fe6-8740-9ed95a47049f"
      },
      "source": [
        "final_dataset.fillna(0,inplace=True)\n",
        "final_dataset.head()"
      ],
      "execution_count": 9,
      "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>userId</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "      <th>6</th>\n",
              "      <th>7</th>\n",
              "      <th>8</th>\n",
              "      <th>9</th>\n",
              "      <th>10</th>\n",
              "      <th>11</th>\n",
              "      <th>12</th>\n",
              "      <th>13</th>\n",
              "      <th>14</th>\n",
              "      <th>15</th>\n",
              "      <th>16</th>\n",
              "      <th>17</th>\n",
              "      <th>18</th>\n",
              "      <th>19</th>\n",
              "      <th>20</th>\n",
              "      <th>21</th>\n",
              "      <th>22</th>\n",
              "      <th>23</th>\n",
              "      <th>24</th>\n",
              "      <th>25</th>\n",
              "      <th>26</th>\n",
              "      <th>27</th>\n",
              "      <th>28</th>\n",
              "      <th>29</th>\n",
              "      <th>30</th>\n",
              "      <th>31</th>\n",
              "      <th>32</th>\n",
              "      <th>33</th>\n",
              "      <th>34</th>\n",
              "      <th>35</th>\n",
              "      <th>36</th>\n",
              "      <th>37</th>\n",
              "      <th>38</th>\n",
              "      <th>39</th>\n",
              "      <th>40</th>\n",
              "      <th>...</th>\n",
              "      <th>571</th>\n",
              "      <th>572</th>\n",
              "      <th>573</th>\n",
              "      <th>574</th>\n",
              "      <th>575</th>\n",
              "      <th>576</th>\n",
              "      <th>577</th>\n",
              "      <th>578</th>\n",
              "      <th>579</th>\n",
              "      <th>580</th>\n",
              "      <th>581</th>\n",
              "      <th>582</th>\n",
              "      <th>583</th>\n",
              "      <th>584</th>\n",
              "      <th>585</th>\n",
              "      <th>586</th>\n",
              "      <th>587</th>\n",
              "      <th>588</th>\n",
              "      <th>589</th>\n",
              "      <th>590</th>\n",
              "      <th>591</th>\n",
              "      <th>592</th>\n",
              "      <th>593</th>\n",
              "      <th>594</th>\n",
              "      <th>595</th>\n",
              "      <th>596</th>\n",
              "      <th>597</th>\n",
              "      <th>598</th>\n",
              "      <th>599</th>\n",
              "      <th>600</th>\n",
              "      <th>601</th>\n",
              "      <th>602</th>\n",
              "      <th>603</th>\n",
              "      <th>604</th>\n",
              "      <th>605</th>\n",
              "      <th>606</th>\n",
              "      <th>607</th>\n",
              "      <th>608</th>\n",
              "      <th>609</th>\n",
              "      <th>610</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>movieId</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.5</td>\n",
              "      <td>3.5</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 610 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "userId   1    2    3    4    5    6    7    ...  604  605  606  607  608  609  610\n",
              "movieId                                     ...                                   \n",
              "1        4.0  0.0  0.0  0.0  4.0  0.0  4.5  ...  3.0  4.0  2.5  4.0  2.5  3.0  5.0\n",
              "2        0.0  0.0  0.0  0.0  0.0  4.0  0.0  ...  5.0  3.5  0.0  0.0  2.0  0.0  0.0\n",
              "3        4.0  0.0  0.0  0.0  0.0  5.0  0.0  ...  0.0  0.0  0.0  0.0  2.0  0.0  0.0\n",
              "4        0.0  0.0  0.0  0.0  0.0  3.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "5        0.0  0.0  0.0  0.0  0.0  5.0  0.0  ...  3.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "\n",
              "[5 rows x 610 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4DmZVaRKSCJo"
      },
      "source": [
        "no_user_voted = ratings.groupby('movieId')['rating'].agg('count')\n",
        "no_movies_voted = ratings.groupby('userId')['rating'].agg('count')"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "CBIlhUxKSCL3",
        "outputId": "e528a863-1b28-4e62-e284-dc63eafb8563"
      },
      "source": [
        "f,ax = plt.subplots(1,1,figsize=(16,4))\n",
        "# ratings['rating'].plot(kind='hist')\n",
        "plt.scatter(no_user_voted.index,no_user_voted,color='mediumseagreen')\n",
        "plt.axhline(y=10,color='r')\n",
        "plt.xlabel('MovieId')\n",
        "plt.ylabel('No. of users voted')\n",
        "plt.show()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "luiEIaSETqIV"
      },
      "source": [
        "final_dataset = final_dataset.loc[no_user_voted[no_user_voted > 10].index,:]"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "0kXIsCkzTpKH",
        "outputId": "db4e09c1-8a02-4e98-d913-edb81191a57b"
      },
      "source": [
        "f,ax = plt.subplots(1,1,figsize=(16,4))\n",
        "plt.scatter(no_movies_voted.index,no_movies_voted,color='mediumseagreen')\n",
        "plt.axhline(y=50,color='r')\n",
        "plt.xlabel('UserId')\n",
        "plt.ylabel('No. of votes by user')\n",
        "plt.show()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 467
        },
        "id": "Y3GMq_nxTosD",
        "outputId": "0396aee9-aa95-4043-a0c5-6f33cd22b313"
      },
      "source": [
        "final_dataset=final_dataset.loc[:,no_movies_voted[no_movies_voted > 50].index]\n",
        "final_dataset"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.5</td>\n",
              "      <td>3.5</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>...</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.5</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.5</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.5</td>\n",
              "      <td>...</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.5</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</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",
              "      <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",
              "      <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",
              "      <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",
              "      <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",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>174055</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.5</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
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              "      <td>4.0</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>176371</th>\n",
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              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.5</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.5</td>\n",
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              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>177765</th>\n",
              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>1.5</td>\n",
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              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
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              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>4.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>179819</th>\n",
              "      <td>0.0</td>\n",
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              "      <td>3.5</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>187593</th>\n",
              "      <td>0.0</td>\n",
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              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
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              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
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              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2121 rows × 378 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "userId   1    4    6    7    10   11   15   ...  603  604  605  606  607  608  610\n",
              "movieId                                     ...                                   \n",
              "1        4.0  0.0  0.0  4.5  0.0  0.0  2.5  ...  4.0  3.0  4.0  2.5  4.0  2.5  5.0\n",
              "2        0.0  0.0  4.0  0.0  0.0  0.0  0.0  ...  0.0  5.0  3.5  0.0  0.0  2.0  0.0\n",
              "3        4.0  0.0  5.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  2.0  0.0\n",
              "5        0.0  0.0  5.0  0.0  0.0  0.0  0.0  ...  0.0  3.0  0.0  0.0  0.0  0.0  0.0\n",
              "6        4.0  0.0  4.0  0.0  0.0  5.0  0.0  ...  4.0  3.0  0.0  0.0  0.0  0.0  5.0\n",
              "...      ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...\n",
              "174055   0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "176371   0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "177765   0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "179819   0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "187593   0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "\n",
              "[2121 rows x 378 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GRjU-4-ySCOh",
        "outputId": "917d943f-5aa5-429d-b6fe-799392b414fa"
      },
      "source": [
        "sample = np.array([[0,0,3,0,0],[4,0,0,0,2],[0,0,0,0,1]])\n",
        "sparsity = 1.0 - ( np.count_nonzero(sample) / float(sample.size) )\n",
        "print(sparsity)"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.7333333333333334\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_MHR4mNfSCQz",
        "outputId": "72ed65cf-5010-4e9a-b255-4b11d404ee8f"
      },
      "source": [
        "csr_sample = csr_matrix(sample)\n",
        "print(csr_sample)"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "  (0, 2)\t3\n",
            "  (1, 0)\t4\n",
            "  (1, 4)\t2\n",
            "  (2, 4)\t1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZSqqKhqDSCTe"
      },
      "source": [
        "csr_data = csr_matrix(final_dataset.values)\n",
        "final_dataset.reset_index(inplace=True)"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "M8CxpsYWUnEe",
        "outputId": "c7ae8c15-e682-4b34-85dd-c9e85e83714c"
      },
      "source": [
        "knn = NearestNeighbors(metric='cosine', algorithm='brute', n_neighbors=20, n_jobs=-1)\n",
        "knn.fit(csr_data)"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "NearestNeighbors(algorithm='brute', leaf_size=30, metric='cosine',\n",
              "                 metric_params=None, n_jobs=-1, n_neighbors=20, p=2,\n",
              "                 radius=1.0)"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rYmXj4OKUnK_"
      },
      "source": [
        "def get_movie_recommendation(movie_name):\n",
        "    n_movies_to_reccomend = 10\n",
        "    movie_list = movies[movies['title'].str.contains(movie_name)]  \n",
        "    if len(movie_list):        \n",
        "        movie_idx= movie_list.iloc[0]['movieId']\n",
        "        movie_idx = final_dataset[final_dataset['movieId'] == movie_idx].index[0]\n",
        "        distances , indices = knn.kneighbors(csr_data[movie_idx],n_neighbors=n_movies_to_reccomend+1)    \n",
        "        rec_movie_indices = sorted(list(zip(indices.squeeze().tolist(),distances.squeeze().tolist())),key=lambda x: x[1])[:0:-1]\n",
        "        recommend_frame = []\n",
        "        for val in rec_movie_indices:\n",
        "            movie_idx = final_dataset.iloc[val[0]]['movieId']\n",
        "            idx = movies[movies['movieId'] == movie_idx].index\n",
        "            recommend_frame.append({'Title':movies.iloc[idx]['title'].values[0],'Distance':val[1]})\n",
        "        df = pd.DataFrame(recommend_frame,index=range(1,n_movies_to_reccomend+1))\n",
        "        return df\n",
        "    else:\n",
        "        return \"No movies found. Please check your input\""
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "id": "rfykVnxAUnQ6",
        "outputId": "c5dd3f8d-e919-455e-c6cd-cb1baf7c8bf4"
      },
      "source": [
        "get_movie_recommendation('Iron Man')"
      ],
      "execution_count": 22,
      "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>Title</th>\n",
              "      <th>Distance</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Up (2009)</td>\n",
              "      <td>0.368857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Guardians of the Galaxy (2014)</td>\n",
              "      <td>0.368758</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Watchmen (2009)</td>\n",
              "      <td>0.368558</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Star Trek (2009)</td>\n",
              "      <td>0.366029</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Batman Begins (2005)</td>\n",
              "      <td>0.362759</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Avatar (2009)</td>\n",
              "      <td>0.310893</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Iron Man 2 (2010)</td>\n",
              "      <td>0.307492</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>WALL·E (2008)</td>\n",
              "      <td>0.298138</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Dark Knight, The (2008)</td>\n",
              "      <td>0.285835</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Avengers, The (2012)</td>\n",
              "      <td>0.285319</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                             Title  Distance\n",
              "1                        Up (2009)  0.368857\n",
              "2   Guardians of the Galaxy (2014)  0.368758\n",
              "3                  Watchmen (2009)  0.368558\n",
              "4                 Star Trek (2009)  0.366029\n",
              "5             Batman Begins (2005)  0.362759\n",
              "6                    Avatar (2009)  0.310893\n",
              "7                Iron Man 2 (2010)  0.307492\n",
              "8                    WALL·E (2008)  0.298138\n",
              "9          Dark Knight, The (2008)  0.285835\n",
              "10            Avengers, The (2012)  0.285319"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    }
  ]
}