Movie_Recommendation_System.ipynb

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      "name": "Movie Recommendation System.ipynb",
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        "## Movie Recommendation System based on item collaborative filtering\r\n",
        "\r\n",
        "1) Import the libraries\r\n",
        "\r\n",
        "2) Import the dataset\r\n",
        "\r\n",
        "3) Perform item based collaborative filtering on one of the movie samples\r\n",
        "\r\n",
        "4) Visualize the data\r\n",
        "\r\n",
        "5) Create an item based collaborative filtering model for the entire dataset\r\n",
        "\r\n"
      ]
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    {
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      "source": [
        "# Import the libraries\r\n",
        "\r\n",
        "import pandas as pd\r\n",
        "import numpy as np\r\n",
        "import matplotlib.pyplot as plt\r\n",
        "import seaborn as sns"
      ],
      "execution_count": 1,
      "outputs": []
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    {
      "cell_type": "code",
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      "source": [
        "# import the data\r\n",
        "\r\n",
        "df = pd.read_csv('Movie_Id_Titles')"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
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      "source": [
        "df"
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      "execution_count": 5,
      "outputs": [
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              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Toy Story (1995)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>GoldenEye (1995)</td>\n",
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              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Four Rooms (1995)</td>\n",
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              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Get Shorty (1995)</td>\n",
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              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Copycat (1995)</td>\n",
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              "      <th>1677</th>\n",
              "      <td>1678</td>\n",
              "      <td>Mat' i syn (1997)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1678</th>\n",
              "      <td>1679</td>\n",
              "      <td>B. Monkey (1998)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1679</th>\n",
              "      <td>1680</td>\n",
              "      <td>Sliding Doors (1998)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1680</th>\n",
              "      <td>1681</td>\n",
              "      <td>You So Crazy (1994)</td>\n",
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              "    <tr>\n",
              "      <th>1681</th>\n",
              "      <td>1682</td>\n",
              "      <td>Scream of Stone (Schrei aus Stein) (1991)</td>\n",
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              "      item_id                                      title\n",
              "0           1                           Toy Story (1995)\n",
              "1           2                           GoldenEye (1995)\n",
              "2           3                          Four Rooms (1995)\n",
              "3           4                          Get Shorty (1995)\n",
              "4           5                             Copycat (1995)\n",
              "...       ...                                        ...\n",
              "1677     1678                          Mat' i syn (1997)\n",
              "1678     1679                           B. Monkey (1998)\n",
              "1679     1680                       Sliding Doors (1998)\n",
              "1680     1681                        You So Crazy (1994)\n",
              "1681     1682  Scream of Stone (Schrei aus Stein) (1991)\n",
              "\n",
              "[1682 rows x 2 columns]"
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      "source": [
        "df2 = pd.read_csv('u.data', sep = '\\t', names = ['user_id','item_id','rating','timestamp'])"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
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              "<p>100003 rows × 4 columns</p>\n",
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              "        user_id  item_id  rating  timestamp\n",
              "0             0       50       5  881250949\n",
              "1             0      172       5  881250949\n",
              "2             0      133       1  881250949\n",
              "3           196      242       3  881250949\n",
              "4           186      302       3  891717742\n",
              "...         ...      ...     ...        ...\n",
              "99998       880      476       3  880175444\n",
              "99999       716      204       5  879795543\n",
              "100000      276     1090       1  874795795\n",
              "100001       13      225       2  882399156\n",
              "100002       12      203       3  879959583\n",
              "\n",
              "[100003 rows x 4 columns]"
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      "source": [
        "# Dropping the timestamp column\r\n",
        "\r\n",
        "df2.drop(['timestamp'], axis=1, inplace=True)"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RPBlqGZhuqvz"
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      "source": [
        "# Merging the two dataframes together\r\n",
        "\r\n",
        "movies = pd.merge(df2, df, on='item_id')"
      ],
      "execution_count": 13,
      "outputs": []
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      "source": [
        "movies"
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      "execution_count": 14,
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              "      <td>Eighth Day, The (1996)</td>\n",
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              "        user_id  ...                                              title\n",
              "0             0  ...                                   Star Wars (1977)\n",
              "1           290  ...                                   Star Wars (1977)\n",
              "2            79  ...                                   Star Wars (1977)\n",
              "3             2  ...                                   Star Wars (1977)\n",
              "4             8  ...                                   Star Wars (1977)\n",
              "...         ...  ...                                                ...\n",
              "99998       840  ...                                  Mamma Roma (1962)\n",
              "99999       655  ...                             Eighth Day, The (1996)\n",
              "100000      655  ...                                  Girls Town (1996)\n",
              "100001      655  ...  Silence of the Palace, The (Saimt el Qusur) (1...\n",
              "100002      655  ...                                    Dadetown (1995)\n",
              "\n",
              "[100003 rows x 4 columns]"
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          "execution_count": 14
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      "source": [
        "movies.groupby('title').describe()"
      ],
      "execution_count": 15,
      "outputs": [
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              "      <th>'Til There Was You (1997)</th>\n",
              "      <td>9.0</td>\n",
              "      <td>383.777778</td>\n",
              "      <td>204.272354</td>\n",
              "      <td>152.0</td>\n",
              "      <td>223.0</td>\n",
              "      <td>342.0</td>\n",
              "      <td>530.0</td>\n",
              "      <td>782.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>1300.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1300.0</td>\n",
              "      <td>1300.0</td>\n",
              "      <td>1300.0</td>\n",
              "      <td>1300.0</td>\n",
              "      <td>1300.0</td>\n",
              "      <td>9.0</td>\n",
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              "      <td>5.0</td>\n",
              "      <td>477.000000</td>\n",
              "      <td>244.344020</td>\n",
              "      <td>181.0</td>\n",
              "      <td>385.0</td>\n",
              "      <td>405.0</td>\n",
              "      <td>581.0</td>\n",
              "      <td>833.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1353.0</td>\n",
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              "      <td>1353.0</td>\n",
              "      <td>1353.0</td>\n",
              "      <td>1353.0</td>\n",
              "      <td>1353.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.600000</td>\n",
              "      <td>1.516575</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101 Dalmatians (1996)</th>\n",
              "      <td>109.0</td>\n",
              "      <td>450.330275</td>\n",
              "      <td>295.142779</td>\n",
              "      <td>1.0</td>\n",
              "      <td>183.0</td>\n",
              "      <td>435.0</td>\n",
              "      <td>699.0</td>\n",
              "      <td>938.0</td>\n",
              "      <td>109.0</td>\n",
              "      <td>225.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>225.0</td>\n",
              "      <td>225.0</td>\n",
              "      <td>225.0</td>\n",
              "      <td>225.0</td>\n",
              "      <td>225.0</td>\n",
              "      <td>109.0</td>\n",
              "      <td>2.908257</td>\n",
              "      <td>1.076184</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.00</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12 Angry Men (1957)</th>\n",
              "      <td>125.0</td>\n",
              "      <td>453.552000</td>\n",
              "      <td>255.588677</td>\n",
              "      <td>1.0</td>\n",
              "      <td>268.0</td>\n",
              "      <td>429.0</td>\n",
              "      <td>661.0</td>\n",
              "      <td>932.0</td>\n",
              "      <td>125.0</td>\n",
              "      <td>178.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>178.0</td>\n",
              "      <td>178.0</td>\n",
              "      <td>178.0</td>\n",
              "      <td>178.0</td>\n",
              "      <td>178.0</td>\n",
              "      <td>125.0</td>\n",
              "      <td>4.344000</td>\n",
              "      <td>0.719588</td>\n",
              "      <td>2.0</td>\n",
              "      <td>4.00</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>187 (1997)</th>\n",
              "      <td>41.0</td>\n",
              "      <td>517.097561</td>\n",
              "      <td>241.098300</td>\n",
              "      <td>3.0</td>\n",
              "      <td>416.0</td>\n",
              "      <td>532.0</td>\n",
              "      <td>698.0</td>\n",
              "      <td>894.0</td>\n",
              "      <td>41.0</td>\n",
              "      <td>330.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>330.0</td>\n",
              "      <td>330.0</td>\n",
              "      <td>330.0</td>\n",
              "      <td>330.0</td>\n",
              "      <td>330.0</td>\n",
              "      <td>41.0</td>\n",
              "      <td>3.024390</td>\n",
              "      <td>1.172344</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.00</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Young Guns II (1990)</th>\n",
              "      <td>44.0</td>\n",
              "      <td>504.068182</td>\n",
              "      <td>254.101371</td>\n",
              "      <td>87.0</td>\n",
              "      <td>301.0</td>\n",
              "      <td>459.0</td>\n",
              "      <td>732.5</td>\n",
              "      <td>943.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>1188.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1188.0</td>\n",
              "      <td>1188.0</td>\n",
              "      <td>1188.0</td>\n",
              "      <td>1188.0</td>\n",
              "      <td>1188.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>2.772727</td>\n",
              "      <td>1.008421</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.00</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Young Poisoner's Handbook, The (1995)</th>\n",
              "      <td>41.0</td>\n",
              "      <td>452.487805</td>\n",
              "      <td>286.352241</td>\n",
              "      <td>7.0</td>\n",
              "      <td>246.0</td>\n",
              "      <td>473.0</td>\n",
              "      <td>634.0</td>\n",
              "      <td>936.0</td>\n",
              "      <td>41.0</td>\n",
              "      <td>547.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>547.0</td>\n",
              "      <td>547.0</td>\n",
              "      <td>547.0</td>\n",
              "      <td>547.0</td>\n",
              "      <td>547.0</td>\n",
              "      <td>41.0</td>\n",
              "      <td>3.341463</td>\n",
              "      <td>1.237129</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.00</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Zeus and Roxanne (1997)</th>\n",
              "      <td>6.0</td>\n",
              "      <td>532.833333</td>\n",
              "      <td>343.690219</td>\n",
              "      <td>82.0</td>\n",
              "      <td>251.5</td>\n",
              "      <td>627.5</td>\n",
              "      <td>796.5</td>\n",
              "      <td>881.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>1164.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1164.0</td>\n",
              "      <td>1164.0</td>\n",
              "      <td>1164.0</td>\n",
              "      <td>1164.0</td>\n",
              "      <td>1164.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>2.166667</td>\n",
              "      <td>0.983192</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.25</td>\n",
              "      <td>2.5</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>unknown</th>\n",
              "      <td>9.0</td>\n",
              "      <td>311.888889</td>\n",
              "      <td>264.160200</td>\n",
              "      <td>1.0</td>\n",
              "      <td>130.0</td>\n",
              "      <td>297.0</td>\n",
              "      <td>422.0</td>\n",
              "      <td>833.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>267.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>267.0</td>\n",
              "      <td>267.0</td>\n",
              "      <td>267.0</td>\n",
              "      <td>267.0</td>\n",
              "      <td>267.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>3.444444</td>\n",
              "      <td>1.130388</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.00</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Á köldum klaka (Cold Fever) (1994)</th>\n",
              "      <td>1.0</td>\n",
              "      <td>655.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>655.0</td>\n",
              "      <td>655.0</td>\n",
              "      <td>655.0</td>\n",
              "      <td>655.0</td>\n",
              "      <td>655.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1633.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1633.0</td>\n",
              "      <td>1633.0</td>\n",
              "      <td>1633.0</td>\n",
              "      <td>1633.0</td>\n",
              "      <td>1633.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.00</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1664 rows × 24 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                      user_id              ... rating     \n",
              "                                        count        mean  ...    75%  max\n",
              "title                                                      ...            \n",
              "'Til There Was You (1997)                 9.0  383.777778  ...    3.0  4.0\n",
              "1-900 (1994)                              5.0  477.000000  ...    4.0  4.0\n",
              "101 Dalmatians (1996)                   109.0  450.330275  ...    4.0  5.0\n",
              "12 Angry Men (1957)                     125.0  453.552000  ...    5.0  5.0\n",
              "187 (1997)                               41.0  517.097561  ...    4.0  5.0\n",
              "...                                       ...         ...  ...    ...  ...\n",
              "Young Guns II (1990)                     44.0  504.068182  ...    3.0  5.0\n",
              "Young Poisoner's Handbook, The (1995)    41.0  452.487805  ...    4.0  5.0\n",
              "Zeus and Roxanne (1997)                   6.0  532.833333  ...    3.0  3.0\n",
              "unknown                                   9.0  311.888889  ...    4.0  5.0\n",
              "Á köldum klaka (Cold Fever) (1994)        1.0  655.000000  ...    3.0  3.0\n",
              "\n",
              "[1664 rows x 24 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 437
        },
        "id": "m1LiWgzq0lbf",
        "outputId": "7db55f41-9228-432b-b7c1-118d59150001"
      },
      "source": [
        "movies.groupby('title')['rating'].describe()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>count</th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>'Til There Was You (1997)</th>\n",
              "      <td>9.0</td>\n",
              "      <td>2.333333</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.00</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1-900 (1994)</th>\n",
              "      <td>5.0</td>\n",
              "      <td>2.600000</td>\n",
              "      <td>1.516575</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101 Dalmatians (1996)</th>\n",
              "      <td>109.0</td>\n",
              "      <td>2.908257</td>\n",
              "      <td>1.076184</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.00</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12 Angry Men (1957)</th>\n",
              "      <td>125.0</td>\n",
              "      <td>4.344000</td>\n",
              "      <td>0.719588</td>\n",
              "      <td>2.0</td>\n",
              "      <td>4.00</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>187 (1997)</th>\n",
              "      <td>41.0</td>\n",
              "      <td>3.024390</td>\n",
              "      <td>1.172344</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.00</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Young Guns II (1990)</th>\n",
              "      <td>44.0</td>\n",
              "      <td>2.772727</td>\n",
              "      <td>1.008421</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.00</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Young Poisoner's Handbook, The (1995)</th>\n",
              "      <td>41.0</td>\n",
              "      <td>3.341463</td>\n",
              "      <td>1.237129</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.00</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Zeus and Roxanne (1997)</th>\n",
              "      <td>6.0</td>\n",
              "      <td>2.166667</td>\n",
              "      <td>0.983192</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.25</td>\n",
              "      <td>2.5</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>unknown</th>\n",
              "      <td>9.0</td>\n",
              "      <td>3.444444</td>\n",
              "      <td>1.130388</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.00</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Á köldum klaka (Cold Fever) (1994)</th>\n",
              "      <td>1.0</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.00</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1664 rows × 8 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                       count      mean       std  ...  50%  75%  max\n",
              "title                                                             ...               \n",
              "'Til There Was You (1997)                9.0  2.333333  1.000000  ...  2.0  3.0  4.0\n",
              "1-900 (1994)                             5.0  2.600000  1.516575  ...  3.0  4.0  4.0\n",
              "101 Dalmatians (1996)                  109.0  2.908257  1.076184  ...  3.0  4.0  5.0\n",
              "12 Angry Men (1957)                    125.0  4.344000  0.719588  ...  4.0  5.0  5.0\n",
              "187 (1997)                              41.0  3.024390  1.172344  ...  3.0  4.0  5.0\n",
              "...                                      ...       ...       ...  ...  ...  ...  ...\n",
              "Young Guns II (1990)                    44.0  2.772727  1.008421  ...  3.0  3.0  5.0\n",
              "Young Poisoner's Handbook, The (1995)   41.0  3.341463  1.237129  ...  4.0  4.0  5.0\n",
              "Zeus and Roxanne (1997)                  6.0  2.166667  0.983192  ...  2.5  3.0  3.0\n",
              "unknown                                  9.0  3.444444  1.130388  ...  4.0  4.0  5.0\n",
              "Á köldum klaka (Cold Fever) (1994)       1.0  3.000000       NaN  ...  3.0  3.0  3.0\n",
              "\n",
              "[1664 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rLuSeWwq0wuK"
      },
      "source": [
        "rating_count = movies.groupby('title')['rating'].describe()['count']"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "njbc9j3T1VSv"
      },
      "source": [
        "rating_mean = movies.groupby('title')['rating'].describe()['mean']"
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PszkX9aN1hK8"
      },
      "source": [
        "rating_mean_count = pd.concat([rating_count, rating_mean], axis = 1)"
      ],
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        },
        "id": "KiI6f9Oo19TZ",
        "outputId": "81cbd860-7f58-471e-80c6-aaf41ee04c7e"
      },
      "source": [
        "rating_mean_count.reset_index()"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<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>count</th>\n",
              "      <th>mean</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>'Til There Was You (1997)</td>\n",
              "      <td>9.0</td>\n",
              "      <td>2.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1-900 (1994)</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>101 Dalmatians (1996)</td>\n",
              "      <td>109.0</td>\n",
              "      <td>2.908257</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>12 Angry Men (1957)</td>\n",
              "      <td>125.0</td>\n",
              "      <td>4.344000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>187 (1997)</td>\n",
              "      <td>41.0</td>\n",
              "      <td>3.024390</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1659</th>\n",
              "      <td>Young Guns II (1990)</td>\n",
              "      <td>44.0</td>\n",
              "      <td>2.772727</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1660</th>\n",
              "      <td>Young Poisoner's Handbook, The (1995)</td>\n",
              "      <td>41.0</td>\n",
              "      <td>3.341463</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1661</th>\n",
              "      <td>Zeus and Roxanne (1997)</td>\n",
              "      <td>6.0</td>\n",
              "      <td>2.166667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1662</th>\n",
              "      <td>unknown</td>\n",
              "      <td>9.0</td>\n",
              "      <td>3.444444</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1663</th>\n",
              "      <td>Á köldum klaka (Cold Fever) (1994)</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1664 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                      title  count      mean\n",
              "0                 'Til There Was You (1997)    9.0  2.333333\n",
              "1                              1-900 (1994)    5.0  2.600000\n",
              "2                     101 Dalmatians (1996)  109.0  2.908257\n",
              "3                       12 Angry Men (1957)  125.0  4.344000\n",
              "4                                187 (1997)   41.0  3.024390\n",
              "...                                     ...    ...       ...\n",
              "1659                   Young Guns II (1990)   44.0  2.772727\n",
              "1660  Young Poisoner's Handbook, The (1995)   41.0  3.341463\n",
              "1661                Zeus and Roxanne (1997)    6.0  2.166667\n",
              "1662                                unknown    9.0  3.444444\n",
              "1663     Á köldum klaka (Cold Fever) (1994)    1.0  3.000000\n",
              "\n",
              "[1664 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "P50-hbwh1_cP",
        "outputId": "ad5d9771-c5f6-4dcd-dde1-521e423e2c31"
      },
      "source": [
        "rating_mean_count['count'].plot(bins=100, kind='hist', color='r');"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "yXUbNuYi2bPv",
        "outputId": "a271f7c2-5e8d-4024-e096-9395d486ec2b"
      },
      "source": [
        "rating_mean_count['mean'].plot(bins=100, kind='hist', color='b');"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 437
        },
        "id": "8AWvcFxI2pS3",
        "outputId": "1b135457-a14e-456f-be5b-e59b02b61239"
      },
      "source": [
        "rating_mean_count.sort_values('count', ascending = False).head(100)"
      ],
      "execution_count": 32,
      "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>count</th>\n",
              "      <th>mean</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>title</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Star Wars (1977)</th>\n",
              "      <td>584.0</td>\n",
              "      <td>4.359589</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Contact (1997)</th>\n",
              "      <td>509.0</td>\n",
              "      <td>3.803536</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fargo (1996)</th>\n",
              "      <td>508.0</td>\n",
              "      <td>4.155512</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Return of the Jedi (1983)</th>\n",
              "      <td>507.0</td>\n",
              "      <td>4.007890</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Liar Liar (1997)</th>\n",
              "      <td>485.0</td>\n",
              "      <td>3.156701</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Aladdin (1992)</th>\n",
              "      <td>219.0</td>\n",
              "      <td>3.812785</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Babe (1995)</th>\n",
              "      <td>219.0</td>\n",
              "      <td>3.995434</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Volcano (1997)</th>\n",
              "      <td>219.0</td>\n",
              "      <td>2.808219</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>To Kill a Mockingbird (1962)</th>\n",
              "      <td>219.0</td>\n",
              "      <td>4.292237</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Murder at 1600 (1997)</th>\n",
              "      <td>218.0</td>\n",
              "      <td>3.087156</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>100 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                              count      mean\n",
              "title                                        \n",
              "Star Wars (1977)              584.0  4.359589\n",
              "Contact (1997)                509.0  3.803536\n",
              "Fargo (1996)                  508.0  4.155512\n",
              "Return of the Jedi (1983)     507.0  4.007890\n",
              "Liar Liar (1997)              485.0  3.156701\n",
              "...                             ...       ...\n",
              "Aladdin (1992)                219.0  3.812785\n",
              "Babe (1995)                   219.0  3.995434\n",
              "Volcano (1997)                219.0  2.808219\n",
              "To Kill a Mockingbird (1962)  219.0  4.292237\n",
              "Murder at 1600 (1997)         218.0  3.087156\n",
              "\n",
              "[100 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OIP-XReS26me"
      },
      "source": [
        "userid_matrix = movies.pivot_table(index='user_id', columns='title',values='rating')"
      ],
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 559
        },
        "id": "XOk_jPu_47y8",
        "outputId": "bc17cefb-7001-4158-bbe5-ae282da04fce"
      },
      "source": [
        "userid_matrix"
      ],
      "execution_count": 35,
      "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>title</th>\n",
              "      <th>'Til There Was You (1997)</th>\n",
              "      <th>1-900 (1994)</th>\n",
              "      <th>101 Dalmatians (1996)</th>\n",
              "      <th>12 Angry Men (1957)</th>\n",
              "      <th>187 (1997)</th>\n",
              "      <th>2 Days in the Valley (1996)</th>\n",
              "      <th>20,000 Leagues Under the Sea (1954)</th>\n",
              "      <th>2001: A Space Odyssey (1968)</th>\n",
              "      <th>3 Ninjas: High Noon At Mega Mountain (1998)</th>\n",
              "      <th>39 Steps, The (1935)</th>\n",
              "      <th>8 1/2 (1963)</th>\n",
              "      <th>8 Heads in a Duffel Bag (1997)</th>\n",
              "      <th>8 Seconds (1994)</th>\n",
              "      <th>A Chef in Love (1996)</th>\n",
              "      <th>Above the Rim (1994)</th>\n",
              "      <th>Absolute Power (1997)</th>\n",
              "      <th>Abyss, The (1989)</th>\n",
              "      <th>Ace Ventura: Pet Detective (1994)</th>\n",
              "      <th>Ace Ventura: When Nature Calls (1995)</th>\n",
              "      <th>Across the Sea of Time (1995)</th>\n",
              "      <th>Addams Family Values (1993)</th>\n",
              "      <th>Addicted to Love (1997)</th>\n",
              "      <th>Addiction, The (1995)</th>\n",
              "      <th>Adventures of Pinocchio, The (1996)</th>\n",
              "      <th>Adventures of Priscilla, Queen of the Desert, The (1994)</th>\n",
              "      <th>Adventures of Robin Hood, The (1938)</th>\n",
              "      <th>Affair to Remember, An (1957)</th>\n",
              "      <th>African Queen, The (1951)</th>\n",
              "      <th>Afterglow (1997)</th>\n",
              "      <th>Age of Innocence, The (1993)</th>\n",
              "      <th>Aiqing wansui (1994)</th>\n",
              "      <th>Air Bud (1997)</th>\n",
              "      <th>Air Force One (1997)</th>\n",
              "      <th>Air Up There, The (1994)</th>\n",
              "      <th>Airheads (1994)</th>\n",
              "      <th>Akira (1988)</th>\n",
              "      <th>Aladdin (1992)</th>\n",
              "      <th>Aladdin and the King of Thieves (1996)</th>\n",
              "      <th>Alaska (1996)</th>\n",
              "      <th>Albino Alligator (1996)</th>\n",
              "      <th>...</th>\n",
              "      <th>Whole Wide World, The (1996)</th>\n",
              "      <th>Widows' Peak (1994)</th>\n",
              "      <th>Wife, The (1995)</th>\n",
              "      <th>Wild America (1997)</th>\n",
              "      <th>Wild Bill (1995)</th>\n",
              "      <th>Wild Bunch, The (1969)</th>\n",
              "      <th>Wild Reeds (1994)</th>\n",
              "      <th>Wild Things (1998)</th>\n",
              "      <th>William Shakespeare's Romeo and Juliet (1996)</th>\n",
              "      <th>Willy Wonka and the Chocolate Factory (1971)</th>\n",
              "      <th>Window to Paris (1994)</th>\n",
              "      <th>Wings of Courage (1995)</th>\n",
              "      <th>Wings of Desire (1987)</th>\n",
              "      <th>Wings of the Dove, The (1997)</th>\n",
              "      <th>Winnie the Pooh and the Blustery Day (1968)</th>\n",
              "      <th>Winter Guest, The (1997)</th>\n",
              "      <th>Wishmaster (1997)</th>\n",
              "      <th>With Honors (1994)</th>\n",
              "      <th>Withnail and I (1987)</th>\n",
              "      <th>Witness (1985)</th>\n",
              "      <th>Wizard of Oz, The (1939)</th>\n",
              "      <th>Wolf (1994)</th>\n",
              "      <th>Woman in Question, The (1950)</th>\n",
              "      <th>Women, The (1939)</th>\n",
              "      <th>Wonderful, Horrible Life of Leni Riefenstahl, The (1993)</th>\n",
              "      <th>Wonderland (1997)</th>\n",
              "      <th>Wooden Man's Bride, The (Wu Kui) (1994)</th>\n",
              "      <th>World of Apu, The (Apur Sansar) (1959)</th>\n",
              "      <th>Wrong Trousers, The (1993)</th>\n",
              "      <th>Wyatt Earp (1994)</th>\n",
              "      <th>Yankee Zulu (1994)</th>\n",
              "      <th>Year of the Horse (1997)</th>\n",
              "      <th>You So Crazy (1994)</th>\n",
              "      <th>Young Frankenstein (1974)</th>\n",
              "      <th>Young Guns (1988)</th>\n",
              "      <th>Young Guns II (1990)</th>\n",
              "      <th>Young Poisoner's Handbook, The (1995)</th>\n",
              "      <th>Zeus and Roxanne (1997)</th>\n",
              "      <th>unknown</th>\n",
              "      <th>Á köldum klaka (Cold Fever) (1994)</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>user_id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <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",
              "      <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",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\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>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>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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</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>3.0</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>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</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>4.0</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>4.0</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>5.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5.0</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\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>1.0</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>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>4.0</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>...</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>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>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\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>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>...</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>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",
              "    </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>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>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>...</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>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",
              "    </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",
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              "      <td>3.0</td>\n",
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              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>944 rows × 1664 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "title    'Til There Was You (1997)  ...  Á köldum klaka (Cold Fever) (1994)\n",
              "user_id                             ...                                    \n",
              "0                              NaN  ...                                 NaN\n",
              "1                              NaN  ...                                 NaN\n",
              "2                              NaN  ...                                 NaN\n",
              "3                              NaN  ...                                 NaN\n",
              "4                              NaN  ...                                 NaN\n",
              "...                            ...  ...                                 ...\n",
              "939                            NaN  ...                                 NaN\n",
              "940                            NaN  ...                                 NaN\n",
              "941                            NaN  ...                                 NaN\n",
              "942                            NaN  ...                                 NaN\n",
              "943                            NaN  ...                                 NaN\n",
              "\n",
              "[944 rows x 1664 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Vvt7OSN-4-ei"
      },
      "source": [
        "titanic = userid_matrix['Titanic (1997)']"
      ],
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "70tQ3s207d4o",
        "outputId": "acb7ccb0-ac1d-408e-8319-0c01406e6917"
      },
      "source": [
        "titanic"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "user_id\n",
              "0      NaN\n",
              "1      NaN\n",
              "2      5.0\n",
              "3      NaN\n",
              "4      NaN\n",
              "      ... \n",
              "939    NaN\n",
              "940    5.0\n",
              "941    NaN\n",
              "942    3.0\n",
              "943    NaN\n",
              "Name: Titanic (1997), Length: 944, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Qomvl27X7e7I",
        "outputId": "96374d80-7a1a-4c16-b01e-6ac75b2bf796"
      },
      "source": [
        "titanic_correlations = pd.DataFrame(userid_matrix.corrwith(titanic), columns=['correlations'])"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/numpy/lib/function_base.py:2551: 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:2480: RuntimeWarning: divide by zero encountered in true_divide\n",
            "  c *= np.true_divide(1, fact)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "351HqZmW8Vso"
      },
      "source": [
        "titanic_correlations = titanic_correlations.join(rating_mean_count['count'])"
      ],
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xyg4khMp8jdF"
      },
      "source": [
        "titanic_correlations.dropna(inplace=True)"
      ],
      "execution_count": 52,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 437
        },
        "id": "n5Y4UmMF9oyx",
        "outputId": "0ada5833-47d5-43e2-d316-f40de9f7d087"
      },
      "source": [
        "titanic_correlations"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<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>correlations</th>\n",
              "      <th>count</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>title</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>'Til There Was You (1997)</th>\n",
              "      <td>-0.062017</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101 Dalmatians (1996)</th>\n",
              "      <td>0.120113</td>\n",
              "      <td>109.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12 Angry Men (1957)</th>\n",
              "      <td>0.077700</td>\n",
              "      <td>125.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>187 (1997)</th>\n",
              "      <td>0.315654</td>\n",
              "      <td>41.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2 Days in the Valley (1996)</th>\n",
              "      <td>0.017295</td>\n",
              "      <td>93.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Year of the Horse (1997)</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Young Frankenstein (1974)</th>\n",
              "      <td>0.107666</td>\n",
              "      <td>200.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Young Guns (1988)</th>\n",
              "      <td>0.199931</td>\n",
              "      <td>101.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Young Guns II (1990)</th>\n",
              "      <td>0.317274</td>\n",
              "      <td>44.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Young Poisoner's Handbook, The (1995)</th>\n",
              "      <td>0.356783</td>\n",
              "      <td>41.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1356 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                       correlations  count\n",
              "title                                                     \n",
              "'Til There Was You (1997)                 -0.062017    9.0\n",
              "101 Dalmatians (1996)                      0.120113  109.0\n",
              "12 Angry Men (1957)                        0.077700  125.0\n",
              "187 (1997)                                 0.315654   41.0\n",
              "2 Days in the Valley (1996)                0.017295   93.0\n",
              "...                                             ...    ...\n",
              "Year of the Horse (1997)                   1.000000    7.0\n",
              "Young Frankenstein (1974)                  0.107666  200.0\n",
              "Young Guns (1988)                          0.199931  101.0\n",
              "Young Guns II (1990)                       0.317274   44.0\n",
              "Young Poisoner's Handbook, The (1995)      0.356783   41.0\n",
              "\n",
              "[1356 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 437
        },
        "id": "WkFgFgD79FbN",
        "outputId": "d335412e-9df5-47e9-d858-fbfff6ea5c93"
      },
      "source": [
        "titanic_correlations.sort_values('correlations',ascending=False)"
      ],
      "execution_count": 54,
      "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>correlations</th>\n",
              "      <th>count</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>title</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Nadja (1994)</th>\n",
              "      <td>1.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Pest, The (1997)</th>\n",
              "      <td>1.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Savage Nights (Nuits fauves, Les) (1992)</th>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>For Ever Mozart (1996)</th>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Jerky Boys, The (1994)</th>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Pather Panchali (1955)</th>\n",
              "      <td>-1.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Angel Baby (1995)</th>\n",
              "      <td>-1.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Blood Beach (1981)</th>\n",
              "      <td>-1.0</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Two Bits (1995)</th>\n",
              "      <td>-1.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Faces (1968)</th>\n",
              "      <td>-1.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1356 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                          correlations  count\n",
              "title                                                        \n",
              "Nadja (1994)                                       1.0    8.0\n",
              "Pest, The (1997)                                   1.0    8.0\n",
              "Savage Nights (Nuits fauves, Les) (1992)           1.0    3.0\n",
              "For Ever Mozart (1996)                             1.0    3.0\n",
              "Jerky Boys, The (1994)                             1.0    3.0\n",
              "...                                                ...    ...\n",
              "Pather Panchali (1955)                            -1.0    8.0\n",
              "Angel Baby (1995)                                 -1.0    4.0\n",
              "Blood Beach (1981)                                -1.0    6.0\n",
              "Two Bits (1995)                                   -1.0    5.0\n",
              "Faces (1968)                                      -1.0    4.0\n",
              "\n",
              "[1356 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 437
        },
        "id": "_xw8kM_N9acZ",
        "outputId": "76708d70-87e3-428a-df41-c8f333cda8d9"
      },
      "source": [
        "titanic_correlations[titanic_correlations['count']>80].sort_values('correlations', ascending=False).head(100)"
      ],
      "execution_count": 55,
      "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",
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              "\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>correlations</th>\n",
              "      <th>count</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>title</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Titanic (1997)</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>350.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>River Wild, The (1994)</th>\n",
              "      <td>0.497600</td>\n",
              "      <td>146.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Abyss, The (1989)</th>\n",
              "      <td>0.472103</td>\n",
              "      <td>151.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bram Stoker's Dracula (1992)</th>\n",
              "      <td>0.443560</td>\n",
              "      <td>120.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>True Lies (1994)</th>\n",
              "      <td>0.435104</td>\n",
              "      <td>208.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Beautiful Girls (1996)</th>\n",
              "      <td>0.264775</td>\n",
              "      <td>115.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Picture Perfect (1997)</th>\n",
              "      <td>0.264406</td>\n",
              "      <td>81.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Seven Years in Tibet (1997)</th>\n",
              "      <td>0.262371</td>\n",
              "      <td>155.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Mulholland Falls (1996)</th>\n",
              "      <td>0.262075</td>\n",
              "      <td>82.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Omen, The (1976)</th>\n",
              "      <td>0.261770</td>\n",
              "      <td>85.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>100 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                              correlations  count\n",
              "title                                            \n",
              "Titanic (1997)                    1.000000  350.0\n",
              "River Wild, The (1994)            0.497600  146.0\n",
              "Abyss, The (1989)                 0.472103  151.0\n",
              "Bram Stoker's Dracula (1992)      0.443560  120.0\n",
              "True Lies (1994)                  0.435104  208.0\n",
              "...                                    ...    ...\n",
              "Beautiful Girls (1996)            0.264775  115.0\n",
              "Picture Perfect (1997)            0.264406   81.0\n",
              "Seven Years in Tibet (1997)       0.262371  155.0\n",
              "Mulholland Falls (1996)           0.262075   82.0\n",
              "Omen, The (1976)                  0.261770   85.0\n",
              "\n",
              "[100 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uc2hIrRj-JZP"
      },
      "source": [
        "# Let's create our own dataframe with our own ratings!\r\n",
        "myRatings = pd.read_csv(\"My_Ratings.csv\")\r\n"
      ],
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AbBZh-h9MBUh"
      },
      "source": [
        "movie_correlations = userid_matrix.corr(method = 'pearson', min_periods = 80)\r\n",
        "# pearson : standard correlation coefficient\r\n",
        "# Obtain the correlations between all movies in the dataframe"
      ],
      "execution_count": 61,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 108
        },
        "id": "Aw0gpBTTLisK",
        "outputId": "9b9ef43e-f34f-4900-dc20-e08a66725459"
      },
      "source": [
        "myRatings"
      ],
      "execution_count": 58,
      "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>Movie Name</th>\n",
              "      <th>Ratings</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Liar Liar (1997)</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Star Wars (1977)</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Movie Name  Ratings\n",
              "0  Liar Liar (1997)        5\n",
              "1  Star Wars (1977)        1"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YodYeCfuLmd2",
        "outputId": "c130827c-dd38-4651-9d16-db8b4add5bac"
      },
      "source": [
        "similar_movies_list = pd.Series()\r\n",
        "for i in range(0, 2):\r\n",
        "    similar_movie = movie_correlations[myRatings['Movie Name'][i]].dropna() # Get same movies with same ratings\r\n",
        "    similar_movie = similar_movie.map(lambda x: x * myRatings['Ratings'][i]) # Scale the similarity by your given ratings\r\n",
        "    similar_movies_list = similar_movies_list.append(similar_movie)"
      ],
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:1: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SvBtSTuuL512",
        "outputId": "be5ca6a0-f703-4434-f761-79df161dbc10"
      },
      "source": [
        "similar_movies_list.sort_values(inplace = True, ascending = False)\r\n",
        "print (similar_movies_list.head(10))"
      ],
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Liar Liar (1997)                             5.000000\n",
            "Con Air (1997)                               2.349141\n",
            "Pretty Woman (1990)                          2.348951\n",
            "Michael (1996)                               2.210110\n",
            "Indiana Jones and the Last Crusade (1989)    2.072136\n",
            "Top Gun (1986)                               2.028602\n",
            "G.I. Jane (1997)                             1.989656\n",
            "Multiplicity (1996)                          1.984302\n",
            "Grumpier Old Men (1995)                      1.953494\n",
            "Ghost and the Darkness, The (1996)           1.895376\n",
            "dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p3pN_bsJMJ_G"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}