Sistema_de_recomendação_básico.ipynb

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    "colab": {
      "name": "Sistema de recomendação básico",
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    },
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      "name": "python3",
      "display_name": "Python 3"
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      "name": "python"
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  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "BOlyeO1W7Fbb"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "pQL06rBs7QAG",
        "outputId": "8a3759df-bbca-4a28-8e39-8870e09891ed"
      },
      "source": [
        "column_names = ['user_id', 'item_id', 'rating', 'timestamp']\n",
        "df = pd.read_csv('u.data', sep='\\t', names=column_names)\n",
        "filmes = pd.read_csv('Movie_Id_Titles')\n",
        "filmes.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>item_id</th>\n",
              "      <th>title</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Four Rooms (1995)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Get Shorty (1995)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Copycat (1995)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   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)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 118
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CA65y0YTBdAu"
      },
      "source": [
        "Unindo os dados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oLqM_kBEBVKF"
      },
      "source": [
        "df =df.merge(filmes, on='item_id')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "twlP9VN4CABj"
      },
      "source": [
        "Vamos criar um dataframes de ratings com classificação média e número de avaliações:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8eOsGY_gB-ai",
        "outputId": "69c6a3a0-3a45-4777-c083-489df34bc95d"
      },
      "source": [
        "ratings = df.groupby('title')['rating'].mean()\n",
        "ratings.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "title\n",
              "'Til There Was You (1997)    2.333333\n",
              "1-900 (1994)                 2.600000\n",
              "101 Dalmatians (1996)        2.908257\n",
              "12 Angry Men (1957)          4.344000\n",
              "187 (1997)                   3.024390\n",
              "Name: rating, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 89
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
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          "base_uri": "https://localhost:8080/"
        },
        "id": "lb8a8q20Cuzz",
        "outputId": "eaa7efb5-2b23-413a-e4d3-54944240e8b6"
      },
      "source": [
        "ratings['numero_de_avaliacoes'] = df.groupby('title')['rating'].count()\n",
        "ratings.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "title\n",
              "'Til There Was You (1997)    2.33333\n",
              "1-900 (1994)                     2.6\n",
              "101 Dalmatians (1996)        2.90826\n",
              "12 Angry Men (1957)            4.344\n",
              "187 (1997)                   3.02439\n",
              "Name: rating, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fvcpyER-DqGv"
      },
      "source": [
        "Recomendando filmes"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        },
        "id": "jtcgx63wDmA8",
        "outputId": "649cfaa2-0d55-4a95-d43f-ac05a05dda81"
      },
      "source": [
        "recom = pd.pivot_table(data=df,index='user_id', columns='title', values='rating')\n",
        "recom.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>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",
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              "      <td>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",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 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",
              "[5 rows x 1664 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 91
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oPWMWsMGEcOL",
        "outputId": "ff8d1407-05d1-4bcb-c33a-a2a9b19c3d83"
      },
      "source": [
        "toy_story = recom['Toy Story (1995)']\n",
        "toy_story"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "user_id\n",
              "0      NaN\n",
              "1      5.0\n",
              "2      4.0\n",
              "3      NaN\n",
              "4      NaN\n",
              "      ... \n",
              "939    NaN\n",
              "940    NaN\n",
              "941    5.0\n",
              "942    NaN\n",
              "943    NaN\n",
              "Name: Toy Story (1995), Length: 944, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 92
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iUhNDOGhFUSq",
        "outputId": "a6ad1bbb-b31e-417f-d0b2-6abb16949d30"
      },
      "source": [
        "similar = recom.corrwith(toy_story)\n",
        "similar.sort_values(ascending=False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/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/python3.7/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"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "title\n",
              "Ladybird Ladybird (1994)                                                             1.0\n",
              "Albino Alligator (1996)                                                              1.0\n",
              "Old Lady Who Walked in the Sea, The (Vieille qui marchait dans la mer, La) (1991)    1.0\n",
              "Critical Care (1997)                                                                 1.0\n",
              "Late Bloomers (1996)                                                                 1.0\n",
              "                                                                                    ... \n",
              "Woman in Question, The (1950)                                                        NaN\n",
              "Wonderland (1997)                                                                    NaN\n",
              "Yankee Zulu (1994)                                                                   NaN\n",
              "You So Crazy (1994)                                                                  NaN\n",
              "Á köldum klaka (Cold Fever) (1994)                                                   NaN\n",
              "Length: 1664, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 93
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "id": "MKkvcH3uGFSc",
        "outputId": "37b7ed3e-6724-40fd-c3cc-8d1e1b4c3186"
      },
      "source": [
        "recomendados = pd.DataFrame(similar, columns=['correlation'])\n",
        "recomendados.dropna(inplace=True)\n",
        "recomendados.sort_values('correlation', ascending=False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
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              "        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>correlation</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>title</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Old Lady Who Walked in the Sea, The (Vieille qui marchait dans la mer, La) (1991)</th>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Reckless (1995)</th>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Ladybird Ladybird (1994)</th>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Infinity (1996)</th>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Albino Alligator (1996)</th>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Slingshot, The (1993)</th>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Heavy (1995)</th>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Feast of July (1995)</th>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Stalker (1979)</th>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Love and Death on Long Island (1997)</th>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1370 rows × 1 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                    correlation\n",
              "title                                                          \n",
              "Old Lady Who Walked in the Sea, The (Vieille qu...          1.0\n",
              "Reckless (1995)                                             1.0\n",
              "Ladybird Ladybird (1994)                                    1.0\n",
              "Infinity (1996)                                             1.0\n",
              "Albino Alligator (1996)                                     1.0\n",
              "...                                                         ...\n",
              "Slingshot, The (1993)                                      -1.0\n",
              "Heavy (1995)                                               -1.0\n",
              "Feast of July (1995)                                       -1.0\n",
              "Stalker (1979)                                             -1.0\n",
              "Love and Death on Long Island (1997)                       -1.0\n",
              "\n",
              "[1370 rows x 1 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 94
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UkYuaIwEG8QJ"
      },
      "source": [
        "recomendados = recomendados.join(ratings['numero_de_avaliacoes'])\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "id": "IuD24FW9HVwV",
        "outputId": "96cb79db-fede-4651-e99b-0d7e69be402c"
      },
      "source": [
        "recomendados.sort_values('rating', ascending=False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>correlation</th>\n",
              "      <th>rating</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>0.180020</td>\n",
              "      <td>584</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Contact (1997)</th>\n",
              "      <td>0.155088</td>\n",
              "      <td>509</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fargo (1996)</th>\n",
              "      <td>0.105460</td>\n",
              "      <td>508</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Return of the Jedi (1983)</th>\n",
              "      <td>0.187092</td>\n",
              "      <td>507</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Liar Liar (1997)</th>\n",
              "      <td>0.342576</td>\n",
              "      <td>485</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Line King: Al Hirschfeld, The (1996)</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Golden Earrings (1947)</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Good Man in Africa, A (1994)</th>\n",
              "      <td>-1.000000</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Johnny 100 Pesos (1993)</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Slingshot, The (1993)</th>\n",
              "      <td>-1.000000</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1370 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                      correlation  rating\n",
              "title                                                    \n",
              "Star Wars (1977)                         0.180020     584\n",
              "Contact (1997)                           0.155088     509\n",
              "Fargo (1996)                             0.105460     508\n",
              "Return of the Jedi (1983)                0.187092     507\n",
              "Liar Liar (1997)                         0.342576     485\n",
              "...                                           ...     ...\n",
              "Line King: Al Hirschfeld, The (1996)     1.000000       2\n",
              "Golden Earrings (1947)                   1.000000       2\n",
              "Good Man in Africa, A (1994)            -1.000000       2\n",
              "Johnny 100 Pesos (1993)                  1.000000       2\n",
              "Slingshot, The (1993)                   -1.000000       2\n",
              "\n",
              "[1370 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 96
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "id": "FY-Wi4j0HZja",
        "outputId": "cf6763b0-aeaf-4d3b-bb66-75f20f057768"
      },
      "source": [
        "recomendados[recomendados['rating']>100].sort_values('correlation', ascending=False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "      <th>rating</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>Toy Story (1995)</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>452</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Craft, The (1996)</th>\n",
              "      <td>0.549100</td>\n",
              "      <td>104</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Down Periscope (1996)</th>\n",
              "      <td>0.457995</td>\n",
              "      <td>101</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Miracle on 34th Street (1994)</th>\n",
              "      <td>0.456291</td>\n",
              "      <td>101</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G.I. Jane (1997)</th>\n",
              "      <td>0.454756</td>\n",
              "      <td>175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Raging Bull (1980)</th>\n",
              "      <td>-0.083523</td>\n",
              "      <td>116</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Boogie Nights (1997)</th>\n",
              "      <td>-0.086194</td>\n",
              "      <td>189</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Clockwork Orange, A (1971)</th>\n",
              "      <td>-0.087710</td>\n",
              "      <td>221</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Apt Pupil (1998)</th>\n",
              "      <td>-0.104066</td>\n",
              "      <td>160</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Harold and Maude (1971)</th>\n",
              "      <td>-0.181697</td>\n",
              "      <td>121</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>334 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                               correlation  rating\n",
              "title                                             \n",
              "Toy Story (1995)                  1.000000     452\n",
              "Craft, The (1996)                 0.549100     104\n",
              "Down Periscope (1996)             0.457995     101\n",
              "Miracle on 34th Street (1994)     0.456291     101\n",
              "G.I. Jane (1997)                  0.454756     175\n",
              "...                                    ...     ...\n",
              "Raging Bull (1980)               -0.083523     116\n",
              "Boogie Nights (1997)             -0.086194     189\n",
              "Clockwork Orange, A (1971)       -0.087710     221\n",
              "Apt Pupil (1998)                 -0.104066     160\n",
              "Harold and Maude (1971)          -0.181697     121\n",
              "\n",
              "[334 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 97
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8pOPB4TEIBui"
      },
      "source": [
        "def recomendar(nome):\n",
        "  filme = recom[nome]\n",
        "  similar = recom.corrwith(filme)\n",
        "  similar.sort_values(ascending=False)\n",
        "  recomendados = pd.DataFrame(similar, columns=['correlation'])\n",
        "  recomendados.dropna(inplace=True)\n",
        "  recomendados.sort_values('correlation', ascending=False)\n",
        "  recomendados = recomendados.join(ratings['numero_de_avaliacoes'])\n",
        "  recomendados.sort_values('rating', ascending=False)\n",
        "  recomendados = recomendados[recomendados['rating']>100].sort_values('correlation', ascending=False).head()[1:]\n",
        "  return recomendados"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292
        },
        "id": "vOOdM0G5I4de",
        "outputId": "1a358951-9a8f-4f57-93bf-8e72d6c4f9b8"
      },
      "source": [
        "recomendar('Miracle on 34th Street (1994)')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/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/python3.7/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"
        },
        {
          "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>correlation</th>\n",
              "      <th>rating</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>Alien: Resurrection (1997)</th>\n",
              "      <td>0.790207</td>\n",
              "      <td>124</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Rosewood (1997)</th>\n",
              "      <td>0.732306</td>\n",
              "      <td>114</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Mimic (1997)</th>\n",
              "      <td>0.670820</td>\n",
              "      <td>101</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>It's a Wonderful Life (1946)</th>\n",
              "      <td>0.616887</td>\n",
              "      <td>231</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                              correlation  rating\n",
              "title                                            \n",
              "Alien: Resurrection (1997)       0.790207     124\n",
              "Rosewood (1997)                  0.732306     114\n",
              "Mimic (1997)                     0.670820     101\n",
              "It's a Wonderful Life (1946)     0.616887     231"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 113
        }
      ]
    }
  ]
}