MarvelRecomverse_Sistema_de_Recomendación.ipynb

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    "colab": {
      "name": "MarvelRecomverse: Sistema de Recomendación.ipynb",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/josemanuelvinhas/MarvelRecomverse/blob/main/MarvelRecomverse_Sistema_de_Recomendaci%C3%B3n.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Qs-U-sth7aGM"
      },
      "source": [
        "#**0. Sistema de Recomendación**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NPVG3f518s5p"
      },
      "source": [
        "En este Notebook se realiza la implementación del sistema de recomendación de la aplicación.\n",
        "\n",
        "En el primer punto se calcula la matriz de parecidos entre todos los personajes del dataset. Se realiza a modo de prueba, ya que no es necesario para la aplicación.\n",
        "\n",
        "En el segundo punto se buscan los personajes más similares a una persona en función de dos criterios distintos:\n",
        "1. Descripción\n",
        "2. Descripción + Valoración Comentarios + Valoración Directa (Likes) + Valoración Media Comentarios\n",
        "\n",
        "El uso de distintos criterios se realiza únicamente para comprobar como afectan al resultado final. Se decide emplear el segundo criterio porque también se tienen en cuenta las opiniones directas de los usuarios.\n",
        "\n",
        "*NOTA: el dataset que se empleará está disponible [aquí](https://github.com/josemanuelvinhas/MarvelRecomverse/tree/main/datasets)*\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "54P_biry_Hja"
      },
      "source": [
        "#**1. Cálculo de la matriz de parecidos**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "f9NGK9x2W0Q1"
      },
      "source": [
        "##**1.1 Preprocesado del dataset**\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uGvIkJ9EYr6m"
      },
      "source": [
        "Para poder trabajar con los datos se deberá realizar un preprocesado de las descripciones.\n",
        "\n",
        "El dataset con el que se trabaja contiene una colección de 281 personajes. Cada uno tiene dos campos:\n",
        "\n",
        "1.   *name*: nombre del personaje\n",
        "2.   *description*: descripcion del personaje\n",
        "\n",
        "Se hará uso de la librería *pandas* para el preprocesado. A continuación se carga el csv con los datos\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zEu5A0usY2u1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "6f46d3ef-5db6-4cc8-c636-1e3ba6ce24d0"
      },
      "source": [
        "import pandas as pd\n",
        "\n",
        "originalData = pd.read_csv('marvel.csv')\n",
        "originalData"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>description</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A-Bomb (HAS)</td>\n",
              "      <td>Rick Jones has been Hulk's best bud since day ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A.I.M.</td>\n",
              "      <td>AIM is a terrorist organization bent on destro...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Abomination (Emil Blonsky)</td>\n",
              "      <td>Formerly known as Emil Blonsky, a spy of Sovie...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Adam Warlock</td>\n",
              "      <td>Adam Warlock is an artificially created human ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Agent X (Nijo)</td>\n",
              "      <td>Originally a partner of the mind-altering assa...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>276</th>\n",
              "      <td>Zarek</td>\n",
              "      <td>Zarek is a member of the Kree race with no sup...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>277</th>\n",
              "      <td>Zodiak</td>\n",
              "      <td>Twelve demons merged with Norman Harrison, who...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>278</th>\n",
              "      <td>Zombie (Simon Garth)</td>\n",
              "      <td>War hero Simon Garth was turned into a zombie ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>279</th>\n",
              "      <td>Zuras</td>\n",
              "      <td>Zuras was once the leader of the Eternals.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>280</th>\n",
              "      <td>Zzzax</td>\n",
              "      <td>A chain reaction in an atomic reactor, a resul...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>281 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                           name                                        description\n",
              "0                  A-Bomb (HAS)  Rick Jones has been Hulk's best bud since day ...\n",
              "1                        A.I.M.  AIM is a terrorist organization bent on destro...\n",
              "2    Abomination (Emil Blonsky)  Formerly known as Emil Blonsky, a spy of Sovie...\n",
              "3                  Adam Warlock  Adam Warlock is an artificially created human ...\n",
              "4                Agent X (Nijo)  Originally a partner of the mind-altering assa...\n",
              "..                          ...                                                ...\n",
              "276                       Zarek  Zarek is a member of the Kree race with no sup...\n",
              "277                      Zodiak  Twelve demons merged with Norman Harrison, who...\n",
              "278        Zombie (Simon Garth)  War hero Simon Garth was turned into a zombie ...\n",
              "279                       Zuras         Zuras was once the leader of the Eternals.\n",
              "280                       Zzzax  A chain reaction in an atomic reactor, a resul...\n",
              "\n",
              "[281 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DjR6ElxnayRM"
      },
      "source": [
        "A continuación se llevará a cabo el preprocesado, en la que se usarán 3 técnicas:\n",
        "\n",
        "1.   ***Tokenization***: división del texto en palabras \n",
        "2.   Eliminación de ***stopwords***\n",
        "3. ***Stemmization***: permite la obtención de la raíz de cada palabra sin que el resultado sea una palabra real."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S7JGI2P_cbWk",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "outputId": "327e6b56-9067-4639-edf0-6dfeec02ccad"
      },
      "source": [
        "from nltk.tokenize import word_tokenize \n",
        "from nltk.corpus import stopwords\n",
        "from nltk.stem import PorterStemmer\n",
        "\n",
        "import nltk\n",
        "nltk.download('punkt')\n",
        "nltk.download('stopwords')\n",
        "\n",
        "ps = PorterStemmer()\n",
        "\n",
        "preprocessedText = []\n",
        "\n",
        "for row in originalData.itertuples():\n",
        "    text = word_tokenize(row[2]) ## indice de la columna que contiene la descripcion\n",
        "    ## Remove stop words\n",
        "    stops = set(stopwords.words(\"english\"))\n",
        "    text = [ps.stem(w) for w in text if not w in stops and w.isalnum()]\n",
        "    text = \" \".join(text)\n",
        "    \n",
        "    preprocessedText.append(text)\n",
        "\n",
        "preprocessedData = originalData\n",
        "preprocessedData['processed_text'] = preprocessedText\n",
        "\n",
        "preprocessedData"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Unzipping tokenizers/punkt.zip.\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Unzipping corpora/stopwords.zip.\n"
          ],
          "name": "stdout"
        },
        {
          "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>name</th>\n",
              "      <th>description</th>\n",
              "      <th>processed_text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A-Bomb (HAS)</td>\n",
              "      <td>Rick Jones has been Hulk's best bud since day ...</td>\n",
              "      <td>rick jone hulk best bud sinc day one friend te...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A.I.M.</td>\n",
              "      <td>AIM is a terrorist organization bent on destro...</td>\n",
              "      <td>aim terrorist organ bent destroy world</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Abomination (Emil Blonsky)</td>\n",
              "      <td>Formerly known as Emil Blonsky, a spy of Sovie...</td>\n",
              "      <td>formerli known emil blonski spi soviet yugosla...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Adam Warlock</td>\n",
              "      <td>Adam Warlock is an artificially created human ...</td>\n",
              "      <td>adam warlock artifici creat human born cocoon ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Agent X (Nijo)</td>\n",
              "      <td>Originally a partner of the mind-altering assa...</td>\n",
              "      <td>origin partner assassin black swan nijo spi de...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>276</th>\n",
              "      <td>Zarek</td>\n",
              "      <td>Zarek is a member of the Kree race with no sup...</td>\n",
              "      <td>zarek member kree race superhuman abil special...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>277</th>\n",
              "      <td>Zodiak</td>\n",
              "      <td>Twelve demons merged with Norman Harrison, who...</td>\n",
              "      <td>twelv demon merg norman harrison soon adopt gu...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>278</th>\n",
              "      <td>Zombie (Simon Garth)</td>\n",
              "      <td>War hero Simon Garth was turned into a zombie ...</td>\n",
              "      <td>war hero simon garth turn zombi secretari layl...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>279</th>\n",
              "      <td>Zuras</td>\n",
              "      <td>Zuras was once the leader of the Eternals.</td>\n",
              "      <td>zura leader etern</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>280</th>\n",
              "      <td>Zzzax</td>\n",
              "      <td>A chain reaction in an atomic reactor, a resul...</td>\n",
              "      <td>A chain reaction atom reactor result terrorist...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>281 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                           name  ...                                     processed_text\n",
              "0                  A-Bomb (HAS)  ...  rick jone hulk best bud sinc day one friend te...\n",
              "1                        A.I.M.  ...             aim terrorist organ bent destroy world\n",
              "2    Abomination (Emil Blonsky)  ...  formerli known emil blonski spi soviet yugosla...\n",
              "3                  Adam Warlock  ...  adam warlock artifici creat human born cocoon ...\n",
              "4                Agent X (Nijo)  ...  origin partner assassin black swan nijo spi de...\n",
              "..                          ...  ...                                                ...\n",
              "276                       Zarek  ...  zarek member kree race superhuman abil special...\n",
              "277                      Zodiak  ...  twelv demon merg norman harrison soon adopt gu...\n",
              "278        Zombie (Simon Garth)  ...  war hero simon garth turn zombi secretari layl...\n",
              "279                       Zuras  ...                                  zura leader etern\n",
              "280                       Zzzax  ...  A chain reaction atom reactor result terrorist...\n",
              "\n",
              "[281 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xC1FaiVbekx0"
      },
      "source": [
        "##**1.2 Creación de la bolsa de palabras (BoW) con TF-IDF**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DMTTBR8TfFmd"
      },
      "source": [
        "Se parte de los datos almacenados en \"preprocessedData\", en donde para cada personaje existe un campo 'preprocessed_text' que contiene la descripción preprocesada.\n",
        "\n",
        "El objetivo es transformar todos los textos de sinopsis en vectores de frecuencias (Bag of words), aplicando además la ponderación TF-IDF para los valores de dichas frecuencias.\n",
        "\n",
        "El paquete sklearn ofrece una clase llamada *TfidfVectorizer* que crea automáticamente la matriz compuesta por todos los vectores de frecuencias ponderados a partir de un array de textos (preprocessedData['processed_text'])\n",
        "\n",
        "Si se quiere emplear la bolsa de palabras sin ponderación TF-IDF puede usarse la clase *CountVectorized* del mismo paquete"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NME2qKMRhxhu",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "84dc213e-8ad8-4da1-f445-ea3fdfbc0d7a"
      },
      "source": [
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "\n",
        "bagOfWordsModel = TfidfVectorizer()\n",
        "bagOfWordsModel.fit(preprocessedData['processed_text'])\n",
        "textsBoW= bagOfWordsModel.transform(preprocessedData['processed_text'])\n",
        "print(\"Finished\")"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Finished\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IJD_Baauh4I1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bf8ce6cd-0c09-4024-c9c0-6251f934d914"
      },
      "source": [
        "textsBoW.shape"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(281, 2283)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mj2IJzFWh6mj",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7f956f36-8bb3-410f-aa15-cd081d8ef3d6"
      },
      "source": [
        "print(textsBoW)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "  (0, 2137)\t0.130889104582123\n",
            "  (0, 2058)\t0.14217279372193212\n",
            "  (0, 2004)\t0.22205823661448335\n",
            "  (0, 1974)\t0.22205823661448335\n",
            "  (0, 1894)\t0.1961840975559547\n",
            "  (0, 1790)\t0.1961840975559547\n",
            "  (0, 1779)\t0.1752944840330487\n",
            "  (0, 1634)\t0.22205823661448335\n",
            "  (0, 1505)\t0.10190245579244313\n",
            "  (0, 1404)\t0.11629865466340347\n",
            "  (0, 1174)\t0.16198034620346324\n",
            "  (0, 1086)\t0.22205823661448335\n",
            "  (0, 968)\t0.1468449451157794\n",
            "  (0, 840)\t0.20692283552679946\n",
            "  (0, 816)\t0.17030995849742606\n",
            "  (0, 797)\t0.14942034497452006\n",
            "  (0, 695)\t0.1752944840330487\n",
            "  (0, 647)\t0.16198034620346324\n",
            "  (0, 537)\t0.1878544852619919\n",
            "  (0, 496)\t0.1878544852619919\n",
            "  (0, 475)\t0.22205823661448335\n",
            "  (0, 284)\t0.20692283552679946\n",
            "  (0, 251)\t0.22205823661448335\n",
            "  (0, 242)\t0.1878544852619919\n",
            "  (0, 214)\t0.1752944840330487\n",
            "  :\t:\n",
            "  (278, 818)\t0.30506443106319997\n",
            "  (278, 81)\t0.2225292018497309\n",
            "  (279, 2282)\t0.6554139206650713\n",
            "  (279, 1148)\t0.49150479114816825\n",
            "  (279, 669)\t0.5734593559066198\n",
            "  (280, 1993)\t0.22286926032113236\n",
            "  (280, 1726)\t0.25226282639126546\n",
            "  (280, 1662)\t0.25226282639126546\n",
            "  (280, 1623)\t0.2134066455942286\n",
            "  (280, 1577)\t0.25226282639126546\n",
            "  (280, 1576)\t0.25226282639126546\n",
            "  (280, 1346)\t0.23506869247776788\n",
            "  (280, 970)\t0.159087426424004\n",
            "  (280, 868)\t0.19913822007758497\n",
            "  (280, 775)\t0.16974465400745184\n",
            "  (280, 695)\t0.19913822007758497\n",
            "  (280, 647)\t0.18401307952409543\n",
            "  (280, 620)\t0.25226282639126546\n",
            "  (280, 456)\t0.16408212818086607\n",
            "  (280, 340)\t0.25226282639126546\n",
            "  (280, 255)\t0.22286926032113236\n",
            "  (280, 158)\t0.25226282639126546\n",
            "  (280, 157)\t0.23506869247776788\n",
            "  (280, 22)\t0.22286926032113236\n",
            "  (280, 17)\t0.23506869247776788\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mN43uXK-h_tf",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cbd7ca4f-7c49-425a-fe73-6267d55c553f"
      },
      "source": [
        "bagOfWordsModel.get_feature_names()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['13',\n",
              " '1910',\n",
              " '1930',\n",
              " '1931',\n",
              " '1940',\n",
              " '19th',\n",
              " '21st',\n",
              " '31st',\n",
              " '53rd',\n",
              " '60',\n",
              " 'abandon',\n",
              " 'abduct',\n",
              " 'abil',\n",
              " 'abl',\n",
              " 'abomin',\n",
              " 'abraham',\n",
              " 'abruptli',\n",
              " 'absorb',\n",
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              " 'give',\n",
              " 'given',\n",
              " 'gleason',\n",
              " 'glenn',\n",
              " 'glue',\n",
              " 'go',\n",
              " 'god',\n",
              " 'goddess',\n",
              " 'godfath',\n",
              " 'goe',\n",
              " 'gold',\n",
              " 'goliath',\n",
              " 'golmen',\n",
              " 'good',\n",
              " 'got',\n",
              " 'govern',\n",
              " 'graduat',\n",
              " 'graft',\n",
              " 'grandeur',\n",
              " 'grandfath',\n",
              " 'grandmast',\n",
              " 'grandmoth',\n",
              " 'grant',\n",
              " 'grave',\n",
              " 'great',\n",
              " 'greatest',\n",
              " 'green',\n",
              " 'greer',\n",
              " 'gregor',\n",
              " 'grew',\n",
              " 'grey',\n",
              " 'grimm',\n",
              " 'groot',\n",
              " 'grotesqu',\n",
              " 'group',\n",
              " 'groupi',\n",
              " 'grow',\n",
              " 'grown',\n",
              " 'guard',\n",
              " 'guardian',\n",
              " 'guardsmen',\n",
              " 'guid',\n",
              " 'guido',\n",
              " 'guilt',\n",
              " 'guis',\n",
              " 'gun',\n",
              " 'gunnar',\n",
              " 'guy',\n",
              " 'gwen',\n",
              " 'gyp',\n",
              " 'hair',\n",
              " 'half',\n",
              " 'hammer',\n",
              " 'hand',\n",
              " 'hank',\n",
              " 'happen',\n",
              " 'har',\n",
              " 'harada',\n",
              " 'hard',\n",
              " 'hardest',\n",
              " 'harlem',\n",
              " 'harmon',\n",
              " 'harrelson',\n",
              " 'harrison',\n",
              " 'harsh',\n",
              " 'hate',\n",
              " 'hawkey',\n",
              " 'he',\n",
              " 'head',\n",
              " 'heal',\n",
              " 'heart',\n",
              " 'heather',\n",
              " 'heavili',\n",
              " 'hector',\n",
              " 'heighten',\n",
              " 'heir',\n",
              " 'held',\n",
              " 'hell',\n",
              " 'hellfir',\n",
              " 'hellip',\n",
              " 'helmet',\n",
              " 'helmut',\n",
              " 'help',\n",
              " 'henri',\n",
              " 'her',\n",
              " 'herald',\n",
              " 'herman',\n",
              " 'hero',\n",
              " 'heroic',\n",
              " 'hi',\n",
              " 'hidden',\n",
              " 'hide',\n",
              " 'high',\n",
              " 'highli',\n",
              " 'hire',\n",
              " 'hiroshima',\n",
              " 'hit',\n",
              " 'hobgoblin',\n",
              " 'hogzilla',\n",
              " 'hold',\n",
              " 'holograph',\n",
              " 'home',\n",
              " 'homeland',\n",
              " 'homework',\n",
              " 'homo',\n",
              " 'hone',\n",
              " 'honor',\n",
              " 'hook',\n",
              " 'hope',\n",
              " 'hopeless',\n",
              " 'hord',\n",
              " 'horrif',\n",
              " 'horrifi',\n",
              " 'horseman',\n",
              " 'host',\n",
              " 'hostag',\n",
              " 'hound',\n",
              " 'hous',\n",
              " 'howev',\n",
              " 'howlett',\n",
              " 'hudson',\n",
              " 'huge',\n",
              " 'hulk',\n",
              " 'hulkbust',\n",
              " 'human',\n",
              " 'humankind',\n",
              " 'humanoid',\n",
              " 'hunter',\n",
              " 'hurt',\n",
              " 'husband',\n",
              " 'hybrid',\n",
              " 'hydra',\n",
              " 'hydraul',\n",
              " 'hyperact',\n",
              " 'idea',\n",
              " 'ident',\n",
              " 'ii',\n",
              " 'il',\n",
              " 'ill',\n",
              " 'illeg',\n",
              " 'illegitim',\n",
              " 'illinoi',\n",
              " 'imag',\n",
              " 'imbecil',\n",
              " 'immatur',\n",
              " 'immedi',\n",
              " 'immigr',\n",
              " 'immort',\n",
              " 'impenetr',\n",
              " 'imperi',\n",
              " 'implant',\n",
              " 'imprint',\n",
              " 'imprison',\n",
              " 'improvis',\n",
              " ...]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L09Hmv3LiIKP",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "9ec539b6-9d2b-47cc-ec8f-3e474ed3835a"
      },
      "source": [
        "bagOfWordsModel.get_feature_names()[1005]"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'includ'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "B2zSKMi4-iMF"
      },
      "source": [
        "#**2 Búsqueda de los personajes más similares a una persona**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HsWZiUoMiaQL"
      },
      "source": [
        "##**2.1 Basado únicamente en descripción**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Wu6Omh-2vYGH"
      },
      "source": [
        "Para realizar este proceso hay que realizar todo el proceso anterior incluyendo a la persona con su descripción. De esta forma, se calculará la distancia entre el usuario y todos los personajes.\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GHtovSslBams"
      },
      "source": [
        "En la siguiente celda se debe intrroducir el nombre y la descripción con la que se quiera calcular la distancia"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gR8VNUWuVpv9"
      },
      "source": [
        "nombre = \"Pepe\" #Introducir nombre\n",
        "descripcion = \"I was once the leader of the Eternals. I am strong as iron and as small as an ant. I am also a terrorist.\" #Descripcion"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kfwORkBqBtQ6"
      },
      "source": [
        "Se realiza el mismo proceso que en el punto 1"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ak2_zptvxak-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "b09fde76-2c98-4dcd-ca86-51e0b0b8a95d"
      },
      "source": [
        "import pandas as pd\n",
        "\n",
        "originalData = pd.read_csv('marvel.csv')\n",
        "originalData = originalData.append({'name' : nombre, 'description' : descripcion}, ignore_index=True)\n",
        "originalData"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>description</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A-Bomb (HAS)</td>\n",
              "      <td>Rick Jones has been Hulk's best bud since day ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A.I.M.</td>\n",
              "      <td>AIM is a terrorist organization bent on destro...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Abomination (Emil Blonsky)</td>\n",
              "      <td>Formerly known as Emil Blonsky, a spy of Sovie...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Adam Warlock</td>\n",
              "      <td>Adam Warlock is an artificially created human ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Agent X (Nijo)</td>\n",
              "      <td>Originally a partner of the mind-altering assa...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>277</th>\n",
              "      <td>Zodiak</td>\n",
              "      <td>Twelve demons merged with Norman Harrison, who...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>278</th>\n",
              "      <td>Zombie (Simon Garth)</td>\n",
              "      <td>War hero Simon Garth was turned into a zombie ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>279</th>\n",
              "      <td>Zuras</td>\n",
              "      <td>Zuras was once the leader of the Eternals.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>280</th>\n",
              "      <td>Zzzax</td>\n",
              "      <td>A chain reaction in an atomic reactor, a resul...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>281</th>\n",
              "      <td>Pepe</td>\n",
              "      <td>I was once the leader of the Eternals. I am st...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>282 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                           name                                        description\n",
              "0                  A-Bomb (HAS)  Rick Jones has been Hulk's best bud since day ...\n",
              "1                        A.I.M.  AIM is a terrorist organization bent on destro...\n",
              "2    Abomination (Emil Blonsky)  Formerly known as Emil Blonsky, a spy of Sovie...\n",
              "3                  Adam Warlock  Adam Warlock is an artificially created human ...\n",
              "4                Agent X (Nijo)  Originally a partner of the mind-altering assa...\n",
              "..                          ...                                                ...\n",
              "277                      Zodiak  Twelve demons merged with Norman Harrison, who...\n",
              "278        Zombie (Simon Garth)  War hero Simon Garth was turned into a zombie ...\n",
              "279                       Zuras         Zuras was once the leader of the Eternals.\n",
              "280                       Zzzax  A chain reaction in an atomic reactor, a resul...\n",
              "281                        Pepe  I was once the leader of the Eternals. I am st...\n",
              "\n",
              "[282 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F8PlufFe01oq",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "outputId": "9c686eb2-faa3-4b54-d4fd-983865f8302f"
      },
      "source": [
        "from nltk.tokenize import word_tokenize \n",
        "from nltk.corpus import stopwords\n",
        "from nltk.stem import PorterStemmer\n",
        "\n",
        "import nltk\n",
        "nltk.download('punkt')\n",
        "nltk.download('stopwords')\n",
        "\n",
        "ps = PorterStemmer()\n",
        "\n",
        "preprocessedText = []\n",
        "\n",
        "for row in originalData.itertuples():\n",
        "    text = word_tokenize(row[2]) ## indice de la columna que contiene la descripcion\n",
        "    ## Remove stop words\n",
        "    stops = set(stopwords.words(\"english\"))\n",
        "    text = [ps.stem(w) for w in text if not w in stops and w.isalnum()]\n",
        "    text = \" \".join(text)\n",
        "    \n",
        "    preprocessedText.append(text)\n",
        "\n",
        "preprocessedData = originalData\n",
        "preprocessedData['processed_text'] = preprocessedText\n",
        "\n",
        "preprocessedData"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Package punkt is already up-to-date!\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n"
          ],
          "name": "stdout"
        },
        {
          "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>name</th>\n",
              "      <th>description</th>\n",
              "      <th>processed_text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A-Bomb (HAS)</td>\n",
              "      <td>Rick Jones has been Hulk's best bud since day ...</td>\n",
              "      <td>rick jone hulk best bud sinc day one friend te...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A.I.M.</td>\n",
              "      <td>AIM is a terrorist organization bent on destro...</td>\n",
              "      <td>aim terrorist organ bent destroy world</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Abomination (Emil Blonsky)</td>\n",
              "      <td>Formerly known as Emil Blonsky, a spy of Sovie...</td>\n",
              "      <td>formerli known emil blonski spi soviet yugosla...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Adam Warlock</td>\n",
              "      <td>Adam Warlock is an artificially created human ...</td>\n",
              "      <td>adam warlock artifici creat human born cocoon ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Agent X (Nijo)</td>\n",
              "      <td>Originally a partner of the mind-altering assa...</td>\n",
              "      <td>origin partner assassin black swan nijo spi de...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>277</th>\n",
              "      <td>Zodiak</td>\n",
              "      <td>Twelve demons merged with Norman Harrison, who...</td>\n",
              "      <td>twelv demon merg norman harrison soon adopt gu...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>278</th>\n",
              "      <td>Zombie (Simon Garth)</td>\n",
              "      <td>War hero Simon Garth was turned into a zombie ...</td>\n",
              "      <td>war hero simon garth turn zombi secretari layl...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>279</th>\n",
              "      <td>Zuras</td>\n",
              "      <td>Zuras was once the leader of the Eternals.</td>\n",
              "      <td>zura leader etern</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>280</th>\n",
              "      <td>Zzzax</td>\n",
              "      <td>A chain reaction in an atomic reactor, a resul...</td>\n",
              "      <td>A chain reaction atom reactor result terrorist...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>281</th>\n",
              "      <td>Pepe</td>\n",
              "      <td>I was once the leader of the Eternals. I am st...</td>\n",
              "      <td>I leader etern I strong iron small ant I also ...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>282 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                           name  ...                                     processed_text\n",
              "0                  A-Bomb (HAS)  ...  rick jone hulk best bud sinc day one friend te...\n",
              "1                        A.I.M.  ...             aim terrorist organ bent destroy world\n",
              "2    Abomination (Emil Blonsky)  ...  formerli known emil blonski spi soviet yugosla...\n",
              "3                  Adam Warlock  ...  adam warlock artifici creat human born cocoon ...\n",
              "4                Agent X (Nijo)  ...  origin partner assassin black swan nijo spi de...\n",
              "..                          ...  ...                                                ...\n",
              "277                      Zodiak  ...  twelv demon merg norman harrison soon adopt gu...\n",
              "278        Zombie (Simon Garth)  ...  war hero simon garth turn zombi secretari layl...\n",
              "279                       Zuras  ...                                  zura leader etern\n",
              "280                       Zzzax  ...  A chain reaction atom reactor result terrorist...\n",
              "281                        Pepe  ...  I leader etern I strong iron small ant I also ...\n",
              "\n",
              "[282 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "crNAlGRH032K"
      },
      "source": [
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "\n",
        "bagOfWordsModel = TfidfVectorizer()\n",
        "bagOfWordsModel.fit(preprocessedData['processed_text'])\n",
        "textsBoW= bagOfWordsModel.transform(preprocessedData['processed_text'])"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3IeRcKCOyrRZ"
      },
      "source": [
        "A continuación se crea una matriz N x N (N= número de personajes) en donde el valor de la posición matriz[ i , j ] indique la distancia que existe entre el personaje i y el personaje j. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UPSwZKgPzF4O"
      },
      "source": [
        "from sklearn.metrics import pairwise_distances\n",
        "\n",
        "distance_matrix= pairwise_distances(textsBoW,textsBoW ,metric='cosine')\n"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NcNdTdLmzI8X"
      },
      "source": [
        "Ahora basta con obtener el índice de la persona introducida y las distancias con el resto de personajes"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xgTUQOwSzYdu",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7749bbf3-3ce9-4fb8-c0b5-3e446040a1f5"
      },
      "source": [
        "indexOfTitle = preprocessedData[preprocessedData['name']==nombre].index.values[0]\n",
        "indexOfTitle\n",
        "\n",
        "distance_scores = list(enumerate(distance_matrix[indexOfTitle]))\n",
        "distance_scores"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[(0, 0.9304965120389753),\n",
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              " (124, 1.0),\n",
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              " (126, 0.8891431236019741),\n",
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              " (230, 1.0),\n",
              " (231, 1.0),\n",
              " (232, 1.0),\n",
              " (233, 1.0),\n",
              " (234, 1.0),\n",
              " (235, 1.0),\n",
              " (236, 1.0),\n",
              " (237, 1.0),\n",
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              " (239, 1.0),\n",
              " (240, 1.0),\n",
              " (241, 1.0),\n",
              " (242, 1.0),\n",
              " (243, 1.0),\n",
              " (244, 1.0),\n",
              " (245, 1.0),\n",
              " (246, 1.0),\n",
              " (247, 0.9580085660610814),\n",
              " (248, 1.0),\n",
              " (249, 1.0),\n",
              " (250, 1.0),\n",
              " (251, 1.0),\n",
              " (252, 1.0),\n",
              " (253, 0.9611073221817749),\n",
              " (254, 1.0),\n",
              " (255, 0.922675988610445),\n",
              " (256, 1.0),\n",
              " (257, 1.0),\n",
              " (258, 1.0),\n",
              " (259, 1.0),\n",
              " (260, 1.0),\n",
              " (261, 1.0),\n",
              " (262, 1.0),\n",
              " (263, 1.0),\n",
              " (264, 1.0),\n",
              " (265, 1.0),\n",
              " (266, 1.0),\n",
              " (267, 1.0),\n",
              " (268, 1.0),\n",
              " (269, 1.0),\n",
              " (270, 1.0),\n",
              " (271, 1.0),\n",
              " (272, 0.9294140692189775),\n",
              " (273, 1.0),\n",
              " (274, 1.0),\n",
              " (275, 1.0),\n",
              " (276, 1.0),\n",
              " (277, 1.0),\n",
              " (278, 0.9321076085790826),\n",
              " (279, 0.6591883246077384),\n",
              " (280, 0.9210029764893715),\n",
              " (281, 0.0)]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RxgpoduS1l20"
      },
      "source": [
        "Una vez tenemos las distancias, únicamente debemos ordenarlas, quedarnos con las más cortas y mostrarlas de forma legible."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3Gw4yP-111oI",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2d495a01-51a9-43fa-9681-c9f9d7c57c25"
      },
      "source": [
        "ordered_scores = sorted(distance_scores, key=lambda x: x[1])\n",
        "top_scores = ordered_scores[1:11]\n",
        "top_indexes = [i[0] for i in top_scores]\n",
        "preprocessedData['name'].iloc[top_indexes]"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "279                           Zuras\n",
              "171                           Thena\n",
              "1                            A.I.M.\n",
              "126                          Sprite\n",
              "42        Iron Man/Tony Stark (MAA)\n",
              "43      Iron Patriot (James Rhodes)\n",
              "70                            Sersi\n",
              "170                The Leader (HAS)\n",
              "216                         Vampiro\n",
              "180    Thunderbird (John Proudstar)\n",
              "Name: name, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EDfTQZ-YYix4"
      },
      "source": [
        "##**2.2 Basado en su descripción y parámetros adicionales**\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2k6wuHPgBAIU"
      },
      "source": [
        "**Búsqueda basada en Descripción + Valoración Comentarios + Valoración Directa (Likes) + Valoración Media Comentarios**\n",
        "\n",
        "Ponderación:\n",
        "\n",
        "* Descripción (70%): se basa en el parecido entre la descripción que tenga el usuario y la descripción de cada personaje\n",
        "* Valoración Comentarios (7.5%): se basa en la valoración del comentario textual que realice el usuario a un personaje. Estos valores son extraídos del subsistema de valoración. Puede ser:\n",
        "  * Buena (0)\n",
        "  * Neutra o no valoración (0.5)\n",
        "  * Mala (1)\n",
        "* Valoración Directa por Likes (15%)\n",
        "  * Like (0)\n",
        "  * Dislike (1)\n",
        "  * Ninguna (0.5)\n",
        "* Valoración Media Comentarios (7.5%): se trata de la media de las valoraciones de comentarios de todos los usuarios sobre un personaje. Puede ser un valor entre 0 y 1."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jH_pPcfxZrY9"
      },
      "source": [
        "Para probar esta parte del sistema simularemos tener los datos de las valoraciones de los comentarios y las valoraciones directas.\n",
        "\n",
        "A continuación se generan aleatoriamente las valoraciones:\n",
        "\n",
        "* 0  es valoración positiva\n",
        "* 0.5 es valoración neutra (o no valoración)\n",
        "* 1 es valoración negativa"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "hmv0Dty1Zpm6",
        "outputId": "8cf9e41e-1b89-4909-98c7-98a9b8f6f733"
      },
      "source": [
        "from random import choice, randint\n",
        "\n",
        "valoracion_comentario = []\n",
        "valoracion_directa = []\n",
        "valoracion_media = []\n",
        "\n",
        "for i in range(0,len(preprocessedData)):\n",
        "  valoracion_comentario.append(choice([0.0, 0.5, 1.0]))\n",
        "  valoracion_directa.append(choice([0.0, 0.5, 1.0]))\n",
        "  valoracion_media.append(randint(0.0,100.0)/100.0)\n",
        "\n",
        "preprocessedData['valoracion_comentario'] = valoracion_comentario\n",
        "preprocessedData['valoracion_directa'] = valoracion_directa\n",
        "preprocessedData['valoracion_media'] = valoracion_media\n",
        "\n",
        "preprocessedData"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>description</th>\n",
              "      <th>processed_text</th>\n",
              "      <th>valoracion_comentario</th>\n",
              "      <th>valoracion_directa</th>\n",
              "      <th>valoracion_media</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A-Bomb (HAS)</td>\n",
              "      <td>Rick Jones has been Hulk's best bud since day ...</td>\n",
              "      <td>rick jone hulk best bud sinc day one friend te...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A.I.M.</td>\n",
              "      <td>AIM is a terrorist organization bent on destro...</td>\n",
              "      <td>aim terrorist organ bent destroy world</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Abomination (Emil Blonsky)</td>\n",
              "      <td>Formerly known as Emil Blonsky, a spy of Sovie...</td>\n",
              "      <td>formerli known emil blonski spi soviet yugosla...</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.43</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Adam Warlock</td>\n",
              "      <td>Adam Warlock is an artificially created human ...</td>\n",
              "      <td>adam warlock artifici creat human born cocoon ...</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Agent X (Nijo)</td>\n",
              "      <td>Originally a partner of the mind-altering assa...</td>\n",
              "      <td>origin partner assassin black swan nijo spi de...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>277</th>\n",
              "      <td>Zodiak</td>\n",
              "      <td>Twelve demons merged with Norman Harrison, who...</td>\n",
              "      <td>twelv demon merg norman harrison soon adopt gu...</td>\n",
              "      <td>0.5</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.41</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>278</th>\n",
              "      <td>Zombie (Simon Garth)</td>\n",
              "      <td>War hero Simon Garth was turned into a zombie ...</td>\n",
              "      <td>war hero simon garth turn zombi secretari layl...</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>279</th>\n",
              "      <td>Zuras</td>\n",
              "      <td>Zuras was once the leader of the Eternals.</td>\n",
              "      <td>zura leader etern</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>280</th>\n",
              "      <td>Zzzax</td>\n",
              "      <td>A chain reaction in an atomic reactor, a resul...</td>\n",
              "      <td>A chain reaction atom reactor result terrorist...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>281</th>\n",
              "      <td>Pepe</td>\n",
              "      <td>I was once the leader of the Eternals. I am st...</td>\n",
              "      <td>I leader etern I strong iron small ant I also ...</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.85</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>282 rows × 6 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                           name  ... valoracion_media\n",
              "0                  A-Bomb (HAS)  ...             0.27\n",
              "1                        A.I.M.  ...             0.73\n",
              "2    Abomination (Emil Blonsky)  ...             0.43\n",
              "3                  Adam Warlock  ...             0.68\n",
              "4                Agent X (Nijo)  ...             0.77\n",
              "..                          ...  ...              ...\n",
              "277                      Zodiak  ...             0.41\n",
              "278        Zombie (Simon Garth)  ...             0.80\n",
              "279                       Zuras  ...             0.10\n",
              "280                       Zzzax  ...             0.65\n",
              "281                        Pepe  ...             0.85\n",
              "\n",
              "[282 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "t3sEz5rscK9z"
      },
      "source": [
        "A continuación calculamos las distancias teniendo en cuenta la ponderación"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "knirAu62cP9p",
        "outputId": "4a6d01be-be45-4995-e73f-4ca1e9ac6f1d"
      },
      "source": [
        "distance_scores_final = []\n",
        "\n",
        "for i in range(len(distance_matrix[indexOfTitle])):\n",
        "  valoracion = distance_matrix[indexOfTitle][i]*0.7 + preprocessedData['valoracion_comentario'][i]*0.075 + preprocessedData['valoracion_directa'][i]*0.15 + preprocessedData['valoracion_media'][i]*0.075\n",
        "  distance_scores_final.append((i,valoracion))\n",
        "\n",
        "distance_scores_final"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[(0, 0.8215975584272827),\n",
              " (1, 0.7596701261378571),\n",
              " (2, 0.7697499999999999),\n",
              " (3, 0.8634999999999999),\n",
              " (4, 0.90775),\n",
              " (5, 0.9203166455170355),\n",
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              " (10, 0.7031802355311932),\n",
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              " (12, 0.8612499999999998),\n",
              " (13, 0.8704146636217743),\n",
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              " (15, 0.8199999999999998),\n",
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              " (17, 0.8837499999999999),\n",
              " (18, 0.9137499999999998),\n",
              " (19, 0.9297764314060795),\n",
              " (20, 0.8222499999999999),\n",
              " (21, 0.8214999999999999),\n",
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              " (25, 0.86125),\n",
              " (26, 0.8109999999999999),\n",
              " (27, 0.826),\n",
              " (28, 0.7637499999999999),\n",
              " (29, 0.8905),\n",
              " (30, 0.8859999999999999),\n",
              " (31, 0.8807499999999999),\n",
              " (32, 0.9767499999999999),\n",
              " (33, 0.9849999999999999),\n",
              " (34, 0.7849852724009455),\n",
              " (35, 0.76825),\n",
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              " (37, 0.7749999999999999),\n",
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              " (158, 0.8252499999999999),\n",
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              " (163, 0.889),\n",
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              " (238, 0.9024999999999999),\n",
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              " (240, 0.7772499999999999),\n",
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              " (242, 0.7675),\n",
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              " (246, 0.8402499999999999),\n",
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              " (251, 0.93475),\n",
              " (252, 0.841),\n",
              " (253, 0.6937751255272424),\n",
              " (254, 0.8597499999999999),\n",
              " (255, 0.8476231920273114),\n",
              " (256, 0.8657499999999999),\n",
              " (257, 0.8709999999999999),\n",
              " (258, 0.8357499999999999),\n",
              " (259, 0.8604999999999999),\n",
              " (260, 0.9355),\n",
              " (261, 0.8432499999999999),\n",
              " (262, 0.9295),\n",
              " (263, 0.72475),\n",
              " (264, 0.8484999999999999),\n",
              " (265, 0.7869999999999999),\n",
              " (266, 0.8094999999999999),\n",
              " (267, 0.7689999999999999),\n",
              " (268, 0.7787499999999999),\n",
              " (269, 0.87925),\n",
              " (270, 0.9797499999999999),\n",
              " (271, 0.8252499999999999),\n",
              " (272, 0.8973398484532843),\n",
              " (273, 0.89425),\n",
              " (274, 0.865),\n",
              " (275, 0.8402499999999999),\n",
              " (276, 0.8267499999999999),\n",
              " (277, 0.9182499999999999),\n",
              " (278, 0.7874753260053577),\n",
              " (279, 0.4689318272254168),\n",
              " (280, 0.7684520835425599),\n",
              " (281, 0.17625)]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PpjPk0mYj2cB"
      },
      "source": [
        "A continuación nos quedamos con los personajes más aprecidos"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fXbDIbEJj6It",
        "outputId": "e9a44401-1300-4c3c-f1d8-b6d7a31a33d9"
      },
      "source": [
        "ordered_scores_final = sorted(distance_scores_final, key=lambda x: x[1])\n",
        "top_scores_final = ordered_scores_final[1:11]\n",
        "top_indexes_final = [i[0] for i in top_scores_final]\n",
        "preprocessedData['name'].iloc[top_indexes_final]"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "279                        Zuras\n",
              "171                        Thena\n",
              "220                        Vapor\n",
              "42     Iron Man/Tony Stark (MAA)\n",
              "101                       Skreet\n",
              "253            White Tiger (USM)\n",
              "100                         Skin\n",
              "10      Banshee (Theresa Rourke)\n",
              "65          Scream (Donna Diego)\n",
              "113     Spider-Girl (May Parker)\n",
              "Name: name, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FKFrsus2CaxR"
      },
      "source": [
        "#**3. Resumen de los resultados**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZeDt1-v7Cu1y"
      },
      "source": [
        "**Resultados del punto 2.1**: se muestran a continuación las descripciones para comprobar que existe algún parecido"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "ZMqiuM07Do5S",
        "outputId": "a50e9cbc-9d66-47fa-e579-03ef43533857"
      },
      "source": [
        "descripcion"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'I was once the leader of the Eternals. I am strong as iron and as small as an ant. I am also a terrorist.'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "877r-L08CoDs",
        "outputId": "5120d91c-1359-442e-86e0-5c4e5086c680"
      },
      "source": [
        "preprocessedData['name'].iloc[top_indexes]"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "279                           Zuras\n",
              "171                           Thena\n",
              "1                            A.I.M.\n",
              "126                          Sprite\n",
              "42        Iron Man/Tony Stark (MAA)\n",
              "43      Iron Patriot (James Rhodes)\n",
              "70                            Sersi\n",
              "170                The Leader (HAS)\n",
              "216                         Vampiro\n",
              "180    Thunderbird (John Proudstar)\n",
              "Name: name, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hETRWhQ8Ddpv",
        "outputId": "b12cc1ae-bfe3-4da7-f51b-bce5032bc20f"
      },
      "source": [
        "preprocessedData['description'].iloc[top_indexes]"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "279           Zuras was once the leader of the Eternals.\n",
              "171    Thena, a second generation Eternal, is the eld...\n",
              "1      AIM is a terrorist organization bent on destro...\n",
              "126    Sprite is a mischievous Eternal who maintains ...\n",
              "42     Tony Stark is the genius inventor/billionaire/...\n",
              "43     U.S. Air Force pilot and Tony Stark's friend w...\n",
              "70     Sersi is a member of the Eternals, a species d...\n",
              "170    What the Hulk has in strength, the Leader has ...\n",
              "216    Vampiro, part of the race known as the Eternal...\n",
              "180    An exceptionally strong and vigorous athlete i...\n",
              "Name: description, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bRcsKjkeDDIT"
      },
      "source": [
        "**Resultados del punto 2.2**: se muestran a continuación las descripciones para comprobar que existe algún parecido (se debe tener en cuenta en este caso que la descripción no tiene todo el peso del cálculo)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "mzL4WqAsDsEG",
        "outputId": "bbdca31b-737f-46e4-e9af-6426abd12724"
      },
      "source": [
        "descripcion"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'I was once the leader of the Eternals. I am strong as iron and as small as an ant. I am also a terrorist.'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wFrkYIOeDG5U",
        "outputId": "7a3f77e2-266e-48d5-dde0-71f12d9ea976"
      },
      "source": [
        "preprocessedData['name'].iloc[top_indexes_final]"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "279                        Zuras\n",
              "171                        Thena\n",
              "220                        Vapor\n",
              "42     Iron Man/Tony Stark (MAA)\n",
              "101                       Skreet\n",
              "253            White Tiger (USM)\n",
              "100                         Skin\n",
              "10      Banshee (Theresa Rourke)\n",
              "65          Scream (Donna Diego)\n",
              "113     Spider-Girl (May Parker)\n",
              "Name: name, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Nd5yoyt0DYno",
        "outputId": "ac80e322-1656-4aad-887d-a163abc829cd"
      },
      "source": [
        "preprocessedData['description'].iloc[top_indexes_final]"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "279           Zuras was once the leader of the Eternals.\n",
              "171    Thena, a second generation Eternal, is the eld...\n",
              "220    Vapor, along with her brother, was among the s...\n",
              "42     Tony Stark is the genius inventor/billionaire/...\n",
              "101    The Proemial God Aegis revealed that Skreet wa...\n",
              "253    White Tiger takes everything very seriously. A...\n",
              "100    Angelo Espinosa, a founding member of Generati...\n",
              "10     The daughter of former X-Men member Sean Cassi...\n",
              "65     Out of the five alien symbiotes that were forc...\n",
              "113    May \"Mayday\" Parker is the daughter of Spider-...\n",
              "Name: description, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    }
  ]
}