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      "source": [
        "# UD05 · EX3 — Centrocampistas jóvenes con potencial\n",
        "\n",
        "Este ejemplo muestra cómo crear un sistema experto con lógica difusa para detectar centro-campistas jóvenes con buen potencial.Nos basaremos en el trabajo de Luka Radovanović, un estudiante de la Universidad de Belgrado. El resultado del trabajo se puede encontrar en: https://github.com/lukadlm97/football-manager-researching"
      ]
    },
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      "id": "3c905967364754de",
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      "source": [
        "## Planteamiento del problema\n",
        "\n",
        "Uno de los problemas que encuentran los equipos de fútbol es la detección de jugadores jóvenes con potencial. Es por eso que estamos creando un sistema expertos con lógica difusa que nos ayude a detectar centrocampistas ofensivos jóvenes con potencial.\n",
        "\n",
        "Hemos elegido la posición de un centrocampista ofensivo porque es una posición de lo más difícil de encontrar y, por lo tanto, es una posición que los equipos están buscando mucho.Además, es una posición en la que muchos de los mejores jugadores de la historia han jugado, como: Di Stefano, Maradona, Zidane, Platini, etc."
      ]
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    {
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      "source": [
        "## Pasos previos\n",
        "\n",
        "Necesitamos instalar la libreria `scikit-fuzzy`. Usamos la 0.5.0 con un pequeno parche: la 0.4.2 que se usaba antes ya no funciona en Python 3.12 o posterior.\n"
      ]
    },
    {
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      "id": "H5_kWZbKqFsp",
      "metadata": {
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        "id": "H5_kWZbKqFsp",
        "outputId": "398d684e-1afd-43c4-c49f-f9a2ec60f6af"
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      "source": [
        "%pip install scikit-fuzzy networkx\n",
        "\n",
        "# scikit-fuzzy 0.4.2 ya no arranca en Python 3.12+ (importa `imp` y `distutils`, que\n",
        "# se eliminaron del lenguaje), asi que instalamos la 0.5.0. En esa version todo\n",
        "# funciona menos `ControlSystem.view()`: en su visualizador, la linea que guarda el\n",
        "# sistema quedo dentro de un `if` y nunca se ejecuta. Se arregla en tres lineas:\n",
        "from skfuzzy.control.visualization import ControlSystemVisualizer\n",
        "\n",
        "_init_original = ControlSystemVisualizer.__init__\n",
        "\n",
        "def _init_parcheado(self, control_system):\n",
        "    _init_original(self, control_system)\n",
        "    self.ctrl = control_system\n",
        "\n",
        "ControlSystemVisualizer.__init__ = _init_parcheado\n"
      ]
    },
    {
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      "id": "5982cdc7430c1bb4",
      "metadata": {
        "collapsed": false,
        "id": "5982cdc7430c1bb4"
      },
      "source": [
        "## Anàlisi de les dades\n",
        "\n",
        "Primero cargamos los datos (`EX2.-players_22.csv`) y vemos cómo están estructurados.\n",
        "Cargaremos los datos en un DataFrame de datos de Pandas y observaremos las primeras filas."
      ]
    },
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      "outputs": [
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          "text": [
            "<ipython-input-2-c51e318d3d01>:3: DtypeWarning: Columns (25,108) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv('EX2.-players_22.csv')\n"
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              "      <th></th>\n",
              "      <th>sofifa_id</th>\n",
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              "      <th>long_name</th>\n",
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              "      <th>0</th>\n",
              "      <td>158023</td>\n",
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              "      <td>L. Messi</td>\n",
              "      <td>Lionel Andrés Messi Cuccittini</td>\n",
              "      <td>RW, ST, CF</td>\n",
              "      <td>93</td>\n",
              "      <td>93</td>\n",
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              "      <td>320000.0</td>\n",
              "      <td>34</td>\n",
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              "      <td>50+3</td>\n",
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              "      <td>https://cdn.sofifa.net/flags/ar.png</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>188545</td>\n",
              "      <td>https://sofifa.com/player/188545/robert-lewand...</td>\n",
              "      <td>R. Lewandowski</td>\n",
              "      <td>Robert Lewandowski</td>\n",
              "      <td>ST</td>\n",
              "      <td>92</td>\n",
              "      <td>92</td>\n",
              "      <td>119500000.0</td>\n",
              "      <td>270000.0</td>\n",
              "      <td>32</td>\n",
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              "      <td>60+3</td>\n",
              "      <td>60+3</td>\n",
              "      <td>60+3</td>\n",
              "      <td>61+3</td>\n",
              "      <td>19+3</td>\n",
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              "      <td>https://cdn.sofifa.net/teams/21/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/de.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/1353/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/pl.png</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>20801</td>\n",
              "      <td>https://sofifa.com/player/20801/c-ronaldo-dos-...</td>\n",
              "      <td>Cristiano Ronaldo</td>\n",
              "      <td>Cristiano Ronaldo dos Santos Aveiro</td>\n",
              "      <td>ST, LW</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>45000000.0</td>\n",
              "      <td>270000.0</td>\n",
              "      <td>36</td>\n",
              "      <td>...</td>\n",
              "      <td>53+3</td>\n",
              "      <td>53+3</td>\n",
              "      <td>53+3</td>\n",
              "      <td>60+3</td>\n",
              "      <td>20+3</td>\n",
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              "      <td>https://cdn.sofifa.net/teams/11/60.png</td>\n",
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              "      <td>https://cdn.sofifa.net/teams/1354/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/pt.png</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>190871</td>\n",
              "      <td>https://sofifa.com/player/190871/neymar-da-sil...</td>\n",
              "      <td>Neymar Jr</td>\n",
              "      <td>Neymar da Silva Santos Júnior</td>\n",
              "      <td>LW, CAM</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>129000000.0</td>\n",
              "      <td>270000.0</td>\n",
              "      <td>29</td>\n",
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              "      <td>50+3</td>\n",
              "      <td>50+3</td>\n",
              "      <td>50+3</td>\n",
              "      <td>62+3</td>\n",
              "      <td>20+3</td>\n",
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              "      <td>https://cdn.sofifa.net/teams/73/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/fr.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/br.png</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>192985</td>\n",
              "      <td>https://sofifa.com/player/192985/kevin-de-bruy...</td>\n",
              "      <td>K. De Bruyne</td>\n",
              "      <td>Kevin De Bruyne</td>\n",
              "      <td>CM, CAM</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>125500000.0</td>\n",
              "      <td>350000.0</td>\n",
              "      <td>30</td>\n",
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              "      <td>69+3</td>\n",
              "      <td>69+3</td>\n",
              "      <td>69+3</td>\n",
              "      <td>75+3</td>\n",
              "      <td>21+3</td>\n",
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              "      <td>https://cdn.sofifa.net/teams/10/60.png</td>\n",
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              "      <td>https://cdn.sofifa.net/teams/1325/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/be.png</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <th>19234</th>\n",
              "      <td>261962</td>\n",
              "      <td>https://sofifa.com/player/261962/defu-song/220002</td>\n",
              "      <td>Song Defu</td>\n",
              "      <td>宋德福</td>\n",
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              "      <td>47</td>\n",
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              "      <td>1000.0</td>\n",
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              "      <td>46+2</td>\n",
              "      <td>46+2</td>\n",
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              "      <td>https://cdn.sofifa.net/players/261/962/22_120.png</td>\n",
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              "      <td>https://cdn.sofifa.net/flags/cn.png</td>\n",
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              "      <td>https://cdn.sofifa.net/flags/cn.png</td>\n",
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              "      <th>19235</th>\n",
              "      <td>262040</td>\n",
              "      <td>https://sofifa.com/player/262040/caoimhin-port...</td>\n",
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              "      <td>Caoimhin Porter</td>\n",
              "      <td>CM</td>\n",
              "      <td>47</td>\n",
              "      <td>59</td>\n",
              "      <td>110000.0</td>\n",
              "      <td>500.0</td>\n",
              "      <td>19</td>\n",
              "      <td>...</td>\n",
              "      <td>44+2</td>\n",
              "      <td>44+2</td>\n",
              "      <td>44+2</td>\n",
              "      <td>48+2</td>\n",
              "      <td>14+2</td>\n",
              "      <td>https://cdn.sofifa.net/players/262/040/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/445/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/ie.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/ie.png</td>\n",
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              "      <th>19236</th>\n",
              "      <td>262760</td>\n",
              "      <td>https://sofifa.com/player/262760/nathan-logue/...</td>\n",
              "      <td>N. Logue</td>\n",
              "      <td>Nathan Logue-Cunningham</td>\n",
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              "      <td>47</td>\n",
              "      <td>55</td>\n",
              "      <td>100000.0</td>\n",
              "      <td>500.0</td>\n",
              "      <td>21</td>\n",
              "      <td>...</td>\n",
              "      <td>45+2</td>\n",
              "      <td>45+2</td>\n",
              "      <td>45+2</td>\n",
              "      <td>47+2</td>\n",
              "      <td>12+2</td>\n",
              "      <td>https://cdn.sofifa.net/players/262/760/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/111131/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/ie.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/ie.png</td>\n",
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              "    <tr>\n",
              "      <th>19237</th>\n",
              "      <td>262820</td>\n",
              "      <td>https://sofifa.com/player/262820/luke-rudden/2...</td>\n",
              "      <td>L. Rudden</td>\n",
              "      <td>Luke Rudden</td>\n",
              "      <td>ST</td>\n",
              "      <td>47</td>\n",
              "      <td>60</td>\n",
              "      <td>110000.0</td>\n",
              "      <td>500.0</td>\n",
              "      <td>19</td>\n",
              "      <td>...</td>\n",
              "      <td>26+2</td>\n",
              "      <td>26+2</td>\n",
              "      <td>26+2</td>\n",
              "      <td>32+2</td>\n",
              "      <td>15+2</td>\n",
              "      <td>https://cdn.sofifa.net/players/262/820/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/111131/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/ie.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/ie.png</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19238</th>\n",
              "      <td>264540</td>\n",
              "      <td>https://sofifa.com/player/264540/emanuel-lalch...</td>\n",
              "      <td>E. Lalchhanchhuaha</td>\n",
              "      <td>Emanuel Lalchhanchhuaha</td>\n",
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              "      <td>47</td>\n",
              "      <td>60</td>\n",
              "      <td>110000.0</td>\n",
              "      <td>500.0</td>\n",
              "      <td>19</td>\n",
              "      <td>...</td>\n",
              "      <td>41+2</td>\n",
              "      <td>41+2</td>\n",
              "      <td>41+2</td>\n",
              "      <td>45+2</td>\n",
              "      <td>16+2</td>\n",
              "      <td>https://cdn.sofifa.net/players/264/540/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/113040/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/in.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/in.png</td>\n",
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              "      buttonEl.style.display =\n",
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            "text/plain": [
              "       sofifa_id                                         player_url  \\\n",
              "0         158023  https://sofifa.com/player/158023/lionel-messi/...   \n",
              "1         188545  https://sofifa.com/player/188545/robert-lewand...   \n",
              "2          20801  https://sofifa.com/player/20801/c-ronaldo-dos-...   \n",
              "3         190871  https://sofifa.com/player/190871/neymar-da-sil...   \n",
              "4         192985  https://sofifa.com/player/192985/kevin-de-bruy...   \n",
              "...          ...                                                ...   \n",
              "19234     261962  https://sofifa.com/player/261962/defu-song/220002   \n",
              "19235     262040  https://sofifa.com/player/262040/caoimhin-port...   \n",
              "19236     262760  https://sofifa.com/player/262760/nathan-logue/...   \n",
              "19237     262820  https://sofifa.com/player/262820/luke-rudden/2...   \n",
              "19238     264540  https://sofifa.com/player/264540/emanuel-lalch...   \n",
              "\n",
              "               short_name                            long_name  \\\n",
              "0                L. Messi       Lionel Andrés Messi Cuccittini   \n",
              "1          R. Lewandowski                   Robert Lewandowski   \n",
              "2       Cristiano Ronaldo  Cristiano Ronaldo dos Santos Aveiro   \n",
              "3               Neymar Jr        Neymar da Silva Santos Júnior   \n",
              "4            K. De Bruyne                      Kevin De Bruyne   \n",
              "...                   ...                                  ...   \n",
              "19234           Song Defu                                  宋德福   \n",
              "19235           C. Porter                      Caoimhin Porter   \n",
              "19236            N. Logue              Nathan Logue-Cunningham   \n",
              "19237           L. Rudden                          Luke Rudden   \n",
              "19238  E. Lalchhanchhuaha              Emanuel Lalchhanchhuaha   \n",
              "\n",
              "      player_positions  overall  potential    value_eur  wage_eur  age  ...  \\\n",
              "0           RW, ST, CF       93         93   78000000.0  320000.0   34  ...   \n",
              "1                   ST       92         92  119500000.0  270000.0   32  ...   \n",
              "2               ST, LW       91         91   45000000.0  270000.0   36  ...   \n",
              "3              LW, CAM       91         91  129000000.0  270000.0   29  ...   \n",
              "4              CM, CAM       91         91  125500000.0  350000.0   30  ...   \n",
              "...                ...      ...        ...          ...       ...  ...  ...   \n",
              "19234              CDM       47         52      70000.0    1000.0   22  ...   \n",
              "19235               CM       47         59     110000.0     500.0   19  ...   \n",
              "19236               CM       47         55     100000.0     500.0   21  ...   \n",
              "19237               ST       47         60     110000.0     500.0   19  ...   \n",
              "19238              CAM       47         60     110000.0     500.0   19  ...   \n",
              "\n",
              "        lcb    cb   rcb    rb    gk  \\\n",
              "0      50+3  50+3  50+3  61+3  19+3   \n",
              "1      60+3  60+3  60+3  61+3  19+3   \n",
              "2      53+3  53+3  53+3  60+3  20+3   \n",
              "3      50+3  50+3  50+3  62+3  20+3   \n",
              "4      69+3  69+3  69+3  75+3  21+3   \n",
              "...     ...   ...   ...   ...   ...   \n",
              "19234  46+2  46+2  46+2  48+2  15+2   \n",
              "19235  44+2  44+2  44+2  48+2  14+2   \n",
              "19236  45+2  45+2  45+2  47+2  12+2   \n",
              "19237  26+2  26+2  26+2  32+2  15+2   \n",
              "19238  41+2  41+2  41+2  45+2  16+2   \n",
              "\n",
              "                                         player_face_url  \\\n",
              "0      https://cdn.sofifa.net/players/158/023/22_120.png   \n",
              "1      https://cdn.sofifa.net/players/188/545/22_120.png   \n",
              "2      https://cdn.sofifa.net/players/020/801/22_120.png   \n",
              "3      https://cdn.sofifa.net/players/190/871/22_120.png   \n",
              "4      https://cdn.sofifa.net/players/192/985/22_120.png   \n",
              "...                                                  ...   \n",
              "19234  https://cdn.sofifa.net/players/261/962/22_120.png   \n",
              "19235  https://cdn.sofifa.net/players/262/040/22_120.png   \n",
              "19236  https://cdn.sofifa.net/players/262/760/22_120.png   \n",
              "19237  https://cdn.sofifa.net/players/262/820/22_120.png   \n",
              "19238  https://cdn.sofifa.net/players/264/540/22_120.png   \n",
              "\n",
              "                                    club_logo_url  \\\n",
              "0          https://cdn.sofifa.net/teams/73/60.png   \n",
              "1          https://cdn.sofifa.net/teams/21/60.png   \n",
              "2          https://cdn.sofifa.net/teams/11/60.png   \n",
              "3          https://cdn.sofifa.net/teams/73/60.png   \n",
              "4          https://cdn.sofifa.net/teams/10/60.png   \n",
              "...                                           ...   \n",
              "19234  https://cdn.sofifa.net/teams/112541/60.png   \n",
              "19235     https://cdn.sofifa.net/teams/445/60.png   \n",
              "19236  https://cdn.sofifa.net/teams/111131/60.png   \n",
              "19237  https://cdn.sofifa.net/teams/111131/60.png   \n",
              "19238  https://cdn.sofifa.net/teams/113040/60.png   \n",
              "\n",
              "                                 club_flag_url  \\\n",
              "0          https://cdn.sofifa.net/flags/fr.png   \n",
              "1          https://cdn.sofifa.net/flags/de.png   \n",
              "2      https://cdn.sofifa.net/flags/gb-eng.png   \n",
              "3          https://cdn.sofifa.net/flags/fr.png   \n",
              "4      https://cdn.sofifa.net/flags/gb-eng.png   \n",
              "...                                        ...   \n",
              "19234      https://cdn.sofifa.net/flags/cn.png   \n",
              "19235      https://cdn.sofifa.net/flags/ie.png   \n",
              "19236      https://cdn.sofifa.net/flags/ie.png   \n",
              "19237      https://cdn.sofifa.net/flags/ie.png   \n",
              "19238      https://cdn.sofifa.net/flags/in.png   \n",
              "\n",
              "                                nation_logo_url  \\\n",
              "0      https://cdn.sofifa.net/teams/1369/60.png   \n",
              "1      https://cdn.sofifa.net/teams/1353/60.png   \n",
              "2      https://cdn.sofifa.net/teams/1354/60.png   \n",
              "3                                           NaN   \n",
              "4      https://cdn.sofifa.net/teams/1325/60.png   \n",
              "...                                         ...   \n",
              "19234                                       NaN   \n",
              "19235                                       NaN   \n",
              "19236                                       NaN   \n",
              "19237                                       NaN   \n",
              "19238                                       NaN   \n",
              "\n",
              "                           nation_flag_url  \n",
              "0      https://cdn.sofifa.net/flags/ar.png  \n",
              "1      https://cdn.sofifa.net/flags/pl.png  \n",
              "2      https://cdn.sofifa.net/flags/pt.png  \n",
              "3      https://cdn.sofifa.net/flags/br.png  \n",
              "4      https://cdn.sofifa.net/flags/be.png  \n",
              "...                                    ...  \n",
              "19234  https://cdn.sofifa.net/flags/cn.png  \n",
              "19235  https://cdn.sofifa.net/flags/ie.png  \n",
              "19236  https://cdn.sofifa.net/flags/ie.png  \n",
              "19237  https://cdn.sofifa.net/flags/ie.png  \n",
              "19238  https://cdn.sofifa.net/flags/in.png  \n",
              "\n",
              "[19239 rows x 110 columns]"
            ]
          },
          "execution_count": 2,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import pandas as pd\n",
        "\n",
        "df = pd.read_csv('EX2.-players_22.csv')\n",
        "df"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "bbd69b1307e80857",
      "metadata": {
        "collapsed": false,
        "id": "bbd69b1307e80857"
      },
      "source": [
        "También será útil para nosotros que nos describan los datos para conocer su distribución."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "8e29b37d996817fe",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:42.593008Z",
          "start_time": "2024-01-08T16:45:41.865068Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 350
        },
        "id": "8e29b37d996817fe",
        "outputId": "4be567cc-9600-4c93-d265-91eab3e669b3"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe"
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            "text/html": [
              "\n",
              "  <div id=\"df-ceb26cc8-534c-4cba-9069-3eeea1b77822\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>sofifa_id</th>\n",
              "      <th>overall</th>\n",
              "      <th>potential</th>\n",
              "      <th>value_eur</th>\n",
              "      <th>wage_eur</th>\n",
              "      <th>age</th>\n",
              "      <th>height_cm</th>\n",
              "      <th>weight_kg</th>\n",
              "      <th>club_team_id</th>\n",
              "      <th>league_level</th>\n",
              "      <th>...</th>\n",
              "      <th>mentality_composure</th>\n",
              "      <th>defending_marking_awareness</th>\n",
              "      <th>defending_standing_tackle</th>\n",
              "      <th>defending_sliding_tackle</th>\n",
              "      <th>goalkeeping_diving</th>\n",
              "      <th>goalkeeping_handling</th>\n",
              "      <th>goalkeeping_kicking</th>\n",
              "      <th>goalkeeping_positioning</th>\n",
              "      <th>goalkeeping_reflexes</th>\n",
              "      <th>goalkeeping_speed</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>19239.000000</td>\n",
              "      <td>19239.000000</td>\n",
              "      <td>19239.000000</td>\n",
              "      <td>1.916500e+04</td>\n",
              "      <td>19178.000000</td>\n",
              "      <td>19239.000000</td>\n",
              "      <td>19239.000000</td>\n",
              "      <td>19239.000000</td>\n",
              "      <td>19178.000000</td>\n",
              "      <td>19178.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>19239.000000</td>\n",
              "      <td>19239.000000</td>\n",
              "      <td>19239.000000</td>\n",
              "      <td>19239.000000</td>\n",
              "      <td>19239.000000</td>\n",
              "      <td>19239.000000</td>\n",
              "      <td>19239.000000</td>\n",
              "      <td>19239.000000</td>\n",
              "      <td>19239.000000</td>\n",
              "      <td>2132.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>231468.086959</td>\n",
              "      <td>65.772182</td>\n",
              "      <td>71.079370</td>\n",
              "      <td>2.850452e+06</td>\n",
              "      <td>9017.989363</td>\n",
              "      <td>25.210822</td>\n",
              "      <td>181.299704</td>\n",
              "      <td>74.943032</td>\n",
              "      <td>50580.498123</td>\n",
              "      <td>1.354364</td>\n",
              "      <td>...</td>\n",
              "      <td>57.929830</td>\n",
              "      <td>46.601746</td>\n",
              "      <td>48.045584</td>\n",
              "      <td>45.906700</td>\n",
              "      <td>16.406102</td>\n",
              "      <td>16.192474</td>\n",
              "      <td>16.055356</td>\n",
              "      <td>16.229274</td>\n",
              "      <td>16.491814</td>\n",
              "      <td>36.439962</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>27039.717497</td>\n",
              "      <td>6.880232</td>\n",
              "      <td>6.086213</td>\n",
              "      <td>7.613700e+06</td>\n",
              "      <td>19470.176724</td>\n",
              "      <td>4.748235</td>\n",
              "      <td>6.863179</td>\n",
              "      <td>7.069434</td>\n",
              "      <td>54401.868535</td>\n",
              "      <td>0.747865</td>\n",
              "      <td>...</td>\n",
              "      <td>12.159326</td>\n",
              "      <td>20.200807</td>\n",
              "      <td>21.232718</td>\n",
              "      <td>20.755683</td>\n",
              "      <td>17.574028</td>\n",
              "      <td>16.839528</td>\n",
              "      <td>16.564554</td>\n",
              "      <td>17.059779</td>\n",
              "      <td>17.884833</td>\n",
              "      <td>10.751563</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>41.000000</td>\n",
              "      <td>47.000000</td>\n",
              "      <td>49.000000</td>\n",
              "      <td>9.000000e+03</td>\n",
              "      <td>500.000000</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>155.000000</td>\n",
              "      <td>49.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>15.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>214413.500000</td>\n",
              "      <td>61.000000</td>\n",
              "      <td>67.000000</td>\n",
              "      <td>4.750000e+05</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>21.000000</td>\n",
              "      <td>176.000000</td>\n",
              "      <td>70.000000</td>\n",
              "      <td>479.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>29.000000</td>\n",
              "      <td>28.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>27.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>236543.000000</td>\n",
              "      <td>66.000000</td>\n",
              "      <td>71.000000</td>\n",
              "      <td>9.750000e+05</td>\n",
              "      <td>3000.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>181.000000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>1938.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>59.000000</td>\n",
              "      <td>52.000000</td>\n",
              "      <td>56.000000</td>\n",
              "      <td>53.000000</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>36.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>253532.500000</td>\n",
              "      <td>70.000000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>2.000000e+06</td>\n",
              "      <td>8000.000000</td>\n",
              "      <td>29.000000</td>\n",
              "      <td>186.000000</td>\n",
              "      <td>80.000000</td>\n",
              "      <td>111139.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>66.000000</td>\n",
              "      <td>63.000000</td>\n",
              "      <td>65.000000</td>\n",
              "      <td>63.000000</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>45.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>264640.000000</td>\n",
              "      <td>93.000000</td>\n",
              "      <td>95.000000</td>\n",
              "      <td>1.940000e+08</td>\n",
              "      <td>350000.000000</td>\n",
              "      <td>54.000000</td>\n",
              "      <td>206.000000</td>\n",
              "      <td>110.000000</td>\n",
              "      <td>115820.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>96.000000</td>\n",
              "      <td>93.000000</td>\n",
              "      <td>93.000000</td>\n",
              "      <td>92.000000</td>\n",
              "      <td>91.000000</td>\n",
              "      <td>92.000000</td>\n",
              "      <td>93.000000</td>\n",
              "      <td>92.000000</td>\n",
              "      <td>90.000000</td>\n",
              "      <td>65.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8 rows × 60 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ceb26cc8-534c-4cba-9069-3eeea1b77822')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-ceb26cc8-534c-4cba-9069-3eeea1b77822 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-ceb26cc8-534c-4cba-9069-3eeea1b77822');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-8d5825a0-3bb0-4990-8829-05b7fb06f381\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-8d5825a0-3bb0-4990-8829-05b7fb06f381')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
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              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-8d5825a0-3bb0-4990-8829-05b7fb06f381 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "           sofifa_id       overall     potential     value_eur       wage_eur  \\\n",
              "count   19239.000000  19239.000000  19239.000000  1.916500e+04   19178.000000   \n",
              "mean   231468.086959     65.772182     71.079370  2.850452e+06    9017.989363   \n",
              "std     27039.717497      6.880232      6.086213  7.613700e+06   19470.176724   \n",
              "min        41.000000     47.000000     49.000000  9.000000e+03     500.000000   \n",
              "25%    214413.500000     61.000000     67.000000  4.750000e+05    1000.000000   \n",
              "50%    236543.000000     66.000000     71.000000  9.750000e+05    3000.000000   \n",
              "75%    253532.500000     70.000000     75.000000  2.000000e+06    8000.000000   \n",
              "max    264640.000000     93.000000     95.000000  1.940000e+08  350000.000000   \n",
              "\n",
              "                age     height_cm     weight_kg   club_team_id  league_level  \\\n",
              "count  19239.000000  19239.000000  19239.000000   19178.000000  19178.000000   \n",
              "mean      25.210822    181.299704     74.943032   50580.498123      1.354364   \n",
              "std        4.748235      6.863179      7.069434   54401.868535      0.747865   \n",
              "min       16.000000    155.000000     49.000000       1.000000      1.000000   \n",
              "25%       21.000000    176.000000     70.000000     479.000000      1.000000   \n",
              "50%       25.000000    181.000000     75.000000    1938.000000      1.000000   \n",
              "75%       29.000000    186.000000     80.000000  111139.000000      1.000000   \n",
              "max       54.000000    206.000000    110.000000  115820.000000      5.000000   \n",
              "\n",
              "       ...  mentality_composure  defending_marking_awareness  \\\n",
              "count  ...         19239.000000                 19239.000000   \n",
              "mean   ...            57.929830                    46.601746   \n",
              "std    ...            12.159326                    20.200807   \n",
              "min    ...            12.000000                     4.000000   \n",
              "25%    ...            50.000000                    29.000000   \n",
              "50%    ...            59.000000                    52.000000   \n",
              "75%    ...            66.000000                    63.000000   \n",
              "max    ...            96.000000                    93.000000   \n",
              "\n",
              "       defending_standing_tackle  defending_sliding_tackle  \\\n",
              "count               19239.000000              19239.000000   \n",
              "mean                   48.045584                 45.906700   \n",
              "std                    21.232718                 20.755683   \n",
              "min                     5.000000                  5.000000   \n",
              "25%                    28.000000                 25.000000   \n",
              "50%                    56.000000                 53.000000   \n",
              "75%                    65.000000                 63.000000   \n",
              "max                    93.000000                 92.000000   \n",
              "\n",
              "       goalkeeping_diving  goalkeeping_handling  goalkeeping_kicking  \\\n",
              "count        19239.000000          19239.000000         19239.000000   \n",
              "mean            16.406102             16.192474            16.055356   \n",
              "std             17.574028             16.839528            16.564554   \n",
              "min              2.000000              2.000000             2.000000   \n",
              "25%              8.000000              8.000000             8.000000   \n",
              "50%             11.000000             11.000000            11.000000   \n",
              "75%             14.000000             14.000000            14.000000   \n",
              "max             91.000000             92.000000            93.000000   \n",
              "\n",
              "       goalkeeping_positioning  goalkeeping_reflexes  goalkeeping_speed  \n",
              "count             19239.000000          19239.000000        2132.000000  \n",
              "mean                 16.229274             16.491814          36.439962  \n",
              "std                  17.059779             17.884833          10.751563  \n",
              "min                   2.000000              2.000000          15.000000  \n",
              "25%                   8.000000              8.000000          27.000000  \n",
              "50%                  11.000000             11.000000          36.000000  \n",
              "75%                  14.000000             14.000000          45.000000  \n",
              "max                  92.000000             90.000000          65.000000  \n",
              "\n",
              "[8 rows x 60 columns]"
            ]
          },
          "execution_count": 3,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df.describe()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "de407485c9edc585",
      "metadata": {
        "collapsed": false,
        "id": "de407485c9edc585"
      },
      "source": [
        "Como hemos dicho, estamos buscando un centro-campista ofensivo joven, por lo que eliminaremos a todos los jugadores que no juegan en esta posición (CAM - Center Attacking Midfielders) o tienen más de 24 años."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "2c9c1fd1fbe10412",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:42.667652Z",
          "start_time": "2024-01-08T16:45:42.200140Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "2c9c1fd1fbe10412",
        "outputId": "264e04d3-d1d0-472c-9d51-a471b38cc945"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df"
            },
            "text/html": [
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              "<style scoped>\n",
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              "        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>sofifa_id</th>\n",
              "      <th>player_url</th>\n",
              "      <th>short_name</th>\n",
              "      <th>long_name</th>\n",
              "      <th>player_positions</th>\n",
              "      <th>overall</th>\n",
              "      <th>potential</th>\n",
              "      <th>value_eur</th>\n",
              "      <th>wage_eur</th>\n",
              "      <th>age</th>\n",
              "      <th>...</th>\n",
              "      <th>lcb</th>\n",
              "      <th>cb</th>\n",
              "      <th>rcb</th>\n",
              "      <th>rb</th>\n",
              "      <th>gk</th>\n",
              "      <th>player_face_url</th>\n",
              "      <th>club_logo_url</th>\n",
              "      <th>club_flag_url</th>\n",
              "      <th>nation_logo_url</th>\n",
              "      <th>nation_flag_url</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>138</th>\n",
              "      <td>235790</td>\n",
              "      <td>https://sofifa.com/player/235790/kai-havertz/2...</td>\n",
              "      <td>K. Havertz</td>\n",
              "      <td>Kai Lukas Havertz</td>\n",
              "      <td>CAM, CF, CM</td>\n",
              "      <td>84</td>\n",
              "      <td>92</td>\n",
              "      <td>94500000.0</td>\n",
              "      <td>130000.0</td>\n",
              "      <td>22</td>\n",
              "      <td>...</td>\n",
              "      <td>55+3</td>\n",
              "      <td>55+3</td>\n",
              "      <td>55+3</td>\n",
              "      <td>62+3</td>\n",
              "      <td>17+3</td>\n",
              "      <td>https://cdn.sofifa.net/players/235/790/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/5/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/gb-eng.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/1337/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/de.png</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>139</th>\n",
              "      <td>237692</td>\n",
              "      <td>https://sofifa.com/player/237692/phil-foden/22...</td>\n",
              "      <td>P. Foden</td>\n",
              "      <td>Philip Foden</td>\n",
              "      <td>CAM, LW, CM</td>\n",
              "      <td>84</td>\n",
              "      <td>92</td>\n",
              "      <td>94500000.0</td>\n",
              "      <td>125000.0</td>\n",
              "      <td>21</td>\n",
              "      <td>...</td>\n",
              "      <td>59+3</td>\n",
              "      <td>59+3</td>\n",
              "      <td>59+3</td>\n",
              "      <td>68+3</td>\n",
              "      <td>19+3</td>\n",
              "      <td>https://cdn.sofifa.net/players/237/692/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/10/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/gb-eng.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/1318/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/gb-eng.png</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>193</th>\n",
              "      <td>233064</td>\n",
              "      <td>https://sofifa.com/player/233064/mason-mount/2...</td>\n",
              "      <td>M. Mount</td>\n",
              "      <td>Mason Mount</td>\n",
              "      <td>CAM, CM, RW</td>\n",
              "      <td>83</td>\n",
              "      <td>89</td>\n",
              "      <td>58500000.0</td>\n",
              "      <td>120000.0</td>\n",
              "      <td>22</td>\n",
              "      <td>...</td>\n",
              "      <td>60+3</td>\n",
              "      <td>60+3</td>\n",
              "      <td>60+3</td>\n",
              "      <td>68+3</td>\n",
              "      <td>19+3</td>\n",
              "      <td>https://cdn.sofifa.net/players/233/064/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/5/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/gb-eng.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/1318/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/gb-eng.png</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>252</th>\n",
              "      <td>220697</td>\n",
              "      <td>https://sofifa.com/player/220697/james-maddiso...</td>\n",
              "      <td>J. Maddison</td>\n",
              "      <td>James Maddison</td>\n",
              "      <td>CAM, CM</td>\n",
              "      <td>82</td>\n",
              "      <td>85</td>\n",
              "      <td>41500000.0</td>\n",
              "      <td>100000.0</td>\n",
              "      <td>24</td>\n",
              "      <td>...</td>\n",
              "      <td>57+2</td>\n",
              "      <td>57+2</td>\n",
              "      <td>57+2</td>\n",
              "      <td>65+2</td>\n",
              "      <td>20+2</td>\n",
              "      <td>https://cdn.sofifa.net/players/220/697/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/95/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/gb-eng.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/gb-eng.png</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>254</th>\n",
              "      <td>222665</td>\n",
              "      <td>https://sofifa.com/player/222665/martin-odegaa...</td>\n",
              "      <td>M. Ødegaard</td>\n",
              "      <td>Martin Ødegaard</td>\n",
              "      <td>CAM, CM</td>\n",
              "      <td>82</td>\n",
              "      <td>88</td>\n",
              "      <td>49000000.0</td>\n",
              "      <td>89000.0</td>\n",
              "      <td>22</td>\n",
              "      <td>...</td>\n",
              "      <td>60+3</td>\n",
              "      <td>60+3</td>\n",
              "      <td>60+3</td>\n",
              "      <td>68+3</td>\n",
              "      <td>19+3</td>\n",
              "      <td>https://cdn.sofifa.net/players/222/665/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/1/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/gb-eng.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/1352/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/no.png</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19169</th>\n",
              "      <td>264072</td>\n",
              "      <td>https://sofifa.com/player/264072/bernardo-oliv...</td>\n",
              "      <td>Bernardo</td>\n",
              "      <td>Bernardo Oliveira</td>\n",
              "      <td>CAM</td>\n",
              "      <td>49</td>\n",
              "      <td>67</td>\n",
              "      <td>120000.0</td>\n",
              "      <td>500.0</td>\n",
              "      <td>17</td>\n",
              "      <td>...</td>\n",
              "      <td>39+2</td>\n",
              "      <td>39+2</td>\n",
              "      <td>39+2</td>\n",
              "      <td>42+2</td>\n",
              "      <td>14+2</td>\n",
              "      <td>https://cdn.sofifa.net/players/264/072/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/111393/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/au.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/br.png</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19171</th>\n",
              "      <td>264142</td>\n",
              "      <td>https://sofifa.com/player/264142/aaron-doran/2...</td>\n",
              "      <td>A. Doran</td>\n",
              "      <td>Aaron Doran</td>\n",
              "      <td>CAM</td>\n",
              "      <td>49</td>\n",
              "      <td>62</td>\n",
              "      <td>110000.0</td>\n",
              "      <td>500.0</td>\n",
              "      <td>18</td>\n",
              "      <td>...</td>\n",
              "      <td>42+2</td>\n",
              "      <td>42+2</td>\n",
              "      <td>42+2</td>\n",
              "      <td>44+2</td>\n",
              "      <td>14+2</td>\n",
              "      <td>https://cdn.sofifa.net/players/264/142/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/305/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/ie.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/ie.png</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19194</th>\n",
              "      <td>259649</td>\n",
              "      <td>https://sofifa.com/player/259649/engson-singh/...</td>\n",
              "      <td>E. Singh</td>\n",
              "      <td>Engson Singh</td>\n",
              "      <td>CAM, CM</td>\n",
              "      <td>48</td>\n",
              "      <td>65</td>\n",
              "      <td>120000.0</td>\n",
              "      <td>500.0</td>\n",
              "      <td>18</td>\n",
              "      <td>...</td>\n",
              "      <td>37+2</td>\n",
              "      <td>37+2</td>\n",
              "      <td>37+2</td>\n",
              "      <td>41+2</td>\n",
              "      <td>12+2</td>\n",
              "      <td>https://cdn.sofifa.net/players/259/649/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/113146/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/in.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/in.png</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19233</th>\n",
              "      <td>261818</td>\n",
              "      <td>https://sofifa.com/player/261818/ronan-gallagh...</td>\n",
              "      <td>R. Gallagher</td>\n",
              "      <td>Ronan Gallagher</td>\n",
              "      <td>CAM</td>\n",
              "      <td>47</td>\n",
              "      <td>61</td>\n",
              "      <td>110000.0</td>\n",
              "      <td>500.0</td>\n",
              "      <td>20</td>\n",
              "      <td>...</td>\n",
              "      <td>39+2</td>\n",
              "      <td>39+2</td>\n",
              "      <td>39+2</td>\n",
              "      <td>41+2</td>\n",
              "      <td>15+2</td>\n",
              "      <td>https://cdn.sofifa.net/players/261/818/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/111131/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/ie.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/ie.png</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19238</th>\n",
              "      <td>264540</td>\n",
              "      <td>https://sofifa.com/player/264540/emanuel-lalch...</td>\n",
              "      <td>E. Lalchhanchhuaha</td>\n",
              "      <td>Emanuel Lalchhanchhuaha</td>\n",
              "      <td>CAM</td>\n",
              "      <td>47</td>\n",
              "      <td>60</td>\n",
              "      <td>110000.0</td>\n",
              "      <td>500.0</td>\n",
              "      <td>19</td>\n",
              "      <td>...</td>\n",
              "      <td>41+2</td>\n",
              "      <td>41+2</td>\n",
              "      <td>41+2</td>\n",
              "      <td>45+2</td>\n",
              "      <td>16+2</td>\n",
              "      <td>https://cdn.sofifa.net/players/264/540/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/113040/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/in.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/in.png</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1158 rows × 110 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
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              "    60% {\n",
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              "      border-right-color: var(--fill-color);\n",
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            "text/plain": [
              "       sofifa_id                                         player_url  \\\n",
              "138       235790  https://sofifa.com/player/235790/kai-havertz/2...   \n",
              "139       237692  https://sofifa.com/player/237692/phil-foden/22...   \n",
              "193       233064  https://sofifa.com/player/233064/mason-mount/2...   \n",
              "252       220697  https://sofifa.com/player/220697/james-maddiso...   \n",
              "254       222665  https://sofifa.com/player/222665/martin-odegaa...   \n",
              "...          ...                                                ...   \n",
              "19169     264072  https://sofifa.com/player/264072/bernardo-oliv...   \n",
              "19171     264142  https://sofifa.com/player/264142/aaron-doran/2...   \n",
              "19194     259649  https://sofifa.com/player/259649/engson-singh/...   \n",
              "19233     261818  https://sofifa.com/player/261818/ronan-gallagh...   \n",
              "19238     264540  https://sofifa.com/player/264540/emanuel-lalch...   \n",
              "\n",
              "               short_name                long_name player_positions  overall  \\\n",
              "138            K. Havertz        Kai Lukas Havertz      CAM, CF, CM       84   \n",
              "139              P. Foden             Philip Foden      CAM, LW, CM       84   \n",
              "193              M. Mount              Mason Mount      CAM, CM, RW       83   \n",
              "252           J. Maddison           James Maddison          CAM, CM       82   \n",
              "254           M. Ødegaard          Martin Ødegaard          CAM, CM       82   \n",
              "...                   ...                      ...              ...      ...   \n",
              "19169            Bernardo        Bernardo Oliveira              CAM       49   \n",
              "19171            A. Doran              Aaron Doran              CAM       49   \n",
              "19194            E. Singh             Engson Singh          CAM, CM       48   \n",
              "19233        R. Gallagher          Ronan Gallagher              CAM       47   \n",
              "19238  E. Lalchhanchhuaha  Emanuel Lalchhanchhuaha              CAM       47   \n",
              "\n",
              "       potential   value_eur  wage_eur  age  ...   lcb    cb   rcb    rb  \\\n",
              "138           92  94500000.0  130000.0   22  ...  55+3  55+3  55+3  62+3   \n",
              "139           92  94500000.0  125000.0   21  ...  59+3  59+3  59+3  68+3   \n",
              "193           89  58500000.0  120000.0   22  ...  60+3  60+3  60+3  68+3   \n",
              "252           85  41500000.0  100000.0   24  ...  57+2  57+2  57+2  65+2   \n",
              "254           88  49000000.0   89000.0   22  ...  60+3  60+3  60+3  68+3   \n",
              "...          ...         ...       ...  ...  ...   ...   ...   ...   ...   \n",
              "19169         67    120000.0     500.0   17  ...  39+2  39+2  39+2  42+2   \n",
              "19171         62    110000.0     500.0   18  ...  42+2  42+2  42+2  44+2   \n",
              "19194         65    120000.0     500.0   18  ...  37+2  37+2  37+2  41+2   \n",
              "19233         61    110000.0     500.0   20  ...  39+2  39+2  39+2  41+2   \n",
              "19238         60    110000.0     500.0   19  ...  41+2  41+2  41+2  45+2   \n",
              "\n",
              "         gk                                    player_face_url  \\\n",
              "138    17+3  https://cdn.sofifa.net/players/235/790/22_120.png   \n",
              "139    19+3  https://cdn.sofifa.net/players/237/692/22_120.png   \n",
              "193    19+3  https://cdn.sofifa.net/players/233/064/22_120.png   \n",
              "252    20+2  https://cdn.sofifa.net/players/220/697/22_120.png   \n",
              "254    19+3  https://cdn.sofifa.net/players/222/665/22_120.png   \n",
              "...     ...                                                ...   \n",
              "19169  14+2  https://cdn.sofifa.net/players/264/072/22_120.png   \n",
              "19171  14+2  https://cdn.sofifa.net/players/264/142/22_120.png   \n",
              "19194  12+2  https://cdn.sofifa.net/players/259/649/22_120.png   \n",
              "19233  15+2  https://cdn.sofifa.net/players/261/818/22_120.png   \n",
              "19238  16+2  https://cdn.sofifa.net/players/264/540/22_120.png   \n",
              "\n",
              "                                    club_logo_url  \\\n",
              "138         https://cdn.sofifa.net/teams/5/60.png   \n",
              "139        https://cdn.sofifa.net/teams/10/60.png   \n",
              "193         https://cdn.sofifa.net/teams/5/60.png   \n",
              "252        https://cdn.sofifa.net/teams/95/60.png   \n",
              "254         https://cdn.sofifa.net/teams/1/60.png   \n",
              "...                                           ...   \n",
              "19169  https://cdn.sofifa.net/teams/111393/60.png   \n",
              "19171     https://cdn.sofifa.net/teams/305/60.png   \n",
              "19194  https://cdn.sofifa.net/teams/113146/60.png   \n",
              "19233  https://cdn.sofifa.net/teams/111131/60.png   \n",
              "19238  https://cdn.sofifa.net/teams/113040/60.png   \n",
              "\n",
              "                                 club_flag_url  \\\n",
              "138    https://cdn.sofifa.net/flags/gb-eng.png   \n",
              "139    https://cdn.sofifa.net/flags/gb-eng.png   \n",
              "193    https://cdn.sofifa.net/flags/gb-eng.png   \n",
              "252    https://cdn.sofifa.net/flags/gb-eng.png   \n",
              "254    https://cdn.sofifa.net/flags/gb-eng.png   \n",
              "...                                        ...   \n",
              "19169      https://cdn.sofifa.net/flags/au.png   \n",
              "19171      https://cdn.sofifa.net/flags/ie.png   \n",
              "19194      https://cdn.sofifa.net/flags/in.png   \n",
              "19233      https://cdn.sofifa.net/flags/ie.png   \n",
              "19238      https://cdn.sofifa.net/flags/in.png   \n",
              "\n",
              "                                nation_logo_url  \\\n",
              "138    https://cdn.sofifa.net/teams/1337/60.png   \n",
              "139    https://cdn.sofifa.net/teams/1318/60.png   \n",
              "193    https://cdn.sofifa.net/teams/1318/60.png   \n",
              "252                                         NaN   \n",
              "254    https://cdn.sofifa.net/teams/1352/60.png   \n",
              "...                                         ...   \n",
              "19169                                       NaN   \n",
              "19171                                       NaN   \n",
              "19194                                       NaN   \n",
              "19233                                       NaN   \n",
              "19238                                       NaN   \n",
              "\n",
              "                               nation_flag_url  \n",
              "138        https://cdn.sofifa.net/flags/de.png  \n",
              "139    https://cdn.sofifa.net/flags/gb-eng.png  \n",
              "193    https://cdn.sofifa.net/flags/gb-eng.png  \n",
              "252    https://cdn.sofifa.net/flags/gb-eng.png  \n",
              "254        https://cdn.sofifa.net/flags/no.png  \n",
              "...                                        ...  \n",
              "19169      https://cdn.sofifa.net/flags/br.png  \n",
              "19171      https://cdn.sofifa.net/flags/ie.png  \n",
              "19194      https://cdn.sofifa.net/flags/in.png  \n",
              "19233      https://cdn.sofifa.net/flags/ie.png  \n",
              "19238      https://cdn.sofifa.net/flags/in.png  \n",
              "\n",
              "[1158 rows x 110 columns]"
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df = df[(df['player_positions'].str.contains('CAM')) & (df['age'] <= 24)]\n",
        "df"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "9116dbafc5d11e38",
      "metadata": {
        "collapsed": false,
        "id": "9116dbafc5d11e38"
      },
      "source": [
        "## Análisis del potencial\n",
        "\n",
        "Para hacer una primera aproximación al potencial de los jugadores, hemos hecho una primera hipótesis que nos dice que los jugadores más potenciales son aquellos que son muy jóvenes y tienen una gran habilidad para pasar la pelota.\n",
        "\n",
        "Luego crearemos un sistema difuso con dos variables de entrada: la edad y la capacidad de pasar la pelota. La variable de salida será el potencial.\n",
        "\n",
        "El resumen de las reglas propuestas es el siguiente:\n",
        "\n",
        "### Relación entre la edad y la categoría lingüística\n",
        "\n",
        "| Edad  | Categoría    |\n",
        "|-------|--------------|\n",
        "| 15-18 | Joven        |\n",
        "| 16-22 | Junior       |\n",
        "| 20-24 | Senior-joven |\n",
        "\n",
        "### Relación entre la capacidad de pasar la pelota y la categoría lingüística\n",
        "\n",
        "| Pasar la pelota | Categoría   |\n",
        "|-----------------|-------------|\n",
        "| <=40            | Baja        |\n",
        "| 10-90           | Promedia    |\n",
        "| >=60-100        | Alta        |\n",
        "\n",
        "### Relación entre la categoría lingüística de potencial y su valor numérico\n",
        "\n",
        "Las variables de salida serán triangulares.\n",
        "\n",
        "| Potencial | Valor numérico |\n",
        "|-----------|----------------|\n",
        "| Bajo      | <40            |\n",
        "| Promedio  | 20 - 90        |\n",
        "| Alto      | 80 - 100       |\n",
        "\n",
        "Define los antecedentes y la consecuencia con sus funciones de adhesión."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "d570e67af87d12f9",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:42.737654Z",
          "start_time": "2024-01-08T16:45:42.466405Z"
        },
        "id": "d570e67af87d12f9"
      },
      "outputs": [],
      "source": [
        "# define aquí los antecedentes y el consecuente y a continuación cada una de las funciones de pertenencia (edad, calidad_pasada, potencial)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "60a79313bfaedf90",
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        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:43.822418Z",
          "start_time": "2024-01-08T16:45:42.752608Z"
        },
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          "height": 451
        },
        "id": "60a79313bfaedf90",
        "outputId": "4c171abc-7c7b-4a21-f4de-d5a27fdc9b21"
      },
      "outputs": [
        {
          "data": {
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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# define la función de pertenencia para edad y visualizala"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "f27bce5956089d78",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:44.238335Z",
          "start_time": "2024-01-08T16:45:43.456412Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "id": "f27bce5956089d78",
        "outputId": "1098ffc4-7cb4-4f4f-a5d1-3593cc394565"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# define la función de pertenencia para calidad_pasada y visualizala"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "18feaa47011a4ae",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:44.709282Z",
          "start_time": "2024-01-08T16:45:44.201689Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "id": "18feaa47011a4ae",
        "outputId": "3164f154-2ca1-439f-ec78-34bf894e8c8a"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# define la función de pertenencia para potencial y visualizala"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "a57b05efcd4e406a",
      "metadata": {
        "collapsed": false,
        "id": "a57b05efcd4e406a"
      },
      "source": [
        "## Reglas\n",
        "\n",
        "Debemos definir las reglas que relacionan las variables de entrada con la variable de salida. Será lo siguiente:\n",
        "\n",
        "| Edad         | Calidad pasada | Potencial |\n",
        "|--------------|----------------|-----------|\n",
        "| Joven        | Alta           | Alto      |\n",
        "| Joven        | Promedia       | Promedio  |\n",
        "| Joven        | Baixa          | Promedio  |\n",
        "| Junior       | Alta           | Alto      |\n",
        "| Junior       | Promedia       | Promedio  |\n",
        "| Junior       | Baixa          | Bajo      |\n",
        "| Senior-joven | Alta           | Alto      |\n",
        "| Senior-joven | Promedia       | Bajo      |\n",
        "| Senior-joven | Baixa          | Bajo      |\n",
        "\n",
        "Cree las reglas para nuestro sistema y el sistema de control. Ver las dependencias."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "9934bb898a04af36",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:44.801378Z",
          "start_time": "2024-01-08T16:45:44.711822Z"
        },
        "id": "9934bb898a04af36"
      },
      "outputs": [],
      "source": [
        "# Define aquí las reglas\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "d63e7a3079eb2c34",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:44.827415Z",
          "start_time": "2024-01-08T16:45:44.765062Z"
        },
        "id": "d63e7a3079eb2c34"
      },
      "outputs": [],
      "source": [
        "# Añadelas al sistema de control"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "677e4a0561025f9f",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:45.639063Z",
          "start_time": "2024-01-08T16:45:44.788174Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 406
        },
        "id": "677e4a0561025f9f",
        "outputId": "5050c1ab-2be3-4412-fb60-e4886664dd9f"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Visualizalas"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "5ed1c80a022fdfe0",
      "metadata": {
        "collapsed": false,
        "id": "5ed1c80a022fdfe0"
      },
      "source": [
        "Antes de aplicar nuestro modelo a todos los datos que tenemos, debemos probarlo con un par de ejemplos.\n",
        "¿Cuál será el potencial de un jugador de 17 años y un pase de 40? ¿Y si tuviera un pase de 80? También evalúa los dos casos anteriores si tenía 23 años."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "92e6bd6360022bde",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:45.653835Z",
          "start_time": "2024-01-08T16:45:45.643186Z"
        },
        "id": "92e6bd6360022bde"
      },
      "outputs": [],
      "source": [
        "# Realiza la simulación"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "f46e771595fd22f1",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:45.714943Z",
          "start_time": "2024-01-08T16:45:45.661847Z"
        },
        "id": "f46e771595fd22f1"
      },
      "outputs": [],
      "source": [
        "# Carga los datos para el primer caso de prueba"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "75eaaac98224255a",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:46.261107Z",
          "start_time": "2024-01-08T16:45:45.683683Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
        },
        "id": "75eaaac98224255a",
        "outputId": "2ee34800-d7d8-46ea-9702-96f733de7942"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "54.222222222222186\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Computa y visualiza la solución para la primera prueba"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "1221fffc8ef0abf9",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:46.281331Z",
          "start_time": "2024-01-08T16:45:46.271796Z"
        },
        "id": "1221fffc8ef0abf9"
      },
      "outputs": [],
      "source": [
        "# Carga los datos para el segundo caso de prueba"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "312556a590218f74",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:47.003670Z",
          "start_time": "2024-01-08T16:45:46.285526Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
        },
        "id": "312556a590218f74",
        "outputId": "00c8da25-d635-448e-d64c-e76173bb718f"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "63.465367765381686\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Computa y visualiza la solución para la segunda prueba"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "b77e24637da7aef9",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:47.006149Z",
          "start_time": "2024-01-08T16:45:46.959987Z"
        },
        "id": "b77e24637da7aef9"
      },
      "outputs": [],
      "source": [
        "# Carga los datos para el primer caso de prueba pero con 23 años"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "880b683615d19e3b",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:47.486514Z",
          "start_time": "2024-01-08T16:45:46.974837Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
        },
        "id": "880b683615d19e3b",
        "outputId": "bcbfec14-eb27-434a-f577-d92c2cefed66"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "14.0\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Computa y visualiza la solución para la primera prueba pero con 23 años"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "34fbdedb7a08fb85",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:47.488505Z",
          "start_time": "2024-01-08T16:45:47.455703Z"
        },
        "id": "34fbdedb7a08fb85"
      },
      "outputs": [],
      "source": [
        "# Carga los datos para el segundo caso de prueba pero con 23 años"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "5e652a06f147fd53",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:47.893375Z",
          "start_time": "2024-01-08T16:45:47.479410Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
        },
        "id": "5e652a06f147fd53",
        "outputId": "0baa4011-44df-4526-edb0-048155150ae8"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "52.051282051282044\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Computa y visualiza la solución para la segunda prueba pero con 23 años"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "9da8b8c3fc682959",
      "metadata": {
        "collapsed": false,
        "id": "9da8b8c3fc682959"
      },
      "source": [
        "## Actualitzar el DataFrame\n",
        "\n",
        "Actualiza el DataFrame con los datos calculados por nuestro modelo. Crea una columna llamada \"potencial\" con los datos que hemos calculado."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "5fa929f70bcacbda",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2024-01-08T16:45:49.579006Z",
          "start_time": "2024-01-08T16:45:47.899934Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "5fa929f70bcacbda",
        "outputId": "17e44a6a-9558-457e-b42a-c4ccc258e7b7"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "<ipython-input-22-3fe053d09759>:7: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  df['potencial'] = df.apply(potencial_jugador, axis=1)\n"
          ]
        },
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df"
            },
            "text/html": [
              "\n",
              "  <div id=\"df-f766fea5-850a-44bf-bd13-57bdda91790f\" class=\"colab-df-container\">\n",
              "    <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>sofifa_id</th>\n",
              "      <th>player_url</th>\n",
              "      <th>short_name</th>\n",
              "      <th>long_name</th>\n",
              "      <th>player_positions</th>\n",
              "      <th>overall</th>\n",
              "      <th>potential</th>\n",
              "      <th>value_eur</th>\n",
              "      <th>wage_eur</th>\n",
              "      <th>age</th>\n",
              "      <th>...</th>\n",
              "      <th>cb</th>\n",
              "      <th>rcb</th>\n",
              "      <th>rb</th>\n",
              "      <th>gk</th>\n",
              "      <th>player_face_url</th>\n",
              "      <th>club_logo_url</th>\n",
              "      <th>club_flag_url</th>\n",
              "      <th>nation_logo_url</th>\n",
              "      <th>nation_flag_url</th>\n",
              "      <th>potencial</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>138</th>\n",
              "      <td>235790</td>\n",
              "      <td>https://sofifa.com/player/235790/kai-havertz/2...</td>\n",
              "      <td>K. Havertz</td>\n",
              "      <td>Kai Lukas Havertz</td>\n",
              "      <td>CAM, CF, CM</td>\n",
              "      <td>84</td>\n",
              "      <td>92</td>\n",
              "      <td>94500000.0</td>\n",
              "      <td>130000.0</td>\n",
              "      <td>22</td>\n",
              "      <td>...</td>\n",
              "      <td>55+3</td>\n",
              "      <td>55+3</td>\n",
              "      <td>62+3</td>\n",
              "      <td>17+3</td>\n",
              "      <td>https://cdn.sofifa.net/players/235/790/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/5/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/gb-eng.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/1337/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/de.png</td>\n",
              "      <td>49.751276</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>139</th>\n",
              "      <td>237692</td>\n",
              "      <td>https://sofifa.com/player/237692/phil-foden/22...</td>\n",
              "      <td>P. Foden</td>\n",
              "      <td>Philip Foden</td>\n",
              "      <td>CAM, LW, CM</td>\n",
              "      <td>84</td>\n",
              "      <td>92</td>\n",
              "      <td>94500000.0</td>\n",
              "      <td>125000.0</td>\n",
              "      <td>21</td>\n",
              "      <td>...</td>\n",
              "      <td>59+3</td>\n",
              "      <td>59+3</td>\n",
              "      <td>68+3</td>\n",
              "      <td>19+3</td>\n",
              "      <td>https://cdn.sofifa.net/players/237/692/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/10/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/gb-eng.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/1318/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/gb-eng.png</td>\n",
              "      <td>51.697649</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>193</th>\n",
              "      <td>233064</td>\n",
              "      <td>https://sofifa.com/player/233064/mason-mount/2...</td>\n",
              "      <td>M. Mount</td>\n",
              "      <td>Mason Mount</td>\n",
              "      <td>CAM, CM, RW</td>\n",
              "      <td>83</td>\n",
              "      <td>89</td>\n",
              "      <td>58500000.0</td>\n",
              "      <td>120000.0</td>\n",
              "      <td>22</td>\n",
              "      <td>...</td>\n",
              "      <td>60+3</td>\n",
              "      <td>60+3</td>\n",
              "      <td>68+3</td>\n",
              "      <td>19+3</td>\n",
              "      <td>https://cdn.sofifa.net/players/233/064/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/5/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/gb-eng.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/1318/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/gb-eng.png</td>\n",
              "      <td>60.886335</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>252</th>\n",
              "      <td>220697</td>\n",
              "      <td>https://sofifa.com/player/220697/james-maddiso...</td>\n",
              "      <td>J. Maddison</td>\n",
              "      <td>James Maddison</td>\n",
              "      <td>CAM, CM</td>\n",
              "      <td>82</td>\n",
              "      <td>85</td>\n",
              "      <td>41500000.0</td>\n",
              "      <td>100000.0</td>\n",
              "      <td>24</td>\n",
              "      <td>...</td>\n",
              "      <td>57+2</td>\n",
              "      <td>57+2</td>\n",
              "      <td>65+2</td>\n",
              "      <td>20+2</td>\n",
              "      <td>https://cdn.sofifa.net/players/220/697/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/95/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/gb-eng.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/gb-eng.png</td>\n",
              "      <td>63.118280</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>254</th>\n",
              "      <td>222665</td>\n",
              "      <td>https://sofifa.com/player/222665/martin-odegaa...</td>\n",
              "      <td>M. Ødegaard</td>\n",
              "      <td>Martin Ødegaard</td>\n",
              "      <td>CAM, CM</td>\n",
              "      <td>82</td>\n",
              "      <td>88</td>\n",
              "      <td>49000000.0</td>\n",
              "      <td>89000.0</td>\n",
              "      <td>22</td>\n",
              "      <td>...</td>\n",
              "      <td>60+3</td>\n",
              "      <td>60+3</td>\n",
              "      <td>68+3</td>\n",
              "      <td>19+3</td>\n",
              "      <td>https://cdn.sofifa.net/players/222/665/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/1/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/gb-eng.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/1352/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/no.png</td>\n",
              "      <td>58.224722</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19169</th>\n",
              "      <td>264072</td>\n",
              "      <td>https://sofifa.com/player/264072/bernardo-oliv...</td>\n",
              "      <td>Bernardo</td>\n",
              "      <td>Bernardo Oliveira</td>\n",
              "      <td>CAM</td>\n",
              "      <td>49</td>\n",
              "      <td>67</td>\n",
              "      <td>120000.0</td>\n",
              "      <td>500.0</td>\n",
              "      <td>17</td>\n",
              "      <td>...</td>\n",
              "      <td>39+2</td>\n",
              "      <td>39+2</td>\n",
              "      <td>42+2</td>\n",
              "      <td>14+2</td>\n",
              "      <td>https://cdn.sofifa.net/players/264/072/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/111393/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/au.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/br.png</td>\n",
              "      <td>54.222222</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19171</th>\n",
              "      <td>264142</td>\n",
              "      <td>https://sofifa.com/player/264142/aaron-doran/2...</td>\n",
              "      <td>A. Doran</td>\n",
              "      <td>Aaron Doran</td>\n",
              "      <td>CAM</td>\n",
              "      <td>49</td>\n",
              "      <td>62</td>\n",
              "      <td>110000.0</td>\n",
              "      <td>500.0</td>\n",
              "      <td>18</td>\n",
              "      <td>...</td>\n",
              "      <td>42+2</td>\n",
              "      <td>42+2</td>\n",
              "      <td>44+2</td>\n",
              "      <td>14+2</td>\n",
              "      <td>https://cdn.sofifa.net/players/264/142/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/305/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/ie.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/ie.png</td>\n",
              "      <td>53.611111</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19194</th>\n",
              "      <td>259649</td>\n",
              "      <td>https://sofifa.com/player/259649/engson-singh/...</td>\n",
              "      <td>E. Singh</td>\n",
              "      <td>Engson Singh</td>\n",
              "      <td>CAM, CM</td>\n",
              "      <td>48</td>\n",
              "      <td>65</td>\n",
              "      <td>120000.0</td>\n",
              "      <td>500.0</td>\n",
              "      <td>18</td>\n",
              "      <td>...</td>\n",
              "      <td>37+2</td>\n",
              "      <td>37+2</td>\n",
              "      <td>41+2</td>\n",
              "      <td>12+2</td>\n",
              "      <td>https://cdn.sofifa.net/players/259/649/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/113146/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/in.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/in.png</td>\n",
              "      <td>53.611111</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19233</th>\n",
              "      <td>261818</td>\n",
              "      <td>https://sofifa.com/player/261818/ronan-gallagh...</td>\n",
              "      <td>R. Gallagher</td>\n",
              "      <td>Ronan Gallagher</td>\n",
              "      <td>CAM</td>\n",
              "      <td>47</td>\n",
              "      <td>61</td>\n",
              "      <td>110000.0</td>\n",
              "      <td>500.0</td>\n",
              "      <td>20</td>\n",
              "      <td>...</td>\n",
              "      <td>39+2</td>\n",
              "      <td>39+2</td>\n",
              "      <td>41+2</td>\n",
              "      <td>15+2</td>\n",
              "      <td>https://cdn.sofifa.net/players/261/818/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/111131/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/ie.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/ie.png</td>\n",
              "      <td>53.611111</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19238</th>\n",
              "      <td>264540</td>\n",
              "      <td>https://sofifa.com/player/264540/emanuel-lalch...</td>\n",
              "      <td>E. Lalchhanchhuaha</td>\n",
              "      <td>Emanuel Lalchhanchhuaha</td>\n",
              "      <td>CAM</td>\n",
              "      <td>47</td>\n",
              "      <td>60</td>\n",
              "      <td>110000.0</td>\n",
              "      <td>500.0</td>\n",
              "      <td>19</td>\n",
              "      <td>...</td>\n",
              "      <td>41+2</td>\n",
              "      <td>41+2</td>\n",
              "      <td>45+2</td>\n",
              "      <td>16+2</td>\n",
              "      <td>https://cdn.sofifa.net/players/264/540/22_120.png</td>\n",
              "      <td>https://cdn.sofifa.net/teams/113040/60.png</td>\n",
              "      <td>https://cdn.sofifa.net/flags/in.png</td>\n",
              "      <td>NaN</td>\n",
              "      <td>https://cdn.sofifa.net/flags/in.png</td>\n",
              "      <td>53.379630</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1158 rows × 111 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f766fea5-850a-44bf-bd13-57bdda91790f')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
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              "      const buttonEl =\n",
              "        document.querySelector('#df-f766fea5-850a-44bf-bd13-57bdda91790f button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-f766fea5-850a-44bf-bd13-57bdda91790f');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "\n",
              "\n",
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              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-010f93cb-2482-4b1f-b060-a9b81d7f86c6')\"\n",
              "            title=\"Suggest charts\"\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
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              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
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              "    30% {\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
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              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-010f93cb-2482-4b1f-b060-a9b81d7f86c6 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_376a2921-aa1a-48de-a7eb-7aa9f43b5f45\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
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              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_376a2921-aa1a-48de-a7eb-7aa9f43b5f45 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "       sofifa_id                                         player_url  \\\n",
              "138       235790  https://sofifa.com/player/235790/kai-havertz/2...   \n",
              "139       237692  https://sofifa.com/player/237692/phil-foden/22...   \n",
              "193       233064  https://sofifa.com/player/233064/mason-mount/2...   \n",
              "252       220697  https://sofifa.com/player/220697/james-maddiso...   \n",
              "254       222665  https://sofifa.com/player/222665/martin-odegaa...   \n",
              "...          ...                                                ...   \n",
              "19169     264072  https://sofifa.com/player/264072/bernardo-oliv...   \n",
              "19171     264142  https://sofifa.com/player/264142/aaron-doran/2...   \n",
              "19194     259649  https://sofifa.com/player/259649/engson-singh/...   \n",
              "19233     261818  https://sofifa.com/player/261818/ronan-gallagh...   \n",
              "19238     264540  https://sofifa.com/player/264540/emanuel-lalch...   \n",
              "\n",
              "               short_name                long_name player_positions  overall  \\\n",
              "138            K. Havertz        Kai Lukas Havertz      CAM, CF, CM       84   \n",
              "139              P. Foden             Philip Foden      CAM, LW, CM       84   \n",
              "193              M. Mount              Mason Mount      CAM, CM, RW       83   \n",
              "252           J. Maddison           James Maddison          CAM, CM       82   \n",
              "254           M. Ødegaard          Martin Ødegaard          CAM, CM       82   \n",
              "...                   ...                      ...              ...      ...   \n",
              "19169            Bernardo        Bernardo Oliveira              CAM       49   \n",
              "19171            A. Doran              Aaron Doran              CAM       49   \n",
              "19194            E. Singh             Engson Singh          CAM, CM       48   \n",
              "19233        R. Gallagher          Ronan Gallagher              CAM       47   \n",
              "19238  E. Lalchhanchhuaha  Emanuel Lalchhanchhuaha              CAM       47   \n",
              "\n",
              "       potential   value_eur  wage_eur  age  ...    cb   rcb    rb    gk  \\\n",
              "138           92  94500000.0  130000.0   22  ...  55+3  55+3  62+3  17+3   \n",
              "139           92  94500000.0  125000.0   21  ...  59+3  59+3  68+3  19+3   \n",
              "193           89  58500000.0  120000.0   22  ...  60+3  60+3  68+3  19+3   \n",
              "252           85  41500000.0  100000.0   24  ...  57+2  57+2  65+2  20+2   \n",
              "254           88  49000000.0   89000.0   22  ...  60+3  60+3  68+3  19+3   \n",
              "...          ...         ...       ...  ...  ...   ...   ...   ...   ...   \n",
              "19169         67    120000.0     500.0   17  ...  39+2  39+2  42+2  14+2   \n",
              "19171         62    110000.0     500.0   18  ...  42+2  42+2  44+2  14+2   \n",
              "19194         65    120000.0     500.0   18  ...  37+2  37+2  41+2  12+2   \n",
              "19233         61    110000.0     500.0   20  ...  39+2  39+2  41+2  15+2   \n",
              "19238         60    110000.0     500.0   19  ...  41+2  41+2  45+2  16+2   \n",
              "\n",
              "                                         player_face_url  \\\n",
              "138    https://cdn.sofifa.net/players/235/790/22_120.png   \n",
              "139    https://cdn.sofifa.net/players/237/692/22_120.png   \n",
              "193    https://cdn.sofifa.net/players/233/064/22_120.png   \n",
              "252    https://cdn.sofifa.net/players/220/697/22_120.png   \n",
              "254    https://cdn.sofifa.net/players/222/665/22_120.png   \n",
              "...                                                  ...   \n",
              "19169  https://cdn.sofifa.net/players/264/072/22_120.png   \n",
              "19171  https://cdn.sofifa.net/players/264/142/22_120.png   \n",
              "19194  https://cdn.sofifa.net/players/259/649/22_120.png   \n",
              "19233  https://cdn.sofifa.net/players/261/818/22_120.png   \n",
              "19238  https://cdn.sofifa.net/players/264/540/22_120.png   \n",
              "\n",
              "                                    club_logo_url  \\\n",
              "138         https://cdn.sofifa.net/teams/5/60.png   \n",
              "139        https://cdn.sofifa.net/teams/10/60.png   \n",
              "193         https://cdn.sofifa.net/teams/5/60.png   \n",
              "252        https://cdn.sofifa.net/teams/95/60.png   \n",
              "254         https://cdn.sofifa.net/teams/1/60.png   \n",
              "...                                           ...   \n",
              "19169  https://cdn.sofifa.net/teams/111393/60.png   \n",
              "19171     https://cdn.sofifa.net/teams/305/60.png   \n",
              "19194  https://cdn.sofifa.net/teams/113146/60.png   \n",
              "19233  https://cdn.sofifa.net/teams/111131/60.png   \n",
              "19238  https://cdn.sofifa.net/teams/113040/60.png   \n",
              "\n",
              "                                 club_flag_url  \\\n",
              "138    https://cdn.sofifa.net/flags/gb-eng.png   \n",
              "139    https://cdn.sofifa.net/flags/gb-eng.png   \n",
              "193    https://cdn.sofifa.net/flags/gb-eng.png   \n",
              "252    https://cdn.sofifa.net/flags/gb-eng.png   \n",
              "254    https://cdn.sofifa.net/flags/gb-eng.png   \n",
              "...                                        ...   \n",
              "19169      https://cdn.sofifa.net/flags/au.png   \n",
              "19171      https://cdn.sofifa.net/flags/ie.png   \n",
              "19194      https://cdn.sofifa.net/flags/in.png   \n",
              "19233      https://cdn.sofifa.net/flags/ie.png   \n",
              "19238      https://cdn.sofifa.net/flags/in.png   \n",
              "\n",
              "                                nation_logo_url  \\\n",
              "138    https://cdn.sofifa.net/teams/1337/60.png   \n",
              "139    https://cdn.sofifa.net/teams/1318/60.png   \n",
              "193    https://cdn.sofifa.net/teams/1318/60.png   \n",
              "252                                         NaN   \n",
              "254    https://cdn.sofifa.net/teams/1352/60.png   \n",
              "...                                         ...   \n",
              "19169                                       NaN   \n",
              "19171                                       NaN   \n",
              "19194                                       NaN   \n",
              "19233                                       NaN   \n",
              "19238                                       NaN   \n",
              "\n",
              "                               nation_flag_url  potencial  \n",
              "138        https://cdn.sofifa.net/flags/de.png  49.751276  \n",
              "139    https://cdn.sofifa.net/flags/gb-eng.png  51.697649  \n",
              "193    https://cdn.sofifa.net/flags/gb-eng.png  60.886335  \n",
              "252    https://cdn.sofifa.net/flags/gb-eng.png  63.118280  \n",
              "254        https://cdn.sofifa.net/flags/no.png  58.224722  \n",
              "...                                        ...        ...  \n",
              "19169      https://cdn.sofifa.net/flags/br.png  54.222222  \n",
              "19171      https://cdn.sofifa.net/flags/ie.png  53.611111  \n",
              "19194      https://cdn.sofifa.net/flags/in.png  53.611111  \n",
              "19233      https://cdn.sofifa.net/flags/ie.png  53.611111  \n",
              "19238      https://cdn.sofifa.net/flags/in.png  53.379630  \n",
              "\n",
              "[1158 rows x 111 columns]"
            ]
          },
          "execution_count": 22,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Crea la columna potencial con los datos que hemos calculado"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "a58ebdc3b1442324",
      "metadata": {
        "collapsed": false,
        "id": "a58ebdc3b1442324"
      },
      "source": [
        "## Conclusiones\n",
        "\n",
        "Si observamos los resultados, podemos concluir que nuestro modelo es bastante consistente, incluso si los números no son del todo realistas.\n",
        "¿Cómo podemos mejorar el modelo? Agrega cierta mejora o basate en el trabajo de Luka Radovanović y comenta los resultados."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "c416230c",
      "metadata": {
        "id": "c416230c"
      },
      "outputs": [],
      "source": [
        "# Agrega las celdas de código que necesites"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "a5a04473",
      "metadata": {
        "id": "a5a04473"
      },
      "source": [
        "Agrega también las celdas de markdown que necesites para explicarlo"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "0415ded4",
      "metadata": {
        "id": "0415ded4"
      },
      "source": [
        "# Entrega\n",
        "\n",
        "Una vez completado el Notebook y ejecutado completamente (comprueba que funcionan todas las celdas) y añadidas las mejoras. Envialo a la tarea correspondiente de AULES."
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 2
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      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython2",
      "version": "2.7.6"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}