bundesliga_2005_to_2023_season.ipynb

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      "source": [
        "# BUNDESLIGA - Primera división del Fútbol Alemán 🟡⚫🔴⚽\n",
        "<img src=\"https://is3-ssl.mzstatic.com/image/thumb/Purple126/v4/cc/b0/3b/ccb03bd7-1df2-9de0-7933-9fba47516663/AppIcon-0-1x_U007emarketing-0-7-0-85-220.png/1200x630wa.png\" width=600> <img src=\"https://phantom-marca.unidadeditorial.es/3c1a8c687eb23f3e15aa791fd27b8803/crop/66x47/2046x1160/resize/1200/f/webp/assets/multimedia/imagenes/2022/05/08/16520367037523.jpg\" width=600>"
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      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_bundesliga = pd.read_csv(\"/content/drive/MyDrive/Pandas/Bundesliga_Seasons_2005_06-to-2022_23.csv\")\n",
        "df_bundesliga.head(5)"
      ],
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              "   Unnamed: 0           MATCH_DATE                       LEAGUE_NAME  SEASON  \\\n",
              "0           0  2005-08-05 20:30:00  1. Fussball-Bundesliga 2005/2006    2005   \n",
              "1           1  2005-08-06 15:30:00  1. Fussball-Bundesliga 2005/2006    2005   \n",
              "2           2  2005-08-06 15:30:00  1. Fussball-Bundesliga 2005/2006    2005   \n",
              "3           3  2005-08-06 15:30:00  1. Fussball-Bundesliga 2005/2006    2005   \n",
              "4           4  2005-08-06 15:30:00  1. Fussball-Bundesliga 2005/2006    2005   \n",
              "\n",
              "  LEAGUE  FINISHED   LOCATION  VIEWER     MATCHDAY  MATCHDAY_NR  ...  \\\n",
              "0    bl1      True    München     NaN  1. Spieltag            1  ...   \n",
              "1    bl1      True       Köln     NaN  1. Spieltag            1  ...   \n",
              "2    bl1      True   Duisburg     NaN  1. Spieltag            1  ...   \n",
              "3    bl1      True    Hamburg     NaN  1. Spieltag            1  ...   \n",
              "4    bl1      True  Wolfsburg     NaN  1. Spieltag            1  ...   \n",
              "\n",
              "                                           HOME_ICON AWAY_TEAM_ID  \\\n",
              "0                    https://i.imgur.com/jJEsJrj.png           87   \n",
              "1  https://upload.wikimedia.org/wikipedia/en/thum...           81   \n",
              "2  https://upload.wikimedia.org/wikipedia/en/c/c8...           16   \n",
              "3  https://upload.wikimedia.org/wikipedia/commons...           79   \n",
              "4                    https://i.imgur.com/ucqKV4B.png            7   \n",
              "\n",
              "             AWAY_TEAM_NAME  AWAY_TEAM  \\\n",
              "0  Borussia Mönchengladbach   Gladbach   \n",
              "1           1. FSV Mainz 05      Mainz   \n",
              "2             VfB Stuttgart  Stuttgart   \n",
              "3            1. FC Nürnberg   Nürnberg   \n",
              "4         Borussia Dortmund        BVB   \n",
              "\n",
              "                                           AWAY_ICON GOALS_HOME GOALS_AWAY  \\\n",
              "0                    https://i.imgur.com/KSIk0Eu.png          3          0   \n",
              "1  https://upload.wikimedia.org/wikipedia/commons...          1          0   \n",
              "2                    https://i.imgur.com/v0tkpNx.png          1          1   \n",
              "3  https://upload.wikimedia.org/wikipedia/commons...          3          0   \n",
              "4  https://upload.wikimedia.org/wikipedia/commons...          2          2   \n",
              "\n",
              "  DRAW  WIN_HOME  WIN_AWAY  \n",
              "0  0.0       1.0       0.0  \n",
              "1  0.0       1.0       0.0  \n",
              "2  1.0       0.0       0.0  \n",
              "3  0.0       1.0       0.0  \n",
              "4  1.0       0.0       0.0  \n",
              "\n",
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              "      <td>81</td>\n",
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              "      <td>1. Fussball-Bundesliga 2005/2006</td>\n",
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          "metadata": {},
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    },
    {
      "cell_type": "markdown",
      "source": [
        "## Información del dataFrame"
      ],
      "metadata": {
        "id": "iA4vr6Oe1L-E"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_bundesliga.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "u17zkJWO1Rub",
        "outputId": "8935e560-c485-40bb-f867-4e236fbe9632"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 5508 entries, 0 to 5507\n",
            "Data columns (total 23 columns):\n",
            " #   Column          Non-Null Count  Dtype  \n",
            "---  ------          --------------  -----  \n",
            " 0   Unnamed: 0      5508 non-null   int64  \n",
            " 1   MATCH_DATE      5508 non-null   object \n",
            " 2   LEAGUE_NAME     5508 non-null   object \n",
            " 3   SEASON          5508 non-null   int64  \n",
            " 4   LEAGUE          5508 non-null   object \n",
            " 5   FINISHED        5508 non-null   bool   \n",
            " 6   LOCATION        5508 non-null   object \n",
            " 7   VIEWER          1682 non-null   float64\n",
            " 8   MATCHDAY        5508 non-null   object \n",
            " 9   MATCHDAY_NR     5508 non-null   int64  \n",
            " 10  HOME_TEAM_ID    5508 non-null   int64  \n",
            " 11  HOME_TEAM_NAME  5508 non-null   object \n",
            " 12  HOME_TEAM       5508 non-null   object \n",
            " 13  HOME_ICON       5508 non-null   object \n",
            " 14  AWAY_TEAM_ID    5508 non-null   int64  \n",
            " 15  AWAY_TEAM_NAME  5508 non-null   object \n",
            " 16  AWAY_TEAM       5474 non-null   object \n",
            " 17  AWAY_ICON       5508 non-null   object \n",
            " 18  GOALS_HOME      5508 non-null   int64  \n",
            " 19  GOALS_AWAY      5508 non-null   int64  \n",
            " 20  DRAW            5508 non-null   float64\n",
            " 21  WIN_HOME        5508 non-null   float64\n",
            " 22  WIN_AWAY        5508 non-null   float64\n",
            "dtypes: bool(1), float64(4), int64(7), object(11)\n",
            "memory usage: 952.2+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('La forma del dataFrame es de',df_bundesliga.shape)\n",
        "print(f'Tiene {df_bundesliga.shape[0]} filas y {df_bundesliga.shape[1]} columnas')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xzXliq3NowAy",
        "outputId": "8766abfc-22d5-487f-8e48-dc74e7dee19b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "La forma del dataFrame es de (5508, 20)\n",
            "Tiene 5508 filas y 20 columnas\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_bundesliga.columns"
      ],
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        },
        "id": "AqefXzjMAjfu",
        "outputId": "c895558a-3cfd-453b-c81f-c5d0a5448d2f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Unnamed: 0', 'MATCH_DATE', 'LEAGUE_NAME', 'SEASON', 'LEAGUE',\n",
              "       'FINISHED', 'LOCATION', 'VIEWER', 'MATCHDAY', 'MATCHDAY_NR',\n",
              "       'HOME_TEAM_ID', 'HOME_TEAM_NAME', 'HOME_TEAM', 'HOME_ICON',\n",
              "       'AWAY_TEAM_ID', 'AWAY_TEAM_NAME', 'AWAY_TEAM', 'AWAY_ICON',\n",
              "       'GOALS_HOME', 'GOALS_AWAY', 'DRAW', 'WIN_HOME', 'WIN_AWAY'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_bundesliga.memory_usage(deep=True)"
      ],
      "metadata": {
        "colab": {
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        },
        "id": "-MHXbSsA1wRH",
        "outputId": "948ada5f-1cf1-4676-ed91-40bc02c51779"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index                128\n",
              "MATCH_DATE        418608\n",
              "LEAGUE_NAME       560592\n",
              "SEASON             44064\n",
              "LEAGUE            330480\n",
              "FINISHED            5508\n",
              "LOCATION          376023\n",
              "VIEWER             44064\n",
              "MATCHDAY          378594\n",
              "MATCHDAY_NR        44064\n",
              "HOME_TEAM_ID       44064\n",
              "HOME_TEAM_NAME    420002\n",
              "HOME_TEAM         365177\n",
              "AWAY_TEAM_ID       44064\n",
              "AWAY_TEAM_NAME    420002\n",
              "AWAY_TEAM         363987\n",
              "GOALS_HOME         44064\n",
              "GOALS_AWAY         44064\n",
              "DRAW               44064\n",
              "WIN_HOME           44064\n",
              "WIN_AWAY           44064\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Limpiar el DataFrame.\n",
        "Eliminaremos la columna Unnamed ya que solo almacena el índice, otras columnas que vamos a eliminar son *'HOME_ICON'y 'AWAY_ICON'* ya que almacena los enlaces URL de los escudos de los equipos locales y visitantes. Las columnas se eliminaran del dataFrame."
      ],
      "metadata": {
        "id": "f0K8XbYkBmTt"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_bundesliga.drop(['Unnamed: 0','HOME_ICON','AWAY_ICON'],axis=1,inplace=True)"
      ],
      "metadata": {
        "id": "fhlqbAHoAwNq"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_bundesliga.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hLXUo1iLCyWM",
        "outputId": "8e05187f-83c1-4011-b323-20344432232d"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['MATCH_DATE', 'LEAGUE_NAME', 'SEASON', 'LEAGUE', 'FINISHED', 'LOCATION',\n",
              "       'VIEWER', 'MATCHDAY', 'MATCHDAY_NR', 'HOME_TEAM_ID', 'HOME_TEAM_NAME',\n",
              "       'HOME_TEAM', 'AWAY_TEAM_ID', 'AWAY_TEAM_NAME', 'AWAY_TEAM',\n",
              "       'GOALS_HOME', 'GOALS_AWAY', 'DRAW', 'WIN_HOME', 'WIN_AWAY',\n",
              "       'HOME_POINTS', 'AWAY_POINTS'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_bundesliga.tail(3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 311
        },
        "id": "xMufKl_lC6uf",
        "outputId": "2b13f381-f23d-437d-f295-54795e01bcc3"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               MATCH_DATE                      LEAGUE_NAME  SEASON LEAGUE  \\\n",
              "5505  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5506  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5507  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "\n",
              "      FINISHED   LOCATION  VIEWER      MATCHDAY  MATCHDAY_NR  HOME_TEAM_ID  \\\n",
              "5505      True  Stuttgart     NaN  34. Spieltag           34            16   \n",
              "5506      True     Berlin     NaN  34. Spieltag           34            80   \n",
              "5507      True  Wolfsburg     NaN  34. Spieltag           34           131   \n",
              "\n",
              "          HOME_TEAM_NAME     HOME_TEAM  AWAY_TEAM_ID       AWAY_TEAM_NAME  \\\n",
              "5505       VfB Stuttgart     Stuttgart           175  TSG 1899 Hoffenheim   \n",
              "5506  1. FC Union Berlin  Union Berlin           134        Werder Bremen   \n",
              "5507       VfL Wolfsburg     Wolfsburg            54           Hertha BSC   \n",
              "\n",
              "       AWAY_TEAM  GOALS_HOME  GOALS_AWAY  DRAW  WIN_HOME  WIN_AWAY  \n",
              "5505  Hoffenheim           1           1   1.0       0.0       0.0  \n",
              "5506      Bremen           1           0   0.0       1.0       0.0  \n",
              "5507      Hertha           1           2   0.0       0.0       1.0  "
            ],
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              "      <th>5505</th>\n",
              "      <td>2023-05-27 15:30:00</td>\n",
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              "      <th>5506</th>\n",
              "      <td>2023-05-27 15:30:00</td>\n",
              "      <td>1. Fußball-Bundesliga 2022/2023</td>\n",
              "      <td>2022</td>\n",
              "      <td>bl1</td>\n",
              "      <td>True</td>\n",
              "      <td>Berlin</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34. Spieltag</td>\n",
              "      <td>34</td>\n",
              "      <td>80</td>\n",
              "      <td>1. FC Union Berlin</td>\n",
              "      <td>Union Berlin</td>\n",
              "      <td>134</td>\n",
              "      <td>Werder Bremen</td>\n",
              "      <td>Bremen</td>\n",
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              "    <tr>\n",
              "      <th>5507</th>\n",
              "      <td>2023-05-27 15:30:00</td>\n",
              "      <td>1. Fußball-Bundesliga 2022/2023</td>\n",
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              "      <td>Wolfsburg</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34. Spieltag</td>\n",
              "      <td>34</td>\n",
              "      <td>131</td>\n",
              "      <td>VfL Wolfsburg</td>\n",
              "      <td>Wolfsburg</td>\n",
              "      <td>54</td>\n",
              "      <td>Hertha BSC</td>\n",
              "      <td>Hertha</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0.0</td>\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
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              "          const element = document.querySelector('#df-00c12842-410e-4665-89ee-cd1f75d9446b');\n",
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              "            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",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Filtrando algunas columnas y filas"
      ],
      "metadata": {
        "id": "tNUxTYUejRr_"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **1. Filtrando solo los datos de la temporada 2022 y algunas columnas importantes**."
      ],
      "metadata": {
        "id": "TXYH2onSmD8E"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "<img src=\"https://mibundesliga.com/wp-content/uploads/2022/06/MiBundesliga-Twitter-4.png\" width=600>"
      ],
      "metadata": {
        "id": "K7istRsgaBHY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_bundesliga.loc[5202:5507,['SEASON','MATCHDAY_NR','HOME_TEAM','AWAY_TEAM','DRAW','WIN_HOME','WIN_AWAY']]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "7s3r7nYDjVCH",
        "outputId": "763f807d-37fc-404e-872c-fb589740ee0a"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      SEASON  MATCHDAY_NR     HOME_TEAM   AWAY_TEAM  DRAW  WIN_HOME  WIN_AWAY\n",
              "5202    2022            1     Frankfurt      Bayern   0.0       0.0       1.0\n",
              "5203    2022            1      Augsburg    Freiburg   0.0       0.0       1.0\n",
              "5204    2022            1        Bochum       Mainz   0.0       0.0       1.0\n",
              "5205    2022            1      Gladbach  Hoffenheim   0.0       1.0       0.0\n",
              "5206    2022            1  Union Berlin      Hertha   0.0       1.0       0.0\n",
              "...      ...          ...           ...         ...   ...       ...       ...\n",
              "5503    2022           34          Köln      Bayern   0.0       0.0       1.0\n",
              "5504    2022           34       Leipzig     Schalke   0.0       1.0       0.0\n",
              "5505    2022           34     Stuttgart  Hoffenheim   1.0       0.0       0.0\n",
              "5506    2022           34  Union Berlin      Bremen   0.0       1.0       0.0\n",
              "5507    2022           34     Wolfsburg      Hertha   0.0       0.0       1.0\n",
              "\n",
              "[306 rows x 7 columns]"
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              "      <th>5204</th>\n",
              "      <td>2022</td>\n",
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              "      <th>5206</th>\n",
              "      <td>2022</td>\n",
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              "      <td>Hertha</td>\n",
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              "      <td>1.0</td>\n",
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              "      <td>Bayern</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
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              "    <tr>\n",
              "      <th>5504</th>\n",
              "      <td>2022</td>\n",
              "      <td>34</td>\n",
              "      <td>Leipzig</td>\n",
              "      <td>Schalke</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5505</th>\n",
              "      <td>2022</td>\n",
              "      <td>34</td>\n",
              "      <td>Stuttgart</td>\n",
              "      <td>Hoffenheim</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>5506</th>\n",
              "      <td>2022</td>\n",
              "      <td>34</td>\n",
              "      <td>Union Berlin</td>\n",
              "      <td>Bremen</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>5507</th>\n",
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              "      <td>Hertha</td>\n",
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              "      <td>1.0</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>306 rows × 7 columns</p>\n",
              "</div>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_filtrar_por_temporada = df_bundesliga['SEASON'] == 2022\n",
        "df_bundesliga[df_filtrar_por_temporada]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 834
        },
        "id": "YZ73c34Ds3DU",
        "outputId": "666ef1d5-b8e2-4dbf-cc0c-2d3de92cff05"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               MATCH_DATE                      LEAGUE_NAME  SEASON LEAGUE  \\\n",
              "5202  2022-08-05 20:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5203  2022-08-06 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5204  2022-08-06 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5205  2022-08-06 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5206  2022-08-06 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "...                   ...                              ...     ...    ...   \n",
              "5503  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5504  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5505  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5506  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5507  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "\n",
              "      FINISHED   LOCATION  VIEWER      MATCHDAY  MATCHDAY_NR  HOME_TEAM_ID  \\\n",
              "5202      True  Frankfurt     NaN   1. Spieltag            1            91   \n",
              "5203      True   Augsburg     NaN   1. Spieltag            1            95   \n",
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              "5205      True   Gladbach     NaN   1. Spieltag            1            87   \n",
              "5206      True     Berlin     NaN   1. Spieltag            1            80   \n",
              "...        ...        ...     ...           ...          ...           ...   \n",
              "5503      True       Köln     NaN  34. Spieltag           34            65   \n",
              "5504      True    Leipzig     NaN  34. Spieltag           34          1635   \n",
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              "5506      True     Berlin     NaN  34. Spieltag           34            80   \n",
              "5507      True  Wolfsburg     NaN  34. Spieltag           34           131   \n",
              "\n",
              "                HOME_TEAM_NAME     HOME_TEAM  AWAY_TEAM_ID  \\\n",
              "5202       Eintracht Frankfurt     Frankfurt            40   \n",
              "5203               FC Augsburg      Augsburg           112   \n",
              "5204                VfL Bochum        Bochum            81   \n",
              "5205  Borussia Mönchengladbach      Gladbach           175   \n",
              "5206        1. FC Union Berlin  Union Berlin            54   \n",
              "...                        ...           ...           ...   \n",
              "5503                1. FC Köln          Köln            40   \n",
              "5504                RB Leipzig       Leipzig             9   \n",
              "5505             VfB Stuttgart     Stuttgart           175   \n",
              "5506        1. FC Union Berlin  Union Berlin           134   \n",
              "5507             VfL Wolfsburg     Wolfsburg            54   \n",
              "\n",
              "           AWAY_TEAM_NAME   AWAY_TEAM  GOALS_HOME  GOALS_AWAY  DRAW  WIN_HOME  \\\n",
              "5202    FC Bayern München      Bayern           1           6   0.0       0.0   \n",
              "5203          SC Freiburg    Freiburg           0           4   0.0       0.0   \n",
              "5204      1. FSV Mainz 05       Mainz           1           2   0.0       0.0   \n",
              "5205  TSG 1899 Hoffenheim  Hoffenheim           3           1   0.0       1.0   \n",
              "5206           Hertha BSC      Hertha           3           1   0.0       1.0   \n",
              "...                   ...         ...         ...         ...   ...       ...   \n",
              "5503    FC Bayern München      Bayern           1           2   0.0       0.0   \n",
              "5504        FC Schalke 04     Schalke           4           2   0.0       1.0   \n",
              "5505  TSG 1899 Hoffenheim  Hoffenheim           1           1   1.0       0.0   \n",
              "5506        Werder Bremen      Bremen           1           0   0.0       1.0   \n",
              "5507           Hertha BSC      Hertha           1           2   0.0       0.0   \n",
              "\n",
              "      WIN_AWAY  \n",
              "5202       1.0  \n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-45fcfb1c-8e86-4b1d-a7bd-0973c18818c8')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
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            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**2. Filtrando a equipos que perdieron de locales en la primera jornada de la Bundesliga en la temporada 2022**."
      ],
      "metadata": {
        "id": "HnhYIyX2njWr"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "<img src = https://mibundesliga.com/wp-content/uploads/2023/05/fbl-ger-bundesliga-leipzig-schalke-scaled.jpg width = 600>"
      ],
      "metadata": {
        "id": "6KUElfCQaYb2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_noWinHome = (df_bundesliga['SEASON'] == 2022) & (df_bundesliga['WIN_HOME'] == 0) & (df_bundesliga['MATCHDAY_NR'] == 1)\n",
        "df_equipo = df_bundesliga[df_noWinHome][['MATCH_DATE','SEASON','MATCHDAY_NR','LOCATION','HOME_TEAM_NAME','AWAY_TEAM_NAME','GOALS_HOME','GOALS_AWAY']]\n",
        "df_equipo"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "mo-bFHdCtOiX",
        "outputId": "5afad567-a121-4a87-affd-8cbe5da3efb9"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               MATCH_DATE  SEASON  MATCHDAY_NR   LOCATION  \\\n",
              "5202  2022-08-05 20:30:00    2022            1  Frankfurt   \n",
              "5203  2022-08-06 15:30:00    2022            1   Augsburg   \n",
              "5204  2022-08-06 15:30:00    2022            1     Bochum   \n",
              "5207  2022-08-06 15:30:00    2022            1  Wolfsburg   \n",
              "5209  2022-08-07 15:30:00    2022            1  Stuttgart   \n",
              "\n",
              "           HOME_TEAM_NAME     AWAY_TEAM_NAME  GOALS_HOME  GOALS_AWAY  \n",
              "5202  Eintracht Frankfurt  FC Bayern München           1           6  \n",
              "5203          FC Augsburg        SC Freiburg           0           4  \n",
              "5204           VfL Bochum    1. FSV Mainz 05           1           2  \n",
              "5207        VfL Wolfsburg      Werder Bremen           2           2  \n",
              "5209        VfB Stuttgart         RB Leipzig           1           1  "
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              "      <th>5204</th>\n",
              "      <td>2022-08-06 15:30:00</td>\n",
              "      <td>2022</td>\n",
              "      <td>1</td>\n",
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              "      <td>VfL Wolfsburg</td>\n",
              "      <td>Werder Bremen</td>\n",
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              "      <th>5209</th>\n",
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              "      <td>2022</td>\n",
              "      <td>1</td>\n",
              "      <td>Stuttgart</td>\n",
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              "      <td>RB Leipzig</td>\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
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          },
          "metadata": {},
          "execution_count": 49
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      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**3. Filtrar las veces que se han jugado en las ciudades alemanas durante la temporada 2005 hasta la temporada 2023.**"
      ],
      "metadata": {
        "id": "ifYqmQeqmgKt"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "<img src = https://as01.epimg.net/futbol/imagenes/2016/07/21/internacional/1469104398_393634_1469104582_noticia_normal.jpg width = 500>\n",
        "<img src = https://e00-expansion.uecdn.es/assets/multimedia/imagenes/2016/07/28/14697188549244.jpg width = 500>\n",
        "\n"
      ],
      "metadata": {
        "id": "SpqfmaG-bK5G"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_location_count = pd.DataFrame(df_bundesliga['LOCATION'].value_counts())\n",
        "df_location_count = df_location_count.reset_index().rename(columns={'index':'LOCATION','LOCATION':'COUNT'})\n",
        "df_location_count"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "8vBNOD7LmRbz",
        "outputId": "8da88f7f-0b0f-4c30-ecee-9c9404ce76f2"
      },
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          LOCATION  COUNT\n",
              "0           Berlin    340\n",
              "1          München    306\n",
              "2        Wolfsburg    306\n",
              "3         Dortmund    306\n",
              "4       Leverkusen    306\n",
              "5         Gladbach    289\n",
              "6           Bremen    289\n",
              "7    Gelsenkirchen    289\n",
              "8        Frankfurt    289\n",
              "9            Mainz    272\n",
              "10       Stuttgart    272\n",
              "11        Sinsheim    255\n",
              "12         Hamburg    238\n",
              "13        Hannover    221\n",
              "14        Freiburg    221\n",
              "15            Köln    221\n",
              "16        Augsburg    204\n",
              "17        Nürnberg    153\n",
              "18         Leipzig    119\n",
              "19          Bochum    102\n",
              "20       Bielefeld    102\n",
              "21         Cottbus     51\n",
              "22  Kaiserslautern     51\n",
              "23      Düsseldorf     51\n",
              "24       Karlsruhe     34\n",
              "25        Duisburg     34\n",
              "26           Fürth     34\n",
              "27       Paderborn     34\n",
              "28       Darmstadt     34\n",
              "29      Ingolstadt     34\n",
              "30          Aachen     17\n",
              "31    Braunschweig     17\n",
              "32         Rostock     17"
            ],
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              "\n",
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              "      <td>153</td>\n",
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              "      <th>18</th>\n",
              "      <td>Leipzig</td>\n",
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              "      <th>20</th>\n",
              "      <td>Bielefeld</td>\n",
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              "      <th>21</th>\n",
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              "      <th>23</th>\n",
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              "      <td>51</td>\n",
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              "      <th>24</th>\n",
              "      <td>Karlsruhe</td>\n",
              "      <td>34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>Duisburg</td>\n",
              "      <td>34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>Fürth</td>\n",
              "      <td>34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>Paderborn</td>\n",
              "      <td>34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Darmstadt</td>\n",
              "      <td>34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>Ingolstadt</td>\n",
              "      <td>34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>Aachen</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>Braunschweig</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>Rostock</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
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          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###4.Filtrar el rendimiento del Borussia Dortmund en las últimas 5 jornadas desde la temporada 2005 a la temporada 2022"
      ],
      "metadata": {
        "id": "CjNaV2dIgKAT"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "<img src = https://assets-es.imgfoot.com/erling-haaland-bvb-2021.jpg width = 600>"
      ],
      "metadata": {
        "id": "Zu54NrcMb9zp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_bvd_final_season = df_bundesliga[(df_bundesliga['MATCHDAY_NR'] >= 30) & (df_bundesliga['MATCHDAY_NR'] <= 34) ].loc[(df_bundesliga.HOME_TEAM_NAME == 'Borussia Dortmund') | (df_bundesliga.AWAY_TEAM_NAME == 'Borussia Dortmund')]\n",
        "df_bvd_final_season"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 834
        },
        "id": "d2Ui6Vk2Na_5",
        "outputId": "0f216425-96f3-482d-c9d1-c2b1b548573f"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               MATCH_DATE                       LEAGUE_NAME  SEASON LEAGUE  \\\n",
              "263   2006-04-15 15:30:00  1. Fussball-Bundesliga 2005/2006    2005    bl1   \n",
              "274   2006-04-22 15:30:00  1. Fussball-Bundesliga 2005/2006    2005    bl1   \n",
              "281   2006-05-02 20:00:00  1. Fussball-Bundesliga 2005/2006    2005    bl1   \n",
              "295   2006-05-06 15:30:00  1. Fussball-Bundesliga 2005/2006    2005    bl1   \n",
              "299   2006-05-13 15:30:00  1. Fussball-Bundesliga 2005/2006    2005    bl1   \n",
              "...                   ...                               ...     ...    ...   \n",
              "5463  2023-04-28 20:30:00   1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5480  2023-05-07 17:30:00   1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5487  2023-05-13 18:30:00   1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5497  2023-05-21 17:30:00   1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5500  2023-05-27 15:30:00   1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "\n",
              "      FINISHED  LOCATION  VIEWER      MATCHDAY  MATCHDAY_NR  HOME_TEAM_ID  \\\n",
              "263       True    Berlin     NaN  30. Spieltag           30            54   \n",
              "274       True  Dortmund     NaN  31. Spieltag           31             7   \n",
              "281       True  Hannover     NaN  32. Spieltag           32            55   \n",
              "295       True  Dortmund     NaN  33. Spieltag           33             7   \n",
              "299       True   München     NaN  34. Spieltag           34            40   \n",
              "...        ...       ...     ...           ...          ...           ...   \n",
              "5463      True    Bochum     NaN  30. Spieltag           30           129   \n",
              "5480      True  Dortmund     NaN  31. Spieltag           31             7   \n",
              "5487      True  Dortmund     NaN  32. Spieltag           32             7   \n",
              "5497      True  Augsburg     NaN  33. Spieltag           33            95   \n",
              "5500      True  Dortmund     NaN  34. Spieltag           34             7   \n",
              "\n",
              "         HOME_TEAM_NAME HOME_TEAM  AWAY_TEAM_ID            AWAY_TEAM_NAME  \\\n",
              "263          Hertha BSC    Hertha             7         Borussia Dortmund   \n",
              "274   Borussia Dortmund       BVB            79            1. FC Nürnberg   \n",
              "281         Hannover 96  Hannover             7         Borussia Dortmund   \n",
              "295   Borussia Dortmund       BVB            91       Eintracht Frankfurt   \n",
              "299   FC Bayern München    Bayern             7         Borussia Dortmund   \n",
              "...                 ...       ...           ...                       ...   \n",
              "5463         VfL Bochum    Bochum             7         Borussia Dortmund   \n",
              "5480  Borussia Dortmund       BVB           131             VfL Wolfsburg   \n",
              "5487  Borussia Dortmund       BVB            87  Borussia Mönchengladbach   \n",
              "5497        FC Augsburg  Augsburg             7         Borussia Dortmund   \n",
              "5500  Borussia Dortmund       BVB            81           1. FSV Mainz 05   \n",
              "\n",
              "      AWAY_TEAM  GOALS_HOME  GOALS_AWAY  DRAW  WIN_HOME  WIN_AWAY  \n",
              "263         BVB           0           0   1.0       0.0       0.0  \n",
              "274    Nürnberg           2           1   0.0       1.0       0.0  \n",
              "281         BVB           1           2   0.0       0.0       1.0  \n",
              "295   Frankfurt           1           1   1.0       0.0       0.0  \n",
              "299         BVB           3           3   1.0       0.0       0.0  \n",
              "...         ...         ...         ...   ...       ...       ...  \n",
              "5463        BVB           1           1   1.0       0.0       0.0  \n",
              "5480  Wolfsburg           6           0   0.0       1.0       0.0  \n",
              "5487   Gladbach           5           2   0.0       1.0       0.0  \n",
              "5497        BVB           0           3   0.0       0.0       1.0  \n",
              "5500      Mainz           2           2   1.0       0.0       0.0  \n",
              "\n",
              "[90 rows x 20 columns]"
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              "      <th></th>\n",
              "      <th>MATCH_DATE</th>\n",
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              "      <th>263</th>\n",
              "      <td>2006-04-15 15:30:00</td>\n",
              "      <td>1. Fussball-Bundesliga 2005/2006</td>\n",
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              "      <td>30</td>\n",
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              "      <td>Borussia Dortmund</td>\n",
              "      <td>BVB</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
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              "    <tr>\n",
              "      <th>274</th>\n",
              "      <td>2006-04-22 15:30:00</td>\n",
              "      <td>1. Fussball-Bundesliga 2005/2006</td>\n",
              "      <td>2005</td>\n",
              "      <td>bl1</td>\n",
              "      <td>True</td>\n",
              "      <td>Dortmund</td>\n",
              "      <td>NaN</td>\n",
              "      <td>31. Spieltag</td>\n",
              "      <td>31</td>\n",
              "      <td>7</td>\n",
              "      <td>Borussia Dortmund</td>\n",
              "      <td>BVB</td>\n",
              "      <td>79</td>\n",
              "      <td>1. FC Nürnberg</td>\n",
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              "      <th>281</th>\n",
              "      <td>2006-05-02 20:00:00</td>\n",
              "      <td>1. Fussball-Bundesliga 2005/2006</td>\n",
              "      <td>2005</td>\n",
              "      <td>bl1</td>\n",
              "      <td>True</td>\n",
              "      <td>Hannover</td>\n",
              "      <td>NaN</td>\n",
              "      <td>32. Spieltag</td>\n",
              "      <td>32</td>\n",
              "      <td>55</td>\n",
              "      <td>Hannover 96</td>\n",
              "      <td>Hannover</td>\n",
              "      <td>7</td>\n",
              "      <td>Borussia Dortmund</td>\n",
              "      <td>BVB</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>2006-05-06 15:30:00</td>\n",
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              "      <td>2005</td>\n",
              "      <td>bl1</td>\n",
              "      <td>True</td>\n",
              "      <td>Dortmund</td>\n",
              "      <td>NaN</td>\n",
              "      <td>33. Spieltag</td>\n",
              "      <td>33</td>\n",
              "      <td>7</td>\n",
              "      <td>Borussia Dortmund</td>\n",
              "      <td>BVB</td>\n",
              "      <td>91</td>\n",
              "      <td>Eintracht Frankfurt</td>\n",
              "      <td>Frankfurt</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
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              "      <td>0.0</td>\n",
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              "      <td>2006-05-13 15:30:00</td>\n",
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              "      <td>2005</td>\n",
              "      <td>bl1</td>\n",
              "      <td>True</td>\n",
              "      <td>München</td>\n",
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              "      <td>34. Spieltag</td>\n",
              "      <td>34</td>\n",
              "      <td>40</td>\n",
              "      <td>FC Bayern München</td>\n",
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              "      <td>32</td>\n",
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              "      <td>Borussia Dortmund</td>\n",
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              "      <td>87</td>\n",
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              "      <td>2023-05-21 17:30:00</td>\n",
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              "      <td>bl1</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>33. Spieltag</td>\n",
              "      <td>33</td>\n",
              "      <td>95</td>\n",
              "      <td>FC Augsburg</td>\n",
              "      <td>Augsburg</td>\n",
              "      <td>7</td>\n",
              "      <td>Borussia Dortmund</td>\n",
              "      <td>BVB</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5500</th>\n",
              "      <td>2023-05-27 15:30:00</td>\n",
              "      <td>1. Fußball-Bundesliga 2022/2023</td>\n",
              "      <td>2022</td>\n",
              "      <td>bl1</td>\n",
              "      <td>True</td>\n",
              "      <td>Dortmund</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34. Spieltag</td>\n",
              "      <td>34</td>\n",
              "      <td>7</td>\n",
              "      <td>Borussia Dortmund</td>\n",
              "      <td>BVB</td>\n",
              "      <td>81</td>\n",
              "      <td>1. FSV Mainz 05</td>\n",
              "      <td>Mainz</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>90 rows × 20 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-435e97ee-fc9b-497c-b5eb-41be4960df87')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "    .colab-df-container {\n",
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              "    .colab-df-convert {\n",
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              "      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",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\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-435e97ee-fc9b-497c-b5eb-41be4960df87 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-435e97ee-fc9b-497c-b5eb-41be4960df87');\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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###5.Estadística de goles, partidos empatados, victorias de local y visitante"
      ],
      "metadata": {
        "id": "83q3C_dXnNMG"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "<img src=\"https://upload.wikimedia.org/wikipedia/en/thumb/d/df/Bundesliga_logo_%282017%29.svg/1200px-Bundesliga_logo_%282017%29.svg.png\" width=300>"
      ],
      "metadata": {
        "id": "a9m-hwtEdMDL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_bundesliga.groupby('SEASON').agg({'GOALS_HOME':['sum','mean'],\n",
        "                                     'GOALS_AWAY':['sum','mean'],\n",
        "                                     'DRAW':'sum',\n",
        "                                     'WIN_HOME':'sum',\n",
        "                                     'WIN_AWAY':'sum'\n",
        "                                     })"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "rGPPa-Ojj-4Q",
        "outputId": "b4a670ed-f191-4a4d-b32f-48d583bb72a4"
      },
      "execution_count": 152,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       GOALS_HOME           GOALS_AWAY             DRAW WIN_HOME WIN_AWAY\n",
              "              sum      mean        sum      mean    sum      sum      sum\n",
              "SEASON                                                                   \n",
              "2005          492  1.607843        369  1.205882   96.0    131.0     79.0\n",
              "2006          448  1.464052        389  1.271242   79.0    134.0     93.0\n",
              "2007          511  1.669935        349  1.140523   78.0    143.0     85.0\n",
              "2008          520  1.699346        374  1.222222   74.0    147.0     85.0\n",
              "2009          463  1.513072        403  1.316993   86.0    125.0     95.0\n",
              "2010          504  1.647059        390  1.274510   63.0    141.0    102.0\n",
              "2011          508  1.660131        367  1.199346   79.0    139.0     88.0\n",
              "2012          487  1.591503        411  1.343137   78.0    130.0     98.0\n",
              "2013          535  1.748366        432  1.411765   64.0    145.0     97.0\n",
              "2014          486  1.588235        357  1.166667   82.0    145.0     79.0\n",
              "2015          209  0.683007        168  0.549020  125.0    100.0     81.0\n",
              "2016          226  0.738562        154  0.503268  132.0    116.0     58.0\n",
              "2017          232  0.758170        150  0.490196  109.0    127.0     70.0\n",
              "2018          230  0.751634        174  0.568627  118.0    106.0     82.0\n",
              "2019          209  0.683007        204  0.666667  109.0     99.0     98.0\n",
              "2020          513  1.676471        415  1.356209   81.0    129.0     96.0\n",
              "2021          539  1.761438        415  1.356209   73.0    143.0     90.0\n",
              "2022          568  1.856209        403  1.316993   75.0    145.0     86.0"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-09934c7f-1a59-4cd6-8ed2-c95921622eb6\">\n",
              "    <div 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 tr th {\n",
              "        text-align: left;\n",
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              "\n",
              "    .dataframe thead tr:last-of-type th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th colspan=\"2\" halign=\"left\">GOALS_HOME</th>\n",
              "      <th colspan=\"2\" halign=\"left\">GOALS_AWAY</th>\n",
              "      <th>DRAW</th>\n",
              "      <th>WIN_HOME</th>\n",
              "      <th>WIN_AWAY</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>sum</th>\n",
              "      <th>mean</th>\n",
              "      <th>sum</th>\n",
              "      <th>mean</th>\n",
              "      <th>sum</th>\n",
              "      <th>sum</th>\n",
              "      <th>sum</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SEASON</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2005</th>\n",
              "      <td>492</td>\n",
              "      <td>1.607843</td>\n",
              "      <td>369</td>\n",
              "      <td>1.205882</td>\n",
              "      <td>96.0</td>\n",
              "      <td>131.0</td>\n",
              "      <td>79.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006</th>\n",
              "      <td>448</td>\n",
              "      <td>1.464052</td>\n",
              "      <td>389</td>\n",
              "      <td>1.271242</td>\n",
              "      <td>79.0</td>\n",
              "      <td>134.0</td>\n",
              "      <td>93.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2007</th>\n",
              "      <td>511</td>\n",
              "      <td>1.669935</td>\n",
              "      <td>349</td>\n",
              "      <td>1.140523</td>\n",
              "      <td>78.0</td>\n",
              "      <td>143.0</td>\n",
              "      <td>85.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2008</th>\n",
              "      <td>520</td>\n",
              "      <td>1.699346</td>\n",
              "      <td>374</td>\n",
              "      <td>1.222222</td>\n",
              "      <td>74.0</td>\n",
              "      <td>147.0</td>\n",
              "      <td>85.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009</th>\n",
              "      <td>463</td>\n",
              "      <td>1.513072</td>\n",
              "      <td>403</td>\n",
              "      <td>1.316993</td>\n",
              "      <td>86.0</td>\n",
              "      <td>125.0</td>\n",
              "      <td>95.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010</th>\n",
              "      <td>504</td>\n",
              "      <td>1.647059</td>\n",
              "      <td>390</td>\n",
              "      <td>1.274510</td>\n",
              "      <td>63.0</td>\n",
              "      <td>141.0</td>\n",
              "      <td>102.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2011</th>\n",
              "      <td>508</td>\n",
              "      <td>1.660131</td>\n",
              "      <td>367</td>\n",
              "      <td>1.199346</td>\n",
              "      <td>79.0</td>\n",
              "      <td>139.0</td>\n",
              "      <td>88.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2012</th>\n",
              "      <td>487</td>\n",
              "      <td>1.591503</td>\n",
              "      <td>411</td>\n",
              "      <td>1.343137</td>\n",
              "      <td>78.0</td>\n",
              "      <td>130.0</td>\n",
              "      <td>98.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2013</th>\n",
              "      <td>535</td>\n",
              "      <td>1.748366</td>\n",
              "      <td>432</td>\n",
              "      <td>1.411765</td>\n",
              "      <td>64.0</td>\n",
              "      <td>145.0</td>\n",
              "      <td>97.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014</th>\n",
              "      <td>486</td>\n",
              "      <td>1.588235</td>\n",
              "      <td>357</td>\n",
              "      <td>1.166667</td>\n",
              "      <td>82.0</td>\n",
              "      <td>145.0</td>\n",
              "      <td>79.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015</th>\n",
              "      <td>209</td>\n",
              "      <td>0.683007</td>\n",
              "      <td>168</td>\n",
              "      <td>0.549020</td>\n",
              "      <td>125.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>81.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>226</td>\n",
              "      <td>0.738562</td>\n",
              "      <td>154</td>\n",
              "      <td>0.503268</td>\n",
              "      <td>132.0</td>\n",
              "      <td>116.0</td>\n",
              "      <td>58.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>232</td>\n",
              "      <td>0.758170</td>\n",
              "      <td>150</td>\n",
              "      <td>0.490196</td>\n",
              "      <td>109.0</td>\n",
              "      <td>127.0</td>\n",
              "      <td>70.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>230</td>\n",
              "      <td>0.751634</td>\n",
              "      <td>174</td>\n",
              "      <td>0.568627</td>\n",
              "      <td>118.0</td>\n",
              "      <td>106.0</td>\n",
              "      <td>82.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019</th>\n",
              "      <td>209</td>\n",
              "      <td>0.683007</td>\n",
              "      <td>204</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>109.0</td>\n",
              "      <td>99.0</td>\n",
              "      <td>98.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020</th>\n",
              "      <td>513</td>\n",
              "      <td>1.676471</td>\n",
              "      <td>415</td>\n",
              "      <td>1.356209</td>\n",
              "      <td>81.0</td>\n",
              "      <td>129.0</td>\n",
              "      <td>96.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021</th>\n",
              "      <td>539</td>\n",
              "      <td>1.761438</td>\n",
              "      <td>415</td>\n",
              "      <td>1.356209</td>\n",
              "      <td>73.0</td>\n",
              "      <td>143.0</td>\n",
              "      <td>90.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022</th>\n",
              "      <td>568</td>\n",
              "      <td>1.856209</td>\n",
              "      <td>403</td>\n",
              "      <td>1.316993</td>\n",
              "      <td>75.0</td>\n",
              "      <td>145.0</td>\n",
              "      <td>86.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "            + ' 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 152
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### 5.1 Estadística del Borussia Dortmund en goles, partidos empatados, victorias de local y visitante\n",
        "<img src = \"https://upload.wikimedia.org/wikipedia/commons/thumb/6/67/Borussia_Dortmund_logo.svg/1200px-Borussia_Dortmund_logo.svg.png\" width=200>"
      ],
      "metadata": {
        "id": "9vuk1M1kdybk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_bundesliga.loc[df_bundesliga.AWAY_TEAM_NAME == 'Borussia Dortmund'].groupby('SEASON').agg({'GOALS_HOME':['sum','mean'],\n",
        "                                     'GOALS_AWAY':['sum','mean'],\n",
        "                                     'DRAW':'sum',\n",
        "                                     'WIN_HOME':'sum',\n",
        "                                     'WIN_AWAY':'sum'\n",
        "                                     })"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "ac8_qH5O1a3X",
        "outputId": "237f69c1-18d3-43fa-94a7-9dd1e9e3cd93"
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       GOALS_HOME           GOALS_AWAY           DRAW WIN_HOME WIN_AWAY\n",
              "              sum      mean        sum      mean  sum      sum      sum\n",
              "SEASON                                                                 \n",
              "2005           24  1.411765         22  1.294118  9.0      5.0      3.0\n",
              "2006           26  1.529412         22  1.294118  2.0      9.0      6.0\n",
              "2007           38  2.235294         21  1.235294  5.0      9.0      3.0\n",
              "2008           26  1.529412         26  1.529412  5.0      5.0      7.0\n",
              "2009           28  1.647059         25  1.470588  5.0      6.0      6.0\n",
              "2010           14  0.823529         32  1.882353  2.0      4.0     11.0\n",
              "2011           13  0.764706         36  2.117647  4.0      2.0     11.0\n",
              "2012           23  1.352941         41  2.411765  6.0      2.0      9.0\n",
              "2013           19  1.117647         39  2.294118  3.0      3.0     11.0\n",
              "2014           27  1.588235         21  1.235294  4.0      9.0      4.0\n",
              "2015            9  0.529412         13  0.764706  5.0      4.0      8.0\n",
              "2016           12  0.705882         13  0.764706  6.0      6.0      5.0\n",
              "2017           13  0.764706         12  0.705882  7.0      4.0      6.0\n",
              "2018           12  0.705882         12  0.705882  4.0      6.0      7.0\n",
              "2019            8  0.470588         12  0.705882  7.0      3.0      7.0\n",
              "2020           26  1.529412         35  2.058824  2.0      6.0      9.0\n",
              "2021           24  1.411765         33  1.941176  3.0      5.0      9.0\n",
              "2022           27  1.588235         28  1.647059  3.0      6.0      8.0"
            ],
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              "\n",
              "  <div id=\"df-a2e6c09e-457b-4c08-8aab-e9c30ef30c77\">\n",
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              "  <thead>\n",
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              "      <th colspan=\"2\" halign=\"left\">GOALS_HOME</th>\n",
              "      <th colspan=\"2\" halign=\"left\">GOALS_AWAY</th>\n",
              "      <th>DRAW</th>\n",
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              "      <th>WIN_AWAY</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>sum</th>\n",
              "      <th>mean</th>\n",
              "      <th>sum</th>\n",
              "      <th>mean</th>\n",
              "      <th>sum</th>\n",
              "      <th>sum</th>\n",
              "      <th>sum</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SEASON</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2005</th>\n",
              "      <td>24</td>\n",
              "      <td>1.411765</td>\n",
              "      <td>22</td>\n",
              "      <td>1.294118</td>\n",
              "      <td>9.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006</th>\n",
              "      <td>26</td>\n",
              "      <td>1.529412</td>\n",
              "      <td>22</td>\n",
              "      <td>1.294118</td>\n",
              "      <td>2.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2007</th>\n",
              "      <td>38</td>\n",
              "      <td>2.235294</td>\n",
              "      <td>21</td>\n",
              "      <td>1.235294</td>\n",
              "      <td>5.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2008</th>\n",
              "      <td>26</td>\n",
              "      <td>1.529412</td>\n",
              "      <td>26</td>\n",
              "      <td>1.529412</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009</th>\n",
              "      <td>28</td>\n",
              "      <td>1.647059</td>\n",
              "      <td>25</td>\n",
              "      <td>1.470588</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010</th>\n",
              "      <td>14</td>\n",
              "      <td>0.823529</td>\n",
              "      <td>32</td>\n",
              "      <td>1.882353</td>\n",
              "      <td>2.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2011</th>\n",
              "      <td>13</td>\n",
              "      <td>0.764706</td>\n",
              "      <td>36</td>\n",
              "      <td>2.117647</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2012</th>\n",
              "      <td>23</td>\n",
              "      <td>1.352941</td>\n",
              "      <td>41</td>\n",
              "      <td>2.411765</td>\n",
              "      <td>6.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2013</th>\n",
              "      <td>19</td>\n",
              "      <td>1.117647</td>\n",
              "      <td>39</td>\n",
              "      <td>2.294118</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014</th>\n",
              "      <td>27</td>\n",
              "      <td>1.588235</td>\n",
              "      <td>21</td>\n",
              "      <td>1.235294</td>\n",
              "      <td>4.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015</th>\n",
              "      <td>9</td>\n",
              "      <td>0.529412</td>\n",
              "      <td>13</td>\n",
              "      <td>0.764706</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>12</td>\n",
              "      <td>0.705882</td>\n",
              "      <td>13</td>\n",
              "      <td>0.764706</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>13</td>\n",
              "      <td>0.764706</td>\n",
              "      <td>12</td>\n",
              "      <td>0.705882</td>\n",
              "      <td>7.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>12</td>\n",
              "      <td>0.705882</td>\n",
              "      <td>12</td>\n",
              "      <td>0.705882</td>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019</th>\n",
              "      <td>8</td>\n",
              "      <td>0.470588</td>\n",
              "      <td>12</td>\n",
              "      <td>0.705882</td>\n",
              "      <td>7.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020</th>\n",
              "      <td>26</td>\n",
              "      <td>1.529412</td>\n",
              "      <td>35</td>\n",
              "      <td>2.058824</td>\n",
              "      <td>2.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021</th>\n",
              "      <td>24</td>\n",
              "      <td>1.411765</td>\n",
              "      <td>33</td>\n",
              "      <td>1.941176</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022</th>\n",
              "      <td>27</td>\n",
              "      <td>1.588235</td>\n",
              "      <td>28</td>\n",
              "      <td>1.647059</td>\n",
              "      <td>3.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a2e6c09e-457b-4c08-8aab-e9c30ef30c77')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      <script>\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "            + ' to learn more about interactive tables.';\n",
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            ]
          },
          "metadata": {},
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### 5.2 Estadística del Bayer Munchen en goles, partidos empatados, victorias de local y visitante\n",
        "<img src = \"https://upload.wikimedia.org/wikipedia/commons/thumb/1/1b/FC_Bayern_M%C3%BCnchen_logo_%282017%29.svg/1200px-FC_Bayern_M%C3%BCnchen_logo_%282017%29.svg.png\" width=200>"
      ],
      "metadata": {
        "id": "h4L-hF78d767"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_bundesliga.loc[df_bundesliga.AWAY_TEAM_NAME == 'FC Bayern München'].groupby('SEASON').agg({'GOALS_HOME':['sum','mean'],\n",
        "                                     'GOALS_AWAY':['sum','mean'],\n",
        "                                     'DRAW':'sum',\n",
        "                                     'WIN_HOME':'sum',\n",
        "                                     'WIN_AWAY':'sum'\n",
        "                                     })"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "EI0APGHo1-gd",
        "outputId": "b5239a28-8b78-48b2-9156-12793c37771e"
      },
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       GOALS_HOME           GOALS_AWAY           DRAW WIN_HOME WIN_AWAY\n",
              "              sum      mean        sum      mean  sum      sum      sum\n",
              "SEASON                                                                 \n",
              "2005           18  1.058824         25  1.470588  7.0      2.0      8.0\n",
              "2006           26  1.529412         26  1.529412  2.0      8.0      7.0\n",
              "2007           13  0.764706         27  1.588235  5.0      2.0     10.0\n",
              "2008           19  1.117647         26  1.529412  5.0      4.0      8.0\n",
              "2009           18  1.058824         33  1.941176  6.0      3.0      8.0\n",
              "2010           27  1.588235         33  1.941176  6.0      5.0      6.0\n",
              "2011           16  0.941176         28  1.647059  3.0      5.0      9.0\n",
              "2012            7  0.411765         42  2.470588  2.0      0.0     15.0\n",
              "2013            8  0.470588         46  2.705882  2.0      1.0     14.0\n",
              "2014           11  0.647059         34  2.000000  3.0      3.0     11.0\n",
              "2015            3  0.176471         11  0.647059  9.0      0.0      8.0\n",
              "2016            8  0.470588         13  0.764706  8.0      4.0      5.0\n",
              "2017            7  0.411765         14  0.823529  5.0      4.0      8.0\n",
              "2018            7  0.411765         19  1.117647  5.0      1.0     11.0\n",
              "2019            6  0.352941         27  1.588235  4.0      1.0     12.0\n",
              "2020           23  1.352941         35  2.058824  2.0      4.0     11.0\n",
              "2021           22  1.294118         49  2.882353  3.0      3.0     11.0\n",
              "2022           21  1.235294         39  2.294118  3.0      4.0     10.0"
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              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2005</th>\n",
              "      <td>18</td>\n",
              "      <td>1.058824</td>\n",
              "      <td>25</td>\n",
              "      <td>1.470588</td>\n",
              "      <td>7.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006</th>\n",
              "      <td>26</td>\n",
              "      <td>1.529412</td>\n",
              "      <td>26</td>\n",
              "      <td>1.529412</td>\n",
              "      <td>2.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2007</th>\n",
              "      <td>13</td>\n",
              "      <td>0.764706</td>\n",
              "      <td>27</td>\n",
              "      <td>1.588235</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2008</th>\n",
              "      <td>19</td>\n",
              "      <td>1.117647</td>\n",
              "      <td>26</td>\n",
              "      <td>1.529412</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009</th>\n",
              "      <td>18</td>\n",
              "      <td>1.058824</td>\n",
              "      <td>33</td>\n",
              "      <td>1.941176</td>\n",
              "      <td>6.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010</th>\n",
              "      <td>27</td>\n",
              "      <td>1.588235</td>\n",
              "      <td>33</td>\n",
              "      <td>1.941176</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2011</th>\n",
              "      <td>16</td>\n",
              "      <td>0.941176</td>\n",
              "      <td>28</td>\n",
              "      <td>1.647059</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2012</th>\n",
              "      <td>7</td>\n",
              "      <td>0.411765</td>\n",
              "      <td>42</td>\n",
              "      <td>2.470588</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2013</th>\n",
              "      <td>8</td>\n",
              "      <td>0.470588</td>\n",
              "      <td>46</td>\n",
              "      <td>2.705882</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>14.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014</th>\n",
              "      <td>11</td>\n",
              "      <td>0.647059</td>\n",
              "      <td>34</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015</th>\n",
              "      <td>3</td>\n",
              "      <td>0.176471</td>\n",
              "      <td>11</td>\n",
              "      <td>0.647059</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>8</td>\n",
              "      <td>0.470588</td>\n",
              "      <td>13</td>\n",
              "      <td>0.764706</td>\n",
              "      <td>8.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>7</td>\n",
              "      <td>0.411765</td>\n",
              "      <td>14</td>\n",
              "      <td>0.823529</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>7</td>\n",
              "      <td>0.411765</td>\n",
              "      <td>19</td>\n",
              "      <td>1.117647</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019</th>\n",
              "      <td>6</td>\n",
              "      <td>0.352941</td>\n",
              "      <td>27</td>\n",
              "      <td>1.588235</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>12.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020</th>\n",
              "      <td>23</td>\n",
              "      <td>1.352941</td>\n",
              "      <td>35</td>\n",
              "      <td>2.058824</td>\n",
              "      <td>2.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021</th>\n",
              "      <td>22</td>\n",
              "      <td>1.294118</td>\n",
              "      <td>49</td>\n",
              "      <td>2.882353</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022</th>\n",
              "      <td>21</td>\n",
              "      <td>1.235294</td>\n",
              "      <td>39</td>\n",
              "      <td>2.294118</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###6.Calcular los puntos obtenidos por cada equipo en las diferentes jornadas de todas las temporadas."
      ],
      "metadata": {
        "id": "fHOYnPmb20Pp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def point_team(win,draw):\n",
        "  if win == 1:\n",
        "    return win * 3\n",
        "  elif draw == 1:\n",
        "    return draw\n",
        "  else:\n",
        "    return 0"
      ],
      "metadata": {
        "id": "TsgCF6KC0Tea"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_bundesliga['HOME_POINTS'] = df_bundesliga[['WIN_HOME','DRAW']].apply(lambda row: point_team(row['WIN_HOME'],row['DRAW']),axis=1)\n",
        "df_bundesliga['AWAY_POINTS'] = df_bundesliga[['WIN_AWAY','DRAW']].apply(lambda row: point_team(row['WIN_AWAY'],row['DRAW']),axis=1)"
      ],
      "metadata": {
        "id": "ewi0Iro39d1U"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_bundesliga.tail(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 803
        },
        "id": "sCssMGvt2ulL",
        "outputId": "4cc8c7f1-96b6-4afe-81cd-c75680905a70"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               MATCH_DATE                      LEAGUE_NAME  SEASON LEAGUE  \\\n",
              "5498  2023-05-21 19:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5499  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5500  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5501  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5502  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5503  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5504  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5505  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5506  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "5507  2023-05-27 15:30:00  1. Fußball-Bundesliga 2022/2023    2022    bl1   \n",
              "\n",
              "      FINISHED    LOCATION  VIEWER      MATCHDAY  MATCHDAY_NR  HOME_TEAM_ID  \\\n",
              "5498      True  Leverkusen     NaN  33. Spieltag           33             6   \n",
              "5499      True      Bochum     NaN  34. Spieltag           34           129   \n",
              "5500      True    Dortmund     NaN  34. Spieltag           34             7   \n",
              "5501      True    Gladbach     NaN  34. Spieltag           34            87   \n",
              "5502      True   Frankfurt     NaN  34. Spieltag           34            91   \n",
              "5503      True        Köln     NaN  34. Spieltag           34            65   \n",
              "5504      True     Leipzig     NaN  34. Spieltag           34          1635   \n",
              "5505      True   Stuttgart     NaN  34. Spieltag           34            16   \n",
              "5506      True      Berlin     NaN  34. Spieltag           34            80   \n",
              "5507      True   Wolfsburg     NaN  34. Spieltag           34           131   \n",
              "\n",
              "      ... AWAY_TEAM_ID            AWAY_TEAM_NAME   AWAY_TEAM GOALS_HOME  \\\n",
              "5498  ...           87  Borussia Mönchengladbach    Gladbach          2   \n",
              "5499  ...            6          Bayer Leverkusen  Leverkusen          3   \n",
              "5500  ...           81           1. FSV Mainz 05       Mainz          2   \n",
              "5501  ...           95               FC Augsburg    Augsburg          2   \n",
              "5502  ...          112               SC Freiburg    Freiburg          2   \n",
              "5503  ...           40         FC Bayern München      Bayern          1   \n",
              "5504  ...            9             FC Schalke 04     Schalke          4   \n",
              "5505  ...          175       TSG 1899 Hoffenheim  Hoffenheim          1   \n",
              "5506  ...          134             Werder Bremen      Bremen          1   \n",
              "5507  ...           54                Hertha BSC      Hertha          1   \n",
              "\n",
              "     GOALS_AWAY  DRAW  WIN_HOME  WIN_AWAY  HOME_POINTS  AWAY_POINTS  \n",
              "5498          2   1.0       0.0       0.0          1.0          1.0  \n",
              "5499          0   0.0       1.0       0.0          3.0          0.0  \n",
              "5500          2   1.0       0.0       0.0          1.0          1.0  \n",
              "5501          0   0.0       1.0       0.0          3.0          0.0  \n",
              "5502          1   0.0       1.0       0.0          3.0          0.0  \n",
              "5503          2   0.0       0.0       1.0          0.0          3.0  \n",
              "5504          2   0.0       1.0       0.0          3.0          0.0  \n",
              "5505          1   1.0       0.0       0.0          1.0          1.0  \n",
              "5506          0   0.0       1.0       0.0          3.0          0.0  \n",
              "5507          2   0.0       0.0       1.0          0.0          3.0  \n",
              "\n",
              "[10 rows x 22 columns]"
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>MATCH_DATE</th>\n",
              "      <th>LEAGUE_NAME</th>\n",
              "      <th>SEASON</th>\n",
              "      <th>LEAGUE</th>\n",
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              "      <th>DRAW</th>\n",
              "      <th>WIN_HOME</th>\n",
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              "      <th>5498</th>\n",
              "      <td>2023-05-21 19:30:00</td>\n",
              "      <td>1. Fußball-Bundesliga 2022/2023</td>\n",
              "      <td>2022</td>\n",
              "      <td>bl1</td>\n",
              "      <td>True</td>\n",
              "      <td>Leverkusen</td>\n",
              "      <td>NaN</td>\n",
              "      <td>33. Spieltag</td>\n",
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              "      <td>6</td>\n",
              "      <td>...</td>\n",
              "      <td>87</td>\n",
              "      <td>Borussia Mönchengladbach</td>\n",
              "      <td>Gladbach</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
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              "    <tr>\n",
              "      <th>5499</th>\n",
              "      <td>2023-05-27 15:30:00</td>\n",
              "      <td>1. Fußball-Bundesliga 2022/2023</td>\n",
              "      <td>2022</td>\n",
              "      <td>bl1</td>\n",
              "      <td>True</td>\n",
              "      <td>Bochum</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34. Spieltag</td>\n",
              "      <td>34</td>\n",
              "      <td>129</td>\n",
              "      <td>...</td>\n",
              "      <td>6</td>\n",
              "      <td>Bayer Leverkusen</td>\n",
              "      <td>Leverkusen</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
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              "      <th>5500</th>\n",
              "      <td>2023-05-27 15:30:00</td>\n",
              "      <td>1. Fußball-Bundesliga 2022/2023</td>\n",
              "      <td>2022</td>\n",
              "      <td>bl1</td>\n",
              "      <td>True</td>\n",
              "      <td>Dortmund</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34. Spieltag</td>\n",
              "      <td>34</td>\n",
              "      <td>7</td>\n",
              "      <td>...</td>\n",
              "      <td>81</td>\n",
              "      <td>1. FSV Mainz 05</td>\n",
              "      <td>Mainz</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5501</th>\n",
              "      <td>2023-05-27 15:30:00</td>\n",
              "      <td>1. Fußball-Bundesliga 2022/2023</td>\n",
              "      <td>2022</td>\n",
              "      <td>bl1</td>\n",
              "      <td>True</td>\n",
              "      <td>Gladbach</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34. Spieltag</td>\n",
              "      <td>34</td>\n",
              "      <td>87</td>\n",
              "      <td>...</td>\n",
              "      <td>95</td>\n",
              "      <td>FC Augsburg</td>\n",
              "      <td>Augsburg</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5502</th>\n",
              "      <td>2023-05-27 15:30:00</td>\n",
              "      <td>1. Fußball-Bundesliga 2022/2023</td>\n",
              "      <td>2022</td>\n",
              "      <td>bl1</td>\n",
              "      <td>True</td>\n",
              "      <td>Frankfurt</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34. Spieltag</td>\n",
              "      <td>34</td>\n",
              "      <td>91</td>\n",
              "      <td>...</td>\n",
              "      <td>112</td>\n",
              "      <td>SC Freiburg</td>\n",
              "      <td>Freiburg</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5503</th>\n",
              "      <td>2023-05-27 15:30:00</td>\n",
              "      <td>1. Fußball-Bundesliga 2022/2023</td>\n",
              "      <td>2022</td>\n",
              "      <td>bl1</td>\n",
              "      <td>True</td>\n",
              "      <td>Köln</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34. Spieltag</td>\n",
              "      <td>34</td>\n",
              "      <td>65</td>\n",
              "      <td>...</td>\n",
              "      <td>40</td>\n",
              "      <td>FC Bayern München</td>\n",
              "      <td>Bayern</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5504</th>\n",
              "      <td>2023-05-27 15:30:00</td>\n",
              "      <td>1. Fußball-Bundesliga 2022/2023</td>\n",
              "      <td>2022</td>\n",
              "      <td>bl1</td>\n",
              "      <td>True</td>\n",
              "      <td>Leipzig</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34. Spieltag</td>\n",
              "      <td>34</td>\n",
              "      <td>1635</td>\n",
              "      <td>...</td>\n",
              "      <td>9</td>\n",
              "      <td>FC Schalke 04</td>\n",
              "      <td>Schalke</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5505</th>\n",
              "      <td>2023-05-27 15:30:00</td>\n",
              "      <td>1. Fußball-Bundesliga 2022/2023</td>\n",
              "      <td>2022</td>\n",
              "      <td>bl1</td>\n",
              "      <td>True</td>\n",
              "      <td>Stuttgart</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34. Spieltag</td>\n",
              "      <td>34</td>\n",
              "      <td>16</td>\n",
              "      <td>...</td>\n",
              "      <td>175</td>\n",
              "      <td>TSG 1899 Hoffenheim</td>\n",
              "      <td>Hoffenheim</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5506</th>\n",
              "      <td>2023-05-27 15:30:00</td>\n",
              "      <td>1. Fußball-Bundesliga 2022/2023</td>\n",
              "      <td>2022</td>\n",
              "      <td>bl1</td>\n",
              "      <td>True</td>\n",
              "      <td>Berlin</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34. Spieltag</td>\n",
              "      <td>34</td>\n",
              "      <td>80</td>\n",
              "      <td>...</td>\n",
              "      <td>134</td>\n",
              "      <td>Werder Bremen</td>\n",
              "      <td>Bremen</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5507</th>\n",
              "      <td>2023-05-27 15:30:00</td>\n",
              "      <td>1. Fußball-Bundesliga 2022/2023</td>\n",
              "      <td>2022</td>\n",
              "      <td>bl1</td>\n",
              "      <td>True</td>\n",
              "      <td>Wolfsburg</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34. Spieltag</td>\n",
              "      <td>34</td>\n",
              "      <td>131</td>\n",
              "      <td>...</td>\n",
              "      <td>54</td>\n",
              "      <td>Hertha BSC</td>\n",
              "      <td>Hertha</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>10 rows × 22 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-35e5aa87-e05f-4398-9f72-9ccb12544f63')\"\n",
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              "\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "                                                     [key], {});\n",
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              "\n",
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              "            + ' to learn more about interactive tables.';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###7.Calcular los puntos adquiridos jugando de locales en la temporada 2022-2023"
      ],
      "metadata": {
        "id": "y5jb1taj8usL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_HOME_BDL = df_bundesliga.loc[df_bundesliga.MATCH_DATE >='2022-08-05'].groupby(['HOME_TEAM_NAME']).agg({\n",
        "                                     'DRAW':'sum',\n",
        "                                     'WIN_HOME':'sum',\n",
        "                                     'HOME_POINTS':'sum'\n",
        "                                     }).sort_values('HOME_POINTS',ascending=False)\n",
        "df_HOME_BDL = df_HOME_BDL.rename(columns={'DRAW':'DRAW_HOME'})\n",
        "df_HOME_BDL"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 645
        },
        "id": "piOqNals5GhP",
        "outputId": "3a8417df-245a-4d16-aab9-17624cf7508a"
      },
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                          DRAW_HOME  WIN_HOME  HOME_POINTS\n",
              "HOME_TEAM_NAME                                            \n",
              "Borussia Dortmund               2.0      14.0         44.0\n",
              "RB Leipzig                      2.0      13.0         41.0\n",
              "1. FC Union Berlin              6.0      11.0         39.0\n",
              "FC Bayern München               5.0      11.0         38.0\n",
              "SC Freiburg                     4.0      10.0         34.0\n",
              "Borussia Mönchengladbach        3.0      10.0         33.0\n",
              "Eintracht Frankfurt             5.0       9.0         32.0\n",
              "Bayer Leverkusen                3.0       8.0         27.0\n",
              "VfL Bochum                      2.0       8.0         26.0\n",
              "VfL Wolfsburg                   7.0       6.0         25.0\n",
              "1. FSV Mainz 05                 6.0       6.0         24.0\n",
              "1. FC Köln                      5.0       6.0         23.0\n",
              "TSG 1899 Hoffenheim             2.0       7.0         23.0\n",
              "FC Augsburg                     4.0       6.0         22.0\n",
              "Hertha BSC                      6.0       5.0         21.0\n",
              "VfB Stuttgart                   6.0       5.0         21.0\n",
              "FC Schalke 04                   5.0       5.0         20.0\n",
              "Werder Bremen                   2.0       5.0         17.0"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d497e51d-ee1a-4559-9504-b9ad5a67da14\">\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>DRAW_HOME</th>\n",
              "      <th>WIN_HOME</th>\n",
              "      <th>HOME_POINTS</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>HOME_TEAM_NAME</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Borussia Dortmund</th>\n",
              "      <td>2.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>44.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RB Leipzig</th>\n",
              "      <td>2.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>41.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1. FC Union Berlin</th>\n",
              "      <td>6.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FC Bayern München</th>\n",
              "      <td>5.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>38.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SC Freiburg</th>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>34.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Borussia Mönchengladbach</th>\n",
              "      <td>3.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>33.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Eintracht Frankfurt</th>\n",
              "      <td>5.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>32.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bayer Leverkusen</th>\n",
              "      <td>3.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>27.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>VfL Bochum</th>\n",
              "      <td>2.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>26.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>VfL Wolfsburg</th>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>25.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1. FSV Mainz 05</th>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>24.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1. FC Köln</th>\n",
              "      <td>5.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>23.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TSG 1899 Hoffenheim</th>\n",
              "      <td>2.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>23.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FC Augsburg</th>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>22.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Hertha BSC</th>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>21.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>VfB Stuttgart</th>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>21.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FC Schalke 04</th>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>20.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Werder Bremen</th>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>17.0</td>\n",
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              "    [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-d497e51d-ee1a-4559-9504-b9ad5a67da14 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-d497e51d-ee1a-4559-9504-b9ad5a67da14');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 69
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###8.Calcular los puntos adquiridos jugando de visitante en la temporada 2022-2023"
      ],
      "metadata": {
        "id": "dFpNq4Q7BfwD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_AWAY_BDL = df_bundesliga.loc[df_bundesliga.MATCH_DATE >='2022-08-05'].groupby(['AWAY_TEAM_NAME']).agg({\n",
        "                                     'DRAW':'sum',\n",
        "                                     'WIN_AWAY':'sum',\n",
        "                                     'AWAY_POINTS':'sum'\n",
        "                                     }).sort_values('AWAY_POINTS',ascending=False)\n",
        "df_AWAY_BDL= df_AWAY_BDL.rename(columns={'DRAW':'DRAW_AWAY'})\n",
        "df_AWAY_BDL"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 645
        },
        "id": "KHugs4isALeU",
        "outputId": "a4995c32-66b0-4535-fdb1-6e19e557074d"
      },
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                          DRAW_AWAY  WIN_AWAY  AWAY_POINTS\n",
              "AWAY_TEAM_NAME                                            \n",
              "FC Bayern München               3.0      10.0         33.0\n",
              "Borussia Dortmund               3.0       8.0         27.0\n",
              "SC Freiburg                     4.0       7.0         25.0\n",
              "RB Leipzig                      4.0       7.0         25.0\n",
              "VfL Wolfsburg                   3.0       7.0         24.0\n",
              "1. FC Union Berlin              2.0       7.0         23.0\n",
              "Bayer Leverkusen                5.0       6.0         23.0\n",
              "1. FSV Mainz 05                 4.0       6.0         22.0\n",
              "1. FC Köln                      7.0       4.0         19.0\n",
              "Werder Bremen                   4.0       5.0         19.0\n",
              "Eintracht Frankfurt             6.0       4.0         18.0\n",
              "TSG 1899 Hoffenheim             4.0       3.0         13.0\n",
              "FC Augsburg                     3.0       3.0         12.0\n",
              "VfB Stuttgart                   6.0       2.0         12.0\n",
              "FC Schalke 04                   5.0       2.0         11.0\n",
              "Borussia Mönchengladbach        7.0       1.0         10.0\n",
              "VfL Bochum                      3.0       2.0          9.0\n",
              "Hertha BSC                      2.0       2.0          8.0"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f254bad2-113a-42f2-bcd8-b9444ffa9675\">\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>DRAW_AWAY</th>\n",
              "      <th>WIN_AWAY</th>\n",
              "      <th>AWAY_POINTS</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AWAY_TEAM_NAME</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>FC Bayern München</th>\n",
              "      <td>3.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>33.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Borussia Dortmund</th>\n",
              "      <td>3.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>27.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SC Freiburg</th>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>25.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RB Leipzig</th>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>25.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>VfL Wolfsburg</th>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>24.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1. FC Union Berlin</th>\n",
              "      <td>2.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>23.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bayer Leverkusen</th>\n",
              "      <td>5.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>23.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1. FSV Mainz 05</th>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>22.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1. FC Köln</th>\n",
              "      <td>7.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>19.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Werder Bremen</th>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>19.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Eintracht Frankfurt</th>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>18.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TSG 1899 Hoffenheim</th>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>13.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FC Augsburg</th>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>12.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>VfB Stuttgart</th>\n",
              "      <td>6.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>12.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FC Schalke 04</th>\n",
              "      <td>5.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Borussia Mönchengladbach</th>\n",
              "      <td>7.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>VfL Bochum</th>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Hertha BSC</th>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f254bad2-113a-42f2-bcd8-b9444ffa9675')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
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              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "      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-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-f254bad2-113a-42f2-bcd8-b9444ffa9675 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-f254bad2-113a-42f2-bcd8-b9444ffa9675');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###9.Diferencia de goles de cada equipo cuando está de local."
      ],
      "metadata": {
        "id": "gyFW-5u9PZ70"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_diff_home_goals = df_bundesliga.loc[df_bundesliga.MATCH_DATE >='2022-08-05'].groupby('HOME_TEAM_NAME').agg({'GOALS_HOME':'sum','GOALS_AWAY':'sum'})\n",
        "df_diff_home_goals['GD_HOME'] = df_diff_home_goals['GOALS_HOME'] - df_diff_home_goals['GOALS_AWAY']\n",
        "df_diff_home_goals = df_diff_home_goals.sort_values('GD_HOME',ascending=True).rename(columns={'GOALS_HOME':'GF_HOME_TEAM_NAME','GOALS_AWAY':'GA_AWAY'})\n",
        "df_diff_home_goals"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 645
        },
        "id": "a3XnIsB2M1Ov",
        "outputId": "7b763070-ba1c-4b8e-8d3c-a71cc7e35d5e"
      },
      "execution_count": 122,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                          GF_HOME_TEAM_NAME  GA_AWAY  GD_HOME\n",
              "HOME_TEAM_NAME                                               \n",
              "FC Schalke 04                            23       36      -13\n",
              "FC Augsburg                              16       24       -8\n",
              "VfL Bochum                               28       32       -4\n",
              "Hertha BSC                               24       27       -3\n",
              "Werder Bremen                            26       28       -2\n",
              "TSG 1899 Hoffenheim                      28       29       -1\n",
              "VfB Stuttgart                            23       22        1\n",
              "1. FSV Mainz 05                          31       25        6\n",
              "1. FC Köln                               28       20        8\n",
              "VfL Wolfsburg                            34       25        9\n",
              "Bayer Leverkusen                         35       23       12\n",
              "Borussia Mönchengladbach                 33       18       15\n",
              "SC Freiburg                              28       13       15\n",
              "Eintracht Frankfurt                      35       18       17\n",
              "1. FC Union Berlin                       30       11       19\n",
              "RB Leipzig                               38       18       20\n",
              "FC Bayern München                        53       17       36\n",
              "Borussia Dortmund                        55       17       38"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1b6ee8cc-1566-41ea-9079-d16687536c55\">\n",
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              "\n",
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              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>GF_HOME_TEAM_NAME</th>\n",
              "      <th>GA_AWAY</th>\n",
              "      <th>GD_HOME</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>HOME_TEAM_NAME</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>FC Schalke 04</th>\n",
              "      <td>23</td>\n",
              "      <td>36</td>\n",
              "      <td>-13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FC Augsburg</th>\n",
              "      <td>16</td>\n",
              "      <td>24</td>\n",
              "      <td>-8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>VfL Bochum</th>\n",
              "      <td>28</td>\n",
              "      <td>32</td>\n",
              "      <td>-4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Hertha BSC</th>\n",
              "      <td>24</td>\n",
              "      <td>27</td>\n",
              "      <td>-3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Werder Bremen</th>\n",
              "      <td>26</td>\n",
              "      <td>28</td>\n",
              "      <td>-2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TSG 1899 Hoffenheim</th>\n",
              "      <td>28</td>\n",
              "      <td>29</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>VfB Stuttgart</th>\n",
              "      <td>23</td>\n",
              "      <td>22</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1. FSV Mainz 05</th>\n",
              "      <td>31</td>\n",
              "      <td>25</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1. FC Köln</th>\n",
              "      <td>28</td>\n",
              "      <td>20</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>VfL Wolfsburg</th>\n",
              "      <td>34</td>\n",
              "      <td>25</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bayer Leverkusen</th>\n",
              "      <td>35</td>\n",
              "      <td>23</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Borussia Mönchengladbach</th>\n",
              "      <td>33</td>\n",
              "      <td>18</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SC Freiburg</th>\n",
              "      <td>28</td>\n",
              "      <td>13</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Eintracht Frankfurt</th>\n",
              "      <td>35</td>\n",
              "      <td>18</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1. FC Union Berlin</th>\n",
              "      <td>30</td>\n",
              "      <td>11</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RB Leipzig</th>\n",
              "      <td>38</td>\n",
              "      <td>18</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FC Bayern München</th>\n",
              "      <td>53</td>\n",
              "      <td>17</td>\n",
              "      <td>36</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Borussia Dortmund</th>\n",
              "      <td>55</td>\n",
              "      <td>17</td>\n",
              "      <td>38</td>\n",
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              "  "
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          "metadata": {},
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      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###10.Diferencia de goles de cada equipo cuando está de visitante."
      ],
      "metadata": {
        "id": "ICsbFqcyPk_L"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_diff_away_goals = df_bundesliga.loc[df_bundesliga.MATCH_DATE >='2022-08-05'].groupby('AWAY_TEAM_NAME').agg({'GOALS_AWAY':'sum','GOALS_HOME':'sum'})\n",
        "df_diff_away_goals['GD_AWAY'] = df_diff_away_goals['GOALS_AWAY'] - df_diff_away_goals['GOALS_HOME']\n",
        "df_diff_away_goals = df_diff_away_goals.sort_values('GD_AWAY',ascending=False).rename(columns={'GOALS_AWAY':'GF_AWAY_TEAM_NAME','GOALS_HOME':'GA_HOME'})\n",
        "df_diff_away_goals"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 645
        },
        "id": "5af-jEZlO5tj",
        "outputId": "e04b9c16-8678-4fbf-e967-fa8d9c69b55c"
      },
      "execution_count": 123,
      "outputs": [
        {
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            "text/plain": [
              "                          GF_AWAY_TEAM_NAME  GA_HOME  GD_AWAY\n",
              "AWAY_TEAM_NAME                                               \n",
              "FC Bayern München                        39       21       18\n",
              "RB Leipzig                               26       23        3\n",
              "Borussia Dortmund                        28       27        1\n",
              "VfL Wolfsburg                            23       23        0\n",
              "Bayer Leverkusen                         22       26       -4\n",
              "1. FC Union Berlin                       21       27       -6\n",
              "1. FSV Mainz 05                          23       30       -7\n",
              "SC Freiburg                              23       31       -8\n",
              "TSG 1899 Hoffenheim                      20       28       -8\n",
              "Werder Bremen                            25       36      -11\n",
              "Eintracht Frankfurt                      23       34      -11\n",
              "VfB Stuttgart                            22       35      -13\n",
              "1. FC Köln                               21       34      -13\n",
              "FC Augsburg                              26       39      -13\n",
              "Borussia Mönchengladbach                 19       37      -18\n",
              "FC Schalke 04                            12       35      -23\n",
              "Hertha BSC                               18       42      -24\n",
              "VfL Bochum                               12       40      -28"
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              "                                                     [key], {});\n",
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              "          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",
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          },
          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_goals_stats = pd.concat([df_diff_home_goals,df_diff_away_goals],axis=1)\n",
        "df_goals_stats.reset_index().rename(columns={'index':'TEAM NAME'})\n",
        "df_goals_stats['GF'] = df_goals_stats['GF_HOME_TEAM_NAME'] + df_goals_stats['GF_AWAY_TEAM_NAME']\n",
        "df_goals_stats['GA'] = df_goals_stats['GA_AWAY'] + df_goals_stats['GA_HOME']\n",
        "df_goals_stats['DF'] = df_goals_stats['GF'] - df_goals_stats['GA']\n",
        "df_goals_stats = df_goals_stats[['GF','GA','DF']]\n",
        "df_goals_stats"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 613
        },
        "id": "XpYwnYSWRhwy",
        "outputId": "a5097b49-b6a9-4a53-9853-947cfb01adae"
      },
      "execution_count": 125,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                          GF  GA  DF\n",
              "FC Schalke 04             35  71 -36\n",
              "FC Augsburg               42  63 -21\n",
              "VfL Bochum                40  72 -32\n",
              "Hertha BSC                42  69 -27\n",
              "Werder Bremen             51  64 -13\n",
              "TSG 1899 Hoffenheim       48  57  -9\n",
              "VfB Stuttgart             45  57 -12\n",
              "1. FSV Mainz 05           54  55  -1\n",
              "1. FC Köln                49  54  -5\n",
              "VfL Wolfsburg             57  48   9\n",
              "Bayer Leverkusen          57  49   8\n",
              "Borussia Mönchengladbach  52  55  -3\n",
              "SC Freiburg               51  44   7\n",
              "Eintracht Frankfurt       58  52   6\n",
              "1. FC Union Berlin        51  38  13\n",
              "RB Leipzig                64  41  23\n",
              "FC Bayern München         92  38  54\n",
              "Borussia Dortmund         83  44  39"
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              "    <tr>\n",
              "      <th>RB Leipzig</th>\n",
              "      <td>64</td>\n",
              "      <td>41</td>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FC Bayern München</th>\n",
              "      <td>92</td>\n",
              "      <td>38</td>\n",
              "      <td>54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Borussia Dortmund</th>\n",
              "      <td>83</td>\n",
              "      <td>44</td>\n",
              "      <td>39</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 125
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**11.TABLA DE CLASIFICACIÓN TEMPORADA 2022-2023**"
      ],
      "metadata": {
        "id": "0hAGGrPvJ_zy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "bf_season_2022_2023 = pd.concat([df_HOME_BDL,df_AWAY_BDL,df_goals_stats],axis=1)\n",
        "bf_season_2022_2023 = bf_season_2022_2023.reset_index().rename(columns={'index':'SEASON 2022-2023'})\n",
        "bf_season_2022_2023['Pts'] = bf_season_2022_2023['HOME_POINTS'] + bf_season_2022_2023['AWAY_POINTS']\n",
        "bf_season_2022_2023 = bf_season_2022_2023[['SEASON 2022-2023','GF','GA','DF','Pts']].sort_values(['Pts','DF'],ascending=False).reset_index(drop=True)\n",
        "bf_season_2022_2023.index = bf_season_2022_2023.index + 1 #Reiniciar los índices para la tabla de posición.\n",
        "bf_season_2022_2023"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 613
        },
        "id": "OwVXWNZwFxKQ",
        "outputId": "857f1ece-b870-4d40-f922-c736ca87fe8f"
      },
      "execution_count": 149,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            SEASON 2022-2023  GF  GA  DF   Pts\n",
              "1          FC Bayern München  92  38  54  71.0\n",
              "2          Borussia Dortmund  83  44  39  71.0\n",
              "3                 RB Leipzig  64  41  23  66.0\n",
              "4         1. FC Union Berlin  51  38  13  62.0\n",
              "5                SC Freiburg  51  44   7  59.0\n",
              "6           Bayer Leverkusen  57  49   8  50.0\n",
              "7        Eintracht Frankfurt  58  52   6  50.0\n",
              "8              VfL Wolfsburg  57  48   9  49.0\n",
              "9            1. FSV Mainz 05  54  55  -1  46.0\n",
              "10  Borussia Mönchengladbach  52  55  -3  43.0\n",
              "11                1. FC Köln  49  54  -5  42.0\n",
              "12       TSG 1899 Hoffenheim  48  57  -9  36.0\n",
              "13             Werder Bremen  51  64 -13  36.0\n",
              "14                VfL Bochum  40  72 -32  35.0\n",
              "15               FC Augsburg  42  63 -21  34.0\n",
              "16             VfB Stuttgart  45  57 -12  33.0\n",
              "17             FC Schalke 04  35  71 -36  31.0\n",
              "18                Hertha BSC  42  69 -27  29.0"
            ],
            "text/html": [
              "\n",
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              "      <th>SEASON 2022-2023</th>\n",
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              "      <th>GA</th>\n",
              "      <th>DF</th>\n",
              "      <th>Pts</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>FC Bayern München</td>\n",
              "      <td>92</td>\n",
              "      <td>38</td>\n",
              "      <td>54</td>\n",
              "      <td>71.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Borussia Dortmund</td>\n",
              "      <td>83</td>\n",
              "      <td>44</td>\n",
              "      <td>39</td>\n",
              "      <td>71.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>RB Leipzig</td>\n",
              "      <td>64</td>\n",
              "      <td>41</td>\n",
              "      <td>23</td>\n",
              "      <td>66.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1. FC Union Berlin</td>\n",
              "      <td>51</td>\n",
              "      <td>38</td>\n",
              "      <td>13</td>\n",
              "      <td>62.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>SC Freiburg</td>\n",
              "      <td>51</td>\n",
              "      <td>44</td>\n",
              "      <td>7</td>\n",
              "      <td>59.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Bayer Leverkusen</td>\n",
              "      <td>57</td>\n",
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              "      <td>8</td>\n",
              "      <td>50.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Eintracht Frankfurt</td>\n",
              "      <td>58</td>\n",
              "      <td>52</td>\n",
              "      <td>6</td>\n",
              "      <td>50.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>VfL Wolfsburg</td>\n",
              "      <td>57</td>\n",
              "      <td>48</td>\n",
              "      <td>9</td>\n",
              "      <td>49.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>1. FSV Mainz 05</td>\n",
              "      <td>54</td>\n",
              "      <td>55</td>\n",
              "      <td>-1</td>\n",
              "      <td>46.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Borussia Mönchengladbach</td>\n",
              "      <td>52</td>\n",
              "      <td>55</td>\n",
              "      <td>-3</td>\n",
              "      <td>43.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>1. FC Köln</td>\n",
              "      <td>49</td>\n",
              "      <td>54</td>\n",
              "      <td>-5</td>\n",
              "      <td>42.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>TSG 1899 Hoffenheim</td>\n",
              "      <td>48</td>\n",
              "      <td>57</td>\n",
              "      <td>-9</td>\n",
              "      <td>36.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Werder Bremen</td>\n",
              "      <td>51</td>\n",
              "      <td>64</td>\n",
              "      <td>-13</td>\n",
              "      <td>36.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>VfL Bochum</td>\n",
              "      <td>40</td>\n",
              "      <td>72</td>\n",
              "      <td>-32</td>\n",
              "      <td>35.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>FC Augsburg</td>\n",
              "      <td>42</td>\n",
              "      <td>63</td>\n",
              "      <td>-21</td>\n",
              "      <td>34.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>VfB Stuttgart</td>\n",
              "      <td>45</td>\n",
              "      <td>57</td>\n",
              "      <td>-12</td>\n",
              "      <td>33.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>FC Schalke 04</td>\n",
              "      <td>35</td>\n",
              "      <td>71</td>\n",
              "      <td>-36</td>\n",
              "      <td>31.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Hertha BSC</td>\n",
              "      <td>42</td>\n",
              "      <td>69</td>\n",
              "      <td>-27</td>\n",
              "      <td>29.0</td>\n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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            ]
          },
          "metadata": {},
          "execution_count": 149
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### **11.1 CAMPÉON DE LA BUNDESLIGA 🏆**\n",
        "<img src=\"https://ak.uecdn.es/p/110/thumbnail/entry_id/0_kn4rpqj9/width/1200/type/2/bgcolor/000000/0_kn4rpqj9.jpg\" width=500>"
      ],
      "metadata": {
        "id": "5RfuHhcJeYMA"
      }
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    {
      "cell_type": "code",
      "source": [
        "bf_season_2022_2023.head(1)"
      ],
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        "id": "ecC4bd8Rejmc",
        "outputId": "b6ce1ef3-073c-45bc-f237-24c2e2470a34",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        }
      },
      "execution_count": 155,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    SEASON 2022-2023  GF  GA  DF   Pts\n",
              "1  FC Bayern München  92  38  54  71.0"
            ],
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              "      <th>GA</th>\n",
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              "      <th>1</th>\n",
              "      <td>FC Bayern München</td>\n",
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              "                                                     [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",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 155
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### **11.2 Descendidos de la bundesliga 😥**\n",
        "<img src=\"https://st1.uvnimg.com/3d/ff/20b404c441de9a08387dadc5ff41/marcador-bundesliga.jpeg\" width=400>"
      ],
      "metadata": {
        "id": "9pwM3Rqne0Cl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "bf_season_2022_2023.tail(3)"
      ],
      "metadata": {
        "id": "uCoGV07-e5HL",
        "outputId": "bf67bb77-fb8a-45c2-bb49-c29aa35104ff",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        }
      },
      "execution_count": 156,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   SEASON 2022-2023  GF  GA  DF   Pts\n",
              "16    VfB Stuttgart  45  57 -12  33.0\n",
              "17    FC Schalke 04  35  71 -36  31.0\n",
              "18       Hertha BSC  42  69 -27  29.0"
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              "      <td>35</td>\n",
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              "      <td>31.0</td>\n",
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              "      <th>18</th>\n",
              "      <td>Hertha BSC</td>\n",
              "      <td>42</td>\n",
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              "  "
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          "metadata": {},
          "execution_count": 156
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    }
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}