pandasEjerciciosDataFrame.ipynb

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      "source": [
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Muestra un DataFrame con los datos de la siguiente tabla:\n",
        "\n",
        "```\n",
        "  Mes     Ingresos     Gastos\n",
        "  Enero   21500        17000\n",
        "  Febrero 17600        15400\n",
        "  Marzo   25000        19200\n",
        "  Abril   34800        22500\n",
        "```\n",
        "\n"
      ],
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      "source": [
        "datos = {'Mes':['Enero','Febrero','Marzo','Abril'],'Ingresos':[21500,17600,25000,34800],'Gastos':[17000,15400,19200,22500]}\n",
        "df = pd.DataFrame(datos)\n",
        "df"
      ],
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              "       Mes  Ingresos  Gastos\n",
              "0    Enero     21500   17000\n",
              "1  Febrero     17600   15400\n",
              "2    Marzo     25000   19200\n",
              "3    Abril     34800   22500"
            ],
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              "      <th></th>\n",
              "      <th>Mes</th>\n",
              "      <th>Ingresos</th>\n",
              "      <th>Gastos</th>\n",
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              "      <th>0</th>\n",
              "      <td>Enero</td>\n",
              "      <td>21500</td>\n",
              "      <td>17000</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Febrero</td>\n",
              "      <td>17600</td>\n",
              "      <td>15400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Marzo</td>\n",
              "      <td>25000</td>\n",
              "      <td>19200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Abril</td>\n",
              "      <td>34800</td>\n",
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    },
    {
      "cell_type": "markdown",
      "source": [
        "Escribe una funcion que reciba el DataFrame del ejercicio anterior y devuelva el beneficio total de cada mes (Ingresos - Gastos).\n"
      ],
      "metadata": {
        "id": "VvUwIClSAm9V"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def beneficio(datos):\n",
        "  datos['Beneficios']=datos.Ingresos - datos.Gastos\n",
        "  return datos\n"
      ],
      "metadata": {
        "id": "Lf80YYwZADEC"
      },
      "execution_count": 5,
      "outputs": []
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    {
      "cell_type": "code",
      "source": [
        "beneficio(df)"
      ],
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              "       Mes  Ingresos  Gastos  beneficios  Beneficios\n",
              "0    Enero     21500   17000        4500        4500\n",
              "1  Febrero     17600   15400        2200        2200\n",
              "2    Marzo     25000   19200        5800        5800\n",
              "3    Abril     34800   22500       12300       12300"
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              "      <th>Mes</th>\n",
              "      <th>Ingresos</th>\n",
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              "      <th>beneficios</th>\n",
              "      <th>Beneficios</th>\n",
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              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Enero</td>\n",
              "      <td>21500</td>\n",
              "      <td>17000</td>\n",
              "      <td>4500</td>\n",
              "      <td>4500</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Febrero</td>\n",
              "      <td>17600</td>\n",
              "      <td>15400</td>\n",
              "      <td>2200</td>\n",
              "      <td>2200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Marzo</td>\n",
              "      <td>25000</td>\n",
              "      <td>19200</td>\n",
              "      <td>5800</td>\n",
              "      <td>5800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Abril</td>\n",
              "      <td>34800</td>\n",
              "      <td>22500</td>\n",
              "      <td>12300</td>\n",
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              "                                                     [key], {});\n",
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              "\n",
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              "            '<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": "markdown",
      "source": [
        "En github he subido el fichero titanic.csv (obtenido de kaggle.com) y realizar las siguientes operaciones.\n",
        "\n",
        "\n",
        "1.   Generar un DataFrame con los datos del fichero indicado.\n",
        "2.   Mostrar sus dimensiones, el numero de datos que contiene, nombres de las columnas y filas, tipos de datos de las columnas y mostrar las 5 primeras filas y las 5 ultimas.\n",
        "3.   Mostrar los datos del pasajero con identificador 121.\n",
        "4.   Mostrar las filas impares del DataFrame.\n",
        "5.   Cuantas personas sobrevivieron y murieron, indicar porcentaje.\n",
        "6.   Personas que estaban en segunda clase por orden alfabetico.\n",
        "7.   Eliminar los pasajeros que no tengan registrada su edad o sea nula.\n",
        "8.   Porcentaje de personas que murieron por cada clase.\n",
        "9.   Edad media de hombres y mujeres que viajaban en cada clase.\n",
        "10.  Añadir nueva columna que indique si el pasajero era menor de edad o no.\n",
        "11.  Mostrar el porcentaje de menores y mayores de edad que sobrevivieron.\n",
        "\n"
      ],
      "metadata": {
        "id": "crWOWAlZBNWV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "n1SAYEp9TM5g",
        "outputId": "d571d3a8-e4e7-495f-de3c-1cd1557e65dd"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#1. Cargamos dataset\n",
        "titanic = pd.read_csv('/content/drive/MyDrive/datasets/titanic.csv',index_col=0)\n",
        "titanic.head()"
      ],
      "metadata": {
        "id": "oqo_S22zA8lC",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "outputId": "3d59a694-1c1f-4fae-cf85-445300a5cca1"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             Survived  Pclass  \\\n",
              "PassengerId                     \n",
              "1                   0       3   \n",
              "2                   1       1   \n",
              "3                   1       3   \n",
              "4                   1       1   \n",
              "5                   0       3   \n",
              "\n",
              "                                                          Name     Sex   Age  \\\n",
              "PassengerId                                                                    \n",
              "1                                      Braund, Mr. Owen Harris    male  22.0   \n",
              "2            Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0   \n",
              "3                                       Heikkinen, Miss. Laina  female  26.0   \n",
              "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0   \n",
              "5                                     Allen, Mr. William Henry    male  35.0   \n",
              "\n",
              "             SibSp  Parch            Ticket     Fare Cabin Embarked  \n",
              "PassengerId                                                          \n",
              "1                1      0         A/5 21171   7.2500   NaN        S  \n",
              "2                1      0          PC 17599  71.2833   C85        C  \n",
              "3                0      0  STON/O2. 3101282   7.9250   NaN        S  \n",
              "4                1      0            113803  53.1000  C123        S  \n",
              "5                0      0            373450   8.0500   NaN        S  "
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              "      <td>22.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>A/5 21171</td>\n",
              "      <td>7.2500</td>\n",
              "      <td>NaN</td>\n",
              "      <td>S</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
              "      <td>female</td>\n",
              "      <td>38.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>PC 17599</td>\n",
              "      <td>71.2833</td>\n",
              "      <td>C85</td>\n",
              "      <td>C</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>Heikkinen, Miss. Laina</td>\n",
              "      <td>female</td>\n",
              "      <td>26.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>STON/O2. 3101282</td>\n",
              "      <td>7.9250</td>\n",
              "      <td>NaN</td>\n",
              "      <td>S</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
              "      <td>female</td>\n",
              "      <td>35.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>113803</td>\n",
              "      <td>53.1000</td>\n",
              "      <td>C123</td>\n",
              "      <td>S</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>Allen, Mr. William Henry</td>\n",
              "      <td>male</td>\n",
              "      <td>35.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>373450</td>\n",
              "      <td>8.0500</td>\n",
              "      <td>NaN</td>\n",
              "      <td>S</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e11853a9-a4e4-40ce-9346-6bb50151932f')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "    .colab-df-convert:hover {\n",
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              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-e11853a9-a4e4-40ce-9346-6bb50151932f 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-e11853a9-a4e4-40ce-9346-6bb50151932f');\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",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#2. Mostramos dimensiones\n",
        "print(\"Dimensiones : \",titanic.shape)\n",
        "print(\"Numero de datos : \",titanic.size)\n",
        "print(\"Columnas : \",titanic.columns)\n",
        "print(\"Filas : \",titanic.index)\n",
        "print(\"Tipos de datos : \",titanic.dtypes)\n",
        "print(\"Primeras filas :\",titanic.head(5))\n",
        "print(\"Ultimas filas : \",titanic.tail(5))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "C72NXfX5UF45",
        "outputId": "a2d5a51f-3dfd-4f05-db9b-b84663064d04"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dimensiones :  (891, 11)\n",
            "Numero de datos :  9801\n",
            "Columnas :  Index(['Survived', 'Pclass', 'Name', 'Sex', 'Age', 'SibSp', 'Parch', 'Ticket',\n",
            "       'Fare', 'Cabin', 'Embarked'],\n",
            "      dtype='object')\n",
            "Filas :  Int64Index([  1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
            "            ...\n",
            "            882, 883, 884, 885, 886, 887, 888, 889, 890, 891],\n",
            "           dtype='int64', name='PassengerId', length=891)\n",
            "Tipos de datos :  Survived      int64\n",
            "Pclass        int64\n",
            "Name         object\n",
            "Sex          object\n",
            "Age         float64\n",
            "SibSp         int64\n",
            "Parch         int64\n",
            "Ticket       object\n",
            "Fare        float64\n",
            "Cabin        object\n",
            "Embarked     object\n",
            "dtype: object\n",
            "Primeras filas :              Survived  Pclass  \\\n",
            "PassengerId                     \n",
            "1                   0       3   \n",
            "2                   1       1   \n",
            "3                   1       3   \n",
            "4                   1       1   \n",
            "5                   0       3   \n",
            "\n",
            "                                                          Name     Sex   Age  \\\n",
            "PassengerId                                                                    \n",
            "1                                      Braund, Mr. Owen Harris    male  22.0   \n",
            "2            Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0   \n",
            "3                                       Heikkinen, Miss. Laina  female  26.0   \n",
            "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0   \n",
            "5                                     Allen, Mr. William Henry    male  35.0   \n",
            "\n",
            "             SibSp  Parch            Ticket     Fare Cabin Embarked  \n",
            "PassengerId                                                          \n",
            "1                1      0         A/5 21171   7.2500   NaN        S  \n",
            "2                1      0          PC 17599  71.2833   C85        C  \n",
            "3                0      0  STON/O2. 3101282   7.9250   NaN        S  \n",
            "4                1      0            113803  53.1000  C123        S  \n",
            "5                0      0            373450   8.0500   NaN        S  \n",
            "Ultimas filas :               Survived  Pclass                                      Name  \\\n",
            "PassengerId                                                               \n",
            "887                 0       2                     Montvila, Rev. Juozas   \n",
            "888                 1       1              Graham, Miss. Margaret Edith   \n",
            "889                 0       3  Johnston, Miss. Catherine Helen \"Carrie\"   \n",
            "890                 1       1                     Behr, Mr. Karl Howell   \n",
            "891                 0       3                       Dooley, Mr. Patrick   \n",
            "\n",
            "                Sex   Age  SibSp  Parch      Ticket   Fare Cabin Embarked  \n",
            "PassengerId                                                                \n",
            "887            male  27.0      0      0      211536  13.00   NaN        S  \n",
            "888          female  19.0      0      0      112053  30.00   B42        S  \n",
            "889          female   NaN      1      2  W./C. 6607  23.45   NaN        S  \n",
            "890            male  26.0      0      0      111369  30.00  C148        C  \n",
            "891            male  32.0      0      0      370376   7.75   NaN        Q  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#3. Pasajero 121\n",
        "titanic.loc[121]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RvTzn4QXUpLM",
        "outputId": "c17fbc70-9c2d-48f4-8c38-07dce4bee2cc"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Survived                              0\n",
              "Pclass                                2\n",
              "Name        Hickman, Mr. Stanley George\n",
              "Sex                                male\n",
              "Age                                21.0\n",
              "SibSp                                 2\n",
              "Parch                                 0\n",
              "Ticket                     S.O.C. 14879\n",
              "Fare                               73.5\n",
              "Cabin                               NaN\n",
              "Embarked                              S\n",
              "Name: 121, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#4. Filas impares\n",
        "titanic_impares = titanic.iloc[range(0,titanic.shape[0],2)]\n",
        "titanic_impares.head(15)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 595
        },
        "id": "1lze0boEVqhw",
        "outputId": "547f9386-79d0-4416-cfc6-7a23769d0eea"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             Survived  Pclass  \\\n",
              "PassengerId                     \n",
              "1                   0       3   \n",
              "3                   1       3   \n",
              "5                   0       3   \n",
              "7                   0       1   \n",
              "9                   1       3   \n",
              "11                  1       3   \n",
              "13                  0       3   \n",
              "15                  0       3   \n",
              "17                  0       3   \n",
              "19                  0       3   \n",
              "21                  0       2   \n",
              "23                  1       3   \n",
              "25                  0       3   \n",
              "27                  0       3   \n",
              "29                  1       3   \n",
              "\n",
              "                                                          Name     Sex   Age  \\\n",
              "PassengerId                                                                    \n",
              "1                                      Braund, Mr. Owen Harris    male  22.0   \n",
              "3                                       Heikkinen, Miss. Laina  female  26.0   \n",
              "5                                     Allen, Mr. William Henry    male  35.0   \n",
              "7                                      McCarthy, Mr. Timothy J    male  54.0   \n",
              "9            Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)  female  27.0   \n",
              "11                             Sandstrom, Miss. Marguerite Rut  female   4.0   \n",
              "13                              Saundercock, Mr. William Henry    male  20.0   \n",
              "15                        Vestrom, Miss. Hulda Amanda Adolfina  female  14.0   \n",
              "17                                        Rice, Master. Eugene    male   2.0   \n",
              "19           Vander Planke, Mrs. Julius (Emelia Maria Vande...  female  31.0   \n",
              "21                                        Fynney, Mr. Joseph J    male  35.0   \n",
              "23                                 McGowan, Miss. Anna \"Annie\"  female  15.0   \n",
              "25                               Palsson, Miss. Torborg Danira  female   8.0   \n",
              "27                                     Emir, Mr. Farred Chehab    male   NaN   \n",
              "29                               O'Dwyer, Miss. Ellen \"Nellie\"  female   NaN   \n",
              "\n",
              "             SibSp  Parch            Ticket     Fare Cabin Embarked  \n",
              "PassengerId                                                          \n",
              "1                1      0         A/5 21171   7.2500   NaN        S  \n",
              "3                0      0  STON/O2. 3101282   7.9250   NaN        S  \n",
              "5                0      0            373450   8.0500   NaN        S  \n",
              "7                0      0             17463  51.8625   E46        S  \n",
              "9                0      2            347742  11.1333   NaN        S  \n",
              "11               1      1           PP 9549  16.7000    G6        S  \n",
              "13               0      0         A/5. 2151   8.0500   NaN        S  \n",
              "15               0      0            350406   7.8542   NaN        S  \n",
              "17               4      1            382652  29.1250   NaN        Q  \n",
              "19               1      0            345763  18.0000   NaN        S  \n",
              "21               0      0            239865  26.0000   NaN        S  \n",
              "23               0      0            330923   8.0292   NaN        Q  \n",
              "25               3      1            349909  21.0750   NaN        S  \n",
              "27               0      0              2631   7.2250   NaN        C  \n",
              "29               0      0            330959   7.8792   NaN        Q  "
            ],
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              "      <td>female</td>\n",
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              "      <td>Rice, Master. Eugene</td>\n",
              "      <td>male</td>\n",
              "      <td>2.0</td>\n",
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              "      <td>NaN</td>\n",
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              "      <th>19</th>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>Vander Planke, Mrs. Julius (Emelia Maria Vande...</td>\n",
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              "      <th>21</th>\n",
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              "      <td>2</td>\n",
              "      <td>Fynney, Mr. Joseph J</td>\n",
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              "      <th>23</th>\n",
              "      <td>1</td>\n",
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              "      <td>McGowan, Miss. Anna \"Annie\"</td>\n",
              "      <td>female</td>\n",
              "      <td>15.0</td>\n",
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              "      <td>NaN</td>\n",
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              "      <th>25</th>\n",
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              "      <td>Palsson, Miss. Torborg Danira</td>\n",
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              "      <th>27</th>\n",
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              "      <td>Emir, Mr. Farred Chehab</td>\n",
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              "      <td>C</td>\n",
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              "      <th>29</th>\n",
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              "      <td>O'Dwyer, Miss. Ellen \"Nellie\"</td>\n",
              "      <td>female</td>\n",
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              "      <td>Q</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fe5b3af0-d566-48ce-ba49-71e1270c2461')\"\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#5. Supervivientes\n",
        "porcentaje_titanic=titanic['Survived'].value_counts()/titanic['Survived'].count()*100\n",
        "porcentaje_titanic"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Jpt7NkFrWKpW",
        "outputId": "6b1fc8a4-3826-47cf-cb44-93ffad0426ee"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    61.616162\n",
              "1    38.383838\n",
              "Name: Survived, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#6. Segunda clase\n",
        "pasajeros_segunda=titanic[titanic['Pclass']==2]['Name'].sort_values()\n",
        "pasajeros_segunda.head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U8LqC2J_Wuf4",
        "outputId": "16997d23-8d1c-4485-d481-1aeb0f5a9c93"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PassengerId\n",
              "309                                  Abelson, Mr. Samuel\n",
              "875                Abelson, Mrs. Samuel (Hannah Wizosky)\n",
              "145                           Andrew, Mr. Edgardo Samuel\n",
              "519    Angle, Mrs. William A (Florence \"Mary\" Agnes H...\n",
              "758                             Bailey, Mr. Percy Andrew\n",
              "Name: Name, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#7. Elimina nulos edad\n",
        "titanic=titanic.dropna(subset=['Age'])\n",
        "titanic"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "VVd3_H1tXbhB",
        "outputId": "5cde5af8-e00f-4f50-fc92-676065ee8110"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             Survived  Pclass  \\\n",
              "PassengerId                     \n",
              "1                   0       3   \n",
              "2                   1       1   \n",
              "3                   1       3   \n",
              "4                   1       1   \n",
              "5                   0       3   \n",
              "...               ...     ...   \n",
              "886                 0       3   \n",
              "887                 0       2   \n",
              "888                 1       1   \n",
              "890                 1       1   \n",
              "891                 0       3   \n",
              "\n",
              "                                                          Name     Sex   Age  \\\n",
              "PassengerId                                                                    \n",
              "1                                      Braund, Mr. Owen Harris    male  22.0   \n",
              "2            Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0   \n",
              "3                                       Heikkinen, Miss. Laina  female  26.0   \n",
              "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0   \n",
              "5                                     Allen, Mr. William Henry    male  35.0   \n",
              "...                                                        ...     ...   ...   \n",
              "886                       Rice, Mrs. William (Margaret Norton)  female  39.0   \n",
              "887                                      Montvila, Rev. Juozas    male  27.0   \n",
              "888                               Graham, Miss. Margaret Edith  female  19.0   \n",
              "890                                      Behr, Mr. Karl Howell    male  26.0   \n",
              "891                                        Dooley, Mr. Patrick    male  32.0   \n",
              "\n",
              "             SibSp  Parch            Ticket     Fare Cabin Embarked  \n",
              "PassengerId                                                          \n",
              "1                1      0         A/5 21171   7.2500   NaN        S  \n",
              "2                1      0          PC 17599  71.2833   C85        C  \n",
              "3                0      0  STON/O2. 3101282   7.9250   NaN        S  \n",
              "4                1      0            113803  53.1000  C123        S  \n",
              "5                0      0            373450   8.0500   NaN        S  \n",
              "...            ...    ...               ...      ...   ...      ...  \n",
              "886              0      5            382652  29.1250   NaN        Q  \n",
              "887              0      0            211536  13.0000   NaN        S  \n",
              "888              0      0            112053  30.0000   B42        S  \n",
              "890              0      0            111369  30.0000  C148        C  \n",
              "891              0      0            370376   7.7500   NaN        Q  \n",
              "\n",
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              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-7dd70e70-2cd5-4d5e-83e7-5e32cd549f51 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-7dd70e70-2cd5-4d5e-83e7-5e32cd549f51');\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",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#8. Muertos por clase\n",
        "titanic_por_clase=titanic.groupby('Pclass')['Survived'].value_counts(normalize=True)*100\n",
        "titanic_por_clase"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p9d9xcM7X7NE",
        "outputId": "f80e8ab4-bfbc-404f-9eea-61f6b3ed82d9"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Pclass  Survived\n",
              "1       1           65.591398\n",
              "        0           34.408602\n",
              "2       0           52.023121\n",
              "        1           47.976879\n",
              "3       0           76.056338\n",
              "        1           23.943662\n",
              "Name: Survived, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#9. Edad media por clase\n",
        "titanic.groupby(['Pclass','Sex'])['Age'].mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Nrs_Bq6rYoGs",
        "outputId": "27cbe1bb-60ad-45ea-cc20-6c1bb67146f8"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Pclass  Sex   \n",
              "1       female    34.611765\n",
              "        male      41.281386\n",
              "2       female    28.722973\n",
              "        male      30.740707\n",
              "3       female    21.750000\n",
              "        male      26.507589\n",
              "Name: Age, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#10. Menor de edad\n",
        "titanic['Menor']=titanic['Age']<18\n",
        "titanic.head(15)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 647
        },
        "id": "xwfoyPMFaBKk",
        "outputId": "1d018b5a-cfab-468a-88d2-12bfb9f5d211"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             Survived  Pclass  \\\n",
              "PassengerId                     \n",
              "1                   0       3   \n",
              "2                   1       1   \n",
              "3                   1       3   \n",
              "4                   1       1   \n",
              "5                   0       3   \n",
              "7                   0       1   \n",
              "8                   0       3   \n",
              "9                   1       3   \n",
              "10                  1       2   \n",
              "11                  1       3   \n",
              "12                  1       1   \n",
              "13                  0       3   \n",
              "14                  0       3   \n",
              "15                  0       3   \n",
              "16                  1       2   \n",
              "\n",
              "                                                          Name     Sex   Age  \\\n",
              "PassengerId                                                                    \n",
              "1                                      Braund, Mr. Owen Harris    male  22.0   \n",
              "2            Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0   \n",
              "3                                       Heikkinen, Miss. Laina  female  26.0   \n",
              "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0   \n",
              "5                                     Allen, Mr. William Henry    male  35.0   \n",
              "7                                      McCarthy, Mr. Timothy J    male  54.0   \n",
              "8                               Palsson, Master. Gosta Leonard    male   2.0   \n",
              "9            Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)  female  27.0   \n",
              "10                         Nasser, Mrs. Nicholas (Adele Achem)  female  14.0   \n",
              "11                             Sandstrom, Miss. Marguerite Rut  female   4.0   \n",
              "12                                    Bonnell, Miss. Elizabeth  female  58.0   \n",
              "13                              Saundercock, Mr. William Henry    male  20.0   \n",
              "14                                 Andersson, Mr. Anders Johan    male  39.0   \n",
              "15                        Vestrom, Miss. Hulda Amanda Adolfina  female  14.0   \n",
              "16                            Hewlett, Mrs. (Mary D Kingcome)   female  55.0   \n",
              "\n",
              "             SibSp  Parch            Ticket     Fare Cabin Embarked  Menor  \n",
              "PassengerId                                                                 \n",
              "1                1      0         A/5 21171   7.2500   NaN        S  False  \n",
              "2                1      0          PC 17599  71.2833   C85        C  False  \n",
              "3                0      0  STON/O2. 3101282   7.9250   NaN        S  False  \n",
              "4                1      0            113803  53.1000  C123        S  False  \n",
              "5                0      0            373450   8.0500   NaN        S  False  \n",
              "7                0      0             17463  51.8625   E46        S  False  \n",
              "8                3      1            349909  21.0750   NaN        S   True  \n",
              "9                0      2            347742  11.1333   NaN        S  False  \n",
              "10               1      0            237736  30.0708   NaN        C   True  \n",
              "11               1      1           PP 9549  16.7000    G6        S   True  \n",
              "12               0      0            113783  26.5500  C103        S  False  \n",
              "13               0      0         A/5. 2151   8.0500   NaN        S  False  \n",
              "14               1      5            347082  31.2750   NaN        S  False  \n",
              "15               0      0            350406   7.8542   NaN        S   True  \n",
              "16               0      0            248706  16.0000   NaN        S  False  "
            ],
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              "      <td>Heikkinen, Miss. Laina</td>\n",
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              "      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-2bbf873c-a9fe-4e78-afec-f7e4415be459 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-2bbf873c-a9fe-4e78-afec-f7e4415be459');\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": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#11. Menores y mayores\n",
        "titanic.groupby(['Pclass','Menor'])['Survived'].value_counts(normalize=True)*100"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "N2GhxPkcahYD",
        "outputId": "2234b763-a999-4750-f97e-b6cd1c576da5"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Pclass  Menor  Survived\n",
              "1       False  1           63.793103\n",
              "               0           36.206897\n",
              "        True   1           91.666667\n",
              "               0            8.333333\n",
              "2       False  0           58.666667\n",
              "               1           41.333333\n",
              "        True   1           91.304348\n",
              "               0            8.695652\n",
              "3       False  0           79.783394\n",
              "               1           20.216606\n",
              "        True   0           62.820513\n",
              "               1           37.179487\n",
              "Name: Survived, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "4tfqrLjbbR8R"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}