3-Aplicando-pandas/16_Group_by_Extrayendo_valor_con_variables_categóricas.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "16.Group by - Extrayendo valor con variables categóricas.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyMuOVDZ21Obzy4Hw7s1qnh2",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/francomanca93/analisis-de-datos/blob/aplicaciones/3-Aplicando-pandas/16_Group_by_Extrayendo_valor_con_variables_categ%C3%B3ricas.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "E0J4Zg51cYdV",
        "colab_type": "text"
      },
      "source": [
        "# Group by - Refozando el uso de esta función\n",
        "\n",
        "En esta sección veremos nuevamente Group by y rezorzaremos con otro dataframe el uso de esta función. Veremos como agrupar nuetro dataframe bajo una categoria y sobre esta aplicar algunas funciones estadísticas. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xt2XXQnbcGpA",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ],
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0txMIaj8c4J7",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "pd.options.display.float_format = '{:,.2f}'.format"
      ],
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xEXSRwHSdGa6",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import seaborn as sns"
      ],
      "execution_count": 45,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "B5ANhRgxdbUu",
        "colab_type": "text"
      },
      "source": [
        "El dataset sobre el que trabajaremos es sobre **propinas**. En él aparecen parámetros sobre la cuenta, la propina que dieron las personas, si fue un hombre o mujer, si era fumador, tambien si como era el día (soleado, nublado, etc), el horario de la misma (desayuno, almuerzo, cena, etc) y cuantas personas compartian la comida. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DPh-JM_UdJXA",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "b0bb3225-9d7b-4be3-db1b-5b1979e3ba49"
      },
      "source": [
        "df = sns.load_dataset('tips')\n",
        "df"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>sex</th>\n",
              "      <th>smoker</th>\n",
              "      <th>day</th>\n",
              "      <th>time</th>\n",
              "      <th>size</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>16.99</td>\n",
              "      <td>1.01</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.34</td>\n",
              "      <td>1.66</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>21.01</td>\n",
              "      <td>3.50</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23.68</td>\n",
              "      <td>3.31</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24.59</td>\n",
              "      <td>3.61</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>239</th>\n",
              "      <td>29.03</td>\n",
              "      <td>5.92</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>27.18</td>\n",
              "      <td>2.00</td>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>22.67</td>\n",
              "      <td>2.00</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>17.82</td>\n",
              "      <td>1.75</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>18.78</td>\n",
              "      <td>3.00</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Thur</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>244 rows × 7 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     total_bill  tip     sex smoker   day    time  size\n",
              "0         16.99 1.01  Female     No   Sun  Dinner     2\n",
              "1         10.34 1.66    Male     No   Sun  Dinner     3\n",
              "2         21.01 3.50    Male     No   Sun  Dinner     3\n",
              "3         23.68 3.31    Male     No   Sun  Dinner     2\n",
              "4         24.59 3.61  Female     No   Sun  Dinner     4\n",
              "..          ...  ...     ...    ...   ...     ...   ...\n",
              "239       29.03 5.92    Male     No   Sat  Dinner     3\n",
              "240       27.18 2.00  Female    Yes   Sat  Dinner     2\n",
              "241       22.67 2.00    Male    Yes   Sat  Dinner     2\n",
              "242       17.82 1.75    Male     No   Sat  Dinner     2\n",
              "243       18.78 3.00  Female     No  Thur  Dinner     2\n",
              "\n",
              "[244 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LgTxEsVMdZfc",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "outputId": "1259b2ae-169a-4d81-b5f4-b33b14480257"
      },
      "source": [
        "df.describe(include='all')"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>sex</th>\n",
              "      <th>smoker</th>\n",
              "      <th>day</th>\n",
              "      <th>time</th>\n",
              "      <th>size</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>244.00</td>\n",
              "      <td>244.00</td>\n",
              "      <td>244</td>\n",
              "      <td>244</td>\n",
              "      <td>244</td>\n",
              "      <td>244</td>\n",
              "      <td>244.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>unique</th>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>top</th>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>freq</th>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>157</td>\n",
              "      <td>151</td>\n",
              "      <td>87</td>\n",
              "      <td>176</td>\n",
              "      <td>nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>19.79</td>\n",
              "      <td>3.00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>8.90</td>\n",
              "      <td>1.38</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>3.07</td>\n",
              "      <td>1.00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>13.35</td>\n",
              "      <td>2.00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>17.80</td>\n",
              "      <td>2.90</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>24.13</td>\n",
              "      <td>3.56</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>50.81</td>\n",
              "      <td>10.00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>6.00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        total_bill    tip   sex smoker  day    time   size\n",
              "count       244.00 244.00   244    244  244     244 244.00\n",
              "unique         nan    nan     2      2    4       2    nan\n",
              "top            nan    nan  Male     No  Sat  Dinner    nan\n",
              "freq           nan    nan   157    151   87     176    nan\n",
              "mean         19.79   3.00   NaN    NaN  NaN     NaN   2.57\n",
              "std           8.90   1.38   NaN    NaN  NaN     NaN   0.95\n",
              "min           3.07   1.00   NaN    NaN  NaN     NaN   1.00\n",
              "25%          13.35   2.00   NaN    NaN  NaN     NaN   2.00\n",
              "50%          17.80   2.90   NaN    NaN  NaN     NaN   2.00\n",
              "75%          24.13   3.56   NaN    NaN  NaN     NaN   3.00\n",
              "max          50.81  10.00   NaN    NaN  NaN     NaN   6.00"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qHilqHhH1sBN",
        "colab_type": "text"
      },
      "source": [
        "La variable **day** tiene 4 categorias. Veamos a esas 4 categorias y contemos cuantas veces se repiten cada una. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OHfaSg1z1CYM",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 104
        },
        "outputId": "2fd17d44-ccc5-4352-af42-5811c348528b"
      },
      "source": [
        "df['day'].value_counts()"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Sat     87\n",
              "Sun     76\n",
              "Thur    62\n",
              "Fri     19\n",
              "Name: day, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4xnJL-NV5DOl",
        "colab_type": "text"
      },
      "source": [
        "Ahora veamos en % los numeros anteriores. Lo que hacemos es dividir la suma de los valores a cada valor y multiplicarlo por 100."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dSgwzfoR1YHX",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 104
        },
        "outputId": "646ac142-23be-48b5-bc85-4a7b846331c1"
      },
      "source": [
        "df['day'].value_counts() / df['day'].value_counts().sum() * 100"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Sat    35.66\n",
              "Sun    31.15\n",
              "Thur   25.41\n",
              "Fri     7.79\n",
              "Name: day, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2XMSwDhK5m29",
        "colab_type": "text"
      },
      "source": [
        "Podemos tener estimaciones estadisticas por alguna de nuestras categorias. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DhYoa_o81fO0",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "d096f2d8-8381-45ac-867a-f0371a67a204"
      },
      "source": [
        "df.groupby('sex').mean()"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>size</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Male</th>\n",
              "      <td>20.74</td>\n",
              "      <td>3.09</td>\n",
              "      <td>2.63</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>18.06</td>\n",
              "      <td>2.83</td>\n",
              "      <td>2.46</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        total_bill  tip  size\n",
              "sex                          \n",
              "Male         20.74 3.09  2.63\n",
              "Female       18.06 2.83  2.46"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VnmqqQcJ6PFr",
        "colab_type": "text"
      },
      "source": [
        "Veamos en porcentaje cuanto corresponde la propina respecto al total de la cuenta."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "d8C2Yc235hbV",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "20cd7bfb-c4b5-4b05-b803-0bfa06873a89"
      },
      "source": [
        "df['porcet_tip'] = df['tip'] / df['total_bill']\n",
        "df"
      ],
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>sex</th>\n",
              "      <th>smoker</th>\n",
              "      <th>day</th>\n",
              "      <th>time</th>\n",
              "      <th>size</th>\n",
              "      <th>porcet_tip</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>16.99</td>\n",
              "      <td>1.01</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.34</td>\n",
              "      <td>1.66</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>21.01</td>\n",
              "      <td>3.50</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23.68</td>\n",
              "      <td>3.31</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24.59</td>\n",
              "      <td>3.61</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>4</td>\n",
              "      <td>0.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>239</th>\n",
              "      <td>29.03</td>\n",
              "      <td>5.92</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>27.18</td>\n",
              "      <td>2.00</td>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>22.67</td>\n",
              "      <td>2.00</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>17.82</td>\n",
              "      <td>1.75</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>18.78</td>\n",
              "      <td>3.00</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Thur</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.16</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>244 rows × 8 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     total_bill  tip     sex smoker   day    time  size  porcet_tip\n",
              "0         16.99 1.01  Female     No   Sun  Dinner     2        0.06\n",
              "1         10.34 1.66    Male     No   Sun  Dinner     3        0.16\n",
              "2         21.01 3.50    Male     No   Sun  Dinner     3        0.17\n",
              "3         23.68 3.31    Male     No   Sun  Dinner     2        0.14\n",
              "4         24.59 3.61  Female     No   Sun  Dinner     4        0.15\n",
              "..          ...  ...     ...    ...   ...     ...   ...         ...\n",
              "239       29.03 5.92    Male     No   Sat  Dinner     3        0.20\n",
              "240       27.18 2.00  Female    Yes   Sat  Dinner     2        0.07\n",
              "241       22.67 2.00    Male    Yes   Sat  Dinner     2        0.09\n",
              "242       17.82 1.75    Male     No   Sat  Dinner     2        0.10\n",
              "243       18.78 3.00  Female     No  Thur  Dinner     2        0.16\n",
              "\n",
              "[244 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HJVXjZzy6JVH",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "a7dbd59e-2a64-4b24-eb77-73627a07dfa4"
      },
      "source": [
        "df.groupby('sex').mean()"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>size</th>\n",
              "      <th>porcet_tip</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Male</th>\n",
              "      <td>20.74</td>\n",
              "      <td>3.09</td>\n",
              "      <td>2.63</td>\n",
              "      <td>0.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>18.06</td>\n",
              "      <td>2.83</td>\n",
              "      <td>2.46</td>\n",
              "      <td>0.17</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        total_bill  tip  size  porcet_tip\n",
              "sex                                      \n",
              "Male         20.74 3.09  2.63        0.16\n",
              "Female       18.06 2.83  2.46        0.17"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iJV306u768nD",
        "colab_type": "text"
      },
      "source": [
        "La porcentaje de propina en las mujeres respecto al total de su cuenta es mayor que el de los hombres. Con esto se puede concluir que las mujeres dejan mayores propinas. \n",
        "\n",
        "Podemos utilizar la función median() que tiene en cuenta una distribución normal de los datos y podemos estimar un porcentaje de propina mas aproximado a lo real. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kk0P8Dz-63-L",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "fddf2dae-4b7e-468a-aaf3-ccc7fc0ef42f"
      },
      "source": [
        "df.groupby('sex').median()"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>size</th>\n",
              "      <th>porcet_tip</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Male</th>\n",
              "      <td>18.35</td>\n",
              "      <td>3.00</td>\n",
              "      <td>2</td>\n",
              "      <td>0.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>16.40</td>\n",
              "      <td>2.75</td>\n",
              "      <td>2</td>\n",
              "      <td>0.16</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        total_bill  tip  size  porcet_tip\n",
              "sex                                      \n",
              "Male         18.35 3.00     2        0.15\n",
              "Female       16.40 2.75     2        0.16"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AshIgsNf76Ra",
        "colab_type": "text"
      },
      "source": [
        "Tambien podemos ver estimadores estadisticos por agrupaciones. En este caso agrupamos por **sex** y luego describimos estadisticamente la bajo la columna **porcet_tip**."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UJxOLK4Y7TKt",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "outputId": "3b2decda-cbb8-44cb-b3fa-41d4452d09f7"
      },
      "source": [
        "df.groupby('sex')[['porcet_tip']].describe()"
      ],
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr th {\n",
              "        text-align: left;\n",
              "    }\n",
              "\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=\"8\" halign=\"left\">porcet_tip</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th></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>Male</th>\n",
              "      <td>157.00</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.12</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>87.00</td>\n",
              "      <td>0.17</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.14</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.42</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       porcet_tip                                   \n",
              "            count mean  std  min  25%  50%  75%  max\n",
              "sex                                                 \n",
              "Male       157.00 0.16 0.06 0.04 0.12 0.15 0.19 0.71\n",
              "Female      87.00 0.17 0.05 0.06 0.14 0.16 0.19 0.42"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4MINhTZ48VfG",
        "colab_type": "text"
      },
      "source": [
        "O lo podemos hacer con dos culumnas."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xMreFopH7rRG",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "outputId": "006d8ed3-632c-491d-d5ef-d9292cca3c39"
      },
      "source": [
        "df.groupby('sex')[['total_bill','porcet_tip']].describe()"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr th {\n",
              "        text-align: left;\n",
              "    }\n",
              "\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=\"8\" halign=\"left\">total_bill</th>\n",
              "      <th colspan=\"8\" halign=\"left\">porcet_tip</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "      <th>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></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>Male</th>\n",
              "      <td>157.00</td>\n",
              "      <td>20.74</td>\n",
              "      <td>9.25</td>\n",
              "      <td>7.25</td>\n",
              "      <td>14.00</td>\n",
              "      <td>18.35</td>\n",
              "      <td>24.71</td>\n",
              "      <td>50.81</td>\n",
              "      <td>157.00</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.12</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>87.00</td>\n",
              "      <td>18.06</td>\n",
              "      <td>8.01</td>\n",
              "      <td>3.07</td>\n",
              "      <td>12.75</td>\n",
              "      <td>16.40</td>\n",
              "      <td>21.52</td>\n",
              "      <td>44.30</td>\n",
              "      <td>87.00</td>\n",
              "      <td>0.17</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.14</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.42</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       total_bill                              ... porcet_tip                         \n",
              "            count  mean  std  min   25%   50%  ...        std  min  25%  50%  75%  max\n",
              "sex                                            ...                                    \n",
              "Male       157.00 20.74 9.25 7.25 14.00 18.35  ...       0.06 0.04 0.12 0.15 0.19 0.71\n",
              "Female      87.00 18.06 8.01 3.07 12.75 16.40  ...       0.05 0.06 0.14 0.16 0.19 0.42\n",
              "\n",
              "[2 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p7wW6URD8sPv",
        "colab_type": "text"
      },
      "source": [
        "Creemoa una funcion para pasar de euros a dolares las cuenta, asumiendo que todo se encuentra en euros."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ncvc4VEH8SbR",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def mean_eur2usd(x):\n",
        "  return np.mean(x) * 1.12"
      ],
      "execution_count": 56,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lXv4T4ek8lNW",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "81bffda1-b0dc-42d3-d522-62ffe0a81a2f"
      },
      "source": [
        "mean_eur2usd(100)"
      ],
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "112.00000000000001"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aGH1W0G09Jqz",
        "colab_type": "text"
      },
      "source": [
        "Podemos aplicar nuestra función a un solo grupo creado por nosotros o a varios grupos. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p_3UAa3R8oLm",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "768bd3cc-8a77-4ca3-beac-1f06a3c787b1"
      },
      "source": [
        "df.groupby('sex')[['total_bill','porcet_tip']].apply(mean_eur2usd)"
      ],
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>porcet_tip</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Male</th>\n",
              "      <td>23.23</td>\n",
              "      <td>0.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>20.22</td>\n",
              "      <td>0.19</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        total_bill  porcet_tip\n",
              "sex                           \n",
              "Male         23.23        0.18\n",
              "Female       20.22        0.19"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4Tu2zxJx83hs",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "23c07630-16c6-483a-9e02-86f15d1d3b84"
      },
      "source": [
        "df.groupby(['sex','time'])[['total_bill','porcet_tip']].apply(mean_eur2usd)"
      ],
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>porcet_tip</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th>time</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Male</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>20.21</td>\n",
              "      <td>0.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>24.04</td>\n",
              "      <td>0.17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>18.30</td>\n",
              "      <td>0.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>21.52</td>\n",
              "      <td>0.19</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               total_bill  porcet_tip\n",
              "sex    time                          \n",
              "Male   Lunch        20.21        0.19\n",
              "       Dinner       24.04        0.17\n",
              "Female Lunch        18.30        0.18\n",
              "       Dinner       21.52        0.19"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "An0ovorfBz9X",
        "colab_type": "text"
      },
      "source": [
        "Podemos realizar lo mismo que la funcion creada pero con lambdas."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YuLKZY5Q9VOQ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "50846178-d6e2-43ed-b369-45362e15b9d5"
      },
      "source": [
        "df.groupby(['sex','time'])[['total_bill','porcet_tip']].apply(lambda x:np.mean(x) * 1.12)"
      ],
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>porcet_tip</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th>time</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Male</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>20.21</td>\n",
              "      <td>0.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>24.04</td>\n",
              "      <td>0.17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>18.30</td>\n",
              "      <td>0.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>21.52</td>\n",
              "      <td>0.19</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               total_bill  porcet_tip\n",
              "sex    time                          \n",
              "Male   Lunch        20.21        0.19\n",
              "       Dinner       24.04        0.17\n",
              "Female Lunch        18.30        0.18\n",
              "       Dinner       21.52        0.19"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2IuRqLIK9XR8",
        "colab_type": "text"
      },
      "source": [
        "Podemos calcular la desviación estadar sobre nuestro grupo."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MPAh_zsZ8-nT",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "66415c24-39ca-41a3-d4e5-7ff7f6de5b2a"
      },
      "source": [
        "df.groupby(['sex','time'])[['total_bill','porcet_tip']].apply(np.std)"
      ],
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>porcet_tip</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th>time</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Male</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>7.83</td>\n",
              "      <td>0.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>9.42</td>\n",
              "      <td>0.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>7.39</td>\n",
              "      <td>0.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>8.12</td>\n",
              "      <td>0.06</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               total_bill  porcet_tip\n",
              "sex    time                          \n",
              "Male   Lunch         7.83        0.05\n",
              "       Dinner        9.42        0.07\n",
              "Female Lunch         7.39        0.03\n",
              "       Dinner        8.12        0.06"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J-dXn_mBB9ja",
        "colab_type": "text"
      },
      "source": [
        "Si quisieramos utilizar mas de una funcion podemos utilizar aggregate"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uxaPTSbuBrAD",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "outputId": "f22a5601-8d2b-4dfa-f1fe-027bf3abf728"
      },
      "source": [
        "df.groupby(['sex','time'])[['total_bill','porcet_tip']].aggregate([np.mean, np.max])"
      ],
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr th {\n",
              "        text-align: left;\n",
              "    }\n",
              "\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></th>\n",
              "      <th colspan=\"2\" halign=\"left\">total_bill</th>\n",
              "      <th colspan=\"2\" halign=\"left\">porcet_tip</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>mean</th>\n",
              "      <th>amax</th>\n",
              "      <th>mean</th>\n",
              "      <th>amax</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th>time</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Male</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>18.05</td>\n",
              "      <td>41.19</td>\n",
              "      <td>0.17</td>\n",
              "      <td>0.27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>21.46</td>\n",
              "      <td>50.81</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>16.34</td>\n",
              "      <td>43.11</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>19.21</td>\n",
              "      <td>44.30</td>\n",
              "      <td>0.17</td>\n",
              "      <td>0.42</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              total_bill       porcet_tip     \n",
              "                    mean  amax       mean amax\n",
              "sex    time                                   \n",
              "Male   Lunch       18.05 41.19       0.17 0.27\n",
              "       Dinner      21.46 50.81       0.16 0.71\n",
              "Female Lunch       16.34 43.11       0.16 0.26\n",
              "       Dinner      19.21 44.30       0.17 0.42"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TaVmFsZ2CXmj",
        "colab_type": "text"
      },
      "source": [
        "Utilizando aggregate podemos tambien agregar diferentes funciones, tambien podemos crear un diccionario para agregar difenretes funciones por categoria, como por ejemplo:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CPT2o130Ci6P",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "outputId": "8e0da90f-2266-46fe-cc59-4c42e6cbda9f"
      },
      "source": [
        "dict_agg = {\n",
        "    'tip':[min, max],\n",
        "    'total_bill':[np.mean, mean_eur2usd]\n",
        "}\n",
        "\n",
        "dict_agg"
      ],
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'tip': [<function min>, <function max>],\n",
              " 'total_bill': [<function numpy.mean>, <function __main__.mean_eur2usd>]}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-XfDXL7LCIXC",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "outputId": "a5700bbe-fb6f-4490-933b-6959288ecae4"
      },
      "source": [
        "df.groupby(['sex','time'])[['total_bill','tip']].agg(dict_agg)"
      ],
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr th {\n",
              "        text-align: left;\n",
              "    }\n",
              "\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></th>\n",
              "      <th colspan=\"2\" halign=\"left\">tip</th>\n",
              "      <th colspan=\"2\" halign=\"left\">total_bill</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>min</th>\n",
              "      <th>max</th>\n",
              "      <th>mean</th>\n",
              "      <th>mean_eur2usd</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th>time</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Male</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>1.44</td>\n",
              "      <td>6.70</td>\n",
              "      <td>18.05</td>\n",
              "      <td>20.21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>1.00</td>\n",
              "      <td>10.00</td>\n",
              "      <td>21.46</td>\n",
              "      <td>24.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>1.25</td>\n",
              "      <td>5.17</td>\n",
              "      <td>16.34</td>\n",
              "      <td>18.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>1.00</td>\n",
              "      <td>6.50</td>\n",
              "      <td>19.21</td>\n",
              "      <td>21.52</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               tip       total_bill             \n",
              "               min   max       mean mean_eur2usd\n",
              "sex    time                                     \n",
              "Male   Lunch  1.44  6.70      18.05        20.21\n",
              "       Dinner 1.00 10.00      21.46        24.04\n",
              "Female Lunch  1.25  5.17      16.34        18.30\n",
              "       Dinner 1.00  6.50      19.21        21.52"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jA-o3pMkDtnO",
        "colab_type": "text"
      },
      "source": [
        "Podemos crear una funcion filtro y aplicarla al group by creado por nosotros"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "afXy1KigC1fP",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def f_filter(x):\n",
        "  return mean_eur2usd(x['total_bill'].mean()) > 20"
      ],
      "execution_count": 65,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_sVYBeJxD_Ac",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "c35989a3-7fc1-4cec-9f37-ccd6d39284e1"
      },
      "source": [
        " df_filtered = df.groupby(['sex', 'time']).filter(f_filter)\n",
        " df_filtered"
      ],
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>sex</th>\n",
              "      <th>smoker</th>\n",
              "      <th>day</th>\n",
              "      <th>time</th>\n",
              "      <th>size</th>\n",
              "      <th>porcet_tip</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>16.99</td>\n",
              "      <td>1.01</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.34</td>\n",
              "      <td>1.66</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>21.01</td>\n",
              "      <td>3.50</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23.68</td>\n",
              "      <td>3.31</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24.59</td>\n",
              "      <td>3.61</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>4</td>\n",
              "      <td>0.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>239</th>\n",
              "      <td>29.03</td>\n",
              "      <td>5.92</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>27.18</td>\n",
              "      <td>2.00</td>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>22.67</td>\n",
              "      <td>2.00</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>17.82</td>\n",
              "      <td>1.75</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>18.78</td>\n",
              "      <td>3.00</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Thur</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.16</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>209 rows × 8 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     total_bill  tip     sex smoker   day    time  size  porcet_tip\n",
              "0         16.99 1.01  Female     No   Sun  Dinner     2        0.06\n",
              "1         10.34 1.66    Male     No   Sun  Dinner     3        0.16\n",
              "2         21.01 3.50    Male     No   Sun  Dinner     3        0.17\n",
              "3         23.68 3.31    Male     No   Sun  Dinner     2        0.14\n",
              "4         24.59 3.61  Female     No   Sun  Dinner     4        0.15\n",
              "..          ...  ...     ...    ...   ...     ...   ...         ...\n",
              "239       29.03 5.92    Male     No   Sat  Dinner     3        0.20\n",
              "240       27.18 2.00  Female    Yes   Sat  Dinner     2        0.07\n",
              "241       22.67 2.00    Male    Yes   Sat  Dinner     2        0.09\n",
              "242       17.82 1.75    Male     No   Sat  Dinner     2        0.10\n",
              "243       18.78 3.00  Female     No  Thur  Dinner     2        0.16\n",
              "\n",
              "[209 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OR4ZJRJrE2Iq",
        "colab_type": "text"
      },
      "source": [
        "En el dataset original teniamos **244 rows**, pero usando el filtro creado ahora tenemos **209 rows**. Esto quiere decir que lo que estamos haciendo es eliminar todas las filas donde el costo promedio de la variable **total_bill** sea mayor a 20."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NeSCuwd8Eusl",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "2cc3174d-558e-47ca-a2a8-de7317518a46"
      },
      "source": [
        "df_filtered.groupby(['sex', 'time']).count()"
      ],
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>smoker</th>\n",
              "      <th>day</th>\n",
              "      <th>size</th>\n",
              "      <th>porcet_tip</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th>time</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 rowspan=\"2\" valign=\"top\">Male</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>33.00</td>\n",
              "      <td>33.00</td>\n",
              "      <td>33.00</td>\n",
              "      <td>33.00</td>\n",
              "      <td>33.00</td>\n",
              "      <td>33.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>124.00</td>\n",
              "      <td>124.00</td>\n",
              "      <td>124.00</td>\n",
              "      <td>124.00</td>\n",
              "      <td>124.00</td>\n",
              "      <td>124.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>52.00</td>\n",
              "      <td>52.00</td>\n",
              "      <td>52.00</td>\n",
              "      <td>52.00</td>\n",
              "      <td>52.00</td>\n",
              "      <td>52.00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               total_bill    tip  smoker    day   size  porcet_tip\n",
              "sex    time                                                       \n",
              "Male   Lunch        33.00  33.00   33.00  33.00  33.00       33.00\n",
              "       Dinner      124.00 124.00  124.00 124.00 124.00      124.00\n",
              "Female Lunch          nan    nan     nan    nan    nan         nan\n",
              "       Dinner       52.00  52.00   52.00  52.00  52.00       52.00"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "K8JEHG1XhMmn",
        "colab_type": "text"
      },
      "source": [
        "# Group By: extraer valor con variables categóricas\n",
        "\n",
        "En la seccion anterior se aprendio como **extraer valor** de las **variables numericas** con las funcion groupby y aggregate, usando categorias. \n",
        "\n",
        "En esta seccion se vera como **extraer valor** de los datos  de las **variables categoricas**."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7_iTy88Bkvfb",
        "colab_type": "text"
      },
      "source": [
        "Veamos nuevamente nuestro dataframe:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nBPxYfPlkYH6",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "ff114f8f-5f69-4d26-a3de-70153bd20dac"
      },
      "source": [
        "df"
      ],
      "execution_count": 68,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>sex</th>\n",
              "      <th>smoker</th>\n",
              "      <th>day</th>\n",
              "      <th>time</th>\n",
              "      <th>size</th>\n",
              "      <th>porcet_tip</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>16.99</td>\n",
              "      <td>1.01</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.34</td>\n",
              "      <td>1.66</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>21.01</td>\n",
              "      <td>3.50</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23.68</td>\n",
              "      <td>3.31</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24.59</td>\n",
              "      <td>3.61</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>4</td>\n",
              "      <td>0.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>239</th>\n",
              "      <td>29.03</td>\n",
              "      <td>5.92</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>27.18</td>\n",
              "      <td>2.00</td>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>22.67</td>\n",
              "      <td>2.00</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>17.82</td>\n",
              "      <td>1.75</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>18.78</td>\n",
              "      <td>3.00</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Thur</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.16</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>244 rows × 8 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     total_bill  tip     sex smoker   day    time  size  porcet_tip\n",
              "0         16.99 1.01  Female     No   Sun  Dinner     2        0.06\n",
              "1         10.34 1.66    Male     No   Sun  Dinner     3        0.16\n",
              "2         21.01 3.50    Male     No   Sun  Dinner     3        0.17\n",
              "3         23.68 3.31    Male     No   Sun  Dinner     2        0.14\n",
              "4         24.59 3.61  Female     No   Sun  Dinner     4        0.15\n",
              "..          ...  ...     ...    ...   ...     ...   ...         ...\n",
              "239       29.03 5.92    Male     No   Sat  Dinner     3        0.20\n",
              "240       27.18 2.00  Female    Yes   Sat  Dinner     2        0.07\n",
              "241       22.67 2.00    Male    Yes   Sat  Dinner     2        0.09\n",
              "242       17.82 1.75    Male     No   Sat  Dinner     2        0.10\n",
              "243       18.78 3.00  Female     No  Thur  Dinner     2        0.16\n",
              "\n",
              "[244 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uBPrFUn9kyQC",
        "colab_type": "text"
      },
      "source": [
        "Creemos una nueva columna llamada **ones** a la cual le pondremos numeros uno unicamente."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HlSo3LLzkYoI",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df['ones'] = 1"
      ],
      "execution_count": 69,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "z93L6q2Skdsq",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "96c0e816-a562-4529-a952-f1efb7c33ea7"
      },
      "source": [
        "df"
      ],
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>sex</th>\n",
              "      <th>smoker</th>\n",
              "      <th>day</th>\n",
              "      <th>time</th>\n",
              "      <th>size</th>\n",
              "      <th>porcet_tip</th>\n",
              "      <th>ones</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>16.99</td>\n",
              "      <td>1.01</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.06</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.34</td>\n",
              "      <td>1.66</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.16</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>21.01</td>\n",
              "      <td>3.50</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.17</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23.68</td>\n",
              "      <td>3.31</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.14</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24.59</td>\n",
              "      <td>3.61</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>4</td>\n",
              "      <td>0.15</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>239</th>\n",
              "      <td>29.03</td>\n",
              "      <td>5.92</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.20</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>27.18</td>\n",
              "      <td>2.00</td>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.07</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>22.67</td>\n",
              "      <td>2.00</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.09</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>17.82</td>\n",
              "      <td>1.75</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.10</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>18.78</td>\n",
              "      <td>3.00</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Thur</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.16</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>244 rows × 9 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     total_bill  tip     sex smoker   day    time  size  porcet_tip  ones\n",
              "0         16.99 1.01  Female     No   Sun  Dinner     2        0.06     1\n",
              "1         10.34 1.66    Male     No   Sun  Dinner     3        0.16     1\n",
              "2         21.01 3.50    Male     No   Sun  Dinner     3        0.17     1\n",
              "3         23.68 3.31    Male     No   Sun  Dinner     2        0.14     1\n",
              "4         24.59 3.61  Female     No   Sun  Dinner     4        0.15     1\n",
              "..          ...  ...     ...    ...   ...     ...   ...         ...   ...\n",
              "239       29.03 5.92    Male     No   Sat  Dinner     3        0.20     1\n",
              "240       27.18 2.00  Female    Yes   Sat  Dinner     2        0.07     1\n",
              "241       22.67 2.00    Male    Yes   Sat  Dinner     2        0.09     1\n",
              "242       17.82 1.75    Male     No   Sat  Dinner     2        0.10     1\n",
              "243       18.78 3.00  Female     No  Thur  Dinner     2        0.16     1\n",
              "\n",
              "[244 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SownQFmKk5ki",
        "colab_type": "text"
      },
      "source": [
        "Con lo anterior, creemos un nuevo dataframe donde tomemos las **categorias** **sexo** y **fumadores**, luego utilizando la columna antes creada hagamos un **conteo** de los mismos separandolos por categorias. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l4C5l5HNkfZP",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 121
        },
        "outputId": "f3547804-037f-4b8d-ef49-e081c5ca0e5a"
      },
      "source": [
        "df_g = df.groupby(['sex', 'smoker'])['ones'].sum()\n",
        "df_g"
      ],
      "execution_count": 71,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "sex     smoker\n",
              "Male    Yes       60\n",
              "        No        97\n",
              "Female  Yes       33\n",
              "        No        54\n",
              "Name: ones, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wW5qlWAolgSM",
        "colab_type": "text"
      },
      "source": [
        "Con esto hicimos un conteo y un analisis con las variables categoricas, las cuales no son numericas, valga la redundancia.\n",
        "\n",
        "Ahora si de lo anterior quisieramos convertirlo en un % lo que hacemos es lo siguiente:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ybe5pHBYkpTj",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 121
        },
        "outputId": "6093c575-05c3-4a19-af45-f125be770f25"
      },
      "source": [
        "df_g.groupby(level=0).apply(\n",
        "    lambda x:\n",
        "      x / x.sum() * 100\n",
        ")"
      ],
      "execution_count": 72,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "sex     smoker\n",
              "Male    Yes      38.22\n",
              "        No       61.78\n",
              "Female  Yes      37.93\n",
              "        No       62.07\n",
              "Name: ones, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 72
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kpAczqiTmH8A",
        "colab_type": "text"
      },
      "source": [
        "Otra forma de crear valor de nuestros datos es transformar alguna variable numerica (continua) en categorica, ¿como hacemos esto?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jC1k1wKmmURO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 243
        },
        "outputId": "b43a47cd-553f-4659-b1cf-65870fe5042d"
      },
      "source": [
        "pd.cut(df['total_bill'], bins=3)"
      ],
      "execution_count": 73,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0       (3.022, 18.983]\n",
              "1       (3.022, 18.983]\n",
              "2      (18.983, 34.897]\n",
              "3      (18.983, 34.897]\n",
              "4      (18.983, 34.897]\n",
              "             ...       \n",
              "239    (18.983, 34.897]\n",
              "240    (18.983, 34.897]\n",
              "241    (18.983, 34.897]\n",
              "242     (3.022, 18.983]\n",
              "243     (3.022, 18.983]\n",
              "Name: total_bill, Length: 244, dtype: category\n",
              "Categories (3, interval[float64]): [(3.022, 18.983] < (18.983, 34.897] < (34.897, 50.81]]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VviNR1EDmoNY",
        "colab_type": "text"
      },
      "source": [
        "Con esto hemos creado categorias con variables numericas. Ahora veamos cuales fueron las categorias creadas:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uPOnNezYmab7",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 86
        },
        "outputId": "31aba087-dbb1-4f2e-b2ed-cdde084c537f"
      },
      "source": [
        "pd.cut(df['total_bill'], bins=3).value_counts()"
      ],
      "execution_count": 74,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(3.022, 18.983]     140\n",
              "(18.983, 34.897]     88\n",
              "(34.897, 50.81]      16\n",
              "Name: total_bill, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 74
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tbiQm3-am2IE",
        "colab_type": "text"
      },
      "source": [
        "Tambien podemos definir el ancho de nuestras categorias:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uru2bs4SmmY4",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 86
        },
        "outputId": "2e496658-b460-4d89-da52-0442c28efad8"
      },
      "source": [
        "pd.cut(df['total_bill'], bins=[3,18,35,60]).value_counts()"
      ],
      "execution_count": 75,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(3, 18]     127\n",
              "(18, 35]    101\n",
              "(35, 60]     16\n",
              "Name: total_bill, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 75
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kmlR9aDYnHue",
        "colab_type": "text"
      },
      "source": [
        "Ahora que creamos categorias de las variables numericas almacenemos lo hecho en nuestro datarame:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SvwcVMn8m-fM",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "a4f49b52-f789-4ae0-9eb2-dc4a345a2c6e"
      },
      "source": [
        "df['bin_total'] = pd.cut(df['total_bill'], bins=[3,18,35,60])\n",
        "df"
      ],
      "execution_count": 76,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>sex</th>\n",
              "      <th>smoker</th>\n",
              "      <th>day</th>\n",
              "      <th>time</th>\n",
              "      <th>size</th>\n",
              "      <th>porcet_tip</th>\n",
              "      <th>ones</th>\n",
              "      <th>bin_total</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>16.99</td>\n",
              "      <td>1.01</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.06</td>\n",
              "      <td>1</td>\n",
              "      <td>(3, 18]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.34</td>\n",
              "      <td>1.66</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.16</td>\n",
              "      <td>1</td>\n",
              "      <td>(3, 18]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>21.01</td>\n",
              "      <td>3.50</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.17</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23.68</td>\n",
              "      <td>3.31</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.14</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24.59</td>\n",
              "      <td>3.61</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>4</td>\n",
              "      <td>0.15</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>239</th>\n",
              "      <td>29.03</td>\n",
              "      <td>5.92</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.20</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>27.18</td>\n",
              "      <td>2.00</td>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.07</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>22.67</td>\n",
              "      <td>2.00</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.09</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>17.82</td>\n",
              "      <td>1.75</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.10</td>\n",
              "      <td>1</td>\n",
              "      <td>(3, 18]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>18.78</td>\n",
              "      <td>3.00</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Thur</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.16</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>244 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     total_bill  tip     sex smoker  ... size porcet_tip  ones  bin_total\n",
              "0         16.99 1.01  Female     No  ...    2       0.06     1    (3, 18]\n",
              "1         10.34 1.66    Male     No  ...    3       0.16     1    (3, 18]\n",
              "2         21.01 3.50    Male     No  ...    3       0.17     1   (18, 35]\n",
              "3         23.68 3.31    Male     No  ...    2       0.14     1   (18, 35]\n",
              "4         24.59 3.61  Female     No  ...    4       0.15     1   (18, 35]\n",
              "..          ...  ...     ...    ...  ...  ...        ...   ...        ...\n",
              "239       29.03 5.92    Male     No  ...    3       0.20     1   (18, 35]\n",
              "240       27.18 2.00  Female    Yes  ...    2       0.07     1   (18, 35]\n",
              "241       22.67 2.00    Male    Yes  ...    2       0.09     1   (18, 35]\n",
              "242       17.82 1.75    Male     No  ...    2       0.10     1    (3, 18]\n",
              "243       18.78 3.00  Female     No  ...    2       0.16     1   (18, 35]\n",
              "\n",
              "[244 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 76
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cR-vMGCGndaW",
        "colab_type": "text"
      },
      "source": [
        "Ahora sobre esta nueva categoria podemos hacer group by. En este caso vamos a contar en funcion de la categoria antes hecha **bin_total** en que horario, **time**, se gasta mas o menos. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mB7ef8KjnY_k",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "outputId": "b60a6bb9-132f-4169-aad6-42006a09ada1"
      },
      "source": [
        "df.groupby(['time', 'bin_total'])[['ones']].count()"
      ],
      "execution_count": 77,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>ones</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>time</th>\n",
              "      <th>bin_total</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">Lunch</th>\n",
              "      <th>(3, 18]</th>\n",
              "      <td>45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>(18, 35]</th>\n",
              "      <td>21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>(35, 60]</th>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">Dinner</th>\n",
              "      <th>(3, 18]</th>\n",
              "      <td>82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>(18, 35]</th>\n",
              "      <td>80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>(35, 60]</th>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  ones\n",
              "time   bin_total      \n",
              "Lunch  (3, 18]      45\n",
              "       (18, 35]     21\n",
              "       (35, 60]      2\n",
              "Dinner (3, 18]      82\n",
              "       (18, 35]     80\n",
              "       (35, 60]     14"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 77
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Jf3uk6nwoeIo",
        "colab_type": "text"
      },
      "source": [
        "Veamos lo anterior en %"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4Ih2iizQnpCm",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "outputId": "e310e797-e2e9-443a-86c8-0982ccb26b42"
      },
      "source": [
        "df.groupby(['time', 'bin_total'])[['ones']].count().groupby(level=0).apply(\n",
        "    lambda x:\n",
        "      x / x.sum() * 100\n",
        ")"
      ],
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>ones</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>time</th>\n",
              "      <th>bin_total</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">Lunch</th>\n",
              "      <th>(3, 18]</th>\n",
              "      <td>66.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>(18, 35]</th>\n",
              "      <td>30.88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>(35, 60]</th>\n",
              "      <td>2.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">Dinner</th>\n",
              "      <th>(3, 18]</th>\n",
              "      <td>46.59</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>(18, 35]</th>\n",
              "      <td>45.45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>(35, 60]</th>\n",
              "      <td>7.95</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  ones\n",
              "time   bin_total      \n",
              "Lunch  (3, 18]   66.18\n",
              "       (18, 35]  30.88\n",
              "       (35, 60]   2.94\n",
              "Dinner (3, 18]   46.59\n",
              "       (18, 35]  45.45\n",
              "       (35, 60]   7.95"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 78
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZoC9iB_DosBG",
        "colab_type": "text"
      },
      "source": [
        "Vemos que en el almuerzo la gente suele pagar facturas mas baratas ya que tenemos un 66.18% de estas en el almuerzo y sobre las facturas de mayor valor, entre 35 y 60 USD solo tenemos un 2.94%.\n",
        "\n",
        "En cambio en la noche, en la cena, esto % cambian. Las personas puede pagar mas por una comina ya que los % de la categoria entre 18-35 USD y 35-60 USD aumentan, haciendo que la primer categoria disminuya. \n",
        "\n",
        "Con esto podemos concluir que la gente suele gastar mas en una cena que en una almuerzo. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7U7tV0U-twb4",
        "colab_type": "text"
      },
      "source": [
        "# Tablas dinámicas con Pivot Table\n",
        "\n",
        "En esta sección veremos como crear tablas dinámicas. Para eso pandas cuenta con una función llamada **pivot_table**, esta nos permite extraer, cuando tenemos variables categoricas, gran informacion y valor de nuestro dataframe."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_fN0sk3Vof4s",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "49527ec0-3e35-4c82-86b3-5a32e13d2f25"
      },
      "source": [
        "df"
      ],
      "execution_count": 79,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>sex</th>\n",
              "      <th>smoker</th>\n",
              "      <th>day</th>\n",
              "      <th>time</th>\n",
              "      <th>size</th>\n",
              "      <th>porcet_tip</th>\n",
              "      <th>ones</th>\n",
              "      <th>bin_total</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>16.99</td>\n",
              "      <td>1.01</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.06</td>\n",
              "      <td>1</td>\n",
              "      <td>(3, 18]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.34</td>\n",
              "      <td>1.66</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.16</td>\n",
              "      <td>1</td>\n",
              "      <td>(3, 18]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>21.01</td>\n",
              "      <td>3.50</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.17</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23.68</td>\n",
              "      <td>3.31</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.14</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24.59</td>\n",
              "      <td>3.61</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>4</td>\n",
              "      <td>0.15</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>239</th>\n",
              "      <td>29.03</td>\n",
              "      <td>5.92</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>0.20</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>27.18</td>\n",
              "      <td>2.00</td>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.07</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>22.67</td>\n",
              "      <td>2.00</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.09</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>17.82</td>\n",
              "      <td>1.75</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.10</td>\n",
              "      <td>1</td>\n",
              "      <td>(3, 18]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>18.78</td>\n",
              "      <td>3.00</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Thur</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.16</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>244 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     total_bill  tip     sex smoker  ... size porcet_tip  ones  bin_total\n",
              "0         16.99 1.01  Female     No  ...    2       0.06     1    (3, 18]\n",
              "1         10.34 1.66    Male     No  ...    3       0.16     1    (3, 18]\n",
              "2         21.01 3.50    Male     No  ...    3       0.17     1   (18, 35]\n",
              "3         23.68 3.31    Male     No  ...    2       0.14     1   (18, 35]\n",
              "4         24.59 3.61  Female     No  ...    4       0.15     1   (18, 35]\n",
              "..          ...  ...     ...    ...  ...  ...        ...   ...        ...\n",
              "239       29.03 5.92    Male     No  ...    3       0.20     1   (18, 35]\n",
              "240       27.18 2.00  Female    Yes  ...    2       0.07     1   (18, 35]\n",
              "241       22.67 2.00    Male    Yes  ...    2       0.09     1   (18, 35]\n",
              "242       17.82 1.75    Male     No  ...    2       0.10     1    (3, 18]\n",
              "243       18.78 3.00  Female     No  ...    2       0.16     1   (18, 35]\n",
              "\n",
              "[244 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 79
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rizRs2JTujdd",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "4cecbe7c-0c57-4682-fcc4-d9afcee1f6a7"
      },
      "source": [
        "df.groupby(['sex', 'time'])[['total_bill']].mean()"
      ],
      "execution_count": 80,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th>time</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Male</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>18.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>21.46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>16.34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>19.21</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               total_bill\n",
              "sex    time              \n",
              "Male   Lunch        18.05\n",
              "       Dinner       21.46\n",
              "Female Lunch        16.34\n",
              "       Dinner       19.21"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 80
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q0PclfXfv_z_",
        "colab_type": "text"
      },
      "source": [
        "Lo que haremos es "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "05dXfqK8vl27",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "outputId": "fda0e98e-435b-486d-a96e-b3a3fcdee58e"
      },
      "source": [
        "df_gp = df.groupby(['sex', 'time'])[['total_bill']].mean().reset_index()\n",
        "df_gp"
      ],
      "execution_count": 81,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>sex</th>\n",
              "      <th>time</th>\n",
              "      <th>total_bill</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Male</td>\n",
              "      <td>Lunch</td>\n",
              "      <td>18.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Male</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>21.46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Female</td>\n",
              "      <td>Lunch</td>\n",
              "      <td>16.34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Female</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>19.21</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      sex    time  total_bill\n",
              "0    Male   Lunch       18.05\n",
              "1    Male  Dinner       21.46\n",
              "2  Female   Lunch       16.34\n",
              "3  Female  Dinner       19.21"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LhMtP_Fzvvk0",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "7812fcff-f822-49aa-c417-2fb9a65f5d16"
      },
      "source": [
        "df_gp.pivot_table(index='sex', columns='time', values='total_bill')"
      ],
      "execution_count": 85,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>time</th>\n",
              "      <th>Lunch</th>\n",
              "      <th>Dinner</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Male</th>\n",
              "      <td>18.05</td>\n",
              "      <td>21.46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>16.34</td>\n",
              "      <td>19.21</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "time    Lunch  Dinner\n",
              "sex                  \n",
              "Male    18.05   21.46\n",
              "Female  16.34   19.21"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 85
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-H1_Wj-DKvUl",
        "colab_type": "text"
      },
      "source": [
        "Que esta pasando con **pivot_table**?\n",
        "\n",
        "La tabla se reestructuran como podemos ver en la imagen:\n",
        "\n",
        "![](https://pandas-docs.github.io/pandas-docs-travis/_images/reshaping_pivot.png)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cNfGU6n9MQkY",
        "colab_type": "text"
      },
      "source": [
        "Internamente **pivot_table** esta realizando el promedio de cada uno de los valores y reestructura a nuestro dataframe en uno nuevo con lo hemos especificado."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZZV14-HpKqmw",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "a3c4c9cd-48a0-4a2c-a93f-5e49ee002d0d"
      },
      "source": [
        "df.pivot_table(index='sex', columns='time', values='total_bill')"
      ],
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>time</th>\n",
              "      <th>Lunch</th>\n",
              "      <th>Dinner</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Male</th>\n",
              "      <td>18.05</td>\n",
              "      <td>21.46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>16.34</td>\n",
              "      <td>19.21</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "time    Lunch  Dinner\n",
              "sex                  \n",
              "Male    18.05   21.46\n",
              "Female  16.34   19.21"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 86
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "f8OfhuR5MuAb",
        "colab_type": "text"
      },
      "source": [
        "Si quisieramos cambiar el tipo de cálculo que hace este lo podemos hacer con el atributo **aggfunc** y especificarle la función."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0a7zAGHbMOTe",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "4a5e148c-6237-4186-b6ae-050af4d66a62"
      },
      "source": [
        "df.pivot_table(index='sex', columns='time', values='total_bill', aggfunc=np.median)"
      ],
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>time</th>\n",
              "      <th>Lunch</th>\n",
              "      <th>Dinner</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Male</th>\n",
              "      <td>16.58</td>\n",
              "      <td>19.63</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>13.42</td>\n",
              "      <td>17.19</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "time    Lunch  Dinner\n",
              "sex                  \n",
              "Male    16.58   19.63\n",
              "Female  13.42   17.19"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SvOJi4jxNAiu",
        "colab_type": "text"
      },
      "source": [
        "Tambien podemos pasarla una lista con las funciones que queremos utilizar para que haga los calculos internos la funcion **pivot_table**. En este caso la media y la desviación estandar."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QKhl0vDxMoYM",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "outputId": "e4364e75-73f6-4eba-e59b-e4fd5ac21c66"
      },
      "source": [
        "df_pivot = df.pivot_table(index='sex', columns='time', values='total_bill', aggfunc=[np.median, np.std])\n",
        "df_pivot"
      ],
      "execution_count": 89,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr th {\n",
              "        text-align: left;\n",
              "    }\n",
              "\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\">median</th>\n",
              "      <th colspan=\"2\" halign=\"left\">std</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>time</th>\n",
              "      <th>Lunch</th>\n",
              "      <th>Dinner</th>\n",
              "      <th>Lunch</th>\n",
              "      <th>Dinner</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Male</th>\n",
              "      <td>16.58</td>\n",
              "      <td>19.63</td>\n",
              "      <td>7.95</td>\n",
              "      <td>9.46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>13.42</td>\n",
              "      <td>17.19</td>\n",
              "      <td>7.50</td>\n",
              "      <td>8.20</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       median          std       \n",
              "time    Lunch Dinner Lunch Dinner\n",
              "sex                              \n",
              "Male    16.58  19.63  7.95   9.46\n",
              "Female  13.42  17.19  7.50   8.20"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 89
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sSsehYMbNbHA",
        "colab_type": "text"
      },
      "source": [
        "Podemos deshacer las categorias y crear un nuevo dataframe de la siguiente manera."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dxvoySUWM-zW",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 191
        },
        "outputId": "c3e524a2-31d4-43af-9dde-9bd0e4c3def0"
      },
      "source": [
        "df_pivot.unstack()"
      ],
      "execution_count": 90,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        time    sex   \n",
              "median  Lunch   Male     16.58\n",
              "                Female   13.42\n",
              "        Dinner  Male     19.63\n",
              "                Female   17.19\n",
              "std     Lunch   Male      7.95\n",
              "                Female    7.50\n",
              "        Dinner  Male      9.46\n",
              "                Female    8.20\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rsIoKivTNk8z",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "outputId": "fdf489d3-77f5-4a8b-9bfc-96a131f83284"
      },
      "source": [
        "df_pivot.unstack().reset_index()"
      ],
      "execution_count": 91,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>level_0</th>\n",
              "      <th>time</th>\n",
              "      <th>sex</th>\n",
              "      <th>0</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>median</td>\n",
              "      <td>Lunch</td>\n",
              "      <td>Male</td>\n",
              "      <td>16.58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>median</td>\n",
              "      <td>Lunch</td>\n",
              "      <td>Female</td>\n",
              "      <td>13.42</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>median</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>Male</td>\n",
              "      <td>19.63</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>median</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>Female</td>\n",
              "      <td>17.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>std</td>\n",
              "      <td>Lunch</td>\n",
              "      <td>Male</td>\n",
              "      <td>7.95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>std</td>\n",
              "      <td>Lunch</td>\n",
              "      <td>Female</td>\n",
              "      <td>7.50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>std</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>Male</td>\n",
              "      <td>9.46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>std</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>Female</td>\n",
              "      <td>8.20</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  level_0    time     sex     0\n",
              "0  median   Lunch    Male 16.58\n",
              "1  median   Lunch  Female 13.42\n",
              "2  median  Dinner    Male 19.63\n",
              "3  median  Dinner  Female 17.19\n",
              "4     std   Lunch    Male  7.95\n",
              "5     std   Lunch  Female  7.50\n",
              "6     std  Dinner    Male  9.46\n",
              "7     std  Dinner  Female  8.20"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 91
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KHMjOmpuNo3t",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}