groupby_2_0_pivot.ipynb

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      "name": "groupby 2.0 pivot.ipynb",
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      "name": "python3",
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Mgobeaalcoba/Full_Pandas/blob/main/groupby_2_0_pivot.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1PeI05sgQTEv",
        "outputId": "f71447d9-805d-4ba4-880c-c61af5ae4b9a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "pd.__version__"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'1.1.5'"
            ]
          },
          "metadata": {},
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vJ1sRGpuQU3p"
      },
      "source": [
        "pd.options.display.float_format = '{:,.3f}'.format"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wcn24xGHZSsL"
      },
      "source": [
        "import seaborn as sns"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dDEGe8sRfpJW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "6e857680-f316-4f30-bb88-28182ac9d2f1"
      },
      "source": [
        "df = sns.load_dataset('tips') # Base de datos de propinas de un restaurante\n",
        "df"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>16.990</td>\n",
              "      <td>1.010</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>10.340</td>\n",
              "      <td>1.660</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>21.010</td>\n",
              "      <td>3.500</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>23.680</td>\n",
              "      <td>3.310</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>24.590</td>\n",
              "      <td>3.610</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>29.030</td>\n",
              "      <td>5.920</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>27.180</td>\n",
              "      <td>2.000</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>22.670</td>\n",
              "      <td>2.000</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>17.820</td>\n",
              "      <td>1.750</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>18.780</td>\n",
              "      <td>3.000</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        16.990 1.010  Female     No   Sun  Dinner     2\n",
              "1        10.340 1.660    Male     No   Sun  Dinner     3\n",
              "2        21.010 3.500    Male     No   Sun  Dinner     3\n",
              "3        23.680 3.310    Male     No   Sun  Dinner     2\n",
              "4        24.590 3.610  Female     No   Sun  Dinner     4\n",
              "..          ...   ...     ...    ...   ...     ...   ...\n",
              "239      29.030 5.920    Male     No   Sat  Dinner     3\n",
              "240      27.180 2.000  Female    Yes   Sat  Dinner     2\n",
              "241      22.670 2.000    Male    Yes   Sat  Dinner     2\n",
              "242      17.820 1.750    Male     No   Sat  Dinner     2\n",
              "243      18.780 3.000  Female     No  Thur  Dinner     2\n",
              "\n",
              "[244 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ys_KSRAFfsV8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "outputId": "8bf3ffcd-86d5-45d1-83ef-2de5eefa5a37"
      },
      "source": [
        "df.describe(include='all') # Lo primero que tenemos que hacer para conocer nuestro datos"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>244.000</td>\n",
              "      <td>244.000</td>\n",
              "      <td>244</td>\n",
              "      <td>244</td>\n",
              "      <td>244</td>\n",
              "      <td>244</td>\n",
              "      <td>244.000</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>19.786</td>\n",
              "      <td>2.998</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.570</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>8.902</td>\n",
              "      <td>1.384</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.951</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>3.070</td>\n",
              "      <td>1.000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>13.348</td>\n",
              "      <td>2.000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>17.795</td>\n",
              "      <td>2.900</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>24.127</td>\n",
              "      <td>3.562</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>50.810</td>\n",
              "      <td>10.000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>6.000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        total_bill     tip   sex smoker  day    time    size\n",
              "count      244.000 244.000   244    244  244     244 244.000\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        19.786   2.998   NaN    NaN  NaN     NaN   2.570\n",
              "std          8.902   1.384   NaN    NaN  NaN     NaN   0.951\n",
              "min          3.070   1.000   NaN    NaN  NaN     NaN   1.000\n",
              "25%         13.348   2.000   NaN    NaN  NaN     NaN   2.000\n",
              "50%         17.795   2.900   NaN    NaN  NaN     NaN   2.000\n",
              "75%         24.127   3.562   NaN    NaN  NaN     NaN   3.000\n",
              "max         50.810  10.000   NaN    NaN  NaN     NaN   6.000"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lhPKssfKf03P",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "566cce4a-fbb0-40d4-ab1f-20082c150319"
      },
      "source": [
        "df['day'].value_counts() # Veo en detalle la variable día"
      ],
      "execution_count": 9,
      "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": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gG4hxMUif9cZ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2ed95d89-5973-4bc3-dc36-99a93cfaf865"
      },
      "source": [
        "df['day'].value_counts() / df['day'].value_counts().sum() * 100 # De esta forma veo en porcentajes la dist de frecuencia entre los días que abre mi restaurante"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Sat    35.656\n",
              "Sun    31.148\n",
              "Thur   25.410\n",
              "Fri     7.787\n",
              "Name: day, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p2KtGFU1gKyx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "outputId": "2e5ba5ea-c5fd-490a-ef82-81c447836576"
      },
      "source": [
        "df.groupby('sex').mean() # Agrupo por sexo de mis comensales y le pido el promedio "
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>20.744</td>\n",
              "      <td>3.090</td>\n",
              "      <td>2.631</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>18.057</td>\n",
              "      <td>2.833</td>\n",
              "      <td>2.460</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        total_bill   tip  size\n",
              "sex                           \n",
              "Male        20.744 3.090 2.631\n",
              "Female      18.057 2.833 2.460"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BYaEKPstgVZe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "080169d8-e901-4f51-b468-e6df1289cafe"
      },
      "source": [
        "df['prct_tip'] = df['tip']/df['total_bill']*100 # Construyo una nueva categoria que es el porcentaje de propina\n",
        "df"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>prct_tip</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>16.990</td>\n",
              "      <td>1.010</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>5.945</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.340</td>\n",
              "      <td>1.660</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>16.054</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>21.010</td>\n",
              "      <td>3.500</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>16.659</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23.680</td>\n",
              "      <td>3.310</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>13.978</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24.590</td>\n",
              "      <td>3.610</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>4</td>\n",
              "      <td>14.681</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>29.030</td>\n",
              "      <td>5.920</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>20.393</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>27.180</td>\n",
              "      <td>2.000</td>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>7.358</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>22.670</td>\n",
              "      <td>2.000</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>8.822</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>17.820</td>\n",
              "      <td>1.750</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>9.820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>18.780</td>\n",
              "      <td>3.000</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Thur</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>15.974</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  prct_tip\n",
              "0        16.990 1.010  Female     No   Sun  Dinner     2     5.945\n",
              "1        10.340 1.660    Male     No   Sun  Dinner     3    16.054\n",
              "2        21.010 3.500    Male     No   Sun  Dinner     3    16.659\n",
              "3        23.680 3.310    Male     No   Sun  Dinner     2    13.978\n",
              "4        24.590 3.610  Female     No   Sun  Dinner     4    14.681\n",
              "..          ...   ...     ...    ...   ...     ...   ...       ...\n",
              "239      29.030 5.920    Male     No   Sat  Dinner     3    20.393\n",
              "240      27.180 2.000  Female    Yes   Sat  Dinner     2     7.358\n",
              "241      22.670 2.000    Male    Yes   Sat  Dinner     2     8.822\n",
              "242      17.820 1.750    Male     No   Sat  Dinner     2     9.820\n",
              "243      18.780 3.000  Female     No  Thur  Dinner     2    15.974\n",
              "\n",
              "[244 rows x 8 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1WeM78MzhSCR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "outputId": "3d32aae2-94ec-4807-f67f-06e3d18124b5"
      },
      "source": [
        "df.groupby('sex').mean() # Veo de nuevo el promedio por sexo y me calcula el promedio de mi promedio de propinas"
      ],
      "execution_count": 19,
      "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>prct_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>20.744</td>\n",
              "      <td>3.090</td>\n",
              "      <td>2.631</td>\n",
              "      <td>15.765</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>18.057</td>\n",
              "      <td>2.833</td>\n",
              "      <td>2.460</td>\n",
              "      <td>16.649</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        total_bill   tip  size  prct_tip\n",
              "sex                                     \n",
              "Male        20.744 3.090 2.631    15.765\n",
              "Female      18.057 2.833 2.460    16.649"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EUR0t62KhWTQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "outputId": "9df56fe6-d93e-41a6-c3cf-5d3f7f0b5c62"
      },
      "source": [
        "df.groupby('sex').median() # Puedo ver la media tambien"
      ],
      "execution_count": 21,
      "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>prct_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>18.350</td>\n",
              "      <td>3.000</td>\n",
              "      <td>2</td>\n",
              "      <td>15.349</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>16.400</td>\n",
              "      <td>2.750</td>\n",
              "      <td>2</td>\n",
              "      <td>15.558</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        total_bill   tip  size  prct_tip\n",
              "sex                                     \n",
              "Male        18.350 3.000     2    15.349\n",
              "Female      16.400 2.750     2    15.558"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Puedo ver con .describe las medidas de tendencia central de cualquier columna luego de un agrupamiento\n",
        "df.groupby(\"sex\")[[\"prct_tip\"]].describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "id": "tJuuZUR-NJyT",
        "outputId": "9c91a83f-8f0c-4b2c-b438-46821887ce79"
      },
      "execution_count": 23,
      "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\">prct_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>157.000</td>\n",
              "      <td>15.765</td>\n",
              "      <td>6.478</td>\n",
              "      <td>3.564</td>\n",
              "      <td>12.139</td>\n",
              "      <td>15.349</td>\n",
              "      <td>18.624</td>\n",
              "      <td>71.034</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>87.000</td>\n",
              "      <td>16.649</td>\n",
              "      <td>5.363</td>\n",
              "      <td>5.643</td>\n",
              "      <td>14.042</td>\n",
              "      <td>15.558</td>\n",
              "      <td>19.427</td>\n",
              "      <td>41.667</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       prct_tip                                               \n",
              "          count   mean   std   min    25%    50%    75%    max\n",
              "sex                                                           \n",
              "Male    157.000 15.765 6.478 3.564 12.139 15.349 18.624 71.034\n",
              "Female   87.000 16.649 5.363 5.643 14.042 15.558 19.427 41.667"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nFyFJB0FhcYw",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 193
        },
        "outputId": "bd431bd5-2cd3-4436-b806-c14be848084e"
      },
      "source": [
        "df.groupby('sex')[['total_bill','prct_tip']].describe()"
      ],
      "execution_count": 24,
      "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\">prct_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>157.000</td>\n",
              "      <td>20.744</td>\n",
              "      <td>9.246</td>\n",
              "      <td>7.250</td>\n",
              "      <td>14.000</td>\n",
              "      <td>18.350</td>\n",
              "      <td>24.710</td>\n",
              "      <td>50.810</td>\n",
              "      <td>157.000</td>\n",
              "      <td>15.765</td>\n",
              "      <td>6.478</td>\n",
              "      <td>3.564</td>\n",
              "      <td>12.139</td>\n",
              "      <td>15.349</td>\n",
              "      <td>18.624</td>\n",
              "      <td>71.034</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>87.000</td>\n",
              "      <td>18.057</td>\n",
              "      <td>8.009</td>\n",
              "      <td>3.070</td>\n",
              "      <td>12.750</td>\n",
              "      <td>16.400</td>\n",
              "      <td>21.520</td>\n",
              "      <td>44.300</td>\n",
              "      <td>87.000</td>\n",
              "      <td>16.649</td>\n",
              "      <td>5.363</td>\n",
              "      <td>5.643</td>\n",
              "      <td>14.042</td>\n",
              "      <td>15.558</td>\n",
              "      <td>19.427</td>\n",
              "      <td>41.667</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       total_bill                            ... prct_tip                            \n",
              "            count   mean   std   min    25%  ...      min    25%    50%    75%    max\n",
              "sex                                          ...                                     \n",
              "Male      157.000 20.744 9.246 7.250 14.000  ...    3.564 12.139 15.349 18.624 71.034\n",
              "Female     87.000 18.057 8.009 3.070 12.750  ...    5.643 14.042 15.558 19.427 41.667\n",
              "\n",
              "[2 rows x 16 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cXhesX5Hhj6-"
      },
      "source": [
        "def mean_eur2usd(x):\n",
        "    y = np.mean(x)*1.12\n",
        "    return y"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Si le paso un numero a mi función me devuelve simplemente ese numero x 1.12\n",
        "mean_eur2usd(100)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rzPqGFn5N_8Z",
        "outputId": "b414a83e-037d-4c7a-f267-036ff1f34a93"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "112.00000000000001"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6BykW2M1h4ne",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5253b2dc-1402-4f7c-cd2b-9f9161340e1b"
      },
      "source": [
        "# Pero si le paso una lista (Como haría con una columna de un dataframe), entonces\n",
        "# me calcula primero el promedio y luego lo multiplica por 1.12\n",
        "mean_eur2usd([100,102])"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "113.12"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "inVHIlAVh8Ob",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "outputId": "765a90b8-cfca-4d68-e51e-b11a6116818b"
      },
      "source": [
        "# A mi agrupamiento le aplico la función definida previamente para verla en dolares\n",
        "df.groupby('sex')[['total_bill','prct_tip']].apply(mean_eur2usd)\n",
        "# Es una variante al .aggregate pero valida para un único indice entre mis columnas"
      ],
      "execution_count": 42,
      "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>prct_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>23.233</td>\n",
              "      <td>17.657</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>20.224</td>\n",
              "      <td>18.647</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        total_bill  prct_tip\n",
              "sex                         \n",
              "Male        23.233    17.657\n",
              "Female      20.224    18.647"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zVnPeE5UiEPC",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "0c482d32-62e9-490d-d5e7-6ba09d42eff6"
      },
      "source": [
        "# Püedo establecer multiples indices en mis filas de la siguiente forma\n",
        "df.groupby(['sex','time'])[['total_bill','prct_tip']].apply(mean_eur2usd)"
      ],
      "execution_count": 43,
      "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>prct_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>20.214</td>\n",
              "      <td>18.601</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>24.037</td>\n",
              "      <td>17.406</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>18.300</td>\n",
              "      <td>18.176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>21.519</td>\n",
              "      <td>18.964</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               total_bill  prct_tip\n",
              "sex    time                        \n",
              "Male   Lunch       20.214    18.601\n",
              "       Dinner      24.037    17.406\n",
              "Female Lunch       18.300    18.176\n",
              "       Dinner      21.519    18.964"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MElNykHLiM0I",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "1c4306b0-6a5a-40d3-e664-0818c88da81b"
      },
      "source": [
        "# Puedo usar el .apply tmb con funciones definidas por numpy\n",
        "df.groupby(['sex','time'])[['total_bill','prct_tip']].apply(np.std)"
      ],
      "execution_count": 45,
      "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>prct_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>7.832</td>\n",
              "      <td>4.503</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>9.423</td>\n",
              "      <td>6.867</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>7.393</td>\n",
              "      <td>3.437</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>8.123</td>\n",
              "      <td>6.279</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               total_bill  prct_tip\n",
              "sex    time                        \n",
              "Male   Lunch        7.832     4.503\n",
              "       Dinner       9.423     6.867\n",
              "Female Lunch        7.393     3.437\n",
              "       Dinner       8.123     6.279"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ST3HKoebiYk4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "07e8ecb8-7261-47a6-c83a-967db8304097"
      },
      "source": [
        "# Podemos tmb definir nuestras propias funciones en el .apply mismo con las funciones lambda\n",
        "df.groupby(['sex','time'])[['total_bill','prct_tip']].apply(lambda x: np.mean(x)*1.12)"
      ],
      "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></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>prct_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>20.214</td>\n",
              "      <td>18.601</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>24.037</td>\n",
              "      <td>17.406</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>18.300</td>\n",
              "      <td>18.176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>21.519</td>\n",
              "      <td>18.964</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               total_bill  prct_tip\n",
              "sex    time                        \n",
              "Male   Lunch       20.214    18.601\n",
              "       Dinner      24.037    17.406\n",
              "Female Lunch       18.300    18.176\n",
              "       Dinner      21.519    18.964"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "31mhii5Vil_N",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "e39128c3-b434-44cf-cf41-7bd59022109f"
      },
      "source": [
        "# Para aplicar mas de una función tengo que usar la función .aggregate\n",
        "df.groupby(['sex','time'])[['total_bill','prct_tip']].aggregate([np.mean,np.max])"
      ],
      "execution_count": 49,
      "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\">prct_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>18.048</td>\n",
              "      <td>41.190</td>\n",
              "      <td>16.608</td>\n",
              "      <td>26.631</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>21.461</td>\n",
              "      <td>50.810</td>\n",
              "      <td>15.541</td>\n",
              "      <td>71.034</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>16.339</td>\n",
              "      <td>43.110</td>\n",
              "      <td>16.228</td>\n",
              "      <td>25.931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>19.213</td>\n",
              "      <td>44.300</td>\n",
              "      <td>16.932</td>\n",
              "      <td>41.667</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              total_bill        prct_tip       \n",
              "                    mean   amax     mean   amax\n",
              "sex    time                                    \n",
              "Male   Lunch      18.048 41.190   16.608 26.631\n",
              "       Dinner     21.461 50.810   15.541 71.034\n",
              "Female Lunch      16.339 43.110   16.228 25.931\n",
              "       Dinner     19.213 44.300   16.932 41.667"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0fxJUyd2iy9U",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "6ebd027c-7165-43c9-f215-566e52e4d07b"
      },
      "source": [
        "# Agg es una forma resumida de aggregate\n",
        "df.groupby(['sex','time'])[['total_bill','prct_tip']].agg([np.mean,np.max])"
      ],
      "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 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\">prct_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>18.048</td>\n",
              "      <td>41.190</td>\n",
              "      <td>16.608</td>\n",
              "      <td>26.631</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>21.461</td>\n",
              "      <td>50.810</td>\n",
              "      <td>15.541</td>\n",
              "      <td>71.034</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>16.339</td>\n",
              "      <td>43.110</td>\n",
              "      <td>16.228</td>\n",
              "      <td>25.931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>19.213</td>\n",
              "      <td>44.300</td>\n",
              "      <td>16.932</td>\n",
              "      <td>41.667</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              total_bill        prct_tip       \n",
              "                    mean   amax     mean   amax\n",
              "sex    time                                    \n",
              "Male   Lunch      18.048 41.190   16.608 26.631\n",
              "       Dinner     21.461 50.810   15.541 71.034\n",
              "Female Lunch      16.339 43.110   16.228 25.931\n",
              "       Dinner     19.213 44.300   16.932 41.667"
            ]
          },
          "metadata": {},
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cJU0uVzOi98h",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "aa1de752-6301-4631-b972-44acd4fb12f2"
      },
      "source": [
        "# Con el uso de un diccionario voy a poder especificar que funciones aplicarque a que columnas.\n",
        "dict_agg = {'tip':[min, max],'total_bill':[np.mean, mean_eur2usd]}\n",
        "dict_agg\n",
        "# Primero armo mi diccionario donde especifico como llaves las columnas y como values mis funciones a aplicar"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'tip': [<function min>, <function max>],\n",
              " 'total_bill': [<function numpy.mean>, <function __main__.mean_eur2usd>]}"
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eyXowXdLjHQ4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "95b9b60c-bf51-4c89-d13d-4c0041d06292"
      },
      "source": [
        "# Luego aplico mi diccionario como funcion dentro del .agg\n",
        "df.groupby(['sex','time'])[['total_bill','tip']].agg(dict_agg)"
      ],
      "execution_count": 57,
      "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>1.440</td>\n",
              "      <td>6.700</td>\n",
              "      <td>18.048</td>\n",
              "      <td>20.214</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>1.000</td>\n",
              "      <td>10.000</td>\n",
              "      <td>21.461</td>\n",
              "      <td>24.037</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>1.250</td>\n",
              "      <td>5.170</td>\n",
              "      <td>16.339</td>\n",
              "      <td>18.300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>1.000</td>\n",
              "      <td>6.500</td>\n",
              "      <td>19.213</td>\n",
              "      <td>21.519</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  1.440  6.700     18.048       20.214\n",
              "       Dinner 1.000 10.000     21.461       24.037\n",
              "Female Lunch  1.250  5.170     16.339       18.300\n",
              "       Dinner 1.000  6.500     19.213       21.519"
            ]
          },
          "metadata": {},
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Si mis columnas están definidas en mi diccionario podría tmb obviarlas en la definición de .agg\n",
        "df.groupby(['sex','time']).agg(dict_agg)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "AcUinjm0R9Q_",
        "outputId": "249187c8-89f5-481c-a77b-ba54614b9016"
      },
      "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 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>1.440</td>\n",
              "      <td>6.700</td>\n",
              "      <td>18.048</td>\n",
              "      <td>20.214</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>1.000</td>\n",
              "      <td>10.000</td>\n",
              "      <td>21.461</td>\n",
              "      <td>24.037</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>1.250</td>\n",
              "      <td>5.170</td>\n",
              "      <td>16.339</td>\n",
              "      <td>18.300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>1.000</td>\n",
              "      <td>6.500</td>\n",
              "      <td>19.213</td>\n",
              "      <td>21.519</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  1.440  6.700     18.048       20.214\n",
              "       Dinner 1.000 10.000     21.461       24.037\n",
              "Female Lunch  1.250  5.170     16.339       18.300\n",
              "       Dinner 1.000  6.500     19.213       21.519"
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MgGJSDh1jlPT"
      },
      "source": [
        "# Tmb puedo definir filtro para mi dataframe agrupado\n",
        "def f_filter(x):\n",
        "    return mean_eur2usd(x['total_bill'].mean()) > 20\n",
        "# Primero genero mi función de filtro\n",
        "# Me debería excluir todas las columnas de mujeres que almuerzan si lo aplico al groupby anterior"
      ],
      "execution_count": 61,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wcVXVb3Jj1RB",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "f00e0d49-5e8c-4c7e-bc04-b9b7ab120789"
      },
      "source": [
        "df_filtered = df.groupby(['sex','time']).filter(f_filter)\n",
        "df_filtered\n",
        "# Me quedaron 209 filas entre 234 originales."
      ],
      "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>prct_tip</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>16.990</td>\n",
              "      <td>1.010</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>5.945</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.340</td>\n",
              "      <td>1.660</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>16.054</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>21.010</td>\n",
              "      <td>3.500</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>16.659</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23.680</td>\n",
              "      <td>3.310</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>13.978</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24.590</td>\n",
              "      <td>3.610</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>4</td>\n",
              "      <td>14.681</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>29.030</td>\n",
              "      <td>5.920</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>20.393</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>27.180</td>\n",
              "      <td>2.000</td>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>7.358</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>22.670</td>\n",
              "      <td>2.000</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>8.822</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>17.820</td>\n",
              "      <td>1.750</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>9.820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>18.780</td>\n",
              "      <td>3.000</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Thur</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>15.974</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  prct_tip\n",
              "0        16.990 1.010  Female     No   Sun  Dinner     2     5.945\n",
              "1        10.340 1.660    Male     No   Sun  Dinner     3    16.054\n",
              "2        21.010 3.500    Male     No   Sun  Dinner     3    16.659\n",
              "3        23.680 3.310    Male     No   Sun  Dinner     2    13.978\n",
              "4        24.590 3.610  Female     No   Sun  Dinner     4    14.681\n",
              "..          ...   ...     ...    ...   ...     ...   ...       ...\n",
              "239      29.030 5.920    Male     No   Sat  Dinner     3    20.393\n",
              "240      27.180 2.000  Female    Yes   Sat  Dinner     2     7.358\n",
              "241      22.670 2.000    Male    Yes   Sat  Dinner     2     8.822\n",
              "242      17.820 1.750    Male     No   Sat  Dinner     2     9.820\n",
              "243      18.780 3.000  Female     No  Thur  Dinner     2    15.974\n",
              "\n",
              "[209 rows x 8 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EGGBE1SOj7mk",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "6dd9aedd-0c2f-43c1-ea36-8d178653020f"
      },
      "source": [
        "df_filtered.groupby(['sex','time']).count()\n",
        "# Compruebo que efectivamente me los excluyo"
      ],
      "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>prct_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>33.000</td>\n",
              "      <td>33.000</td>\n",
              "      <td>33.000</td>\n",
              "      <td>33.000</td>\n",
              "      <td>33.000</td>\n",
              "      <td>33.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>124.000</td>\n",
              "      <td>124.000</td>\n",
              "      <td>124.000</td>\n",
              "      <td>124.000</td>\n",
              "      <td>124.000</td>\n",
              "      <td>124.000</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>52.000</td>\n",
              "      <td>52.000</td>\n",
              "      <td>52.000</td>\n",
              "      <td>52.000</td>\n",
              "      <td>52.000</td>\n",
              "      <td>52.000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               total_bill     tip  smoker     day    size  prct_tip\n",
              "sex    time                                                        \n",
              "Male   Lunch       33.000  33.000  33.000  33.000  33.000    33.000\n",
              "       Dinner     124.000 124.000 124.000 124.000 124.000   124.000\n",
              "Female Lunch          nan     nan     nan     nan     nan       nan\n",
              "       Dinner      52.000  52.000  52.000  52.000  52.000    52.000"
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PaM-1nPmkLHt",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "dd420d74-5d7c-4c2d-ffbf-e8ac640e5c81"
      },
      "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>prct_tip</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>16.990</td>\n",
              "      <td>1.010</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>5.945</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.340</td>\n",
              "      <td>1.660</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>16.054</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>21.010</td>\n",
              "      <td>3.500</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>16.659</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23.680</td>\n",
              "      <td>3.310</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>13.978</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24.590</td>\n",
              "      <td>3.610</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>4</td>\n",
              "      <td>14.681</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>29.030</td>\n",
              "      <td>5.920</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>20.393</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>27.180</td>\n",
              "      <td>2.000</td>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>7.358</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>22.670</td>\n",
              "      <td>2.000</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>8.822</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>17.820</td>\n",
              "      <td>1.750</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>9.820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>18.780</td>\n",
              "      <td>3.000</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Thur</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>15.974</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  prct_tip\n",
              "0        16.990 1.010  Female     No   Sun  Dinner     2     5.945\n",
              "1        10.340 1.660    Male     No   Sun  Dinner     3    16.054\n",
              "2        21.010 3.500    Male     No   Sun  Dinner     3    16.659\n",
              "3        23.680 3.310    Male     No   Sun  Dinner     2    13.978\n",
              "4        24.590 3.610  Female     No   Sun  Dinner     4    14.681\n",
              "..          ...   ...     ...    ...   ...     ...   ...       ...\n",
              "239      29.030 5.920    Male     No   Sat  Dinner     3    20.393\n",
              "240      27.180 2.000  Female    Yes   Sat  Dinner     2     7.358\n",
              "241      22.670 2.000    Male    Yes   Sat  Dinner     2     8.822\n",
              "242      17.820 1.750    Male     No   Sat  Dinner     2     9.820\n",
              "243      18.780 3.000  Female     No  Thur  Dinner     2    15.974\n",
              "\n",
              "[244 rows x 8 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZHRbJmcok5Id"
      },
      "source": [
        "df['ones'] = 1 # Creo una columna que solo contiene numeros unos"
      ],
      "execution_count": 71,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ua8_jYjCk-AT",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "58aef9c0-e614-44f0-d132-8aaec820ab35"
      },
      "source": [
        "df"
      ],
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "<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>prct_tip</th>\n",
              "      <th>ones</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>16.990</td>\n",
              "      <td>1.010</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>5.945</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.340</td>\n",
              "      <td>1.660</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>16.054</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>21.010</td>\n",
              "      <td>3.500</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>16.659</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23.680</td>\n",
              "      <td>3.310</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>13.978</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24.590</td>\n",
              "      <td>3.610</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>4</td>\n",
              "      <td>14.681</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>29.030</td>\n",
              "      <td>5.920</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>20.393</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>27.180</td>\n",
              "      <td>2.000</td>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>7.358</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>22.670</td>\n",
              "      <td>2.000</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>8.822</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>17.820</td>\n",
              "      <td>1.750</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>9.820</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>18.780</td>\n",
              "      <td>3.000</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Thur</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>15.974</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  prct_tip  ones\n",
              "0        16.990 1.010  Female     No   Sun  Dinner     2     5.945     1\n",
              "1        10.340 1.660    Male     No   Sun  Dinner     3    16.054     1\n",
              "2        21.010 3.500    Male     No   Sun  Dinner     3    16.659     1\n",
              "3        23.680 3.310    Male     No   Sun  Dinner     2    13.978     1\n",
              "4        24.590 3.610  Female     No   Sun  Dinner     4    14.681     1\n",
              "..          ...   ...     ...    ...   ...     ...   ...       ...   ...\n",
              "239      29.030 5.920    Male     No   Sat  Dinner     3    20.393     1\n",
              "240      27.180 2.000  Female    Yes   Sat  Dinner     2     7.358     1\n",
              "241      22.670 2.000    Male    Yes   Sat  Dinner     2     8.822     1\n",
              "242      17.820 1.750    Male     No   Sat  Dinner     2     9.820     1\n",
              "243      18.780 3.000  Female     No  Thur  Dinner     2    15.974     1\n",
              "\n",
              "[244 rows x 9 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TGx5uL0Bk-W7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "d625dfae-9326-4235-d3e0-37c8f4fe11a7"
      },
      "source": [
        "df_g = df.groupby(['sex','smoker'])[['ones']].sum() # Agrupo por sexo y fumadores y hago un conteo mediante suma de ones\n",
        "df_g"
      ],
      "execution_count": 73,
      "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>sex</th>\n",
              "      <th>smoker</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Male</th>\n",
              "      <th>Yes</th>\n",
              "      <td>60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>No</th>\n",
              "      <td>97</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Yes</th>\n",
              "      <td>33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>No</th>\n",
              "      <td>54</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               ones\n",
              "sex    smoker      \n",
              "Male   Yes       60\n",
              "       No        97\n",
              "Female Yes       33\n",
              "       No        54"
            ]
          },
          "metadata": {},
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Nt3-cpwdlHYO",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "2ab906f6-fed2-4275-b839-2903557d83d9"
      },
      "source": [
        "df_g.groupby(level=0).apply( # Paso a porcentajes el total de hombres y mujeres fumantes\n",
        "\n",
        "lambda x:\n",
        "x / x.sum() * 100\n",
        "\n",
        ")"
      ],
      "execution_count": 75,
      "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>sex</th>\n",
              "      <th>smoker</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Male</th>\n",
              "      <th>Yes</th>\n",
              "      <td>38.217</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>No</th>\n",
              "      <td>61.783</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Yes</th>\n",
              "      <td>37.931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>No</th>\n",
              "      <td>62.069</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                ones\n",
              "sex    smoker       \n",
              "Male   Yes    38.217\n",
              "       No     61.783\n",
              "Female Yes    37.931\n",
              "       No     62.069"
            ]
          },
          "metadata": {},
          "execution_count": 75
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g8EB2s7RlZ81",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "4c298120-7ada-4c52-d140-af3941ecb213"
      },
      "source": [
        "# Genero categorias de variables numericas con .cut y ,bins\n",
        "df['bin_total'] = pd.cut(df['total_bill'],bins = 3)\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",
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              "\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>prct_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>16.990</td>\n",
              "      <td>1.010</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>5.945</td>\n",
              "      <td>1</td>\n",
              "      <td>(3.022, 18.983]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.340</td>\n",
              "      <td>1.660</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>16.054</td>\n",
              "      <td>1</td>\n",
              "      <td>(3.022, 18.983]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>21.010</td>\n",
              "      <td>3.500</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>16.659</td>\n",
              "      <td>1</td>\n",
              "      <td>(18.983, 34.897]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23.680</td>\n",
              "      <td>3.310</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>13.978</td>\n",
              "      <td>1</td>\n",
              "      <td>(18.983, 34.897]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24.590</td>\n",
              "      <td>3.610</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>4</td>\n",
              "      <td>14.681</td>\n",
              "      <td>1</td>\n",
              "      <td>(18.983, 34.897]</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>29.030</td>\n",
              "      <td>5.920</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>20.393</td>\n",
              "      <td>1</td>\n",
              "      <td>(18.983, 34.897]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>27.180</td>\n",
              "      <td>2.000</td>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>7.358</td>\n",
              "      <td>1</td>\n",
              "      <td>(18.983, 34.897]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>22.670</td>\n",
              "      <td>2.000</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>8.822</td>\n",
              "      <td>1</td>\n",
              "      <td>(18.983, 34.897]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>17.820</td>\n",
              "      <td>1.750</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>9.820</td>\n",
              "      <td>1</td>\n",
              "      <td>(3.022, 18.983]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>18.780</td>\n",
              "      <td>3.000</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Thur</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>15.974</td>\n",
              "      <td>1</td>\n",
              "      <td>(3.022, 18.983]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>244 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     total_bill   tip     sex smoker  ... size prct_tip  ones         bin_total\n",
              "0        16.990 1.010  Female     No  ...    2    5.945     1   (3.022, 18.983]\n",
              "1        10.340 1.660    Male     No  ...    3   16.054     1   (3.022, 18.983]\n",
              "2        21.010 3.500    Male     No  ...    3   16.659     1  (18.983, 34.897]\n",
              "3        23.680 3.310    Male     No  ...    2   13.978     1  (18.983, 34.897]\n",
              "4        24.590 3.610  Female     No  ...    4   14.681     1  (18.983, 34.897]\n",
              "..          ...   ...     ...    ...  ...  ...      ...   ...               ...\n",
              "239      29.030 5.920    Male     No  ...    3   20.393     1  (18.983, 34.897]\n",
              "240      27.180 2.000  Female    Yes  ...    2    7.358     1  (18.983, 34.897]\n",
              "241      22.670 2.000    Male    Yes  ...    2    8.822     1  (18.983, 34.897]\n",
              "242      17.820 1.750    Male     No  ...    2    9.820     1   (3.022, 18.983]\n",
              "243      18.780 3.000  Female     No  ...    2   15.974     1   (3.022, 18.983]\n",
              "\n",
              "[244 rows x 10 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 76
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd.cut(df['total_bill'],bins = 3).value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aQkjagWCU1Es",
        "outputId": "12f3ff9f-6b1c-4c62-812d-c7176892c76d"
      },
      "execution_count": 77,
      "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": {},
          "execution_count": 77
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['bin_total'] = pd.cut(df['total_bill'],bins = [3,18,35,60]) # Establezco los margenes de mis bins con una lista\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "lqJhf47rUwYm",
        "outputId": "524d9069-12c2-45a2-db20-f9450e8169df"
      },
      "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>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>prct_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>16.990</td>\n",
              "      <td>1.010</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>5.945</td>\n",
              "      <td>1</td>\n",
              "      <td>(3, 18]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.340</td>\n",
              "      <td>1.660</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>16.054</td>\n",
              "      <td>1</td>\n",
              "      <td>(3, 18]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>21.010</td>\n",
              "      <td>3.500</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>16.659</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23.680</td>\n",
              "      <td>3.310</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>13.978</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24.590</td>\n",
              "      <td>3.610</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>4</td>\n",
              "      <td>14.681</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>29.030</td>\n",
              "      <td>5.920</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>20.393</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>27.180</td>\n",
              "      <td>2.000</td>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>7.358</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>22.670</td>\n",
              "      <td>2.000</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>8.822</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>17.820</td>\n",
              "      <td>1.750</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>9.820</td>\n",
              "      <td>1</td>\n",
              "      <td>(3, 18]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>18.780</td>\n",
              "      <td>3.000</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Thur</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>15.974</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 prct_tip  ones  bin_total\n",
              "0        16.990 1.010  Female     No  ...    2    5.945     1    (3, 18]\n",
              "1        10.340 1.660    Male     No  ...    3   16.054     1    (3, 18]\n",
              "2        21.010 3.500    Male     No  ...    3   16.659     1   (18, 35]\n",
              "3        23.680 3.310    Male     No  ...    2   13.978     1   (18, 35]\n",
              "4        24.590 3.610  Female     No  ...    4   14.681     1   (18, 35]\n",
              "..          ...   ...     ...    ...  ...  ...      ...   ...        ...\n",
              "239      29.030 5.920    Male     No  ...    3   20.393     1   (18, 35]\n",
              "240      27.180 2.000  Female    Yes  ...    2    7.358     1   (18, 35]\n",
              "241      22.670 2.000    Male    Yes  ...    2    8.822     1   (18, 35]\n",
              "242      17.820 1.750    Male     No  ...    2    9.820     1    (3, 18]\n",
              "243      18.780 3.000  Female     No  ...    2   15.974     1   (18, 35]\n",
              "\n",
              "[244 rows x 10 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 80
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fd0c9Wwelt2F",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a28fab92-20b6-4e31-96d6-85a698876771"
      },
      "source": [
        "pd.cut(df['total_bill'],bins = [3,18,35,60]).value_counts()"
      ],
      "execution_count": 81,
      "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": {},
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JUbq0DpIl6Gl",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "outputId": "d19ae52d-5c68-40b2-a44d-4ad85002e48f"
      },
      "source": [
        "df.groupby(['time','bin_total'])[['ones']].count() # Como se distribuyen los valores entre el el almuerzo y la cena"
      ],
      "execution_count": 83,
      "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": {},
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uiHFL8nRmRVR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "outputId": "40f5ceac-96b2-4f08-a61d-c7bd250e4f8f"
      },
      "source": [
        "df.groupby(['time','bin_total'])[['ones']].count().groupby(level=0).apply(\n",
        "\n",
        "lambda x:\n",
        "x / x.sum() * 100\n",
        "\n",
        ")"
      ],
      "execution_count": 84,
      "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>66.176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>(18, 35]</th>\n",
              "      <td>30.882</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>(35, 60]</th>\n",
              "      <td>2.941</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">Dinner</th>\n",
              "      <th>(3, 18]</th>\n",
              "      <td>46.591</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>(18, 35]</th>\n",
              "      <td>45.455</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>(35, 60]</th>\n",
              "      <td>7.955</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                   ones\n",
              "time   bin_total       \n",
              "Lunch  (3, 18]   66.176\n",
              "       (18, 35]  30.882\n",
              "       (35, 60]   2.941\n",
              "Dinner (3, 18]   46.591\n",
              "       (18, 35]  45.455\n",
              "       (35, 60]   7.955"
            ]
          },
          "metadata": {},
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5QtV_C2_oD86"
      },
      "source": [
        "# Pivot o tablas dinámicas (excel)\n",
        "**Otra forma de agrupar datos en pandas**"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "kHCKwMgBXHad",
        "outputId": "b36894fb-c5a9-4bbd-b366-3a8779c287ec"
      },
      "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></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>prct_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>16.990</td>\n",
              "      <td>1.010</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>5.945</td>\n",
              "      <td>1</td>\n",
              "      <td>(3, 18]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.340</td>\n",
              "      <td>1.660</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>16.054</td>\n",
              "      <td>1</td>\n",
              "      <td>(3, 18]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>21.010</td>\n",
              "      <td>3.500</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>16.659</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23.680</td>\n",
              "      <td>3.310</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>13.978</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24.590</td>\n",
              "      <td>3.610</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>4</td>\n",
              "      <td>14.681</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>29.030</td>\n",
              "      <td>5.920</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "      <td>20.393</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>27.180</td>\n",
              "      <td>2.000</td>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>7.358</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>22.670</td>\n",
              "      <td>2.000</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>8.822</td>\n",
              "      <td>1</td>\n",
              "      <td>(18, 35]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>17.820</td>\n",
              "      <td>1.750</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>9.820</td>\n",
              "      <td>1</td>\n",
              "      <td>(3, 18]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>18.780</td>\n",
              "      <td>3.000</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Thur</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>15.974</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 prct_tip  ones  bin_total\n",
              "0        16.990 1.010  Female     No  ...    2    5.945     1    (3, 18]\n",
              "1        10.340 1.660    Male     No  ...    3   16.054     1    (3, 18]\n",
              "2        21.010 3.500    Male     No  ...    3   16.659     1   (18, 35]\n",
              "3        23.680 3.310    Male     No  ...    2   13.978     1   (18, 35]\n",
              "4        24.590 3.610  Female     No  ...    4   14.681     1   (18, 35]\n",
              "..          ...   ...     ...    ...  ...  ...      ...   ...        ...\n",
              "239      29.030 5.920    Male     No  ...    3   20.393     1   (18, 35]\n",
              "240      27.180 2.000  Female    Yes  ...    2    7.358     1   (18, 35]\n",
              "241      22.670 2.000    Male    Yes  ...    2    8.822     1   (18, 35]\n",
              "242      17.820 1.750    Male     No  ...    2    9.820     1    (3, 18]\n",
              "243      18.780 3.000  Female     No  ...    2   15.974     1   (18, 35]\n",
              "\n",
              "[244 rows x 10 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 85
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rISe0iiJsrV-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "806efb3a-60df-40c4-a177-67df233ac97f"
      },
      "source": [
        "df.groupby(['sex','time'])[['total_bill']].mean()"
      ],
      "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></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>18.048</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>21.461</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>16.339</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>19.213</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               total_bill\n",
              "sex    time              \n",
              "Male   Lunch       18.048\n",
              "       Dinner      21.461\n",
              "Female Lunch       16.339\n",
              "       Dinner      19.213"
            ]
          },
          "metadata": {},
          "execution_count": 86
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DXMCBiV7tBtE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "outputId": "f832b17d-5a70-4ea2-c11e-e96d59127fb7"
      },
      "source": [
        "df_gp = df.groupby(['sex','time'])[['total_bill']].mean().reset_index() # Borro los indices y los vuelvo columnas\n",
        "df_gp\n",
        "# Guardo este nuevo dataframe"
      ],
      "execution_count": 88,
      "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>18.048</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Male</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>21.461</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Female</td>\n",
              "      <td>Lunch</td>\n",
              "      <td>16.339</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Female</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>19.213</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      sex    time  total_bill\n",
              "0    Male   Lunch      18.048\n",
              "1    Male  Dinner      21.461\n",
              "2  Female   Lunch      16.339\n",
              "3  Female  Dinner      19.213"
            ]
          },
          "metadata": {},
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "duN0kWP1tyH5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "outputId": "bdba8949-6de3-4c41-abfc-b64ea740396a"
      },
      "source": [
        "# Sobre el voy a aplicar una tabla dinamica\n",
        "df_gp.pivot_table(values='total_bill', index='sex', columns='time') \n",
        "# Declaro mis valores, mis indices o filas y mis columnas"
      ],
      "execution_count": 90,
      "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>18.048</td>\n",
              "      <td>21.461</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>16.339</td>\n",
              "      <td>19.213</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "time    Lunch  Dinner\n",
              "sex                  \n",
              "Male   18.048  21.461\n",
              "Female 16.339  19.213"
            ]
          },
          "metadata": {},
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "w8AOWzD1uBzV"
      },
      "source": [
        "![](https://pandas-docs.github.io/pandas-docs-travis/_images/reshaping_pivot.png)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fszMZCUHt8DN",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "outputId": "50b769f9-d0fe-4a06-a21e-c2fcca1afb22"
      },
      "source": [
        "df.pivot_table(values='total_bill', index='sex', columns='time') # Por defecto .pivot_table calcula promedio. Pero podría calcular otra cosa si se lo paso como argumento"
      ],
      "execution_count": 92,
      "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>18.048</td>\n",
              "      <td>21.461</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>16.339</td>\n",
              "      <td>19.213</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "time    Lunch  Dinner\n",
              "sex                  \n",
              "Male   18.048  21.461\n",
              "Female 16.339  19.213"
            ]
          },
          "metadata": {},
          "execution_count": 92
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qXRIIetcuKoG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "outputId": "9a4a6a09-6111-48f3-c7b1-8ae29bd17f8a"
      },
      "source": [
        "# Por ejemplo podría calcular la mediana\n",
        "df.pivot_table(values='total_bill', index='sex', columns='time', aggfunc=np.median)"
      ],
      "execution_count": 93,
      "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>16.580</td>\n",
              "      <td>19.630</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>13.420</td>\n",
              "      <td>17.190</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "time    Lunch  Dinner\n",
              "sex                  \n",
              "Male   16.580  19.630\n",
              "Female 13.420  17.190"
            ]
          },
          "metadata": {},
          "execution_count": 93
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LfRGlq3guQf6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "outputId": "153bbd22-e149-4385-b3c8-5a470b2cee9c"
      },
      "source": [
        "# Puedo tmb poner una lista de funciones a calcular en mi tabla dinamica o un diccionario para especificar distintas funciones por columna\n",
        "df_pivot = df.pivot_table(values='total_bill', index='sex', columns='time', aggfunc=[np.median,np.std])\n",
        "df_pivot"
      ],
      "execution_count": 94,
      "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>16.580</td>\n",
              "      <td>19.630</td>\n",
              "      <td>7.953</td>\n",
              "      <td>9.461</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>13.420</td>\n",
              "      <td>17.190</td>\n",
              "      <td>7.501</td>\n",
              "      <td>8.202</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       median          std       \n",
              "time    Lunch Dinner Lunch Dinner\n",
              "sex                              \n",
              "Male   16.580 19.630 7.953  9.461\n",
              "Female 13.420 17.190 7.501  8.202"
            ]
          },
          "metadata": {},
          "execution_count": 94
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_pivot.unstack() # mis columnas pasan a ser filas con .unstack"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3Bwf7D43Y2Vk",
        "outputId": "1006251f-4873-4ba9-8f10-5c83e23a063d"
      },
      "execution_count": 96,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        time    sex   \n",
              "median  Lunch   Male     16.580\n",
              "                Female   13.420\n",
              "        Dinner  Male     19.630\n",
              "                Female   17.190\n",
              "std     Lunch   Male      7.953\n",
              "                Female    7.501\n",
              "        Dinner  Male      9.461\n",
              "                Female    8.202\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 96
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_7BMg7zOuWim",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "outputId": "7ef086aa-2c0e-4f24-8f4e-a948e0e3a1dc"
      },
      "source": [
        "df_pivot.unstack().reset_index() # al resetear mi indice obtengo un nuevo dataframe con mi pivot table"
      ],
      "execution_count": 97,
      "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>16.580</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>median</td>\n",
              "      <td>Lunch</td>\n",
              "      <td>Female</td>\n",
              "      <td>13.420</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>median</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>Male</td>\n",
              "      <td>19.630</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>median</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>Female</td>\n",
              "      <td>17.190</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>std</td>\n",
              "      <td>Lunch</td>\n",
              "      <td>Male</td>\n",
              "      <td>7.953</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>std</td>\n",
              "      <td>Lunch</td>\n",
              "      <td>Female</td>\n",
              "      <td>7.501</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>std</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>Male</td>\n",
              "      <td>9.461</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>std</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>Female</td>\n",
              "      <td>8.202</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  level_0    time     sex      0\n",
              "0  median   Lunch    Male 16.580\n",
              "1  median   Lunch  Female 13.420\n",
              "2  median  Dinner    Male 19.630\n",
              "3  median  Dinner  Female 17.190\n",
              "4     std   Lunch    Male  7.953\n",
              "5     std   Lunch  Female  7.501\n",
              "6     std  Dinner    Male  9.461\n",
              "7     std  Dinner  Female  8.202"
            ]
          },
          "metadata": {},
          "execution_count": 97
        }
      ]
    }
  ]
}