groupby_pivot.ipynb

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    "colab": {
      "name": "groupby pivot.ipynb",
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      "include_colab_link": true
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    "kernelspec": {
      "name": "python3",
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  "cells": [
    {
      "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_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": "6c063fa2-61c4-4ba7-d4a6-0e3b0a63c121",
        "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 # Trabajare con 3 decimales y la coma como separador de miles"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wcn24xGHZSsL"
      },
      "source": [
        "import seaborn as sns # Importo seaborn para usar una de sus bases de datos"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dDEGe8sRfpJW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "7babae3b-471e-4f8c-c55b-c33694c96dc4"
      },
      "source": [
        "df = sns.load_dataset('diamonds')\n",
        "df"
      ],
      "execution_count": 6,
      "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>carat</th>\n",
              "      <th>cut</th>\n",
              "      <th>color</th>\n",
              "      <th>clarity</th>\n",
              "      <th>depth</th>\n",
              "      <th>table</th>\n",
              "      <th>price</th>\n",
              "      <th>x</th>\n",
              "      <th>y</th>\n",
              "      <th>z</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.230</td>\n",
              "      <td>Ideal</td>\n",
              "      <td>E</td>\n",
              "      <td>SI2</td>\n",
              "      <td>61.500</td>\n",
              "      <td>55.000</td>\n",
              "      <td>326</td>\n",
              "      <td>3.950</td>\n",
              "      <td>3.980</td>\n",
              "      <td>2.430</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.210</td>\n",
              "      <td>Premium</td>\n",
              "      <td>E</td>\n",
              "      <td>SI1</td>\n",
              "      <td>59.800</td>\n",
              "      <td>61.000</td>\n",
              "      <td>326</td>\n",
              "      <td>3.890</td>\n",
              "      <td>3.840</td>\n",
              "      <td>2.310</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.230</td>\n",
              "      <td>Good</td>\n",
              "      <td>E</td>\n",
              "      <td>VS1</td>\n",
              "      <td>56.900</td>\n",
              "      <td>65.000</td>\n",
              "      <td>327</td>\n",
              "      <td>4.050</td>\n",
              "      <td>4.070</td>\n",
              "      <td>2.310</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.290</td>\n",
              "      <td>Premium</td>\n",
              "      <td>I</td>\n",
              "      <td>VS2</td>\n",
              "      <td>62.400</td>\n",
              "      <td>58.000</td>\n",
              "      <td>334</td>\n",
              "      <td>4.200</td>\n",
              "      <td>4.230</td>\n",
              "      <td>2.630</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.310</td>\n",
              "      <td>Good</td>\n",
              "      <td>J</td>\n",
              "      <td>SI2</td>\n",
              "      <td>63.300</td>\n",
              "      <td>58.000</td>\n",
              "      <td>335</td>\n",
              "      <td>4.340</td>\n",
              "      <td>4.350</td>\n",
              "      <td>2.750</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>53935</th>\n",
              "      <td>0.720</td>\n",
              "      <td>Ideal</td>\n",
              "      <td>D</td>\n",
              "      <td>SI1</td>\n",
              "      <td>60.800</td>\n",
              "      <td>57.000</td>\n",
              "      <td>2757</td>\n",
              "      <td>5.750</td>\n",
              "      <td>5.760</td>\n",
              "      <td>3.500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53936</th>\n",
              "      <td>0.720</td>\n",
              "      <td>Good</td>\n",
              "      <td>D</td>\n",
              "      <td>SI1</td>\n",
              "      <td>63.100</td>\n",
              "      <td>55.000</td>\n",
              "      <td>2757</td>\n",
              "      <td>5.690</td>\n",
              "      <td>5.750</td>\n",
              "      <td>3.610</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53937</th>\n",
              "      <td>0.700</td>\n",
              "      <td>Very Good</td>\n",
              "      <td>D</td>\n",
              "      <td>SI1</td>\n",
              "      <td>62.800</td>\n",
              "      <td>60.000</td>\n",
              "      <td>2757</td>\n",
              "      <td>5.660</td>\n",
              "      <td>5.680</td>\n",
              "      <td>3.560</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53938</th>\n",
              "      <td>0.860</td>\n",
              "      <td>Premium</td>\n",
              "      <td>H</td>\n",
              "      <td>SI2</td>\n",
              "      <td>61.000</td>\n",
              "      <td>58.000</td>\n",
              "      <td>2757</td>\n",
              "      <td>6.150</td>\n",
              "      <td>6.120</td>\n",
              "      <td>3.740</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53939</th>\n",
              "      <td>0.750</td>\n",
              "      <td>Ideal</td>\n",
              "      <td>D</td>\n",
              "      <td>SI2</td>\n",
              "      <td>62.200</td>\n",
              "      <td>55.000</td>\n",
              "      <td>2757</td>\n",
              "      <td>5.830</td>\n",
              "      <td>5.870</td>\n",
              "      <td>3.640</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>53940 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       carat        cut color clarity  depth  table  price     x     y     z\n",
              "0      0.230      Ideal     E     SI2 61.500 55.000    326 3.950 3.980 2.430\n",
              "1      0.210    Premium     E     SI1 59.800 61.000    326 3.890 3.840 2.310\n",
              "2      0.230       Good     E     VS1 56.900 65.000    327 4.050 4.070 2.310\n",
              "3      0.290    Premium     I     VS2 62.400 58.000    334 4.200 4.230 2.630\n",
              "4      0.310       Good     J     SI2 63.300 58.000    335 4.340 4.350 2.750\n",
              "...      ...        ...   ...     ...    ...    ...    ...   ...   ...   ...\n",
              "53935  0.720      Ideal     D     SI1 60.800 57.000   2757 5.750 5.760 3.500\n",
              "53936  0.720       Good     D     SI1 63.100 55.000   2757 5.690 5.750 3.610\n",
              "53937  0.700  Very Good     D     SI1 62.800 60.000   2757 5.660 5.680 3.560\n",
              "53938  0.860    Premium     H     SI2 61.000 58.000   2757 6.150 6.120 3.740\n",
              "53939  0.750      Ideal     D     SI2 62.200 55.000   2757 5.830 5.870 3.640\n",
              "\n",
              "[53940 rows x 10 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby(\"cut\") # Aqui agrupo por tipo de corte a mis datos"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kIYhTjg8Be7C",
        "outputId": "b4ecd128-fb46-410a-d856-59e54132ce96"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<pandas.core.groupby.generic.DataFrameGroupBy object at 0x7f782b0b6b50>"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Y con esto puedo obtener medidas de tendencia central por ejemplo.\n",
        "df.groupby(\"cut\").mean() # Como el promedio"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "qS4HHPuPBpXq",
        "outputId": "1df5e6b3-0414-4ae8-97c3-b39dee34203a"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
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              "      <th>carat</th>\n",
              "      <th>depth</th>\n",
              "      <th>table</th>\n",
              "      <th>price</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Ideal</th>\n",
              "      <td>0.703</td>\n",
              "      <td>61.709</td>\n",
              "      <td>55.952</td>\n",
              "      <td>3,457.542</td>\n",
              "      <td>5.507</td>\n",
              "      <td>5.520</td>\n",
              "      <td>3.401</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Premium</th>\n",
              "      <td>0.892</td>\n",
              "      <td>61.265</td>\n",
              "      <td>58.746</td>\n",
              "      <td>4,584.258</td>\n",
              "      <td>5.974</td>\n",
              "      <td>5.945</td>\n",
              "      <td>3.647</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Very Good</th>\n",
              "      <td>0.806</td>\n",
              "      <td>61.818</td>\n",
              "      <td>57.956</td>\n",
              "      <td>3,981.760</td>\n",
              "      <td>5.741</td>\n",
              "      <td>5.770</td>\n",
              "      <td>3.560</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Good</th>\n",
              "      <td>0.849</td>\n",
              "      <td>62.366</td>\n",
              "      <td>58.695</td>\n",
              "      <td>3,928.864</td>\n",
              "      <td>5.839</td>\n",
              "      <td>5.851</td>\n",
              "      <td>3.640</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fair</th>\n",
              "      <td>1.046</td>\n",
              "      <td>64.042</td>\n",
              "      <td>59.054</td>\n",
              "      <td>4,358.758</td>\n",
              "      <td>6.247</td>\n",
              "      <td>6.183</td>\n",
              "      <td>3.983</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           carat  depth  table     price     x     y     z\n",
              "cut                                                       \n",
              "Ideal      0.703 61.709 55.952 3,457.542 5.507 5.520 3.401\n",
              "Premium    0.892 61.265 58.746 4,584.258 5.974 5.945 3.647\n",
              "Very Good  0.806 61.818 57.956 3,981.760 5.741 5.770 3.560\n",
              "Good       0.849 62.366 58.695 3,928.864 5.839 5.851 3.640\n",
              "Fair       1.046 64.042 59.054 4,358.758 6.247 6.183 3.983"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby(\"cut\").median() # La mediana"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "CAk1cRwKB1aO",
        "outputId": "29dd82be-779d-49b8-a229-e7341bf15a75"
      },
      "execution_count": 9,
      "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>carat</th>\n",
              "      <th>depth</th>\n",
              "      <th>table</th>\n",
              "      <th>price</th>\n",
              "      <th>x</th>\n",
              "      <th>y</th>\n",
              "      <th>z</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cut</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Ideal</th>\n",
              "      <td>0.540</td>\n",
              "      <td>61.800</td>\n",
              "      <td>56.000</td>\n",
              "      <td>1,810.000</td>\n",
              "      <td>5.250</td>\n",
              "      <td>5.260</td>\n",
              "      <td>3.230</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Premium</th>\n",
              "      <td>0.860</td>\n",
              "      <td>61.400</td>\n",
              "      <td>59.000</td>\n",
              "      <td>3,185.000</td>\n",
              "      <td>6.110</td>\n",
              "      <td>6.060</td>\n",
              "      <td>3.720</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Very Good</th>\n",
              "      <td>0.710</td>\n",
              "      <td>62.100</td>\n",
              "      <td>58.000</td>\n",
              "      <td>2,648.000</td>\n",
              "      <td>5.740</td>\n",
              "      <td>5.770</td>\n",
              "      <td>3.560</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Good</th>\n",
              "      <td>0.820</td>\n",
              "      <td>63.400</td>\n",
              "      <td>58.000</td>\n",
              "      <td>3,050.500</td>\n",
              "      <td>5.980</td>\n",
              "      <td>5.990</td>\n",
              "      <td>3.700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fair</th>\n",
              "      <td>1.000</td>\n",
              "      <td>65.000</td>\n",
              "      <td>58.000</td>\n",
              "      <td>3,282.000</td>\n",
              "      <td>6.175</td>\n",
              "      <td>6.100</td>\n",
              "      <td>3.970</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           carat  depth  table     price     x     y     z\n",
              "cut                                                       \n",
              "Ideal      0.540 61.800 56.000 1,810.000 5.250 5.260 3.230\n",
              "Premium    0.860 61.400 59.000 3,185.000 6.110 6.060 3.720\n",
              "Very Good  0.710 62.100 58.000 2,648.000 5.740 5.770 3.560\n",
              "Good       0.820 63.400 58.000 3,050.500 5.980 5.990 3.700\n",
              "Fair       1.000 65.000 58.000 3,282.000 6.175 6.100 3.970"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Si no quisiera ver la media o mediana de todo mi dataframe puedo seleccionar solo una parte del mismo agregando que columna quiero ver mi medida de tendencia central luego de declarar mi columna para agrupar de la siguiente forma: "
      ],
      "metadata": {
        "id": "qcQqAwzVCCpV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby(\"cut\")[\"carat\"].median()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LFY7pDjFCPtq",
        "outputId": "0dcdf4fd-a16f-46a9-87ea-cb6a16534f0c"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "cut\n",
              "Ideal       0.540\n",
              "Premium     0.860\n",
              "Very Good   0.710\n",
              "Good        0.820\n",
              "Fair        1.000\n",
              "Name: carat, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Puedo no solo ver medidas de tendencia central sino tambien contar los datos que tengo para cada agrupamiento:"
      ],
      "metadata": {
        "id": "jqIBE_qeCZmy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby(\"cut\")[\"carat\"].count()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GCnn8CbCCfmq",
        "outputId": "da4d415c-02a8-44eb-d719-382ddd109aff"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "cut\n",
              "Ideal        21551\n",
              "Premium      13791\n",
              "Very Good    12082\n",
              "Good          4906\n",
              "Fair          1610\n",
              "Name: carat, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby(\"cut\").count()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "oUn_UNplCkuC",
        "outputId": "321c16d3-a348-4072-f1e3-57041dcde460"
      },
      "execution_count": 13,
      "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>carat</th>\n",
              "      <th>color</th>\n",
              "      <th>clarity</th>\n",
              "      <th>depth</th>\n",
              "      <th>table</th>\n",
              "      <th>price</th>\n",
              "      <th>x</th>\n",
              "      <th>y</th>\n",
              "      <th>z</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cut</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>Ideal</th>\n",
              "      <td>21551</td>\n",
              "      <td>21551</td>\n",
              "      <td>21551</td>\n",
              "      <td>21551</td>\n",
              "      <td>21551</td>\n",
              "      <td>21551</td>\n",
              "      <td>21551</td>\n",
              "      <td>21551</td>\n",
              "      <td>21551</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Premium</th>\n",
              "      <td>13791</td>\n",
              "      <td>13791</td>\n",
              "      <td>13791</td>\n",
              "      <td>13791</td>\n",
              "      <td>13791</td>\n",
              "      <td>13791</td>\n",
              "      <td>13791</td>\n",
              "      <td>13791</td>\n",
              "      <td>13791</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Very Good</th>\n",
              "      <td>12082</td>\n",
              "      <td>12082</td>\n",
              "      <td>12082</td>\n",
              "      <td>12082</td>\n",
              "      <td>12082</td>\n",
              "      <td>12082</td>\n",
              "      <td>12082</td>\n",
              "      <td>12082</td>\n",
              "      <td>12082</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Good</th>\n",
              "      <td>4906</td>\n",
              "      <td>4906</td>\n",
              "      <td>4906</td>\n",
              "      <td>4906</td>\n",
              "      <td>4906</td>\n",
              "      <td>4906</td>\n",
              "      <td>4906</td>\n",
              "      <td>4906</td>\n",
              "      <td>4906</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fair</th>\n",
              "      <td>1610</td>\n",
              "      <td>1610</td>\n",
              "      <td>1610</td>\n",
              "      <td>1610</td>\n",
              "      <td>1610</td>\n",
              "      <td>1610</td>\n",
              "      <td>1610</td>\n",
              "      <td>1610</td>\n",
              "      <td>1610</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           carat  color  clarity  depth  table  price      x      y      z\n",
              "cut                                                                       \n",
              "Ideal      21551  21551    21551  21551  21551  21551  21551  21551  21551\n",
              "Premium    13791  13791    13791  13791  13791  13791  13791  13791  13791\n",
              "Very Good  12082  12082    12082  12082  12082  12082  12082  12082  12082\n",
              "Good        4906   4906     4906   4906   4906   4906   4906   4906   4906\n",
              "Fair        1610   1610     1610   1610   1610   1610   1610   1610   1610"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Tmb puedo ver valores maximos o minimos de cada agrupamiento: "
      ],
      "metadata": {
        "id": "rBahsS13Csyh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby(\"cut\")[\"carat\"].max()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ewL1_ctoCxSK",
        "outputId": "9426205f-ce64-4b20-d4a0-f335c2ec711c"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "cut\n",
              "Ideal       3.500\n",
              "Premium     4.010\n",
              "Very Good   4.000\n",
              "Good        3.010\n",
              "Fair        5.010\n",
              "Name: carat, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby(\"cut\")[\"carat\"].min()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EbL5wsHxCzu5",
        "outputId": "8b93c6e7-6ac5-48d0-fba1-2c9cee59749e"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "cut\n",
              "Ideal       0.200\n",
              "Premium     0.200\n",
              "Very Good   0.200\n",
              "Good        0.230\n",
              "Fair        0.220\n",
              "Name: carat, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Podemos entender el group by como un objeto que contiene paquetes y sobre esos paquetes podemos usar diferencias funciones como venimos viendo y otras como los bucles. "
      ],
      "metadata": {
        "id": "1sUhT6MjC50L"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "for key_group, group in df.groupby(\"cut\"):\n",
        "  grouped_price = group[\"price\"].mean()\n",
        "\n",
        "  print(\"Cut: {}, Price U$S{} \\n\".format(key_group, grouped_price))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jkxlhUiMDUS1",
        "outputId": "b05a9c7e-d27b-4ad5-ce05-3cd849fbced8"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cut: Ideal, Price U$S3457.541970210199 \n",
            "\n",
            "Cut: Premium, Price U$S4584.2577042999055 \n",
            "\n",
            "Cut: Very Good, Price U$S3981.7598907465654 \n",
            "\n",
            "Cut: Good, Price U$S3928.864451691806 \n",
            "\n",
            "Cut: Fair, Price U$S4358.757763975155 \n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Puedo hacer un agrupamiento por mas de una columna\n",
        "df.groupby([\"cut\",\"color\"])[\"price\"].mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-CwonMFEDUcN",
        "outputId": "23d89939-9c24-41d2-e1c4-8009a2a154b3"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "cut        color\n",
              "Ideal      D       2,629.095\n",
              "           E       2,597.550\n",
              "           F       3,374.939\n",
              "           G       3,720.706\n",
              "           H       3,889.335\n",
              "           I       4,451.970\n",
              "           J       4,918.186\n",
              "Premium    D       3,631.293\n",
              "           E       3,538.914\n",
              "           F       4,324.890\n",
              "           G       4,500.742\n",
              "           H       5,216.707\n",
              "           I       5,946.181\n",
              "           J       6,294.592\n",
              "Very Good  D       3,470.467\n",
              "           E       3,214.652\n",
              "           F       3,778.820\n",
              "           G       3,872.754\n",
              "           H       4,535.390\n",
              "           I       5,255.880\n",
              "           J       5,103.513\n",
              "Good       D       3,405.382\n",
              "           E       3,423.644\n",
              "           F       3,495.750\n",
              "           G       4,123.482\n",
              "           H       4,276.255\n",
              "           I       5,078.533\n",
              "           J       4,574.173\n",
              "Fair       D       4,291.061\n",
              "           E       3,682.312\n",
              "           F       3,827.003\n",
              "           G       4,239.255\n",
              "           H       5,135.683\n",
              "           I       4,685.446\n",
              "           J       4,975.655\n",
              "Name: price, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Ese mismo agrupamiento puedo verlo como dataframe así: \n",
        "df.groupby([\"cut\",\"color\"])[\"price\"].mean().to_frame()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "IFdvsL38DUgq",
        "outputId": "caf59735-f33f-42ec-d820-c27a0581a645"
      },
      "execution_count": 20,
      "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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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>price</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cut</th>\n",
              "      <th>color</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Ideal</th>\n",
              "      <th>D</th>\n",
              "      <td>2,629.095</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>2,597.550</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>3,374.939</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>3,720.706</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>3,889.335</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>4,451.970</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>4,918.186</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Premium</th>\n",
              "      <th>D</th>\n",
              "      <td>3,631.293</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>3,538.914</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>4,324.890</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>4,500.742</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>5,216.707</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>5,946.181</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>6,294.592</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Very Good</th>\n",
              "      <th>D</th>\n",
              "      <td>3,470.467</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>3,214.652</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>3,778.820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>3,872.754</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>4,535.390</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>5,255.880</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>5,103.513</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Good</th>\n",
              "      <th>D</th>\n",
              "      <td>3,405.382</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>3,423.644</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>3,495.750</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>4,123.482</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>4,276.255</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>5,078.533</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>4,574.173</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Fair</th>\n",
              "      <th>D</th>\n",
              "      <td>4,291.061</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>3,682.312</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>3,827.003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>4,239.255</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>5,135.683</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>4,685.446</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>4,975.655</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                    price\n",
              "cut       color          \n",
              "Ideal     D     2,629.095\n",
              "          E     2,597.550\n",
              "          F     3,374.939\n",
              "          G     3,720.706\n",
              "          H     3,889.335\n",
              "          I     4,451.970\n",
              "          J     4,918.186\n",
              "Premium   D     3,631.293\n",
              "          E     3,538.914\n",
              "          F     4,324.890\n",
              "          G     4,500.742\n",
              "          H     5,216.707\n",
              "          I     5,946.181\n",
              "          J     6,294.592\n",
              "Very Good D     3,470.467\n",
              "          E     3,214.652\n",
              "          F     3,778.820\n",
              "          G     3,872.754\n",
              "          H     4,535.390\n",
              "          I     5,255.880\n",
              "          J     5,103.513\n",
              "Good      D     3,405.382\n",
              "          E     3,423.644\n",
              "          F     3,495.750\n",
              "          G     4,123.482\n",
              "          H     4,276.255\n",
              "          I     5,078.533\n",
              "          J     4,574.173\n",
              "Fair      D     4,291.061\n",
              "          E     3,682.312\n",
              "          F     3,827.003\n",
              "          G     4,239.255\n",
              "          H     5,135.683\n",
              "          I     4,685.446\n",
              "          J     4,975.655"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Con aggregate puedo ver mas de una función para mi agrupamiento\n",
        "df.groupby([\"cut\",\"color\"])[\"price\"].aggregate([min,np.mean,max])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "iJU0lWMGFIzr",
        "outputId": "ba724d20-a70f-42d8-ed92-a9357b6d03db"
      },
      "execution_count": 21,
      "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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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>min</th>\n",
              "      <th>mean</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cut</th>\n",
              "      <th>color</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Ideal</th>\n",
              "      <th>D</th>\n",
              "      <td>367</td>\n",
              "      <td>2,629.095</td>\n",
              "      <td>18693</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>326</td>\n",
              "      <td>2,597.550</td>\n",
              "      <td>18729</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>408</td>\n",
              "      <td>3,374.939</td>\n",
              "      <td>18780</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>361</td>\n",
              "      <td>3,720.706</td>\n",
              "      <td>18806</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>357</td>\n",
              "      <td>3,889.335</td>\n",
              "      <td>18760</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>348</td>\n",
              "      <td>4,451.970</td>\n",
              "      <td>18779</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>340</td>\n",
              "      <td>4,918.186</td>\n",
              "      <td>18508</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Premium</th>\n",
              "      <th>D</th>\n",
              "      <td>367</td>\n",
              "      <td>3,631.293</td>\n",
              "      <td>18575</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>326</td>\n",
              "      <td>3,538.914</td>\n",
              "      <td>18477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>342</td>\n",
              "      <td>4,324.890</td>\n",
              "      <td>18791</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>382</td>\n",
              "      <td>4,500.742</td>\n",
              "      <td>18741</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>368</td>\n",
              "      <td>5,216.707</td>\n",
              "      <td>18795</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>334</td>\n",
              "      <td>5,946.181</td>\n",
              "      <td>18823</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>363</td>\n",
              "      <td>6,294.592</td>\n",
              "      <td>18710</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Very Good</th>\n",
              "      <th>D</th>\n",
              "      <td>357</td>\n",
              "      <td>3,470.467</td>\n",
              "      <td>18542</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>352</td>\n",
              "      <td>3,214.652</td>\n",
              "      <td>18731</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>357</td>\n",
              "      <td>3,778.820</td>\n",
              "      <td>18777</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>354</td>\n",
              "      <td>3,872.754</td>\n",
              "      <td>18818</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>337</td>\n",
              "      <td>4,535.390</td>\n",
              "      <td>18803</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>336</td>\n",
              "      <td>5,255.880</td>\n",
              "      <td>18500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>336</td>\n",
              "      <td>5,103.513</td>\n",
              "      <td>18430</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Good</th>\n",
              "      <th>D</th>\n",
              "      <td>361</td>\n",
              "      <td>3,405.382</td>\n",
              "      <td>18468</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>327</td>\n",
              "      <td>3,423.644</td>\n",
              "      <td>18236</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>357</td>\n",
              "      <td>3,495.750</td>\n",
              "      <td>18686</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>394</td>\n",
              "      <td>4,123.482</td>\n",
              "      <td>18788</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>368</td>\n",
              "      <td>4,276.255</td>\n",
              "      <td>18640</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>351</td>\n",
              "      <td>5,078.533</td>\n",
              "      <td>18707</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>335</td>\n",
              "      <td>4,574.173</td>\n",
              "      <td>18325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Fair</th>\n",
              "      <th>D</th>\n",
              "      <td>536</td>\n",
              "      <td>4,291.061</td>\n",
              "      <td>16386</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>337</td>\n",
              "      <td>3,682.312</td>\n",
              "      <td>15584</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>496</td>\n",
              "      <td>3,827.003</td>\n",
              "      <td>17995</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>369</td>\n",
              "      <td>4,239.255</td>\n",
              "      <td>18574</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>659</td>\n",
              "      <td>5,135.683</td>\n",
              "      <td>18565</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>735</td>\n",
              "      <td>4,685.446</td>\n",
              "      <td>18242</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>416</td>\n",
              "      <td>4,975.655</td>\n",
              "      <td>18531</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 min      mean    max\n",
              "cut       color                      \n",
              "Ideal     D      367 2,629.095  18693\n",
              "          E      326 2,597.550  18729\n",
              "          F      408 3,374.939  18780\n",
              "          G      361 3,720.706  18806\n",
              "          H      357 3,889.335  18760\n",
              "          I      348 4,451.970  18779\n",
              "          J      340 4,918.186  18508\n",
              "Premium   D      367 3,631.293  18575\n",
              "          E      326 3,538.914  18477\n",
              "          F      342 4,324.890  18791\n",
              "          G      382 4,500.742  18741\n",
              "          H      368 5,216.707  18795\n",
              "          I      334 5,946.181  18823\n",
              "          J      363 6,294.592  18710\n",
              "Very Good D      357 3,470.467  18542\n",
              "          E      352 3,214.652  18731\n",
              "          F      357 3,778.820  18777\n",
              "          G      354 3,872.754  18818\n",
              "          H      337 4,535.390  18803\n",
              "          I      336 5,255.880  18500\n",
              "          J      336 5,103.513  18430\n",
              "Good      D      361 3,405.382  18468\n",
              "          E      327 3,423.644  18236\n",
              "          F      357 3,495.750  18686\n",
              "          G      394 4,123.482  18788\n",
              "          H      368 4,276.255  18640\n",
              "          I      351 5,078.533  18707\n",
              "          J      335 4,574.173  18325\n",
              "Fair      D      536 4,291.061  16386\n",
              "          E      337 3,682.312  15584\n",
              "          F      496 3,827.003  17995\n",
              "          G      369 4,239.255  18574\n",
              "          H      659 5,135.683  18565\n",
              "          I      735 4,685.446  18242\n",
              "          J      416 4,975.655  18531"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Puedo con aggregate tmb sumar funciones creadas por mi: \n",
        "def mean_kilo(x):\n",
        "  return np.mean(x)/1000"
      ],
      "metadata": {
        "id": "yLglrf_fFI3E"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby([\"cut\",\"color\"])[\"price\"].aggregate([min,np.mean,max,mean_kilo])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "NUnOcN4-FJCD",
        "outputId": "b498783d-4e14-45ff-d353-67f568a01ae5"
      },
      "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",
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              "    }\n",
              "\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>min</th>\n",
              "      <th>mean</th>\n",
              "      <th>max</th>\n",
              "      <th>mean_kilo</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cut</th>\n",
              "      <th>color</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Ideal</th>\n",
              "      <th>D</th>\n",
              "      <td>367</td>\n",
              "      <td>2,629.095</td>\n",
              "      <td>18693</td>\n",
              "      <td>2.629</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>326</td>\n",
              "      <td>2,597.550</td>\n",
              "      <td>18729</td>\n",
              "      <td>2.598</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>408</td>\n",
              "      <td>3,374.939</td>\n",
              "      <td>18780</td>\n",
              "      <td>3.375</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>361</td>\n",
              "      <td>3,720.706</td>\n",
              "      <td>18806</td>\n",
              "      <td>3.721</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>357</td>\n",
              "      <td>3,889.335</td>\n",
              "      <td>18760</td>\n",
              "      <td>3.889</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>348</td>\n",
              "      <td>4,451.970</td>\n",
              "      <td>18779</td>\n",
              "      <td>4.452</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>340</td>\n",
              "      <td>4,918.186</td>\n",
              "      <td>18508</td>\n",
              "      <td>4.918</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Premium</th>\n",
              "      <th>D</th>\n",
              "      <td>367</td>\n",
              "      <td>3,631.293</td>\n",
              "      <td>18575</td>\n",
              "      <td>3.631</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>326</td>\n",
              "      <td>3,538.914</td>\n",
              "      <td>18477</td>\n",
              "      <td>3.539</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>342</td>\n",
              "      <td>4,324.890</td>\n",
              "      <td>18791</td>\n",
              "      <td>4.325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>382</td>\n",
              "      <td>4,500.742</td>\n",
              "      <td>18741</td>\n",
              "      <td>4.501</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>368</td>\n",
              "      <td>5,216.707</td>\n",
              "      <td>18795</td>\n",
              "      <td>5.217</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>334</td>\n",
              "      <td>5,946.181</td>\n",
              "      <td>18823</td>\n",
              "      <td>5.946</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>363</td>\n",
              "      <td>6,294.592</td>\n",
              "      <td>18710</td>\n",
              "      <td>6.295</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Very Good</th>\n",
              "      <th>D</th>\n",
              "      <td>357</td>\n",
              "      <td>3,470.467</td>\n",
              "      <td>18542</td>\n",
              "      <td>3.470</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>352</td>\n",
              "      <td>3,214.652</td>\n",
              "      <td>18731</td>\n",
              "      <td>3.215</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>357</td>\n",
              "      <td>3,778.820</td>\n",
              "      <td>18777</td>\n",
              "      <td>3.779</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>354</td>\n",
              "      <td>3,872.754</td>\n",
              "      <td>18818</td>\n",
              "      <td>3.873</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>337</td>\n",
              "      <td>4,535.390</td>\n",
              "      <td>18803</td>\n",
              "      <td>4.535</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>336</td>\n",
              "      <td>5,255.880</td>\n",
              "      <td>18500</td>\n",
              "      <td>5.256</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>336</td>\n",
              "      <td>5,103.513</td>\n",
              "      <td>18430</td>\n",
              "      <td>5.104</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Good</th>\n",
              "      <th>D</th>\n",
              "      <td>361</td>\n",
              "      <td>3,405.382</td>\n",
              "      <td>18468</td>\n",
              "      <td>3.405</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>327</td>\n",
              "      <td>3,423.644</td>\n",
              "      <td>18236</td>\n",
              "      <td>3.424</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>357</td>\n",
              "      <td>3,495.750</td>\n",
              "      <td>18686</td>\n",
              "      <td>3.496</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>394</td>\n",
              "      <td>4,123.482</td>\n",
              "      <td>18788</td>\n",
              "      <td>4.123</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>368</td>\n",
              "      <td>4,276.255</td>\n",
              "      <td>18640</td>\n",
              "      <td>4.276</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>351</td>\n",
              "      <td>5,078.533</td>\n",
              "      <td>18707</td>\n",
              "      <td>5.079</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>335</td>\n",
              "      <td>4,574.173</td>\n",
              "      <td>18325</td>\n",
              "      <td>4.574</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Fair</th>\n",
              "      <th>D</th>\n",
              "      <td>536</td>\n",
              "      <td>4,291.061</td>\n",
              "      <td>16386</td>\n",
              "      <td>4.291</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>337</td>\n",
              "      <td>3,682.312</td>\n",
              "      <td>15584</td>\n",
              "      <td>3.682</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>496</td>\n",
              "      <td>3,827.003</td>\n",
              "      <td>17995</td>\n",
              "      <td>3.827</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>369</td>\n",
              "      <td>4,239.255</td>\n",
              "      <td>18574</td>\n",
              "      <td>4.239</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>659</td>\n",
              "      <td>5,135.683</td>\n",
              "      <td>18565</td>\n",
              "      <td>5.136</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>735</td>\n",
              "      <td>4,685.446</td>\n",
              "      <td>18242</td>\n",
              "      <td>4.685</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>416</td>\n",
              "      <td>4,975.655</td>\n",
              "      <td>18531</td>\n",
              "      <td>4.976</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 min      mean    max  mean_kilo\n",
              "cut       color                                 \n",
              "Ideal     D      367 2,629.095  18693      2.629\n",
              "          E      326 2,597.550  18729      2.598\n",
              "          F      408 3,374.939  18780      3.375\n",
              "          G      361 3,720.706  18806      3.721\n",
              "          H      357 3,889.335  18760      3.889\n",
              "          I      348 4,451.970  18779      4.452\n",
              "          J      340 4,918.186  18508      4.918\n",
              "Premium   D      367 3,631.293  18575      3.631\n",
              "          E      326 3,538.914  18477      3.539\n",
              "          F      342 4,324.890  18791      4.325\n",
              "          G      382 4,500.742  18741      4.501\n",
              "          H      368 5,216.707  18795      5.217\n",
              "          I      334 5,946.181  18823      5.946\n",
              "          J      363 6,294.592  18710      6.295\n",
              "Very Good D      357 3,470.467  18542      3.470\n",
              "          E      352 3,214.652  18731      3.215\n",
              "          F      357 3,778.820  18777      3.779\n",
              "          G      354 3,872.754  18818      3.873\n",
              "          H      337 4,535.390  18803      4.535\n",
              "          I      336 5,255.880  18500      5.256\n",
              "          J      336 5,103.513  18430      5.104\n",
              "Good      D      361 3,405.382  18468      3.405\n",
              "          E      327 3,423.644  18236      3.424\n",
              "          F      357 3,495.750  18686      3.496\n",
              "          G      394 4,123.482  18788      4.123\n",
              "          H      368 4,276.255  18640      4.276\n",
              "          I      351 5,078.533  18707      5.079\n",
              "          J      335 4,574.173  18325      4.574\n",
              "Fair      D      536 4,291.061  16386      4.291\n",
              "          E      337 3,682.312  15584      3.682\n",
              "          F      496 3,827.003  17995      3.827\n",
              "          G      369 4,239.255  18574      4.239\n",
              "          H      659 5,135.683  18565      5.136\n",
              "          I      735 4,685.446  18242      4.685\n",
              "          J      416 4,975.655  18531      4.976"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Puedo armar un diccionario para generar multiples indices no solo en las filas sino tmb en las columnas\n",
        "dict_agg = {\n",
        "    \"carat\":[min,max],\n",
        "    \"price\":[np.mean,mean_kilo]\n",
        "}\n",
        "dict_agg"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MKPygh49GH5A",
        "outputId": "53fb4133-ba0d-4ff3-a0c2-6660af56fcce"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'carat': [<function min>, <function max>],\n",
              " 'price': [<function numpy.mean>, <function __main__.mean_kilo>]}"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby([\"cut\",\"color\"]).aggregate(dict_agg)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "8rhP5cl0GH8R",
        "outputId": "06345834-bb7b-41ff-dd1d-4b05cf892922"
      },
      "execution_count": 27,
      "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\">carat</th>\n",
              "      <th colspan=\"2\" halign=\"left\">price</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_kilo</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cut</th>\n",
              "      <th>color</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Ideal</th>\n",
              "      <th>D</th>\n",
              "      <td>0.200</td>\n",
              "      <td>2.750</td>\n",
              "      <td>2,629.095</td>\n",
              "      <td>2.629</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>0.200</td>\n",
              "      <td>2.280</td>\n",
              "      <td>2,597.550</td>\n",
              "      <td>2.598</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>0.230</td>\n",
              "      <td>2.450</td>\n",
              "      <td>3,374.939</td>\n",
              "      <td>3.375</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>0.230</td>\n",
              "      <td>2.540</td>\n",
              "      <td>3,720.706</td>\n",
              "      <td>3.721</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>0.230</td>\n",
              "      <td>3.500</td>\n",
              "      <td>3,889.335</td>\n",
              "      <td>3.889</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>0.230</td>\n",
              "      <td>3.220</td>\n",
              "      <td>4,451.970</td>\n",
              "      <td>4.452</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>0.230</td>\n",
              "      <td>3.010</td>\n",
              "      <td>4,918.186</td>\n",
              "      <td>4.918</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Premium</th>\n",
              "      <th>D</th>\n",
              "      <td>0.200</td>\n",
              "      <td>2.570</td>\n",
              "      <td>3,631.293</td>\n",
              "      <td>3.631</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>0.200</td>\n",
              "      <td>3.050</td>\n",
              "      <td>3,538.914</td>\n",
              "      <td>3.539</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>0.200</td>\n",
              "      <td>3.010</td>\n",
              "      <td>4,324.890</td>\n",
              "      <td>4.325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>0.230</td>\n",
              "      <td>3.010</td>\n",
              "      <td>4,500.742</td>\n",
              "      <td>4.501</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>0.230</td>\n",
              "      <td>3.240</td>\n",
              "      <td>5,216.707</td>\n",
              "      <td>5.217</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>0.230</td>\n",
              "      <td>4.010</td>\n",
              "      <td>5,946.181</td>\n",
              "      <td>5.946</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>0.300</td>\n",
              "      <td>4.010</td>\n",
              "      <td>6,294.592</td>\n",
              "      <td>6.295</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Very Good</th>\n",
              "      <th>D</th>\n",
              "      <td>0.230</td>\n",
              "      <td>2.580</td>\n",
              "      <td>3,470.467</td>\n",
              "      <td>3.470</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>0.200</td>\n",
              "      <td>2.510</td>\n",
              "      <td>3,214.652</td>\n",
              "      <td>3.215</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>0.230</td>\n",
              "      <td>2.480</td>\n",
              "      <td>3,778.820</td>\n",
              "      <td>3.779</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>0.230</td>\n",
              "      <td>2.520</td>\n",
              "      <td>3,872.754</td>\n",
              "      <td>3.873</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>0.230</td>\n",
              "      <td>3.000</td>\n",
              "      <td>4,535.390</td>\n",
              "      <td>4.535</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>0.240</td>\n",
              "      <td>4.000</td>\n",
              "      <td>5,255.880</td>\n",
              "      <td>5.256</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>0.240</td>\n",
              "      <td>2.740</td>\n",
              "      <td>5,103.513</td>\n",
              "      <td>5.104</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Good</th>\n",
              "      <th>D</th>\n",
              "      <td>0.230</td>\n",
              "      <td>2.040</td>\n",
              "      <td>3,405.382</td>\n",
              "      <td>3.405</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>0.230</td>\n",
              "      <td>3.000</td>\n",
              "      <td>3,423.644</td>\n",
              "      <td>3.424</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>0.230</td>\n",
              "      <td>2.670</td>\n",
              "      <td>3,495.750</td>\n",
              "      <td>3.496</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>0.230</td>\n",
              "      <td>2.800</td>\n",
              "      <td>4,123.482</td>\n",
              "      <td>4.123</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>0.250</td>\n",
              "      <td>3.010</td>\n",
              "      <td>4,276.255</td>\n",
              "      <td>4.276</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>0.300</td>\n",
              "      <td>3.010</td>\n",
              "      <td>5,078.533</td>\n",
              "      <td>5.079</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>0.280</td>\n",
              "      <td>3.000</td>\n",
              "      <td>4,574.173</td>\n",
              "      <td>4.574</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"7\" valign=\"top\">Fair</th>\n",
              "      <th>D</th>\n",
              "      <td>0.250</td>\n",
              "      <td>3.400</td>\n",
              "      <td>4,291.061</td>\n",
              "      <td>4.291</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>0.220</td>\n",
              "      <td>2.040</td>\n",
              "      <td>3,682.312</td>\n",
              "      <td>3.682</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>0.250</td>\n",
              "      <td>2.580</td>\n",
              "      <td>3,827.003</td>\n",
              "      <td>3.827</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>0.230</td>\n",
              "      <td>2.600</td>\n",
              "      <td>4,239.255</td>\n",
              "      <td>4.239</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>H</th>\n",
              "      <td>0.330</td>\n",
              "      <td>4.130</td>\n",
              "      <td>5,135.683</td>\n",
              "      <td>5.136</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>I</th>\n",
              "      <td>0.410</td>\n",
              "      <td>3.020</td>\n",
              "      <td>4,685.446</td>\n",
              "      <td>4.685</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>J</th>\n",
              "      <td>0.300</td>\n",
              "      <td>5.010</td>\n",
              "      <td>4,975.655</td>\n",
              "      <td>4.976</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                carat           price          \n",
              "                  min   max      mean mean_kilo\n",
              "cut       color                                \n",
              "Ideal     D     0.200 2.750 2,629.095     2.629\n",
              "          E     0.200 2.280 2,597.550     2.598\n",
              "          F     0.230 2.450 3,374.939     3.375\n",
              "          G     0.230 2.540 3,720.706     3.721\n",
              "          H     0.230 3.500 3,889.335     3.889\n",
              "          I     0.230 3.220 4,451.970     4.452\n",
              "          J     0.230 3.010 4,918.186     4.918\n",
              "Premium   D     0.200 2.570 3,631.293     3.631\n",
              "          E     0.200 3.050 3,538.914     3.539\n",
              "          F     0.200 3.010 4,324.890     4.325\n",
              "          G     0.230 3.010 4,500.742     4.501\n",
              "          H     0.230 3.240 5,216.707     5.217\n",
              "          I     0.230 4.010 5,946.181     5.946\n",
              "          J     0.300 4.010 6,294.592     6.295\n",
              "Very Good D     0.230 2.580 3,470.467     3.470\n",
              "          E     0.200 2.510 3,214.652     3.215\n",
              "          F     0.230 2.480 3,778.820     3.779\n",
              "          G     0.230 2.520 3,872.754     3.873\n",
              "          H     0.230 3.000 4,535.390     4.535\n",
              "          I     0.240 4.000 5,255.880     5.256\n",
              "          J     0.240 2.740 5,103.513     5.104\n",
              "Good      D     0.230 2.040 3,405.382     3.405\n",
              "          E     0.230 3.000 3,423.644     3.424\n",
              "          F     0.230 2.670 3,495.750     3.496\n",
              "          G     0.230 2.800 4,123.482     4.123\n",
              "          H     0.250 3.010 4,276.255     4.276\n",
              "          I     0.300 3.010 5,078.533     5.079\n",
              "          J     0.280 3.000 4,574.173     4.574\n",
              "Fair      D     0.250 3.400 4,291.061     4.291\n",
              "          E     0.220 2.040 3,682.312     3.682\n",
              "          F     0.250 2.580 3,827.003     3.827\n",
              "          G     0.230 2.600 4,239.255     4.239\n",
              "          H     0.330 4.130 5,135.683     5.136\n",
              "          I     0.410 3.020 4,685.446     4.685\n",
              "          J     0.300 5.010 4,975.655     4.976"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Tmb podemos crear filtros.\n",
        "def f_filter(x):\n",
        "  return mean_kilo(x[\"price\"])>4"
      ],
      "metadata": {
        "id": "rv9w5a85GH-0"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby(\"cut\").filter(f_filter)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "gJPUP7WeHTaj",
        "outputId": "5509b121-860a-4639-e2f9-1f8b82071ab6"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>carat</th>\n",
              "      <th>cut</th>\n",
              "      <th>color</th>\n",
              "      <th>clarity</th>\n",
              "      <th>depth</th>\n",
              "      <th>table</th>\n",
              "      <th>price</th>\n",
              "      <th>x</th>\n",
              "      <th>y</th>\n",
              "      <th>z</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.210</td>\n",
              "      <td>Premium</td>\n",
              "      <td>E</td>\n",
              "      <td>SI1</td>\n",
              "      <td>59.800</td>\n",
              "      <td>61.000</td>\n",
              "      <td>326</td>\n",
              "      <td>3.890</td>\n",
              "      <td>3.840</td>\n",
              "      <td>2.310</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.290</td>\n",
              "      <td>Premium</td>\n",
              "      <td>I</td>\n",
              "      <td>VS2</td>\n",
              "      <td>62.400</td>\n",
              "      <td>58.000</td>\n",
              "      <td>334</td>\n",
              "      <td>4.200</td>\n",
              "      <td>4.230</td>\n",
              "      <td>2.630</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>0.220</td>\n",
              "      <td>Fair</td>\n",
              "      <td>E</td>\n",
              "      <td>VS2</td>\n",
              "      <td>65.100</td>\n",
              "      <td>61.000</td>\n",
              "      <td>337</td>\n",
              "      <td>3.870</td>\n",
              "      <td>3.780</td>\n",
              "      <td>2.490</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>0.220</td>\n",
              "      <td>Premium</td>\n",
              "      <td>F</td>\n",
              "      <td>SI1</td>\n",
              "      <td>60.400</td>\n",
              "      <td>61.000</td>\n",
              "      <td>342</td>\n",
              "      <td>3.880</td>\n",
              "      <td>3.840</td>\n",
              "      <td>2.330</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>0.200</td>\n",
              "      <td>Premium</td>\n",
              "      <td>E</td>\n",
              "      <td>SI2</td>\n",
              "      <td>60.200</td>\n",
              "      <td>62.000</td>\n",
              "      <td>345</td>\n",
              "      <td>3.790</td>\n",
              "      <td>3.750</td>\n",
              "      <td>2.270</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>53928</th>\n",
              "      <td>0.790</td>\n",
              "      <td>Premium</td>\n",
              "      <td>E</td>\n",
              "      <td>SI2</td>\n",
              "      <td>61.400</td>\n",
              "      <td>58.000</td>\n",
              "      <td>2756</td>\n",
              "      <td>6.030</td>\n",
              "      <td>5.960</td>\n",
              "      <td>3.680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53930</th>\n",
              "      <td>0.710</td>\n",
              "      <td>Premium</td>\n",
              "      <td>E</td>\n",
              "      <td>SI1</td>\n",
              "      <td>60.500</td>\n",
              "      <td>55.000</td>\n",
              "      <td>2756</td>\n",
              "      <td>5.790</td>\n",
              "      <td>5.740</td>\n",
              "      <td>3.490</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53931</th>\n",
              "      <td>0.710</td>\n",
              "      <td>Premium</td>\n",
              "      <td>F</td>\n",
              "      <td>SI1</td>\n",
              "      <td>59.800</td>\n",
              "      <td>62.000</td>\n",
              "      <td>2756</td>\n",
              "      <td>5.740</td>\n",
              "      <td>5.730</td>\n",
              "      <td>3.430</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53934</th>\n",
              "      <td>0.720</td>\n",
              "      <td>Premium</td>\n",
              "      <td>D</td>\n",
              "      <td>SI1</td>\n",
              "      <td>62.700</td>\n",
              "      <td>59.000</td>\n",
              "      <td>2757</td>\n",
              "      <td>5.690</td>\n",
              "      <td>5.730</td>\n",
              "      <td>3.580</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53938</th>\n",
              "      <td>0.860</td>\n",
              "      <td>Premium</td>\n",
              "      <td>H</td>\n",
              "      <td>SI2</td>\n",
              "      <td>61.000</td>\n",
              "      <td>58.000</td>\n",
              "      <td>2757</td>\n",
              "      <td>6.150</td>\n",
              "      <td>6.120</td>\n",
              "      <td>3.740</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>15401 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       carat      cut color clarity  depth  table  price     x     y     z\n",
              "1      0.210  Premium     E     SI1 59.800 61.000    326 3.890 3.840 2.310\n",
              "3      0.290  Premium     I     VS2 62.400 58.000    334 4.200 4.230 2.630\n",
              "8      0.220     Fair     E     VS2 65.100 61.000    337 3.870 3.780 2.490\n",
              "12     0.220  Premium     F     SI1 60.400 61.000    342 3.880 3.840 2.330\n",
              "14     0.200  Premium     E     SI2 60.200 62.000    345 3.790 3.750 2.270\n",
              "...      ...      ...   ...     ...    ...    ...    ...   ...   ...   ...\n",
              "53928  0.790  Premium     E     SI2 61.400 58.000   2756 6.030 5.960 3.680\n",
              "53930  0.710  Premium     E     SI1 60.500 55.000   2756 5.790 5.740 3.490\n",
              "53931  0.710  Premium     F     SI1 59.800 62.000   2756 5.740 5.730 3.430\n",
              "53934  0.720  Premium     D     SI1 62.700 59.000   2757 5.690 5.730 3.580\n",
              "53938  0.860  Premium     H     SI2 61.000 58.000   2757 6.150 6.120 3.740\n",
              "\n",
              "[15401 rows x 10 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby(\"cut\").filter(f_filter)[\"cut\"].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rR_7BpSKHsjL",
        "outputId": "21509b33-95c4-478b-8f57-8c66a6f711cd"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Premium', 'Fair']\n",
              "Categories (2, object): ['Premium', 'Fair']"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Solo me selecciono los tipos de corte premium y fair que son los mas caros y los que están pasando el filtro que establecí."
      ],
      "metadata": {
        "id": "Jkf-n_r7HzW5"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ys_KSRAFfsV8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "outputId": "25721166-f9c1-43ff-c339-72c8a7c96bd3"
      },
      "source": [
        "df.describe(include='all')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>sex</th>\n",
              "      <th>smoker</th>\n",
              "      <th>day</th>\n",
              "      <th>time</th>\n",
              "      <th>size</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>244.000</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": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lhPKssfKf03P",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 108
        },
        "outputId": "4d8950cb-e98c-4832-d040-4cef5fa530cf"
      },
      "source": [
        "df['day'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Sat     87\n",
              "Sun     76\n",
              "Thur    62\n",
              "Fri     19\n",
              "Name: day, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gG4hxMUif9cZ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 108
        },
        "outputId": "7647136d-b057-41b2-8c5e-f757831bf7a9"
      },
      "source": [
        "df['day'].value_counts() / df['day'].value_counts().sum() * 100"
      ],
      "execution_count": null,
      "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": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p2KtGFU1gKyx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "d9b311f9-2358-4c88-9612-4be3f7f511ba"
      },
      "source": [
        "df.groupby('sex').mean()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>size</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Male</th>\n",
              "      <td>20.744</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": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BYaEKPstgVZe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "2f61ce5f-90eb-4d87-ad8f-f8d8b28345e4"
      },
      "source": [
        "df['prct_tip'] = df['tip']/df['total_bill']\n",
        "df"
      ],
      "execution_count": null,
      "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",
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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",
              "    </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>0.059</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>0.161</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>0.167</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>0.140</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>0.147</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>0.204</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>0.074</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>0.088</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>0.098</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>0.160</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     0.059\n",
              "1        10.340 1.660    Male     No   Sun  Dinner     3     0.161\n",
              "2        21.010 3.500    Male     No   Sun  Dinner     3     0.167\n",
              "3        23.680 3.310    Male     No   Sun  Dinner     2     0.140\n",
              "4        24.590 3.610  Female     No   Sun  Dinner     4     0.147\n",
              "..          ...   ...     ...    ...   ...     ...   ...       ...\n",
              "239      29.030 5.920    Male     No   Sat  Dinner     3     0.204\n",
              "240      27.180 2.000  Female    Yes   Sat  Dinner     2     0.074\n",
              "241      22.670 2.000    Male    Yes   Sat  Dinner     2     0.088\n",
              "242      17.820 1.750    Male     No   Sat  Dinner     2     0.098\n",
              "243      18.780 3.000  Female     No  Thur  Dinner     2     0.160\n",
              "\n",
              "[244 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1WeM78MzhSCR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "ff3a734f-4578-4c7a-962a-a6be5510ea6b"
      },
      "source": [
        "df.groupby('sex').mean()"
      ],
      "execution_count": null,
      "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",
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              "\n",
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              "\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>0.158</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>0.166</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     0.158\n",
              "Female      18.057 2.833 2.460     0.166"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EUR0t62KhWTQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "5f713671-850c-4f34-8829-b831c87a4ad2"
      },
      "source": [
        "df.groupby('sex').median()"
      ],
      "execution_count": null,
      "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",
              "    .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>0.153</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>0.156</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     0.153\n",
              "Female      16.400 2.750     2     0.156"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nFyFJB0FhcYw",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "outputId": "93758c6a-1189-42f0-dff4-72636620170e"
      },
      "source": [
        "df.groupby('sex')[['total_bill','prct_tip']].describe()"
      ],
      "execution_count": null,
      "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",
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              "\n",
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              "\n",
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              "\n",
              "    .dataframe thead tr:last-of-type th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th colspan=\"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>0.158</td>\n",
              "      <td>0.065</td>\n",
              "      <td>0.036</td>\n",
              "      <td>0.121</td>\n",
              "      <td>0.153</td>\n",
              "      <td>0.186</td>\n",
              "      <td>0.710</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>0.166</td>\n",
              "      <td>0.054</td>\n",
              "      <td>0.056</td>\n",
              "      <td>0.140</td>\n",
              "      <td>0.156</td>\n",
              "      <td>0.194</td>\n",
              "      <td>0.417</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  ...    0.036 0.121 0.153 0.186 0.710\n",
              "Female     87.000 18.057 8.009 3.070 12.750  ...    0.056 0.140 0.156 0.194 0.417\n",
              "\n",
              "[2 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cXhesX5Hhj6-"
      },
      "source": [
        "def mean_eur2usd(x):\n",
        "    y = np.mean(x)*1.12\n",
        "    return y"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6BykW2M1h4ne",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "518a425a-545e-4caa-851c-9862d81b5b81"
      },
      "source": [
        "mean_eur2usd([100,102])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "113.12"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "inVHIlAVh8Ob",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "9f956a82-b9f2-4811-f790-f81d50ee3c61"
      },
      "source": [
        "df.groupby('sex')[['total_bill','prct_tip']].apply(mean_eur2usd)"
      ],
      "execution_count": null,
      "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>0.177</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>20.224</td>\n",
              "      <td>0.186</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        total_bill  prct_tip\n",
              "sex                         \n",
              "Male        23.233     0.177\n",
              "Female      20.224     0.186"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zVnPeE5UiEPC",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "28448e30-a3ac-4ee3-affa-f5ccce0c0df9"
      },
      "source": [
        "df.groupby(['sex','time'])[['total_bill','prct_tip']].apply(mean_eur2usd)"
      ],
      "execution_count": null,
      "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>0.186</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>24.037</td>\n",
              "      <td>0.174</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>18.300</td>\n",
              "      <td>0.182</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>21.519</td>\n",
              "      <td>0.190</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               total_bill  prct_tip\n",
              "sex    time                        \n",
              "Male   Lunch       20.214     0.186\n",
              "       Dinner      24.037     0.174\n",
              "Female Lunch       18.300     0.182\n",
              "       Dinner      21.519     0.190"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MElNykHLiM0I",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "8389ce23-a750-4db3-c6dc-0722a65eaa1e"
      },
      "source": [
        "df.groupby(['sex','time'])[['total_bill','prct_tip']].apply(np.std)"
      ],
      "execution_count": null,
      "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>0.045</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>9.423</td>\n",
              "      <td>0.069</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>7.393</td>\n",
              "      <td>0.034</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>8.123</td>\n",
              "      <td>0.063</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               total_bill  prct_tip\n",
              "sex    time                        \n",
              "Male   Lunch        7.832     0.045\n",
              "       Dinner       9.423     0.069\n",
              "Female Lunch        7.393     0.034\n",
              "       Dinner       8.123     0.063"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ST3HKoebiYk4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "08b65e52-36cb-4e13-ed12-ce3ae7a40829"
      },
      "source": [
        "df.groupby(['sex','time'])[['total_bill','prct_tip']].apply(lambda x: np.mean(x)*1.12)"
      ],
      "execution_count": null,
      "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>0.186</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>24.037</td>\n",
              "      <td>0.174</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Female</th>\n",
              "      <th>Lunch</th>\n",
              "      <td>18.300</td>\n",
              "      <td>0.182</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>21.519</td>\n",
              "      <td>0.190</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               total_bill  prct_tip\n",
              "sex    time                        \n",
              "Male   Lunch       20.214     0.186\n",
              "       Dinner      24.037     0.174\n",
              "Female Lunch       18.300     0.182\n",
              "       Dinner      21.519     0.190"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "31mhii5Vil_N",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "outputId": "8026ac6f-9efc-428b-999d-fe57daf82660"
      },
      "source": [
        "df.groupby(['sex','time'])[['total_bill','prct_tip']].aggregate([np.mean,np.max])"
      ],
      "execution_count": null,
      "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",
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              "\n",
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              "\n",
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              "</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>0.166</td>\n",
              "      <td>0.266</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>21.461</td>\n",
              "      <td>50.810</td>\n",
              "      <td>0.155</td>\n",
              "      <td>0.710</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>0.162</td>\n",
              "      <td>0.259</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>19.213</td>\n",
              "      <td>44.300</td>\n",
              "      <td>0.169</td>\n",
              "      <td>0.417</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    0.166 0.266\n",
              "       Dinner     21.461 50.810    0.155 0.710\n",
              "Female Lunch      16.339 43.110    0.162 0.259\n",
              "       Dinner     19.213 44.300    0.169 0.417"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0fxJUyd2iy9U",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "outputId": "8ca37066-6921-446e-b486-9c1fc46e225c"
      },
      "source": [
        "df.groupby(['sex','time'])[['total_bill','prct_tip']].agg([np.mean,np.max])"
      ],
      "execution_count": null,
      "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",
              "    .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>0.166</td>\n",
              "      <td>0.266</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>21.461</td>\n",
              "      <td>50.810</td>\n",
              "      <td>0.155</td>\n",
              "      <td>0.710</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>0.162</td>\n",
              "      <td>0.259</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dinner</th>\n",
              "      <td>19.213</td>\n",
              "      <td>44.300</td>\n",
              "      <td>0.169</td>\n",
              "      <td>0.417</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    0.166 0.266\n",
              "       Dinner     21.461 50.810    0.155 0.710\n",
              "Female Lunch      16.339 43.110    0.162 0.259\n",
              "       Dinner     19.213 44.300    0.169 0.417"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cJU0uVzOi98h",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 53
        },
        "outputId": "8ad3dc57-6fd6-43fb-8fff-ccaa7cf59ff3"
      },
      "source": [
        "dict_agg = {'tip':[min, max],'total_bill':[np.mean, mean_eur2usd]}\n",
        "dict_agg"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'tip': [<function min>, <function max>],\n",
              " 'total_bill': [<function numpy.mean>, <function __main__.mean_eur2usd>]}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eyXowXdLjHQ4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "outputId": "1b87cda3-e2fd-4880-d670-db806763e906"
      },
      "source": [
        "df.groupby(['sex','time'])[['total_bill','tip']].agg(dict_agg)"
      ],
      "execution_count": null,
      "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",
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              "\n",
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              "\n",
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              "\n",
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              "        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": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MgGJSDh1jlPT"
      },
      "source": [
        "def f_filter(x):\n",
        "    return mean_eur2usd(x['total_bill'].mean()) > 20"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wcVXVb3Jj1RB",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "a9eedb57-775c-472a-89f2-1891132261d6"
      },
      "source": [
        "df_filtered = df.groupby(['sex','time']).filter(f_filter)\n",
        "df_filtered"
      ],
      "execution_count": null,
      "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",
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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",
              "    </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>0.059</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>0.161</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>0.167</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>0.140</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>0.147</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>0.204</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>0.074</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>0.088</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>0.098</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>0.160</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     0.059\n",
              "1        10.340 1.660    Male     No   Sun  Dinner     3     0.161\n",
              "2        21.010 3.500    Male     No   Sun  Dinner     3     0.167\n",
              "3        23.680 3.310    Male     No   Sun  Dinner     2     0.140\n",
              "4        24.590 3.610  Female     No   Sun  Dinner     4     0.147\n",
              "..          ...   ...     ...    ...   ...     ...   ...       ...\n",
              "239      29.030 5.920    Male     No   Sat  Dinner     3     0.204\n",
              "240      27.180 2.000  Female    Yes   Sat  Dinner     2     0.074\n",
              "241      22.670 2.000    Male    Yes   Sat  Dinner     2     0.088\n",
              "242      17.820 1.750    Male     No   Sat  Dinner     2     0.098\n",
              "243      18.780 3.000  Female     No  Thur  Dinner     2     0.160\n",
              "\n",
              "[209 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EGGBE1SOj7mk",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "d318cf03-e7dd-4e3d-a47c-2799321e9675"
      },
      "source": [
        "df_filtered.groupby(['sex','time']).count()"
      ],
      "execution_count": null,
      "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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              "</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",
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              "  </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": {
            "tags": []
          },
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PaM-1nPmkLHt",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "2a630bb8-1916-4588-8569-f95b0d3e5f6b"
      },
      "source": [
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <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",
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              "      <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>0.059</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",
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              "      <td>0.161</td>\n",
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              "    <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>0.167</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>0.140</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>0.147</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>0.204</td>\n",
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              "    <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>0.074</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>0.088</td>\n",
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              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>17.820</td>\n",
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              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.098</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>0.160</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     0.059\n",
              "1        10.340 1.660    Male     No   Sun  Dinner     3     0.161\n",
              "2        21.010 3.500    Male     No   Sun  Dinner     3     0.167\n",
              "3        23.680 3.310    Male     No   Sun  Dinner     2     0.140\n",
              "4        24.590 3.610  Female     No   Sun  Dinner     4     0.147\n",
              "..          ...   ...     ...    ...   ...     ...   ...       ...\n",
              "239      29.030 5.920    Male     No   Sat  Dinner     3     0.204\n",
              "240      27.180 2.000  Female    Yes   Sat  Dinner     2     0.074\n",
              "241      22.670 2.000    Male    Yes   Sat  Dinner     2     0.088\n",
              "242      17.820 1.750    Male     No   Sat  Dinner     2     0.098\n",
              "243      18.780 3.000  Female     No  Thur  Dinner     2     0.160\n",
              "\n",
              "[244 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZHRbJmcok5Id"
      },
      "source": [
        "df['ones'] = 1"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ua8_jYjCk-AT",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "168167d9-0cce-4e2b-917a-ccebc95db70f"
      },
      "source": [
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "      <th>3</th>\n",
              "      <td>23.680</td>\n",
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              "      <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",
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              "      <td>3</td>\n",
              "      <td>0.204</td>\n",
              "      <td>1</td>\n",
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              "      <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>0.074</td>\n",
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              "      <td>Yes</td>\n",
              "      <td>Sat</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "      <td>0.088</td>\n",
              "      <td>1</td>\n",
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              "      <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>0.098</td>\n",
              "      <td>1</td>\n",
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              "    <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>0.160</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     0.059     1\n",
              "1        10.340 1.660    Male     No   Sun  Dinner     3     0.161     1\n",
              "2        21.010 3.500    Male     No   Sun  Dinner     3     0.167     1\n",
              "3        23.680 3.310    Male     No   Sun  Dinner     2     0.140     1\n",
              "4        24.590 3.610  Female     No   Sun  Dinner     4     0.147     1\n",
              "..          ...   ...     ...    ...   ...     ...   ...       ...   ...\n",
              "239      29.030 5.920    Male     No   Sat  Dinner     3     0.204     1\n",
              "240      27.180 2.000  Female    Yes   Sat  Dinner     2     0.074     1\n",
              "241      22.670 2.000    Male    Yes   Sat  Dinner     2     0.088     1\n",
              "242      17.820 1.750    Male     No   Sat  Dinner     2     0.098     1\n",
              "243      18.780 3.000  Female     No  Thur  Dinner     2     0.160     1\n",
              "\n",
              "[244 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TGx5uL0Bk-W7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "7f4d78e3-aaa6-40cb-d45f-3fd68ed7dba3"
      },
      "source": [
        "df_g = df.groupby(['sex','smoker'])[['ones']].sum()\n",
        "df_g"
      ],
      "execution_count": null,
      "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",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "\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",
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              "  </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": {
            "tags": []
          },
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Nt3-cpwdlHYO",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "cc5c560c-caa8-43f7-aa01-7f8c8219bb06"
      },
      "source": [
        "df_g.groupby(level=0).apply(\n",
        "\n",
        "lambda x:\n",
        "x / x.sum() * 100\n",
        "\n",
        ")"
      ],
      "execution_count": null,
      "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",
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              "\n",
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              "\n",
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              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>ones</th>\n",
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              "      <th>sex</th>\n",
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              "      <th></th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">Male</th>\n",
              "      <th>Yes</th>\n",
              "      <td>38.217</td>\n",
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              "      <th>No</th>\n",
              "      <td>61.783</td>\n",
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              "      <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": {
            "tags": []
          },
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g8EB2s7RlZ81",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "6252d5c8-25e8-4aea-9f24-6f6024059476"
      },
      "source": [
        "df['bin_total'] = pd.cut(df['total_bill'],bins = [3,18,35,60])\n",
        "df"
      ],
      "execution_count": null,
      "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>0.059</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>0.161</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>0.167</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>0.140</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>0.147</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>0.204</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>0.074</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>0.088</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>0.098</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>0.160</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    0.059     1    (3, 18]\n",
              "1        10.340 1.660    Male     No  ...    3    0.161     1    (3, 18]\n",
              "2        21.010 3.500    Male     No  ...    3    0.167     1   (18, 35]\n",
              "3        23.680 3.310    Male     No  ...    2    0.140     1   (18, 35]\n",
              "4        24.590 3.610  Female     No  ...    4    0.147     1   (18, 35]\n",
              "..          ...   ...     ...    ...  ...  ...      ...   ...        ...\n",
              "239      29.030 5.920    Male     No  ...    3    0.204     1   (18, 35]\n",
              "240      27.180 2.000  Female    Yes  ...    2    0.074     1   (18, 35]\n",
              "241      22.670 2.000    Male    Yes  ...    2    0.088     1   (18, 35]\n",
              "242      17.820 1.750    Male     No  ...    2    0.098     1    (3, 18]\n",
              "243      18.780 3.000  Female     No  ...    2    0.160     1   (18, 35]\n",
              "\n",
              "[244 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fd0c9Wwelt2F",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 90
        },
        "outputId": "a88b4800-f1ce-407d-b0f2-546e3b727e1e"
      },
      "source": [
        "pd.cut(df['total_bill'],bins = [3,18,35,60]).value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(3, 18]     127\n",
              "(18, 35]    101\n",
              "(35, 60]     16\n",
              "Name: total_bill, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JUbq0DpIl6Gl",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "outputId": "55e95cc9-ade4-4843-9b13-7efb641d5fc8"
      },
      "source": [
        "df.groupby(['time','bin_total'])[['ones']].count()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>ones</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>time</th>\n",
              "      <th>bin_total</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">Lunch</th>\n",
              "      <th>(3, 18]</th>\n",
              "      <td>45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>(18, 35]</th>\n",
              "      <td>21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>(35, 60]</th>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">Dinner</th>\n",
              "      <th>(3, 18]</th>\n",
              "      <td>82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>(18, 35]</th>\n",
              "      <td>80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>(35, 60]</th>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  ones\n",
              "time   bin_total      \n",
              "Lunch  (3, 18]      45\n",
              "       (18, 35]     21\n",
              "       (35, 60]      2\n",
              "Dinner (3, 18]      82\n",
              "       (18, 35]     80\n",
              "       (35, 60]     14"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uiHFL8nRmRVR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "outputId": "5d852e43-0fa3-4978-d468-b58ca113f530"
      },
      "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": null,
      "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": {
            "tags": []
          },
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qHkxaeCDmXfO"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5QtV_C2_oD86"
      },
      "source": [
        "# Pivot"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rISe0iiJsrV-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "2a4b6ed9-ad99-43c9-994f-28a80b3a5af0"
      },
      "source": [
        "df.groupby(['sex','time'])[['total_bill']].mean()"
      ],
      "execution_count": null,
      "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": {
            "tags": []
          },
          "execution_count": 117
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DXMCBiV7tBtE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "outputId": "9fe2d9ab-87a0-4813-8c3e-c104ac107213"
      },
      "source": [
        "df_gp = df.groupby(['sex','time'])[['total_bill']].mean().reset_index()\n",
        "df_gp"
      ],
      "execution_count": null,
      "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": {
            "tags": []
          },
          "execution_count": 118
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "duN0kWP1tyH5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "0595b154-51f7-4826-ac30-2333cfcb6903"
      },
      "source": [
        "df_gp.pivot_table(values='total_bill', index='sex', columns='time')"
      ],
      "execution_count": null,
      "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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              "        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": {
            "tags": []
          },
          "execution_count": 119
        }
      ]
    },
    {
      "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": 143
        },
        "outputId": "410b6182-b517-4dcb-d98a-74a1734e5388"
      },
      "source": [
        "df.pivot_table(values='total_bill', index='sex', columns='time')"
      ],
      "execution_count": null,
      "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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              "<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": {
            "tags": []
          },
          "execution_count": 120
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qXRIIetcuKoG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "f3339873-9b58-4839-c42b-42c1515dab95"
      },
      "source": [
        "df.pivot_table(values='total_bill', index='sex', columns='time', aggfunc=np.median)"
      ],
      "execution_count": null,
      "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",
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              "\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": {
            "tags": []
          },
          "execution_count": 121
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LfRGlq3guQf6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "outputId": "c3fa6651-eb03-4cf8-9f44-6c446a44285d"
      },
      "source": [
        "df_pivot = df.pivot_table(values='total_bill', index='sex', columns='time', aggfunc=[np.median,np.std])\n",
        "df_pivot"
      ],
      "execution_count": null,
      "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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              "  <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": {
            "tags": []
          },
          "execution_count": 123
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_7BMg7zOuWim",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "outputId": "89f8f9e3-fba3-44c6-e2aa-11e3f4ee58f7"
      },
      "source": [
        "df_pivot.unstack().reset_index()"
      ],
      "execution_count": null,
      "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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              "</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": {
            "tags": []
          },
          "execution_count": 125
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "26_fBeLbuuJq"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}