multi_index.ipynb

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  "metadata": {
    "colab": {
      "name": "multi-index.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyPr/SVkeeEai8l37F95RZLQ",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "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/multi_index.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "E9b1_XOQz8xO",
        "outputId": "a449a833-49ed-40a7-b9fc-63310a1cf4cb"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from google.colab import drive\n",
        "drive.mount(\"/content/drive\")"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "04tfhRox0fF9",
        "outputId": "9f8f4dbb-b9a0-47d0-c321-695b89a83f5d"
      },
      "source": [
        "dir_pandas = '/content/drive/My Drive/Colab Notebooks/db/{}'\n",
        "dir_pandas"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'/content/drive/My Drive/Colab Notebooks/db/{}'"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "oWtAJVMd0iac",
        "outputId": "c2321cb2-dcbd-461b-e6e4-57d0067cb444"
      },
      "source": [
        "df = pd.read_csv(dir_pandas.format(\"poblacion.csv\")).copy(deep=True)\n",
        "df"
      ],
      "execution_count": 3,
      "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>Country</th>\n",
              "      <th>year</th>\n",
              "      <th>pop</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>2015</td>\n",
              "      <td>3.441360e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Albania</td>\n",
              "      <td>2015</td>\n",
              "      <td>2.880703e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Algeria</td>\n",
              "      <td>2015</td>\n",
              "      <td>3.972802e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>American Samoa</td>\n",
              "      <td>2015</td>\n",
              "      <td>5.581200e+04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Andorra</td>\n",
              "      <td>2015</td>\n",
              "      <td>7.801100e+04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1035</th>\n",
              "      <td>Pre-demographic dividend</td>\n",
              "      <td>2018</td>\n",
              "      <td>9.194854e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1036</th>\n",
              "      <td>Small states</td>\n",
              "      <td>2018</td>\n",
              "      <td>4.057532e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1037</th>\n",
              "      <td>South Asia</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.814389e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1038</th>\n",
              "      <td>South Asia (IDA &amp; IBRD)</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.814389e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1039</th>\n",
              "      <td>Sub-Saharan Africa</td>\n",
              "      <td>2018</td>\n",
              "      <td>1.078307e+09</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1040 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                       Country  year           pop\n",
              "0                  Afghanistan  2015  3.441360e+07\n",
              "1                      Albania  2015  2.880703e+06\n",
              "2                      Algeria  2015  3.972802e+07\n",
              "3               American Samoa  2015  5.581200e+04\n",
              "4                      Andorra  2015  7.801100e+04\n",
              "...                        ...   ...           ...\n",
              "1035  Pre-demographic dividend  2018  9.194854e+08\n",
              "1036              Small states  2018  4.057532e+07\n",
              "1037                South Asia  2018  1.814389e+09\n",
              "1038   South Asia (IDA & IBRD)  2018  1.814389e+09\n",
              "1039        Sub-Saharan Africa  2018  1.078307e+09\n",
              "\n",
              "[1040 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "nQ-S7NK-066V",
        "outputId": "343452d0-ada5-4272-f1a2-76d5d197a994"
      },
      "source": [
        "pd.options.display.float_format=\"{:,.1f}\".format #Cambio el format de notación cientifica al decimal americano\n",
        "df"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Country</th>\n",
              "      <th>year</th>\n",
              "      <th>pop</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>2015</td>\n",
              "      <td>34,413,603.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Albania</td>\n",
              "      <td>2015</td>\n",
              "      <td>2,880,703.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Algeria</td>\n",
              "      <td>2015</td>\n",
              "      <td>39,728,025.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>American Samoa</td>\n",
              "      <td>2015</td>\n",
              "      <td>55,812.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Andorra</td>\n",
              "      <td>2015</td>\n",
              "      <td>78,011.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1035</th>\n",
              "      <td>Pre-demographic dividend</td>\n",
              "      <td>2018</td>\n",
              "      <td>919,485,393.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1036</th>\n",
              "      <td>Small states</td>\n",
              "      <td>2018</td>\n",
              "      <td>40,575,321.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1037</th>\n",
              "      <td>South Asia</td>\n",
              "      <td>2018</td>\n",
              "      <td>1,814,388,744.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1038</th>\n",
              "      <td>South Asia (IDA &amp; IBRD)</td>\n",
              "      <td>2018</td>\n",
              "      <td>1,814,388,744.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1039</th>\n",
              "      <td>Sub-Saharan Africa</td>\n",
              "      <td>2018</td>\n",
              "      <td>1,078,306,520.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1040 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                       Country  year             pop\n",
              "0                  Afghanistan  2015    34,413,603.0\n",
              "1                      Albania  2015     2,880,703.0\n",
              "2                      Algeria  2015    39,728,025.0\n",
              "3               American Samoa  2015        55,812.0\n",
              "4                      Andorra  2015        78,011.0\n",
              "...                        ...   ...             ...\n",
              "1035  Pre-demographic dividend  2018   919,485,393.0\n",
              "1036              Small states  2018    40,575,321.0\n",
              "1037                South Asia  2018 1,814,388,744.0\n",
              "1038   South Asia (IDA & IBRD)  2018 1,814,388,744.0\n",
              "1039        Sub-Saharan Africa  2018 1,078,306,520.0\n",
              "\n",
              "[1040 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NP_szQlj1dUz"
      },
      "source": [
        "# Voy a convertir a categorica la variable year para usar multiples indices\n",
        "df[\"year\"] = pd.Categorical(df[\"year\"])"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "T8nUcNoG1pWE",
        "outputId": "672d17ee-595f-44a0-c1c1-9bf39434438d"
      },
      "source": [
        "df.dtypes"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Country      object\n",
              "year       category\n",
              "pop         float64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "NY6TbBz_1uhl",
        "outputId": "3c753771-75b0-4aff-ab3c-b2ba037b2520"
      },
      "source": [
        "df.sample(5)"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Country</th>\n",
              "      <th>year</th>\n",
              "      <th>pop</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>263</th>\n",
              "      <td>American Samoa</td>\n",
              "      <td>2016</td>\n",
              "      <td>55,741.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>689</th>\n",
              "      <td>Seychelles</td>\n",
              "      <td>2017</td>\n",
              "      <td>95,843.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>943</th>\n",
              "      <td>Samoa</td>\n",
              "      <td>2018</td>\n",
              "      <td>196,130.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>673</th>\n",
              "      <td>Paraguay</td>\n",
              "      <td>2017</td>\n",
              "      <td>6,867,062.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>410</th>\n",
              "      <td>Palau</td>\n",
              "      <td>2016</td>\n",
              "      <td>17,725.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            Country  year         pop\n",
              "263  American Samoa  2016    55,741.0\n",
              "689      Seychelles  2017    95,843.0\n",
              "943           Samoa  2018   196,130.0\n",
              "673        Paraguay  2017 6,867,062.0\n",
              "410           Palau  2016    17,725.0"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IqvjGp5d2LRl",
        "outputId": "679780ff-6a3a-427a-c087-d1958e1eac8c"
      },
      "source": [
        "# Creo un filtro para reducir mi dataframe\n",
        "idx_filtro = df[\"Country\"].isin([\"Argentina\",\"Colombia\"])\n",
        "idx_filtro"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0       False\n",
              "1       False\n",
              "2       False\n",
              "3       False\n",
              "4       False\n",
              "        ...  \n",
              "1035    False\n",
              "1036    False\n",
              "1037    False\n",
              "1038    False\n",
              "1039    False\n",
              "Name: Country, Length: 1040, dtype: bool"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "OZr_qG-E223t",
        "outputId": "9a655a19-d452-434a-b843-570a929ece5a"
      },
      "source": [
        "df_sample = df[idx_filtro]\n",
        "df_sample"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Country</th>\n",
              "      <th>year</th>\n",
              "      <th>pop</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Argentina</td>\n",
              "      <td>2015</td>\n",
              "      <td>43,131,966.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>Colombia</td>\n",
              "      <td>2015</td>\n",
              "      <td>47,520,667.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>267</th>\n",
              "      <td>Argentina</td>\n",
              "      <td>2016</td>\n",
              "      <td>43,590,368.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>302</th>\n",
              "      <td>Colombia</td>\n",
              "      <td>2016</td>\n",
              "      <td>48,171,392.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>527</th>\n",
              "      <td>Argentina</td>\n",
              "      <td>2017</td>\n",
              "      <td>44,044,811.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>562</th>\n",
              "      <td>Colombia</td>\n",
              "      <td>2017</td>\n",
              "      <td>48,901,066.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>787</th>\n",
              "      <td>Argentina</td>\n",
              "      <td>2018</td>\n",
              "      <td>44,494,502.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>822</th>\n",
              "      <td>Colombia</td>\n",
              "      <td>2018</td>\n",
              "      <td>49,648,685.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Country  year          pop\n",
              "7    Argentina  2015 43,131,966.0\n",
              "42    Colombia  2015 47,520,667.0\n",
              "267  Argentina  2016 43,590,368.0\n",
              "302   Colombia  2016 48,171,392.0\n",
              "527  Argentina  2017 44,044,811.0\n",
              "562   Colombia  2017 48,901,066.0\n",
              "787  Argentina  2018 44,494,502.0\n",
              "822   Colombia  2018 49,648,685.0"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 332
        },
        "id": "tu6vdKzV3cak",
        "outputId": "491d3658-60ac-439f-993a-14d97345f5a3"
      },
      "source": [
        "df_sample.set_index([\"year\",\"Country\"]) # Convierto Country & Year en indices"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>pop</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>year</th>\n",
              "      <th>Country</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">2015</th>\n",
              "      <th>Argentina</th>\n",
              "      <td>43,131,966.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Colombia</th>\n",
              "      <td>47,520,667.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">2016</th>\n",
              "      <th>Argentina</th>\n",
              "      <td>43,590,368.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Colombia</th>\n",
              "      <td>48,171,392.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">2017</th>\n",
              "      <th>Argentina</th>\n",
              "      <td>44,044,811.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Colombia</th>\n",
              "      <td>48,901,066.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">2018</th>\n",
              "      <th>Argentina</th>\n",
              "      <td>44,494,502.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Colombia</th>\n",
              "      <td>49,648,685.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                        pop\n",
              "year Country               \n",
              "2015 Argentina 43,131,966.0\n",
              "     Colombia  47,520,667.0\n",
              "2016 Argentina 43,590,368.0\n",
              "     Colombia  48,171,392.0\n",
              "2017 Argentina 44,044,811.0\n",
              "     Colombia  48,901,066.0\n",
              "2018 Argentina 44,494,502.0\n",
              "     Colombia  49,648,685.0"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 332
        },
        "id": "HlpqQV-j4mzF",
        "outputId": "ea5c0686-d1be-4d54-daf7-2f411c7aaac0"
      },
      "source": [
        "df_sample.set_index([\"Country\",\"year\"]) # Convierto Country & Year en indices"
      ],
      "execution_count": 11,
      "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>pop</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country</th>\n",
              "      <th>year</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Argentina</th>\n",
              "      <th>2015</th>\n",
              "      <td>43,131,966.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Colombia</th>\n",
              "      <th>2015</th>\n",
              "      <td>47,520,667.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Argentina</th>\n",
              "      <th>2016</th>\n",
              "      <td>43,590,368.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Colombia</th>\n",
              "      <th>2016</th>\n",
              "      <td>48,171,392.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Argentina</th>\n",
              "      <th>2017</th>\n",
              "      <td>44,044,811.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Colombia</th>\n",
              "      <th>2017</th>\n",
              "      <td>48,901,066.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Argentina</th>\n",
              "      <th>2018</th>\n",
              "      <td>44,494,502.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Colombia</th>\n",
              "      <th>2018</th>\n",
              "      <td>49,648,685.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                        pop\n",
              "Country   year             \n",
              "Argentina 2015 43,131,966.0\n",
              "Colombia  2015 47,520,667.0\n",
              "Argentina 2016 43,590,368.0\n",
              "Colombia  2016 48,171,392.0\n",
              "Argentina 2017 44,044,811.0\n",
              "Colombia  2017 48,901,066.0\n",
              "Argentina 2018 44,494,502.0\n",
              "Colombia  2018 49,648,685.0"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 332
        },
        "id": "HUdPZz3_4I5F",
        "outputId": "8371862d-e177-49ea-a4ad-20ecc7083f2d"
      },
      "source": [
        "df_sample.set_index([\"year\",\"Country\"]).sort_index() #Agrupo los indices para mejor visualización"
      ],
      "execution_count": 12,
      "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>pop</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>year</th>\n",
              "      <th>Country</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">2015</th>\n",
              "      <th>Argentina</th>\n",
              "      <td>43,131,966.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Colombia</th>\n",
              "      <td>47,520,667.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">2016</th>\n",
              "      <th>Argentina</th>\n",
              "      <td>43,590,368.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Colombia</th>\n",
              "      <td>48,171,392.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">2017</th>\n",
              "      <th>Argentina</th>\n",
              "      <td>44,044,811.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Colombia</th>\n",
              "      <td>48,901,066.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">2018</th>\n",
              "      <th>Argentina</th>\n",
              "      <td>44,494,502.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Colombia</th>\n",
              "      <td>49,648,685.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                        pop\n",
              "year Country               \n",
              "2015 Argentina 43,131,966.0\n",
              "     Colombia  47,520,667.0\n",
              "2016 Argentina 43,590,368.0\n",
              "     Colombia  48,171,392.0\n",
              "2017 Argentina 44,044,811.0\n",
              "     Colombia  48,901,066.0\n",
              "2018 Argentina 44,494,502.0\n",
              "     Colombia  49,648,685.0"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 332
        },
        "id": "fGkzHMFY4udM",
        "outputId": "de7bf695-bb5e-45e0-d134-677405f342d9"
      },
      "source": [
        "df_sample = df_sample.set_index([\"Country\",\"year\"]).sort_index() # Guardo mi dataframe como un dataframe con multiples indices\n",
        "df_sample"
      ],
      "execution_count": 40,
      "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>pop</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country</th>\n",
              "      <th>year</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Argentina</th>\n",
              "      <th>2015</th>\n",
              "      <td>43,131,966.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>43,590,368.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>44,044,811.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>44,494,502.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Colombia</th>\n",
              "      <th>2015</th>\n",
              "      <td>47,520,667.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>48,171,392.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>48,901,066.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>49,648,685.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                        pop\n",
              "Country   year             \n",
              "Argentina 2015 43,131,966.0\n",
              "          2016 43,590,368.0\n",
              "          2017 44,044,811.0\n",
              "          2018 44,494,502.0\n",
              "Colombia  2015 47,520,667.0\n",
              "          2016 48,171,392.0\n",
              "          2017 48,901,066.0\n",
              "          2018 49,648,685.0"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "8yGw0gTOaKRD",
        "outputId": "b108a3b4-aba7-4d1b-b619-804c92751101"
      },
      "source": [
        "# Puedo seleccionar por ejemplo todos los datos de colombia con el metodo .loc\n",
        "df_sample.loc[\"Colombia\",:]\n"
      ],
      "execution_count": 41,
      "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>pop</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>year</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015</th>\n",
              "      <td>47,520,667.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>48,171,392.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>48,901,066.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>49,648,685.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              pop\n",
              "year             \n",
              "2015 47,520,667.0\n",
              "2016 48,171,392.0\n",
              "2017 48,901,066.0\n",
              "2018 49,648,685.0"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sM9bPBrJc_L4",
        "outputId": "92db947c-879f-45c8-ecff-125d64eb8a31"
      },
      "source": [
        "df_sample.loc[\"Colombia\",:].loc[2016,:]"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "pop   48,171,392.0\n",
              "Name: 2016, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g_3cr0bqdJIo",
        "outputId": "554059e0-7519-411c-a989-22a7da41686b"
      },
      "source": [
        "df_sample.xs([\"Argentina\",2018])"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "pop   44,494,502.0\n",
              "Name: (Argentina, 2018), dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "N06jTyqMevK_",
        "outputId": "1b17a911-c780-4f62-a918-11140da8a079"
      },
      "source": [
        "df_sample.xs([\"Argentina\"])"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>pop</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>year</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015</th>\n",
              "      <td>43,131,966.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>43,590,368.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>44,044,811.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>44,494,502.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              pop\n",
              "year             \n",
              "2015 43,131,966.0\n",
              "2016 43,590,368.0\n",
              "2017 44,044,811.0\n",
              "2018 44,494,502.0"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "T3QS7JTNe2Jp",
        "outputId": "b581573b-ec00-48f8-8448-99a1c7606023"
      },
      "source": [
        "df_sample.xs(2018,level=\"year\")"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead 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>pop</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Argentina</th>\n",
              "      <td>44,494,502.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Colombia</th>\n",
              "      <td>49,648,685.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                   pop\n",
              "Country               \n",
              "Argentina 44,494,502.0\n",
              "Colombia  49,648,685.0"
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "Rzox6fiEfaoK",
        "outputId": "03433de0-cd01-42a6-c63f-bca247fed662"
      },
      "source": [
        "df_countries = df.set_index([\"Country\",\"year\"]).sort_index(ascending = [True,True]) # Con ascending dentro del sort_index puedo escoger como ordenar mis datos. \n",
        "df_countries"
      ],
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>pop</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country</th>\n",
              "      <th>year</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Afghanistan</th>\n",
              "      <th>2015</th>\n",
              "      <td>34,413,603.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>35,383,128.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>36,296,400.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>37,172,386.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Albania</th>\n",
              "      <th>2015</th>\n",
              "      <td>2,880,703.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Zambia</th>\n",
              "      <th>2018</th>\n",
              "      <td>17,351,822.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Zimbabwe</th>\n",
              "      <th>2015</th>\n",
              "      <td>13,814,629.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>14,030,390.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>14,236,745.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>14,439,018.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1040 rows × 1 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                          pop\n",
              "Country     year             \n",
              "Afghanistan 2015 34,413,603.0\n",
              "            2016 35,383,128.0\n",
              "            2017 36,296,400.0\n",
              "            2018 37,172,386.0\n",
              "Albania     2015  2,880,703.0\n",
              "...                       ...\n",
              "Zambia      2018 17,351,822.0\n",
              "Zimbabwe    2015 13,814,629.0\n",
              "            2016 14,030,390.0\n",
              "            2017 14,236,745.0\n",
              "            2018 14,439,018.0\n",
              "\n",
              "[1040 rows x 1 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SENp18gDgiOr"
      },
      "source": [
        "ids = pd.IndexSlice\n",
        "#df_countries.loc[ids[\"Aruba\":\"Austria\",\"2017\":\"2015\"],:].sort_index()"
      ],
      "execution_count": 71,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "hSLVjTHzhix_",
        "outputId": "f0aa1665-ea26-43de-b547-be7b45639ee9"
      },
      "source": [
        "df_countries.loc[ids[\"Aruba\":\"Austria\",2015:2017],:].sort_index() # Selecciono solo una slice o rebanada de mi dataframe. Previo a eso debo ordenarlo"
      ],
      "execution_count": 79,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>pop</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country</th>\n",
              "      <th>year</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">Aruba</th>\n",
              "      <th>2015</th>\n",
              "      <td>104,341.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>104,872.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>105,366.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">Australia</th>\n",
              "      <th>2015</th>\n",
              "      <td>23,815,995.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>24,190,907.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>24,601,860.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">Austria</th>\n",
              "      <th>2015</th>\n",
              "      <td>8,642,699.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>8,736,668.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>8,797,566.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                        pop\n",
              "Country   year             \n",
              "Aruba     2015    104,341.0\n",
              "          2016    104,872.0\n",
              "          2017    105,366.0\n",
              "Australia 2015 23,815,995.0\n",
              "          2016 24,190,907.0\n",
              "          2017 24,601,860.0\n",
              "Austria   2015  8,642,699.0\n",
              "          2016  8,736,668.0\n",
              "          2017  8,797,566.0"
            ]
          },
          "metadata": {},
          "execution_count": 79
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8qc_ntWQiEkv",
        "outputId": "d914930b-1d1a-47b6-dee4-a2032a7109d4"
      },
      "source": [
        "df_countries.index"
      ],
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "MultiIndex([('Afghanistan', 2015),\n",
              "            ('Afghanistan', 2016),\n",
              "            ('Afghanistan', 2017),\n",
              "            ('Afghanistan', 2018),\n",
              "            (    'Albania', 2015),\n",
              "            (    'Albania', 2016),\n",
              "            (    'Albania', 2017),\n",
              "            (    'Albania', 2018),\n",
              "            (    'Algeria', 2015),\n",
              "            (    'Algeria', 2016),\n",
              "            ...\n",
              "            ('Yemen, Rep.', 2017),\n",
              "            ('Yemen, Rep.', 2018),\n",
              "            (     'Zambia', 2015),\n",
              "            (     'Zambia', 2016),\n",
              "            (     'Zambia', 2017),\n",
              "            (     'Zambia', 2018),\n",
              "            (   'Zimbabwe', 2015),\n",
              "            (   'Zimbabwe', 2016),\n",
              "            (   'Zimbabwe', 2017),\n",
              "            (   'Zimbabwe', 2018)],\n",
              "           names=['Country', 'year'], length=1040)"
            ]
          },
          "metadata": {},
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hH09HCw7iP7j",
        "outputId": "8918cd6d-55e2-4457-9ddd-050fe3813f72"
      },
      "source": [
        "df_countries.index.get_level_values(0)"
      ],
      "execution_count": 82,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Afghanistan', 'Afghanistan', 'Afghanistan', 'Afghanistan', 'Albania',\n",
              "       'Albania', 'Albania', 'Albania', 'Algeria', 'Algeria',\n",
              "       ...\n",
              "       'Yemen, Rep.', 'Yemen, Rep.', 'Zambia', 'Zambia', 'Zambia', 'Zambia',\n",
              "       'Zimbabwe', 'Zimbabwe', 'Zimbabwe', 'Zimbabwe'],\n",
              "      dtype='object', name='Country', length=1040)"
            ]
          },
          "metadata": {},
          "execution_count": 82
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NVP46OTJiQGR",
        "outputId": "32f1e30c-2346-4f6d-cc2b-c4377a99d1f6"
      },
      "source": [
        "df_countries.index.get_level_values(1)"
      ],
      "execution_count": 83,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "CategoricalIndex([2015, 2016, 2017, 2018, 2015, 2016, 2017, 2018, 2015, 2016,\n",
              "                  ...\n",
              "                  2017, 2018, 2015, 2016, 2017, 2018, 2015, 2016, 2017, 2018],\n",
              "                 categories=[2015, 2016, 2017, 2018], ordered=False, name='year', dtype='category', length=1040)"
            ]
          },
          "metadata": {},
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9ThbKp94ig3X",
        "outputId": "b2e24fbe-1daa-44e5-f1e2-2d7ae1fda45f"
      },
      "source": [
        "df_countries[\"pop\"]"
      ],
      "execution_count": 85,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Country      year\n",
              "Afghanistan  2015   34,413,603.0\n",
              "             2016   35,383,128.0\n",
              "             2017   36,296,400.0\n",
              "             2018   37,172,386.0\n",
              "Albania      2015    2,880,703.0\n",
              "                        ...     \n",
              "Zambia       2018   17,351,822.0\n",
              "Zimbabwe     2015   13,814,629.0\n",
              "             2016   14,030,390.0\n",
              "             2017   14,236,745.0\n",
              "             2018   14,439,018.0\n",
              "Name: pop, Length: 1040, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 85
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AsD3mJyDilHm",
        "outputId": "0715b467-c611-40b4-cf9b-ef43255973b3"
      },
      "source": [
        "df_countries[\"pop\"][\"Argentina\"]"
      ],
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "year\n",
              "2015   43,131,966.0\n",
              "2016   43,590,368.0\n",
              "2017   44,044,811.0\n",
              "2018   44,494,502.0\n",
              "Name: pop, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 86
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8-jmVYLdipzl",
        "outputId": "bf048dcf-1ac8-4260-bb8f-caf265774e9a"
      },
      "source": [
        "df_countries[\"pop\"][\"Colombia\"]"
      ],
      "execution_count": 96,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "year\n",
              "2015   47,520,667.0\n",
              "2016   48,171,392.0\n",
              "2017   48,901,066.0\n",
              "2018   49,648,685.0\n",
              "Name: pop, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 96
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Pc3CtPDXjHT9"
      },
      "source": [
        "df_countries[\"pop\"][\"Colombia\"][\"2016\"] #Cadena de instrucciones para extraer un dato especifico"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "R8Wz9aucjjaH"
      },
      "source": [
        "**Tener multiples indices me sirve para poder realizar operaciones matematicas sobre el nivel de indices deseado. Por ejemplo. Sobre el nivel de año quiero que me indique la población mundial**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "0I_6BbyzjukH",
        "outputId": "f3835de1-93cc-4cff-ec73-bbccc9ac06b9"
      },
      "source": [
        "df_countries.sum(level=\"year\")"
      ],
      "execution_count": 102,
      "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>pop</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>year</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015</th>\n",
              "      <td>65,679,147,019.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>66,487,930,677.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>67,294,176,701.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>68,087,886,692.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  pop\n",
              "year                 \n",
              "2015 65,679,147,019.0\n",
              "2016 66,487,930,677.0\n",
              "2017 67,294,176,701.0\n",
              "2018 68,087,886,692.0"
            ]
          },
          "metadata": {},
          "execution_count": 102
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YdZMC5jTkNaN"
      },
      "source": [
        "**puedo convertir indices en columnas con el metodo .unnstack**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 332
        },
        "id": "MdGnTp99kTmn",
        "outputId": "46f47d74-af3e-4732-b05f-9ff41cf17040"
      },
      "source": [
        "df_sample"
      ],
      "execution_count": 103,
      "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>pop</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country</th>\n",
              "      <th>year</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Argentina</th>\n",
              "      <th>2015</th>\n",
              "      <td>43,131,966.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>43,590,368.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>44,044,811.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>44,494,502.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Colombia</th>\n",
              "      <th>2015</th>\n",
              "      <td>47,520,667.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>48,171,392.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>48,901,066.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>49,648,685.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                        pop\n",
              "Country   year             \n",
              "Argentina 2015 43,131,966.0\n",
              "          2016 43,590,368.0\n",
              "          2017 44,044,811.0\n",
              "          2018 44,494,502.0\n",
              "Colombia  2015 47,520,667.0\n",
              "          2016 48,171,392.0\n",
              "          2017 48,901,066.0\n",
              "          2018 49,648,685.0"
            ]
          },
          "metadata": {},
          "execution_count": 103
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "0BDNAJWbkWSd",
        "outputId": "76870ad1-ac02-4dca-a3fa-cda80e81614d"
      },
      "source": [
        "df_sample.unstack(\"year\")"
      ],
      "execution_count": 104,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr th {\n",
              "        text-align: left;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr:last-of-type th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th colspan=\"4\" halign=\"left\">pop</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>year</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Argentina</th>\n",
              "      <td>43,131,966.0</td>\n",
              "      <td>43,590,368.0</td>\n",
              "      <td>44,044,811.0</td>\n",
              "      <td>44,494,502.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Colombia</th>\n",
              "      <td>47,520,667.0</td>\n",
              "      <td>48,171,392.0</td>\n",
              "      <td>48,901,066.0</td>\n",
              "      <td>49,648,685.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                   pop                                       \n",
              "year              2015         2016         2017         2018\n",
              "Country                                                      \n",
              "Argentina 43,131,966.0 43,590,368.0 44,044,811.0 44,494,502.0\n",
              "Colombia  47,520,667.0 48,171,392.0 48,901,066.0 49,648,685.0"
            ]
          },
          "metadata": {},
          "execution_count": 104
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "z8M4UuP_kuya",
        "outputId": "d781e1c2-cf8e-48bb-a248-04a3d3d3d940"
      },
      "source": [
        "df_sample.unstack(\"Country\")"
      ],
      "execution_count": 105,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr th {\n",
              "        text-align: left;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr:last-of-type th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th colspan=\"2\" halign=\"left\">pop</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country</th>\n",
              "      <th>Argentina</th>\n",
              "      <th>Colombia</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>year</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015</th>\n",
              "      <td>43,131,966.0</td>\n",
              "      <td>47,520,667.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>43,590,368.0</td>\n",
              "      <td>48,171,392.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>44,044,811.0</td>\n",
              "      <td>48,901,066.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>44,494,502.0</td>\n",
              "      <td>49,648,685.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 pop             \n",
              "Country    Argentina     Colombia\n",
              "year                             \n",
              "2015    43,131,966.0 47,520,667.0\n",
              "2016    43,590,368.0 48,171,392.0\n",
              "2017    44,044,811.0 48,901,066.0\n",
              "2018    44,494,502.0 49,648,685.0"
            ]
          },
          "metadata": {},
          "execution_count": 105
        }
      ]
    }
  ]
}