Benford_Distribution_Por_Cidade.ipynb

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      "source": [
        "# Analise dos votos das eleições de 2022 na perspectiva da lei de Benford."
      ],
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        "id": "1u-hOYs70jTL"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "https://en.wikipedia.org/wiki/Benford%27s_law\n",
        "\n",
        "---\n",
        "\n"
      ],
      "metadata": {
        "id": "LFLVU1un1UsM"
      }
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    {
      "cell_type": "markdown",
      "source": [
        "**Importate**:\n",
        "A lei de Benford não serve para comprovar irregularidades em eleições, mas ela serve como uma interessante ferramenta para que se procure por anomalias.\n",
        "Sua teoria é complexa, o simples fato de um conjunto de números desviar na distribuição esperada não significa fraude. Usá-la para apontar fraudes sem entender a teoria corretamente é irresponsável.\n",
        "Essa análise faz parte de uma série de análises feitas por mim, em nenhuma delas eu encontrei nada suspeito no processo eleitoral presidencial de 2022.\n",
        "O tamanho das cidades é enviesado e foge da lei de Benford pelo fato de que muitas regiões se emancipam por ter mais de 2 mil habitantes."
      ],
      "metadata": {
        "id": "0DFNeNbN2VJi"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import plotly.express as px\n",
        "from google.colab import drive\n",
        "from pathlib import Path\n",
        "import os\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import math\n",
        "import gspread as gs\n"
      ],
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        "id": "p53gijYDa8pa"
      },
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      "outputs": []
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        "pd.options.display.max_columns = None\n"
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      "outputs": []
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        "drive.mount('/content/drive')\n"
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          "text": [
            "Mounted at /content/drive\n"
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          "data": {
            "text/plain": [
              "        DT_GERACAO HH_GERACAO  ANO_ELEICAO  CD_TIPO_ELEICAO  \\\n",
              "0       31/10/2022   15:35:43         2022                0   \n",
              "2       31/10/2022   15:35:43         2022                0   \n",
              "4       31/10/2022   15:35:43         2022                0   \n",
              "5       31/10/2022   15:35:43         2022                0   \n",
              "8       31/10/2022   15:35:43         2022                0   \n",
              "...            ...        ...          ...              ...   \n",
              "269569  31/10/2022   15:48:51         2022                0   \n",
              "269574  31/10/2022   15:48:51         2022                0   \n",
              "269576  31/10/2022   15:48:51         2022                0   \n",
              "269581  31/10/2022   15:48:51         2022                0   \n",
              "269582  31/10/2022   15:48:51         2022                0   \n",
              "\n",
              "          NM_TIPO_ELEICAO  CD_PLEITO   DT_PLEITO  NR_TURNO  CD_ELEICAO  \\\n",
              "0       Eleição Ordinária        407  30/10/2022         2         545   \n",
              "2       Eleição Ordinária        407  30/10/2022         2         545   \n",
              "4       Eleição Ordinária        407  30/10/2022         2         545   \n",
              "5       Eleição Ordinária        407  30/10/2022         2         545   \n",
              "8       Eleição Ordinária        407  30/10/2022         2         545   \n",
              "...                   ...        ...         ...       ...         ...   \n",
              "269569  Eleição Ordinária        407  30/10/2022         2         545   \n",
              "269574  Eleição Ordinária        407  30/10/2022         2         545   \n",
              "269576  Eleição Ordinária        407  30/10/2022         2         545   \n",
              "269581  Eleição Ordinária        407  30/10/2022         2         545   \n",
              "269582  Eleição Ordinária        407  30/10/2022         2         545   \n",
              "\n",
              "                        DS_ELEICAO SG_UF  CD_MUNICIPIO  \\\n",
              "0       Eleição Geral Federal 2022    AC          1392   \n",
              "2       Eleição Geral Federal 2022    AC          1392   \n",
              "4       Eleição Geral Federal 2022    AC          1392   \n",
              "5       Eleição Geral Federal 2022    AC          1392   \n",
              "8       Eleição Geral Federal 2022    AC          1392   \n",
              "...                            ...   ...           ...   \n",
              "269569  Eleição Geral Federal 2022    BA         30007   \n",
              "269574  Eleição Geral Federal 2022    BA         30007   \n",
              "269576  Eleição Geral Federal 2022    BA         30007   \n",
              "269581  Eleição Geral Federal 2022    BA         30007   \n",
              "269582  Eleição Geral Federal 2022    BA         30007   \n",
              "\n",
              "                  NM_MUNICIPIO  NR_ZONA NR_SECAO  NR_LOCAL_VOTACAO  \\\n",
              "0                   RIO BRANCO        1        3              1279   \n",
              "2                   RIO BRANCO        1        3              1279   \n",
              "4                   RIO BRANCO        1        4              1139   \n",
              "5                   RIO BRANCO        1        4              1139   \n",
              "8                   RIO BRANCO        1        5              1031   \n",
              "...                        ...      ...      ...               ...   \n",
              "269569  LUÍS EDUARDO MAGALHÃES      205      210              1171   \n",
              "269574  LUÍS EDUARDO MAGALHÃES      205      211              1309   \n",
              "269576  LUÍS EDUARDO MAGALHÃES      205      211              1309   \n",
              "269581  LUÍS EDUARDO MAGALHÃES      205      212              1279   \n",
              "269582  LUÍS EDUARDO MAGALHÃES      205      212              1279   \n",
              "\n",
              "        CD_CARGO_PERGUNTA DS_CARGO_PERGUNTA  NR_PARTIDO SG_PARTIDO  \\\n",
              "0                       1        Presidente          13         PT   \n",
              "2                       1        Presidente          22         PL   \n",
              "4                       1        Presidente          22         PL   \n",
              "5                       1        Presidente          13         PT   \n",
              "8                       1        Presidente          13         PT   \n",
              "...                   ...               ...         ...        ...   \n",
              "269569                  1        Presidente          13         PT   \n",
              "269574                  1        Presidente          22         PL   \n",
              "269576                  1        Presidente          13         PT   \n",
              "269581                  1        Presidente          22         PL   \n",
              "269582                  1        Presidente          13         PT   \n",
              "\n",
              "                       NM_PARTIDO       DT_BU_RECEBIDO  QT_APTOS  \\\n",
              "0       Partido dos Trabalhadores  30/10/2022 17:34:43       185   \n",
              "2                 Partido Liberal  30/10/2022 17:34:43       185   \n",
              "4                 Partido Liberal  30/10/2022 17:25:33       339   \n",
              "5       Partido dos Trabalhadores  30/10/2022 17:25:33       339   \n",
              "8       Partido dos Trabalhadores  30/10/2022 17:28:42       341   \n",
              "...                           ...                  ...       ...   \n",
              "269569  Partido dos Trabalhadores  30/10/2022 18:24:56       208   \n",
              "269574            Partido Liberal  30/10/2022 18:10:32       109   \n",
              "269576  Partido dos Trabalhadores  30/10/2022 18:10:32       109   \n",
              "269581            Partido Liberal  30/10/2022 18:36:54       410   \n",
              "269582  Partido dos Trabalhadores  30/10/2022 18:36:54       410   \n",
              "\n",
              "        QT_COMPARECIMENTO  QT_ABSTENCOES  CD_TIPO_URNA DS_TIPO_URNA  \\\n",
              "0                     147             38             1      APURADA   \n",
              "2                     147             38             1      APURADA   \n",
              "4                     259             80             1      APURADA   \n",
              "5                     259             80             1      APURADA   \n",
              "8                     260             81             1      APURADA   \n",
              "...                   ...            ...           ...          ...   \n",
              "269569                193             15             1      APURADA   \n",
              "269574                 87             22             1      APURADA   \n",
              "269576                 87             22             1      APURADA   \n",
              "269581                319             91             1      APURADA   \n",
              "269582                319             91             1      APURADA   \n",
              "\n",
              "        CD_TIPO_VOTAVEL DS_TIPO_VOTAVEL  NR_VOTAVEL      NM_VOTAVEL  QT_VOTOS  \\\n",
              "0                     1         Nominal          13            LULA        48   \n",
              "2                     1         Nominal          22  JAIR BOLSONARO        96   \n",
              "4                     1         Nominal          22  JAIR BOLSONARO       167   \n",
              "5                     1         Nominal          13            LULA        83   \n",
              "8                     1         Nominal          13            LULA        72   \n",
              "...                 ...             ...         ...             ...       ...   \n",
              "269569                1         Nominal          13            LULA        25   \n",
              "269574                1         Nominal          22  JAIR BOLSONARO        58   \n",
              "269576                1         Nominal          13            LULA        27   \n",
              "269581                1         Nominal          22  JAIR BOLSONARO       210   \n",
              "269582                1         Nominal          13            LULA       101   \n",
              "\n",
              "        NR_URNA_EFETIVADA CD_CARGA_1_URNA_EFETIVADA CD_CARGA_2_URNA_EFETIVADA  \\\n",
              "0                 2046404  428.953.752.256.007.171.                   487.308   \n",
              "2                 2046404  428.953.752.256.007.171.                   487.308   \n",
              "4                 2048249  984.509.427.112.588.751.                   686.216   \n",
              "5                 2048249  984.509.427.112.588.751.                   686.216   \n",
              "8                 2048064  984.509.533.412.818.797.                   804.743   \n",
              "...                   ...                       ...                       ...   \n",
              "269569            1016432  757.148.752.850.405.603.                   152.278   \n",
              "269574            1075408  231.996.595.432.396.438.                   158.553   \n",
              "269576            1075408  231.996.595.432.396.438.                   158.553   \n",
              "269581            1047660  050.178.522.914.081.317.                   701.108   \n",
              "269582            1047660  050.178.522.914.081.317.                   701.108   \n",
              "\n",
              "       CD_FLASHCARD_URNA_EFETIVADA DT_CARGA_URNA_EFETIVADA  \\\n",
              "0                         90FF9DFC     23/09/2022 08:44:00   \n",
              "2                         90FF9DFC     23/09/2022 08:44:00   \n",
              "4                         90FF9DFC     23/09/2022 09:34:00   \n",
              "5                         90FF9DFC     23/09/2022 09:34:00   \n",
              "8                         90FF9DFC     23/09/2022 09:46:00   \n",
              "...                            ...                     ...   \n",
              "269569                    D530864C     27/09/2022 16:42:00   \n",
              "269574                    96BD8C44     27/09/2022 20:26:00   \n",
              "269576                    96BD8C44     27/09/2022 20:26:00   \n",
              "269581                    96BD8C44     27/09/2022 19:34:00   \n",
              "269582                    96BD8C44     27/09/2022 19:34:00   \n",
              "\n",
              "       DS_CARGO_PERGUNTA_SECAO DS_AGREGADAS          DT_ABERTURA  \\\n",
              "0                        1 - 3       #NULO#  30/10/2022 06:01:16   \n",
              "2                        1 - 3       #NULO#  30/10/2022 06:01:16   \n",
              "4                        1 - 4       #NULO#  30/10/2022 06:00:01   \n",
              "5                        1 - 4       #NULO#  30/10/2022 06:00:01   \n",
              "8                        1 - 5       #NULO#  30/10/2022 06:00:50   \n",
              "...                        ...          ...                  ...   \n",
              "269569                 1 - 210       #NULO#  30/10/2022 08:00:01   \n",
              "269574                 1 - 211       #NULO#  30/10/2022 08:00:01   \n",
              "269576                 1 - 211       #NULO#  30/10/2022 08:00:01   \n",
              "269581                 1 - 212          148  30/10/2022 08:00:01   \n",
              "269582                 1 - 212          148  30/10/2022 08:00:01   \n",
              "\n",
              "            DT_ENCERRAMENTO  QT_ELEITORES_BIOMETRIA_NH        DT_EMISSAO_BU  \\\n",
              "0       30/10/2022 15:00:59                          9  30/10/2022 15:04:47   \n",
              "2       30/10/2022 15:00:59                          9  30/10/2022 15:04:47   \n",
              "4       30/10/2022 15:01:55                         13  30/10/2022 15:05:12   \n",
              "5       30/10/2022 15:01:55                         13  30/10/2022 15:05:12   \n",
              "8       30/10/2022 15:02:23                          8  30/10/2022 15:05:25   \n",
              "...                     ...                        ...                  ...   \n",
              "269569  30/10/2022 17:00:25                         11  30/10/2022 17:02:24   \n",
              "269574  30/10/2022 17:11:29                         11  30/10/2022 17:13:15   \n",
              "269576  30/10/2022 17:11:29                         11  30/10/2022 17:13:15   \n",
              "269581  30/10/2022 17:01:52                         46  30/10/2022 17:06:21   \n",
              "269582  30/10/2022 17:01:52                         46  30/10/2022 17:06:21   \n",
              "\n",
              "        NR_JUNTA_APURADORA  NR_TURMA_APURADORA  \n",
              "0                       -1                  -1  \n",
              "2                       -1                  -1  \n",
              "4                       -1                  -1  \n",
              "5                       -1                  -1  \n",
              "8                       -1                  -1  \n",
              "...                    ...                 ...  \n",
              "269569                  -1                  -1  \n",
              "269574                  -1                  -1  \n",
              "269576                  -1                  -1  \n",
              "269581                  -1                  -1  \n",
              "269582                  -1                  -1  \n",
              "\n",
              "[943907 rows x 45 columns]"
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>DT_GERACAO</th>\n",
              "      <th>HH_GERACAO</th>\n",
              "      <th>ANO_ELEICAO</th>\n",
              "      <th>CD_TIPO_ELEICAO</th>\n",
              "      <th>NM_TIPO_ELEICAO</th>\n",
              "      <th>CD_PLEITO</th>\n",
              "      <th>DT_PLEITO</th>\n",
              "      <th>NR_TURNO</th>\n",
              "      <th>CD_ELEICAO</th>\n",
              "      <th>DS_ELEICAO</th>\n",
              "      <th>SG_UF</th>\n",
              "      <th>CD_MUNICIPIO</th>\n",
              "      <th>NM_MUNICIPIO</th>\n",
              "      <th>NR_ZONA</th>\n",
              "      <th>NR_SECAO</th>\n",
              "      <th>NR_LOCAL_VOTACAO</th>\n",
              "      <th>CD_CARGO_PERGUNTA</th>\n",
              "      <th>DS_CARGO_PERGUNTA</th>\n",
              "      <th>NR_PARTIDO</th>\n",
              "      <th>SG_PARTIDO</th>\n",
              "      <th>NM_PARTIDO</th>\n",
              "      <th>DT_BU_RECEBIDO</th>\n",
              "      <th>QT_APTOS</th>\n",
              "      <th>QT_COMPARECIMENTO</th>\n",
              "      <th>QT_ABSTENCOES</th>\n",
              "      <th>CD_TIPO_URNA</th>\n",
              "      <th>DS_TIPO_URNA</th>\n",
              "      <th>CD_TIPO_VOTAVEL</th>\n",
              "      <th>DS_TIPO_VOTAVEL</th>\n",
              "      <th>NR_VOTAVEL</th>\n",
              "      <th>NM_VOTAVEL</th>\n",
              "      <th>QT_VOTOS</th>\n",
              "      <th>NR_URNA_EFETIVADA</th>\n",
              "      <th>CD_CARGA_1_URNA_EFETIVADA</th>\n",
              "      <th>CD_CARGA_2_URNA_EFETIVADA</th>\n",
              "      <th>CD_FLASHCARD_URNA_EFETIVADA</th>\n",
              "      <th>DT_CARGA_URNA_EFETIVADA</th>\n",
              "      <th>DS_CARGO_PERGUNTA_SECAO</th>\n",
              "      <th>DS_AGREGADAS</th>\n",
              "      <th>DT_ABERTURA</th>\n",
              "      <th>DT_ENCERRAMENTO</th>\n",
              "      <th>QT_ELEITORES_BIOMETRIA_NH</th>\n",
              "      <th>DT_EMISSAO_BU</th>\n",
              "      <th>NR_JUNTA_APURADORA</th>\n",
              "      <th>NR_TURMA_APURADORA</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>31/10/2022</td>\n",
              "      <td>15:35:43</td>\n",
              "      <td>2022</td>\n",
              "      <td>0</td>\n",
              "      <td>Eleição Ordinária</td>\n",
              "      <td>407</td>\n",
              "      <td>30/10/2022</td>\n",
              "      <td>2</td>\n",
              "      <td>545</td>\n",
              "      <td>Eleição Geral Federal 2022</td>\n",
              "      <td>AC</td>\n",
              "      <td>1392</td>\n",
              "      <td>RIO BRANCO</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1279</td>\n",
              "      <td>1</td>\n",
              "      <td>Presidente</td>\n",
              "      <td>13</td>\n",
              "      <td>PT</td>\n",
              "      <td>Partido dos Trabalhadores</td>\n",
              "      <td>30/10/2022 17:34:43</td>\n",
              "      <td>185</td>\n",
              "      <td>147</td>\n",
              "      <td>38</td>\n",
              "      <td>1</td>\n",
              "      <td>APURADA</td>\n",
              "      <td>1</td>\n",
              "      <td>Nominal</td>\n",
              "      <td>13</td>\n",
              "      <td>LULA</td>\n",
              "      <td>48</td>\n",
              "      <td>2046404</td>\n",
              "      <td>428.953.752.256.007.171.</td>\n",
              "      <td>487.308</td>\n",
              "      <td>90FF9DFC</td>\n",
              "      <td>23/09/2022 08:44:00</td>\n",
              "      <td>1 - 3</td>\n",
              "      <td>#NULO#</td>\n",
              "      <td>30/10/2022 06:01:16</td>\n",
              "      <td>30/10/2022 15:00:59</td>\n",
              "      <td>9</td>\n",
              "      <td>30/10/2022 15:04:47</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>31/10/2022</td>\n",
              "      <td>15:35:43</td>\n",
              "      <td>2022</td>\n",
              "      <td>0</td>\n",
              "      <td>Eleição Ordinária</td>\n",
              "      <td>407</td>\n",
              "      <td>30/10/2022</td>\n",
              "      <td>2</td>\n",
              "      <td>545</td>\n",
              "      <td>Eleição Geral Federal 2022</td>\n",
              "      <td>AC</td>\n",
              "      <td>1392</td>\n",
              "      <td>RIO BRANCO</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1279</td>\n",
              "      <td>1</td>\n",
              "      <td>Presidente</td>\n",
              "      <td>22</td>\n",
              "      <td>PL</td>\n",
              "      <td>Partido Liberal</td>\n",
              "      <td>30/10/2022 17:34:43</td>\n",
              "      <td>185</td>\n",
              "      <td>147</td>\n",
              "      <td>38</td>\n",
              "      <td>1</td>\n",
              "      <td>APURADA</td>\n",
              "      <td>1</td>\n",
              "      <td>Nominal</td>\n",
              "      <td>22</td>\n",
              "      <td>JAIR BOLSONARO</td>\n",
              "      <td>96</td>\n",
              "      <td>2046404</td>\n",
              "      <td>428.953.752.256.007.171.</td>\n",
              "      <td>487.308</td>\n",
              "      <td>90FF9DFC</td>\n",
              "      <td>23/09/2022 08:44:00</td>\n",
              "      <td>1 - 3</td>\n",
              "      <td>#NULO#</td>\n",
              "      <td>30/10/2022 06:01:16</td>\n",
              "      <td>30/10/2022 15:00:59</td>\n",
              "      <td>9</td>\n",
              "      <td>30/10/2022 15:04:47</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>31/10/2022</td>\n",
              "      <td>15:35:43</td>\n",
              "      <td>2022</td>\n",
              "      <td>0</td>\n",
              "      <td>Eleição Ordinária</td>\n",
              "      <td>407</td>\n",
              "      <td>30/10/2022</td>\n",
              "      <td>2</td>\n",
              "      <td>545</td>\n",
              "      <td>Eleição Geral Federal 2022</td>\n",
              "      <td>AC</td>\n",
              "      <td>1392</td>\n",
              "      <td>RIO BRANCO</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1139</td>\n",
              "      <td>1</td>\n",
              "      <td>Presidente</td>\n",
              "      <td>22</td>\n",
              "      <td>PL</td>\n",
              "      <td>Partido Liberal</td>\n",
              "      <td>30/10/2022 17:25:33</td>\n",
              "      <td>339</td>\n",
              "      <td>259</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>APURADA</td>\n",
              "      <td>1</td>\n",
              "      <td>Nominal</td>\n",
              "      <td>22</td>\n",
              "      <td>JAIR BOLSONARO</td>\n",
              "      <td>167</td>\n",
              "      <td>2048249</td>\n",
              "      <td>984.509.427.112.588.751.</td>\n",
              "      <td>686.216</td>\n",
              "      <td>90FF9DFC</td>\n",
              "      <td>23/09/2022 09:34:00</td>\n",
              "      <td>1 - 4</td>\n",
              "      <td>#NULO#</td>\n",
              "      <td>30/10/2022 06:00:01</td>\n",
              "      <td>30/10/2022 15:01:55</td>\n",
              "      <td>13</td>\n",
              "      <td>30/10/2022 15:05:12</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>31/10/2022</td>\n",
              "      <td>15:35:43</td>\n",
              "      <td>2022</td>\n",
              "      <td>0</td>\n",
              "      <td>Eleição Ordinária</td>\n",
              "      <td>407</td>\n",
              "      <td>30/10/2022</td>\n",
              "      <td>2</td>\n",
              "      <td>545</td>\n",
              "      <td>Eleição Geral Federal 2022</td>\n",
              "      <td>AC</td>\n",
              "      <td>1392</td>\n",
              "      <td>RIO BRANCO</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1139</td>\n",
              "      <td>1</td>\n",
              "      <td>Presidente</td>\n",
              "      <td>13</td>\n",
              "      <td>PT</td>\n",
              "      <td>Partido dos Trabalhadores</td>\n",
              "      <td>30/10/2022 17:25:33</td>\n",
              "      <td>339</td>\n",
              "      <td>259</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>APURADA</td>\n",
              "      <td>1</td>\n",
              "      <td>Nominal</td>\n",
              "      <td>13</td>\n",
              "      <td>LULA</td>\n",
              "      <td>83</td>\n",
              "      <td>2048249</td>\n",
              "      <td>984.509.427.112.588.751.</td>\n",
              "      <td>686.216</td>\n",
              "      <td>90FF9DFC</td>\n",
              "      <td>23/09/2022 09:34:00</td>\n",
              "      <td>1 - 4</td>\n",
              "      <td>#NULO#</td>\n",
              "      <td>30/10/2022 06:00:01</td>\n",
              "      <td>30/10/2022 15:01:55</td>\n",
              "      <td>13</td>\n",
              "      <td>30/10/2022 15:05:12</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>31/10/2022</td>\n",
              "      <td>15:35:43</td>\n",
              "      <td>2022</td>\n",
              "      <td>0</td>\n",
              "      <td>Eleição Ordinária</td>\n",
              "      <td>407</td>\n",
              "      <td>30/10/2022</td>\n",
              "      <td>2</td>\n",
              "      <td>545</td>\n",
              "      <td>Eleição Geral Federal 2022</td>\n",
              "      <td>AC</td>\n",
              "      <td>1392</td>\n",
              "      <td>RIO BRANCO</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>1031</td>\n",
              "      <td>1</td>\n",
              "      <td>Presidente</td>\n",
              "      <td>13</td>\n",
              "      <td>PT</td>\n",
              "      <td>Partido dos Trabalhadores</td>\n",
              "      <td>30/10/2022 17:28:42</td>\n",
              "      <td>341</td>\n",
              "      <td>260</td>\n",
              "      <td>81</td>\n",
              "      <td>1</td>\n",
              "      <td>APURADA</td>\n",
              "      <td>1</td>\n",
              "      <td>Nominal</td>\n",
              "      <td>13</td>\n",
              "      <td>LULA</td>\n",
              "      <td>72</td>\n",
              "      <td>2048064</td>\n",
              "      <td>984.509.533.412.818.797.</td>\n",
              "      <td>804.743</td>\n",
              "      <td>90FF9DFC</td>\n",
              "      <td>23/09/2022 09:46:00</td>\n",
              "      <td>1 - 5</td>\n",
              "      <td>#NULO#</td>\n",
              "      <td>30/10/2022 06:00:50</td>\n",
              "      <td>30/10/2022 15:02:23</td>\n",
              "      <td>8</td>\n",
              "      <td>30/10/2022 15:05:25</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <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",
              "      <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",
              "      <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",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>269569</th>\n",
              "      <td>31/10/2022</td>\n",
              "      <td>15:48:51</td>\n",
              "      <td>2022</td>\n",
              "      <td>0</td>\n",
              "      <td>Eleição Ordinária</td>\n",
              "      <td>407</td>\n",
              "      <td>30/10/2022</td>\n",
              "      <td>2</td>\n",
              "      <td>545</td>\n",
              "      <td>Eleição Geral Federal 2022</td>\n",
              "      <td>BA</td>\n",
              "      <td>30007</td>\n",
              "      <td>LUÍS EDUARDO MAGALHÃES</td>\n",
              "      <td>205</td>\n",
              "      <td>210</td>\n",
              "      <td>1171</td>\n",
              "      <td>1</td>\n",
              "      <td>Presidente</td>\n",
              "      <td>13</td>\n",
              "      <td>PT</td>\n",
              "      <td>Partido dos Trabalhadores</td>\n",
              "      <td>30/10/2022 18:24:56</td>\n",
              "      <td>208</td>\n",
              "      <td>193</td>\n",
              "      <td>15</td>\n",
              "      <td>1</td>\n",
              "      <td>APURADA</td>\n",
              "      <td>1</td>\n",
              "      <td>Nominal</td>\n",
              "      <td>13</td>\n",
              "      <td>LULA</td>\n",
              "      <td>25</td>\n",
              "      <td>1016432</td>\n",
              "      <td>757.148.752.850.405.603.</td>\n",
              "      <td>152.278</td>\n",
              "      <td>D530864C</td>\n",
              "      <td>27/09/2022 16:42:00</td>\n",
              "      <td>1 - 210</td>\n",
              "      <td>#NULO#</td>\n",
              "      <td>30/10/2022 08:00:01</td>\n",
              "      <td>30/10/2022 17:00:25</td>\n",
              "      <td>11</td>\n",
              "      <td>30/10/2022 17:02:24</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>269574</th>\n",
              "      <td>31/10/2022</td>\n",
              "      <td>15:48:51</td>\n",
              "      <td>2022</td>\n",
              "      <td>0</td>\n",
              "      <td>Eleição Ordinária</td>\n",
              "      <td>407</td>\n",
              "      <td>30/10/2022</td>\n",
              "      <td>2</td>\n",
              "      <td>545</td>\n",
              "      <td>Eleição Geral Federal 2022</td>\n",
              "      <td>BA</td>\n",
              "      <td>30007</td>\n",
              "      <td>LUÍS EDUARDO MAGALHÃES</td>\n",
              "      <td>205</td>\n",
              "      <td>211</td>\n",
              "      <td>1309</td>\n",
              "      <td>1</td>\n",
              "      <td>Presidente</td>\n",
              "      <td>22</td>\n",
              "      <td>PL</td>\n",
              "      <td>Partido Liberal</td>\n",
              "      <td>30/10/2022 18:10:32</td>\n",
              "      <td>109</td>\n",
              "      <td>87</td>\n",
              "      <td>22</td>\n",
              "      <td>1</td>\n",
              "      <td>APURADA</td>\n",
              "      <td>1</td>\n",
              "      <td>Nominal</td>\n",
              "      <td>22</td>\n",
              "      <td>JAIR BOLSONARO</td>\n",
              "      <td>58</td>\n",
              "      <td>1075408</td>\n",
              "      <td>231.996.595.432.396.438.</td>\n",
              "      <td>158.553</td>\n",
              "      <td>96BD8C44</td>\n",
              "      <td>27/09/2022 20:26:00</td>\n",
              "      <td>1 - 211</td>\n",
              "      <td>#NULO#</td>\n",
              "      <td>30/10/2022 08:00:01</td>\n",
              "      <td>30/10/2022 17:11:29</td>\n",
              "      <td>11</td>\n",
              "      <td>30/10/2022 17:13:15</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>269576</th>\n",
              "      <td>31/10/2022</td>\n",
              "      <td>15:48:51</td>\n",
              "      <td>2022</td>\n",
              "      <td>0</td>\n",
              "      <td>Eleição Ordinária</td>\n",
              "      <td>407</td>\n",
              "      <td>30/10/2022</td>\n",
              "      <td>2</td>\n",
              "      <td>545</td>\n",
              "      <td>Eleição Geral Federal 2022</td>\n",
              "      <td>BA</td>\n",
              "      <td>30007</td>\n",
              "      <td>LUÍS EDUARDO MAGALHÃES</td>\n",
              "      <td>205</td>\n",
              "      <td>211</td>\n",
              "      <td>1309</td>\n",
              "      <td>1</td>\n",
              "      <td>Presidente</td>\n",
              "      <td>13</td>\n",
              "      <td>PT</td>\n",
              "      <td>Partido dos Trabalhadores</td>\n",
              "      <td>30/10/2022 18:10:32</td>\n",
              "      <td>109</td>\n",
              "      <td>87</td>\n",
              "      <td>22</td>\n",
              "      <td>1</td>\n",
              "      <td>APURADA</td>\n",
              "      <td>1</td>\n",
              "      <td>Nominal</td>\n",
              "      <td>13</td>\n",
              "      <td>LULA</td>\n",
              "      <td>27</td>\n",
              "      <td>1075408</td>\n",
              "      <td>231.996.595.432.396.438.</td>\n",
              "      <td>158.553</td>\n",
              "      <td>96BD8C44</td>\n",
              "      <td>27/09/2022 20:26:00</td>\n",
              "      <td>1 - 211</td>\n",
              "      <td>#NULO#</td>\n",
              "      <td>30/10/2022 08:00:01</td>\n",
              "      <td>30/10/2022 17:11:29</td>\n",
              "      <td>11</td>\n",
              "      <td>30/10/2022 17:13:15</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>269581</th>\n",
              "      <td>31/10/2022</td>\n",
              "      <td>15:48:51</td>\n",
              "      <td>2022</td>\n",
              "      <td>0</td>\n",
              "      <td>Eleição Ordinária</td>\n",
              "      <td>407</td>\n",
              "      <td>30/10/2022</td>\n",
              "      <td>2</td>\n",
              "      <td>545</td>\n",
              "      <td>Eleição Geral Federal 2022</td>\n",
              "      <td>BA</td>\n",
              "      <td>30007</td>\n",
              "      <td>LUÍS EDUARDO MAGALHÃES</td>\n",
              "      <td>205</td>\n",
              "      <td>212</td>\n",
              "      <td>1279</td>\n",
              "      <td>1</td>\n",
              "      <td>Presidente</td>\n",
              "      <td>22</td>\n",
              "      <td>PL</td>\n",
              "      <td>Partido Liberal</td>\n",
              "      <td>30/10/2022 18:36:54</td>\n",
              "      <td>410</td>\n",
              "      <td>319</td>\n",
              "      <td>91</td>\n",
              "      <td>1</td>\n",
              "      <td>APURADA</td>\n",
              "      <td>1</td>\n",
              "      <td>Nominal</td>\n",
              "      <td>22</td>\n",
              "      <td>JAIR BOLSONARO</td>\n",
              "      <td>210</td>\n",
              "      <td>1047660</td>\n",
              "      <td>050.178.522.914.081.317.</td>\n",
              "      <td>701.108</td>\n",
              "      <td>96BD8C44</td>\n",
              "      <td>27/09/2022 19:34:00</td>\n",
              "      <td>1 - 212</td>\n",
              "      <td>148</td>\n",
              "      <td>30/10/2022 08:00:01</td>\n",
              "      <td>30/10/2022 17:01:52</td>\n",
              "      <td>46</td>\n",
              "      <td>30/10/2022 17:06:21</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>269582</th>\n",
              "      <td>31/10/2022</td>\n",
              "      <td>15:48:51</td>\n",
              "      <td>2022</td>\n",
              "      <td>0</td>\n",
              "      <td>Eleição Ordinária</td>\n",
              "      <td>407</td>\n",
              "      <td>30/10/2022</td>\n",
              "      <td>2</td>\n",
              "      <td>545</td>\n",
              "      <td>Eleição Geral Federal 2022</td>\n",
              "      <td>BA</td>\n",
              "      <td>30007</td>\n",
              "      <td>LUÍS EDUARDO MAGALHÃES</td>\n",
              "      <td>205</td>\n",
              "      <td>212</td>\n",
              "      <td>1279</td>\n",
              "      <td>1</td>\n",
              "      <td>Presidente</td>\n",
              "      <td>13</td>\n",
              "      <td>PT</td>\n",
              "      <td>Partido dos Trabalhadores</td>\n",
              "      <td>30/10/2022 18:36:54</td>\n",
              "      <td>410</td>\n",
              "      <td>319</td>\n",
              "      <td>91</td>\n",
              "      <td>1</td>\n",
              "      <td>APURADA</td>\n",
              "      <td>1</td>\n",
              "      <td>Nominal</td>\n",
              "      <td>13</td>\n",
              "      <td>LULA</td>\n",
              "      <td>101</td>\n",
              "      <td>1047660</td>\n",
              "      <td>050.178.522.914.081.317.</td>\n",
              "      <td>701.108</td>\n",
              "      <td>96BD8C44</td>\n",
              "      <td>27/09/2022 19:34:00</td>\n",
              "      <td>1 - 212</td>\n",
              "      <td>148</td>\n",
              "      <td>30/10/2022 08:00:01</td>\n",
              "      <td>30/10/2022 17:01:52</td>\n",
              "      <td>46</td>\n",
              "      <td>30/10/2022 17:06:21</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>943907 rows × 45 columns</p>\n",
              "</div>\n",
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              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-cec52929-c401-4a6b-9f67-587201aad36f button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-cec52929-c401-4a6b-9f67-587201aad36f');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-272cc349-1b36-4916-ab59-6454ab01b638\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-272cc349-1b36-4916-ab59-6454ab01b638')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-272cc349-1b36-4916-ab59-6454ab01b638 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ],
      "source": [
        "all = pd.DataFrame()\n",
        "\n",
        "states = ['AC', 'AL', 'AM', 'AP', 'DF', 'ES', 'MA', 'MS', 'MG', 'MT', 'PA', 'PB', 'PE', 'PI', 'PR', 'RJ', 'RN', 'RO', 'RR', 'SC', 'SE', 'ZZ', 'TO', 'SP', 'RS', 'CE', 'GO', 'BA']\n",
        "# states = ['MS']\n",
        "\n",
        "for state in states:\n",
        "  st = pd.read_csv('/content/drive/MyDrive/data/eleicoes2022unziped/bweb_2t_'+state+'_311020221535.csv', encoding=\"ISO-8859-1\", sep = ';',\n",
        "                   dtype={\n",
        "                            \"SG_UF\": pd.CategoricalDtype(),\n",
        "                            \"CD_MUNICIPIO\": pd.Int64Dtype(),\n",
        "                            \"NR_LOCAL_VOTACAO\": pd.Int64Dtype(),\n",
        "                            \"NR_ZONA\": pd.Int64Dtype(),\n",
        "                            \"NR_SECAO\": pd.CategoricalDtype()\n",
        "                        })\n",
        "\n",
        "  st_presidente = st[st.CD_CARGO_PERGUNTA == 1]\n",
        "  filtered_df = st_presidente.loc[(st_presidente['NR_PARTIDO'] == 13) | (st_presidente['NR_PARTIDO'] == 22)]\n",
        "\n",
        "  toUnion = [all, filtered_df]\n",
        "\n",
        "  all = pd.concat(toUnion)\n",
        "\n",
        "all\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2 = all[['NR_LOCAL_VOTACAO',\n",
        "                   'CD_MUNICIPIO',\n",
        "                   'NR_ZONA',\n",
        "                   'NR_SECAO',\n",
        "                   'QT_VOTOS',\n",
        "                   'QT_APTOS',\n",
        "                   'QT_COMPARECIMENTO',\n",
        "                   'CD_CARGO_PERGUNTA',\n",
        "                   'NR_PARTIDO',\n",
        "                   'NM_MUNICIPIO',\n",
        "                   'SG_UF']]"
      ],
      "metadata": {
        "id": "UBYL43ONbWY4"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_lula = df2.loc[(df2['NR_PARTIDO'] == 13)]\n",
        "df_lula_agg = df_lula.groupby([\"CD_MUNICIPIO\", \"NR_PARTIDO\", \"SG_UF\"]).agg({\"QT_VOTOS\": sum, \"QT_APTOS\": sum, \"QT_COMPARECIMENTO\": sum, \"NM_MUNICIPIO\": max})\n",
        "\n",
        "df_lula_agg"
      ],
      "metadata": {
        "id": "J74xNKxyc-u_",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "outputId": "8bdd6167-b769-4dcc-fd9a-71fe1509cdd5"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                               QT_VOTOS  QT_APTOS  QT_COMPARECIMENTO  \\\n",
              "CD_MUNICIPIO NR_PARTIDO SG_UF                                          \n",
              "19           13         RO         6838     28173              20379   \n",
              "35           13         RO        92636    350722             271850   \n",
              "51           13         RO        16711     92356              70203   \n",
              "78           13         RO        10513     69784              51839   \n",
              "94           13         RO        12437     66503              51987   \n",
              "...                                 ...       ...                ...   \n",
              "99180        13         ZZ            9        65                 25   \n",
              "99287        13         ZZ           13        34                 14   \n",
              "99317        13         ZZ          156       250                191   \n",
              "99430        13         ZZ           11       107                 21   \n",
              "99473        13         ZZ           11        50                 40   \n",
              "\n",
              "                                   NM_MUNICIPIO  \n",
              "CD_MUNICIPIO NR_PARTIDO SG_UF                    \n",
              "19           13         RO        GUAJARÁ-MIRIM  \n",
              "35           13         RO          PORTO VELHO  \n",
              "51           13         RO            JI-PARANÁ  \n",
              "78           13         RO            ARIQUEMES  \n",
              "94           13         RO               CACOAL  \n",
              "...                                         ...  \n",
              "99180        13         ZZ               NASSAU  \n",
              "99287        13         ZZ               LUSACA  \n",
              "99317        13         ZZ                TALIN  \n",
              "99430        13         ZZ     KINGSTON-JAMAICA  \n",
              "99473        13         ZZ               BAREIN  \n",
              "\n",
              "[5708 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
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              "    <div>\n",
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              "    .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></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>QT_VOTOS</th>\n",
              "      <th>QT_APTOS</th>\n",
              "      <th>QT_COMPARECIMENTO</th>\n",
              "      <th>NM_MUNICIPIO</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CD_MUNICIPIO</th>\n",
              "      <th>NR_PARTIDO</th>\n",
              "      <th>SG_UF</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <th>13</th>\n",
              "      <th>RO</th>\n",
              "      <td>6838</td>\n",
              "      <td>28173</td>\n",
              "      <td>20379</td>\n",
              "      <td>GUAJARÁ-MIRIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <th>13</th>\n",
              "      <th>RO</th>\n",
              "      <td>92636</td>\n",
              "      <td>350722</td>\n",
              "      <td>271850</td>\n",
              "      <td>PORTO VELHO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <th>13</th>\n",
              "      <th>RO</th>\n",
              "      <td>16711</td>\n",
              "      <td>92356</td>\n",
              "      <td>70203</td>\n",
              "      <td>JI-PARANÁ</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>78</th>\n",
              "      <th>13</th>\n",
              "      <th>RO</th>\n",
              "      <td>10513</td>\n",
              "      <td>69784</td>\n",
              "      <td>51839</td>\n",
              "      <td>ARIQUEMES</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>94</th>\n",
              "      <th>13</th>\n",
              "      <th>RO</th>\n",
              "      <td>12437</td>\n",
              "      <td>66503</td>\n",
              "      <td>51987</td>\n",
              "      <td>CACOAL</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99180</th>\n",
              "      <th>13</th>\n",
              "      <th>ZZ</th>\n",
              "      <td>9</td>\n",
              "      <td>65</td>\n",
              "      <td>25</td>\n",
              "      <td>NASSAU</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99287</th>\n",
              "      <th>13</th>\n",
              "      <th>ZZ</th>\n",
              "      <td>13</td>\n",
              "      <td>34</td>\n",
              "      <td>14</td>\n",
              "      <td>LUSACA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99317</th>\n",
              "      <th>13</th>\n",
              "      <th>ZZ</th>\n",
              "      <td>156</td>\n",
              "      <td>250</td>\n",
              "      <td>191</td>\n",
              "      <td>TALIN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99430</th>\n",
              "      <th>13</th>\n",
              "      <th>ZZ</th>\n",
              "      <td>11</td>\n",
              "      <td>107</td>\n",
              "      <td>21</td>\n",
              "      <td>KINGSTON-JAMAICA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99473</th>\n",
              "      <th>13</th>\n",
              "      <th>ZZ</th>\n",
              "      <td>11</td>\n",
              "      <td>50</td>\n",
              "      <td>40</td>\n",
              "      <td>BAREIN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5708 rows × 4 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-52777156-eadb-4a27-bd63-a84410938b8f')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-52777156-eadb-4a27-bd63-a84410938b8f button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-52777156-eadb-4a27-bd63-a84410938b8f');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
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              "\n",
              "\n",
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              "            title=\"Suggest charts.\"\n",
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              "\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
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              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
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              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-390dc274-de03-4a65-bc9a-43267f5b518e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_bolsonaro = df2.loc[(df2['NR_PARTIDO'] == 22)]\n",
        "df_bolsonaro_agg = df_bolsonaro.groupby([\"CD_MUNICIPIO\", \"NR_PARTIDO\", \"SG_UF\"]).agg({\"QT_VOTOS\": sum, \"QT_APTOS\": sum, \"QT_COMPARECIMENTO\": sum, \"NM_MUNICIPIO\": max})\n",
        "df_bolsonaro_agg\n"
      ],
      "metadata": {
        "id": "uIHyB5gUc_5l",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "outputId": "873c0577-5624-4f33-daed-196cf71e9aa2"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                               QT_VOTOS  QT_APTOS  QT_COMPARECIMENTO  \\\n",
              "CD_MUNICIPIO NR_PARTIDO SG_UF                                          \n",
              "19           22         RO        13001     28173              20379   \n",
              "35           22         RO       169299    350722             271850   \n",
              "51           22         RO        51415     92356              70203   \n",
              "78           22         RO        39901     69784              51839   \n",
              "94           22         RO        37980     66503              51987   \n",
              "...                                 ...       ...                ...   \n",
              "99180        22         ZZ           14        65                 25   \n",
              "99287        22         ZZ            1        34                 14   \n",
              "99317        22         ZZ           23       250                191   \n",
              "99430        22         ZZ           10       107                 21   \n",
              "99473        22         ZZ           25        50                 40   \n",
              "\n",
              "                                   NM_MUNICIPIO  \n",
              "CD_MUNICIPIO NR_PARTIDO SG_UF                    \n",
              "19           22         RO        GUAJARÁ-MIRIM  \n",
              "35           22         RO          PORTO VELHO  \n",
              "51           22         RO            JI-PARANÁ  \n",
              "78           22         RO            ARIQUEMES  \n",
              "94           22         RO               CACOAL  \n",
              "...                                         ...  \n",
              "99180        22         ZZ               NASSAU  \n",
              "99287        22         ZZ               LUSACA  \n",
              "99317        22         ZZ                TALIN  \n",
              "99430        22         ZZ     KINGSTON-JAMAICA  \n",
              "99473        22         ZZ               BAREIN  \n",
              "\n",
              "[5707 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
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              "    <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",
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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></th>\n",
              "      <th>QT_VOTOS</th>\n",
              "      <th>QT_APTOS</th>\n",
              "      <th>QT_COMPARECIMENTO</th>\n",
              "      <th>NM_MUNICIPIO</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CD_MUNICIPIO</th>\n",
              "      <th>NR_PARTIDO</th>\n",
              "      <th>SG_UF</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <th>22</th>\n",
              "      <th>RO</th>\n",
              "      <td>13001</td>\n",
              "      <td>28173</td>\n",
              "      <td>20379</td>\n",
              "      <td>GUAJARÁ-MIRIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <th>22</th>\n",
              "      <th>RO</th>\n",
              "      <td>169299</td>\n",
              "      <td>350722</td>\n",
              "      <td>271850</td>\n",
              "      <td>PORTO VELHO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <th>22</th>\n",
              "      <th>RO</th>\n",
              "      <td>51415</td>\n",
              "      <td>92356</td>\n",
              "      <td>70203</td>\n",
              "      <td>JI-PARANÁ</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>78</th>\n",
              "      <th>22</th>\n",
              "      <th>RO</th>\n",
              "      <td>39901</td>\n",
              "      <td>69784</td>\n",
              "      <td>51839</td>\n",
              "      <td>ARIQUEMES</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>94</th>\n",
              "      <th>22</th>\n",
              "      <th>RO</th>\n",
              "      <td>37980</td>\n",
              "      <td>66503</td>\n",
              "      <td>51987</td>\n",
              "      <td>CACOAL</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99180</th>\n",
              "      <th>22</th>\n",
              "      <th>ZZ</th>\n",
              "      <td>14</td>\n",
              "      <td>65</td>\n",
              "      <td>25</td>\n",
              "      <td>NASSAU</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99287</th>\n",
              "      <th>22</th>\n",
              "      <th>ZZ</th>\n",
              "      <td>1</td>\n",
              "      <td>34</td>\n",
              "      <td>14</td>\n",
              "      <td>LUSACA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99317</th>\n",
              "      <th>22</th>\n",
              "      <th>ZZ</th>\n",
              "      <td>23</td>\n",
              "      <td>250</td>\n",
              "      <td>191</td>\n",
              "      <td>TALIN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99430</th>\n",
              "      <th>22</th>\n",
              "      <th>ZZ</th>\n",
              "      <td>10</td>\n",
              "      <td>107</td>\n",
              "      <td>21</td>\n",
              "      <td>KINGSTON-JAMAICA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99473</th>\n",
              "      <th>22</th>\n",
              "      <th>ZZ</th>\n",
              "      <td>25</td>\n",
              "      <td>50</td>\n",
              "      <td>40</td>\n",
              "      <td>BAREIN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5707 rows × 4 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5cfe7442-6458-48f1-8def-6692f60a7a7f')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-5cfe7442-6458-48f1-8def-6692f60a7a7f button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-5cfe7442-6458-48f1-8def-6692f60a7a7f');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-1a6ea811-d34f-4b12-b5f4-a757ed9c6abb\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-1a6ea811-d34f-4b12-b5f4-a757ed9c6abb')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-1a6ea811-d34f-4b12-b5f4-a757ed9c6abb button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_lula_local = {}\n",
        "for x in range(1, 10):\n",
        "  df_lula_local[x] = df_lula_agg.loc[df_lula_agg['QT_VOTOS'].astype(str).str.startswith(str(x), na=False)]\n",
        "\n",
        "df_lula_local[2]"
      ],
      "metadata": {
        "id": "4HZfBWaifypq"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_bolsonaro_local = {}\n",
        "for x in range(1, 10):\n",
        "  df_bolsonaro_local[x] = df_bolsonaro_agg.loc[df_bolsonaro_agg['QT_VOTOS'].astype(str).str.startswith(str(x), na=False)]\n",
        "\n",
        "df_bolsonaro_local[2]"
      ],
      "metadata": {
        "id": "YlI_1kTCv9gP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "total_lula = 0\n",
        "for k in df_lula_local:\n",
        "  total_lula = total_lula + df_lula_local[k].size\n",
        "total_lula"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VVGlvx69g317",
        "outputId": "564d5b38-abf5-4cb4-f8a0-f146d3272569"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "22832"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "total_bolsonaro = 0\n",
        "for k in df_bolsonaro_local:\n",
        "  total_bolsonaro = total_bolsonaro + df_bolsonaro_local[k].size\n",
        "total_bolsonaro"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_QEF6zdVyY9Q",
        "outputId": "f92bbdc9-32af-4955-fb79-8847d9827398"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "22828"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dic_lula_percentual = {}\n",
        "\n",
        "for x in range(1, 10):\n",
        "  dic_lula_percentual[x] = df_lula_local[x].size  * 100 / total_lula\n",
        "dic_lula_percentual\n",
        "\n",
        "# cem = 0\n",
        "# for k in dic_lula_percentual:\n",
        "#   cem = cem + dic_lula_percentual[k]\n",
        "# cem # (tem de dar 100% a soma)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4u-Q1vURhWpX",
        "outputId": "0669e482-264b-456a-ce70-673601c73b39"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{1: 30.448493342676944,\n",
              " 2: 18.710581639803785,\n",
              " 3: 12.351086194814295,\n",
              " 4: 8.864751226348984,\n",
              " 5: 7.375613174491941,\n",
              " 6: 6.762438682550806,\n",
              " 7: 5.676243868255081,\n",
              " 8: 5.168185003503854,\n",
              " 9: 4.64260686755431}"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dic_bolsonaro_percentual = {}\n",
        "\n",
        "for x in range(1, 10):\n",
        "  dic_bolsonaro_percentual[x] = df_bolsonaro_local[x].size  * 100 / total_bolsonaro\n",
        "dic_bolsonaro_percentual"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MfYrP1fgyZEC",
        "outputId": "f82552e3-2d4e-44c0-b346-53cd2d830860"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{1: 34.99211494655686,\n",
              " 2: 17.592430348694585,\n",
              " 3: 11.897669528649027,\n",
              " 4: 7.9025757841247595,\n",
              " 5: 6.903802347993692,\n",
              " 6: 5.957595934816892,\n",
              " 7: 5.4319257052742245,\n",
              " 8: 4.8011214298230245,\n",
              " 9: 4.520763974066935}"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# `POR CIDADE, LULA`"
      ],
      "metadata": {
        "id": "dn4nUDm0l5Gz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "labels = ['(1): %.2f' %dic_lula_percentual[1],\n",
        "        '(2) %.2f' %dic_lula_percentual[2],\n",
        "        '(3) %.2f' %dic_lula_percentual[3],\n",
        "        '(4) %.2f' %dic_lula_percentual[4],\n",
        "        '(5) %.2f' %dic_lula_percentual[5],\n",
        "        '(6) %.2f' %dic_lula_percentual[6],\n",
        "        '(7) %.2f' %dic_lula_percentual[7],\n",
        "        '(8) %.2f' %dic_lula_percentual[8],\n",
        "        '(9) %.2f' %dic_lula_percentual[9]]\n",
        "\n",
        "valores = [df_lula_local[1].size,\n",
        "        df_lula_local[2].size,\n",
        "        df_lula_local[3].size,\n",
        "        df_lula_local[4].size,\n",
        "        df_lula_local[5].size,\n",
        "        df_lula_local[6].size,\n",
        "        df_lula_local[7].size,\n",
        "        df_lula_local[8].size,\n",
        "        df_lula_local[9].size]\n",
        "numbers = list(labels)\n",
        "amounts = list(valores)\n",
        "# amounts\n",
        "fig = plt.figure(figsize = (10, 5))\n",
        "\n",
        "# creating the bar plot\n",
        "plt.bar(numbers, amounts, color ='maroon',\n",
        "        width = 0.4)\n",
        "\n",
        "plt.xlabel(\"Números\")\n",
        "plt.ylabel(\"Quantidade\")\n",
        "plt.title(\"Benford Distirbution\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "FvalpathgJkF",
        "outputId": "05149ef5-d6e2-4b9b-b47c-76e404afc179"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# POR CIDADE, BOLSONARO"
      ],
      "metadata": {
        "id": "bUBphQC5pikn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "labels = ['(1): %.2f' %dic_bolsonaro_percentual[1],\n",
        "          '(2) %.2f' %dic_bolsonaro_percentual[2],\n",
        "          '(3) %.2f' %dic_bolsonaro_percentual[3],\n",
        "          '(4) %.2f' %dic_bolsonaro_percentual[4],\n",
        "          '(5) %.2f' %dic_bolsonaro_percentual[5],\n",
        "          '(6) %.2f' %dic_bolsonaro_percentual[6],\n",
        "          '(7) %.2f' %dic_bolsonaro_percentual[7],\n",
        "          '(8) %.2f' %dic_bolsonaro_percentual[8],\n",
        "          '(9) %.2f' %dic_bolsonaro_percentual[9]]\n",
        "\n",
        "valores = [df_bolsonaro_local[1].size,\n",
        "          df_bolsonaro_local[2].size,\n",
        "          df_bolsonaro_local[3].size,\n",
        "          df_bolsonaro_local[4].size,\n",
        "          df_bolsonaro_local[5].size,\n",
        "          df_bolsonaro_local[6].size,\n",
        "          df_bolsonaro_local[7].size,\n",
        "          df_bolsonaro_local[8].size,\n",
        "          df_bolsonaro_local[9].size]\n",
        "numbers = list(labels)\n",
        "amounts = list(valores)\n",
        "# amounts\n",
        "fig = plt.figure(figsize = (10, 5))\n",
        "\n",
        "# creating the bar plot\n",
        "plt.bar(numbers, amounts, color ='maroon',\n",
        "width = 0.4)\n",
        "\n",
        "plt.xlabel(\"Números\")\n",
        "plt.ylabel(\"Quantidade\")\n",
        "plt.title(\"Benford Distirbution\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "fFJOKdRDJtPB",
        "outputId": "e07df800-d0a1-4c59-b89c-c5b393af8815"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# COMPARAÇÃO COM APTOS\n",
        "O número de habitantes por cidade é enviesado, por isso a lei de Benford não se adequa perfeitamente neste caso. Aqui uma comparação mostrando que a quantidade de aptos por cidade foge da distribuição."
      ],
      "metadata": {
        "id": "9hj1aK203Z7X"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_lula_aptos_local = {}\n",
        "for x in range(1, 10):\n",
        "  df_lula_aptos_local[x] = df_lula_agg.loc[df_lula_agg['QT_APTOS'].astype(str).str.startswith(str(x), na=False)]\n",
        "\n",
        "df_lula_aptos_local[2]"
      ],
      "metadata": {
        "id": "uP1Nx5uXvTil"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_bolsonaro_aptos_local = {}\n",
        "for x in range(1, 10):\n",
        "  df_bolsonaro_aptos_local[x] = df_bolsonaro_agg.loc[df_bolsonaro_agg['QT_APTOS'].astype(str).str.startswith(str(x), na=False)]\n",
        "\n",
        "df_bolsonaro_aptos_local[2]"
      ],
      "metadata": {
        "id": "AqQUtJI3vcKe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "outputId": "8b979c87-95e5-4053-ba4d-17322f1550ff"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                               QT_VOTOS  QT_APTOS  QT_COMPARECIMENTO  \\\n",
              "CD_MUNICIPIO NR_PARTIDO SG_UF                                          \n",
              "19           22         RO        13001     28173              20379   \n",
              "116          22         RO        14932     26480              20615   \n",
              "256          22         RO        13595     23903              18420   \n",
              "396          22         RO        11490     23639              16644   \n",
              "728          22         RO         1630      2877               2276   \n",
              "...                                 ...       ...                ...   \n",
              "98213        22         RS        12726     25023              20687   \n",
              "98418        22         AM         7935     25234              17719   \n",
              "98817        22         MT         9632     22679              17025   \n",
              "99058        22         MT        13560     22601              17005   \n",
              "99317        22         ZZ           23       250                191   \n",
              "\n",
              "                                        NM_MUNICIPIO  \n",
              "CD_MUNICIPIO NR_PARTIDO SG_UF                         \n",
              "19           22         RO             GUAJARÁ-MIRIM  \n",
              "116          22         RO             PIMENTA BUENO  \n",
              "256          22         RO          ESPIGÃO DO OESTE  \n",
              "396          22         RO        MACHADINHO D'OESTE  \n",
              "728          22         RO     PRIMAVERA DE RONDÔNIA  \n",
              "...                                              ...  \n",
              "98213        22         RS                  TEUTÔNIA  \n",
              "98418        22         AM     PRESIDENTE FIGUEIREDO  \n",
              "98817        22         MT        PEIXOTO DE AZEVEDO  \n",
              "99058        22         MT         GUARANTÃ DO NORTE  \n",
              "99317        22         ZZ                     TALIN  \n",
              "\n",
              "[968 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-0227d515-085f-45bc-8122-6d581c002353\" class=\"colab-df-container\">\n",
              "    <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></th>\n",
              "      <th>QT_VOTOS</th>\n",
              "      <th>QT_APTOS</th>\n",
              "      <th>QT_COMPARECIMENTO</th>\n",
              "      <th>NM_MUNICIPIO</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CD_MUNICIPIO</th>\n",
              "      <th>NR_PARTIDO</th>\n",
              "      <th>SG_UF</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <th>22</th>\n",
              "      <th>RO</th>\n",
              "      <td>13001</td>\n",
              "      <td>28173</td>\n",
              "      <td>20379</td>\n",
              "      <td>GUAJARÁ-MIRIM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>116</th>\n",
              "      <th>22</th>\n",
              "      <th>RO</th>\n",
              "      <td>14932</td>\n",
              "      <td>26480</td>\n",
              "      <td>20615</td>\n",
              "      <td>PIMENTA BUENO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>256</th>\n",
              "      <th>22</th>\n",
              "      <th>RO</th>\n",
              "      <td>13595</td>\n",
              "      <td>23903</td>\n",
              "      <td>18420</td>\n",
              "      <td>ESPIGÃO DO OESTE</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>396</th>\n",
              "      <th>22</th>\n",
              "      <th>RO</th>\n",
              "      <td>11490</td>\n",
              "      <td>23639</td>\n",
              "      <td>16644</td>\n",
              "      <td>MACHADINHO D'OESTE</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>728</th>\n",
              "      <th>22</th>\n",
              "      <th>RO</th>\n",
              "      <td>1630</td>\n",
              "      <td>2877</td>\n",
              "      <td>2276</td>\n",
              "      <td>PRIMAVERA DE RONDÔNIA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98213</th>\n",
              "      <th>22</th>\n",
              "      <th>RS</th>\n",
              "      <td>12726</td>\n",
              "      <td>25023</td>\n",
              "      <td>20687</td>\n",
              "      <td>TEUTÔNIA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98418</th>\n",
              "      <th>22</th>\n",
              "      <th>AM</th>\n",
              "      <td>7935</td>\n",
              "      <td>25234</td>\n",
              "      <td>17719</td>\n",
              "      <td>PRESIDENTE FIGUEIREDO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98817</th>\n",
              "      <th>22</th>\n",
              "      <th>MT</th>\n",
              "      <td>9632</td>\n",
              "      <td>22679</td>\n",
              "      <td>17025</td>\n",
              "      <td>PEIXOTO DE AZEVEDO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99058</th>\n",
              "      <th>22</th>\n",
              "      <th>MT</th>\n",
              "      <td>13560</td>\n",
              "      <td>22601</td>\n",
              "      <td>17005</td>\n",
              "      <td>GUARANTÃ DO NORTE</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99317</th>\n",
              "      <th>22</th>\n",
              "      <th>ZZ</th>\n",
              "      <td>23</td>\n",
              "      <td>250</td>\n",
              "      <td>191</td>\n",
              "      <td>TALIN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>968 rows × 4 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0227d515-085f-45bc-8122-6d581c002353')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-0227d515-085f-45bc-8122-6d581c002353 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-0227d515-085f-45bc-8122-6d581c002353');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-4aeabd19-d76e-40eb-b515-7f072a279719\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-4aeabd19-d76e-40eb-b515-7f072a279719')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-4aeabd19-d76e-40eb-b515-7f072a279719 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "labels = ['(1)',\n",
        "          '(2)',\n",
        "          '(3)',\n",
        "          '(4)',\n",
        "          '(5)',\n",
        "          '(6)',\n",
        "          '(7)',\n",
        "          '(8)',\n",
        "          '(9)']\n",
        "\n",
        "valores = [df_lula_aptos_local[1].size,\n",
        "        df_lula_aptos_local[2].size,\n",
        "        df_lula_aptos_local[3].size,\n",
        "        df_lula_aptos_local[4].size,\n",
        "        df_lula_aptos_local[5].size,\n",
        "        df_lula_aptos_local[6].size,\n",
        "        df_lula_aptos_local[7].size,\n",
        "        df_lula_aptos_local[8].size,\n",
        "        df_lula_aptos_local[9].size]\n",
        "numbers = list(labels)\n",
        "amounts = list(valores)\n",
        "# amounts\n",
        "fig = plt.figure(figsize = (10, 5))\n",
        "\n",
        "# creating the bar plot\n",
        "plt.bar(numbers, amounts, color ='maroon',\n",
        "        width = 0.4)\n",
        "\n",
        "plt.xlabel(\"Números\")\n",
        "plt.ylabel(\"Quantidade\")\n",
        "plt.title(\"Benford Distirbution\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "OQFOeKsgyQ4C",
        "outputId": "3be51efd-ecb2-403b-8bbd-0aca57b0b225"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "labels = ['(1)',\n",
        "          '(2)',\n",
        "          '(3)',\n",
        "          '(4)',\n",
        "          '(5)',\n",
        "          '(6)',\n",
        "          '(7)',\n",
        "          '(8)',\n",
        "          '(9)']\n",
        "\n",
        "valores = [df_bolsonaro_aptos_local[1].size,\n",
        "          df_bolsonaro_aptos_local[2].size,\n",
        "          df_bolsonaro_aptos_local[3].size,\n",
        "          df_bolsonaro_aptos_local[4].size,\n",
        "          df_bolsonaro_aptos_local[5].size,\n",
        "          df_bolsonaro_aptos_local[6].size,\n",
        "          df_bolsonaro_aptos_local[7].size,\n",
        "          df_bolsonaro_aptos_local[8].size,\n",
        "          df_bolsonaro_aptos_local[9].size]\n",
        "numbers = list(labels)\n",
        "amounts = list(valores)\n",
        "# amounts\n",
        "fig = plt.figure(figsize = (10, 5))\n",
        "\n",
        "# creating the bar plot\n",
        "plt.bar(numbers, amounts, color ='maroon',\n",
        "width = 0.4)\n",
        "\n",
        "plt.xlabel(\"Números\")\n",
        "plt.ylabel(\"Quantidade\")\n",
        "plt.title(\"Benford Distirbution\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "1uv1um06ycFS",
        "outputId": "1b2d0a59-92b4-457e-b145-9e39633ef85b"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# POPULAÇÃO DE CIDADES PELA DISTRIBUIÇÃO DE BENFORD\n"
      ],
      "metadata": {
        "id": "dtebiK3k3sP-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "censo_municipios = pd.read_csv('/content/drive/MyDrive/data/dadosBrasil/CD2022_Populacao_Coletada_Imputada_e_Total_Municipio_e_UF.csv', encoding=\"ISO-8859-1\", sep = ',',\n",
        "                    dtype={\n",
        "                            \"UF\": pd.CategoricalDtype(),\n",
        "                            \"COD. MUNIC\": pd.Int64Dtype(),\n",
        "                            \"POP. TOTAL\": pd.StringDtype()\n",
        "                        })\n",
        "\n",
        "censo_municipios = censo_municipios.iloc[:, 1:]\n",
        "censo_municipios[\"POP_TOTAL\"] = censo_municipios[\"POP. TOTAL\"].str.replace(\" \", \"\")\n",
        "censo_municipios[\"POP_TOTAL\"] = censo_municipios[\"POP_TOTAL\"].astype(int)\n",
        "censo_municipios\n"
      ],
      "metadata": {
        "id": "AdlXWdb73WpR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_pop_municipios = {}\n",
        "for x in range(1, 10):\n",
        "  df_pop_municipios[x] = censo_municipios.loc[censo_municipios['POP_TOTAL'].astype(str).str.startswith(str(x), na=False)]\n",
        "\n",
        "df_pop_municipios[6]"
      ],
      "metadata": {
        "id": "pE6gNYyePSw2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "total_pop = 0\n",
        "df_pop_total = {}\n",
        "for x in range(1, 10):\n",
        "  total_pop = total_pop + df_pop_municipios[x].size\n",
        "  df_pop_total[x] = total_pop\n",
        "  total_pop = 0\n",
        "\n",
        "dic_pop_percentual = {}\n",
        "for x in range(1, 10):\n",
        "  dic_pop_percentual[x] = df_pop_total[x]  * 100 / censo_municipios.size\n",
        "dic_pop_percentual"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "spW-1YIhSkcU",
        "outputId": "00750026-31d3-478e-bddd-689f7c07d690"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{1: 29.892280071813286,\n",
              " 2: 18.29443447037702,\n",
              " 3: 13.375224416517055,\n",
              " 4: 10.825852782764812,\n",
              " 5: 7.504488330341113,\n",
              " 6: 6.642728904847397,\n",
              " 7: 5.763016157989228,\n",
              " 8: 4.290843806104129,\n",
              " 9: 3.4111310592459607}"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "labels = ['(1): %.2f' %dic_pop_percentual[1],\n",
        "          '(2) %.2f' %dic_pop_percentual[2],\n",
        "          '(3) %.2f' %dic_pop_percentual[3],\n",
        "          '(4) %.2f' %dic_pop_percentual[4],\n",
        "          '(5) %.2f' %dic_pop_percentual[5],\n",
        "          '(6) %.2f' %dic_pop_percentual[6],\n",
        "          '(7) %.2f' %dic_pop_percentual[7],\n",
        "          '(8) %.2f' %dic_pop_percentual[8],\n",
        "          '(9) %.2f' %dic_pop_percentual[9]]\n",
        "\n",
        "valores = [df_pop_municipios[1].size,\n",
        "        df_pop_municipios[2].size,\n",
        "        df_pop_municipios[3].size,\n",
        "        df_pop_municipios[4].size,\n",
        "        df_pop_municipios[5].size,\n",
        "        df_pop_municipios[6].size,\n",
        "        df_pop_municipios[7].size,\n",
        "        df_pop_municipios[8].size,\n",
        "        df_pop_municipios[9].size]\n",
        "numbers = list(labels)\n",
        "amounts = list(valores)\n",
        "# amounts\n",
        "fig = plt.figure(figsize = (10, 5))\n",
        "\n",
        "# creating the bar plot\n",
        "plt.bar(numbers, amounts, color ='maroon',\n",
        "        width = 0.4)\n",
        "\n",
        "plt.xlabel(\"Números\")\n",
        "plt.ylabel(\"Quantidade\")\n",
        "plt.title(\"Benford Distirbution\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "VN5o3iptPkzK",
        "outputId": "bfd9fa74-982b-487e-bf71-cbceeb3317e1"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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AAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAm9gayNauXauHH35YISEhcnFx0cKFC61pGRkZeuutt1SrVi2VKFFCISEhevrpp3X06FGHZSQlJalz587y9fWVv7+/unfvrtTUVIc+27ZtU5MmTeTp6anQ0FCNHDky21jmzZunatWqydPTU7Vq1dK33357TbYZAAAAALLYGsjOnDmj2rVra8KECdmmnT17Vlu2bNGAAQO0ZcsWzZ8/X3v37tUjjzzi0K9z587auXOnYmJitHjxYq1du1Y9evSwpqekpKhly5aqWLGiNm/erFGjRmnQoEGaPHmy1eenn37SE088oe7du2vr1q1q27at2rZtqx07dly7jQcAAABw03Mxxhi7ByFJLi4uWrBggdq2bZtrn40bN6pBgwY6dOiQKlSooN27d6tGjRrauHGj6tevL0launSpWrVqpd9++00hISH6+OOP1b9/fyUmJsrd3V2S1LdvXy1cuFB79uyRJHXo0EFnzpzR4sWLrXU1atRIderU0aRJk3IcS1pamtLS0qznKSkpCg0NVXJysnx9fa+2HFdtsIuL3UOQJEUXjd0LAAAAuG5SUlLk5+eXr2zwj/oNWXJyslxcXOTv7y9Jio2Nlb+/vxXGJCkiIkKurq5av3691adp06ZWGJOkyMhI7d27VydPnrT6REREOKwrMjJSsbGxuY5l2LBh8vPzsx6hoaHO2kwAAAAAN4l/TCA7f/683nrrLT3xxBNWykxMTFRgYKBDPzc3NwUEBCgxMdHqExQU5NAn6/mV+mRNz0m/fv2UnJxsPY4cOXJ1GwgAAADgpuNm9wDyIyMjQ+3bt5cxRh9//LHdw5EkeXh4yMPDw+5hAAAAAPgHK/KBLCuMHTp0SCtXrnQ4BzM4OFgnTpxw6H/hwgUlJSUpODjY6nP8+HGHPlnPr9QnazoAAAAAXAtF+pTFrDAWHx+v5cuXq3Tp0g7Tw8PDderUKW3evNlqW7lypTIzM9WwYUOrz9q1a5WRkWH1iYmJUdWqVVWqVCmrz4oVKxyWHRMTo/Dw8Gu1aQAAAABgbyBLTU1VXFyc4uLiJEkJCQmKi4vT4cOHlZGRoccff1ybNm3SrFmzdPHiRSUmJioxMVHp6emSpOrVq+uBBx7Qc889pw0bNujHH39Ur1691LFjR4WEhEiSOnXqJHd3d3Xv3l07d+7UnDlz9NFHH6lPnz7WOF555RUtXbpUo0eP1p49ezRo0CBt2rRJvXr1uu41AQAAAHDzsPWy96tXr1bz5s2ztXfp0kWDBg1SWFhYjvOtWrVK9957r6S/bwzdq1cvffPNN3J1dVW7du00duxY+fj4WP23bdumqKgobdy4UWXKlNFLL72kt956y2GZ8+bN09tvv62DBw+qcuXKGjlypFq1apXvbSnIpS2vBy57DwAAANijINmgyNyH7J+OQJYzAhkAAABuNjfsfcgAAAAA4EZCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALCJrYFs7dq1evjhhxUSEiIXFxctXLjQYboxRgMHDlS5cuXk5eWliIgIxcfHO/RJSkpS586d5evrK39/f3Xv3l2pqakOfbZt26YmTZrI09NToaGhGjlyZLaxzJs3T9WqVZOnp6dq1aqlb7/91unbCwAAAACXsjWQnTlzRrVr19aECRNynD5y5EiNHTtWkyZN0vr161WiRAlFRkbq/PnzVp/OnTtr586diomJ0eLFi7V27Vr16NHDmp6SkqKWLVuqYsWK2rx5s0aNGqVBgwZp8uTJVp+ffvpJTzzxhLp3766tW7eqbdu2atu2rXbs2HHtNh4AAADATc/FGGPsHoQkubi4aMGCBWrbtq2kv4+OhYSE6LXXXtPrr78uSUpOTlZQUJCmT5+ujh07avfu3apRo4Y2btyo+vXrS5KWLl2qVq1a6bffflNISIg+/vhj9e/fX4mJiXJ3d5ck9e3bVwsXLtSePXskSR06dNCZM2e0ePFiazyNGjVSnTp1NGnSpBzHm5aWprS0NOt5SkqKQkNDlZycLF9fX6fXp6AGu7jYPQRJUnTR2L0AAACA6yYlJUV+fn75ygZF9jdkCQkJSkxMVEREhNXm5+enhg0bKjY2VpIUGxsrf39/K4xJUkREhFxdXbV+/XqrT9OmTa0wJkmRkZHau3evTp48afW5dD1ZfbLWk5Nhw4bJz8/PeoSGhl79RgMAAAC4qRTZQJaYmChJCgoKcmgPCgqypiUmJiowMNBhupubmwICAhz65LSMS9eRW5+s6Tnp16+fkpOTrceRI0cKuokAAAAAbnJudg/gn8rDw0MeHh52DwMAAADAP1iRPUIWHBwsSTp+/LhD+/Hjx61pwcHBOnHihMP0CxcuKCkpyaFPTsu4dB259cmaDgAAAADXQpENZGFhYQoODtaKFSustpSUFK1fv17h4eGSpPDwcJ06dUqbN2+2+qxcuVKZmZlq2LCh1Wft2rXKyMiw+sTExKhq1aoqVaqU1efS9WT1yVoPAAAAAFwLtgay1NRUxcXFKS4uTtLfF/KIi4vT4cOH5eLiot69e+udd97RokWLtH37dj399NMKCQmxrsRYvXp1PfDAA3ruuee0YcMG/fjjj+rVq5c6duyokJAQSVKnTp3k7u6u7t27a+fOnZozZ44++ugj9enTxxrHK6+8oqVLl2r06NHas2ePBg0apE2bNqlXr17XuyQAAAAAbiK2XvZ+9erVat68ebb2Ll26aPr06TLGKDo6WpMnT9apU6d0zz33aOLEiapSpYrVNykpSb169dI333wjV1dXtWvXTmPHjpWPj4/VZ9u2bYqKitLGjRtVpkwZvfTSS3rrrbcc1jlv3jy9/fbbOnjwoCpXrqyRI0eqVatW+d6Wglza8nrgsvcAAACAPQqSDYrMfcj+6QhkOSOQAQAA4GZzQ9yHDAAAAABudAQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJoUOZKdOndKUKVPUr18/JSUlSZK2bNmi33//3WmDAwAAAIAbmVthZtq2bZsiIiLk5+engwcP6rnnnlNAQIDmz5+vw4cPa+bMmc4eJwAAAADccAp1hKxPnz7q2rWr4uPj5enpabW3atVKa9euddrgAAAAAOBGVqhAtnHjRvXs2TNb+y233KLExMSrHhQAAAAA3AwKFcg8PDyUkpKSrX3fvn0qW7bsVQ8KAAAAAG4GhQpkjzzyiIYMGaKMjAxJkouLiw4fPqy33npL7dq1c+oAAQAAAOBGVaiLeowePVqPP/64AgMDde7cOTVr1kyJiYkKDw/Xu+++6+wxArYb7OJi9xAkSdHG2D0EAAAAOFGhjpD5+fkpJiZG33zzjcaOHatevXrp22+/1Zo1a1SiRAmnDe7ixYsaMGCAwsLC5OXlpdtuu01Dhw6VueRLqTFGAwcOVLly5eTl5aWIiAjFx8c7LCcpKUmdO3eWr6+v/P391b17d6Wmpjr02bZtm5o0aSJPT0+FhoZq5MiRTtsOAAAAAMhJoY6QZbnnnnt0zz33OGss2YwYMUIff/yxZsyYoZo1a2rTpk165pln5Ofnp5dfflmSNHLkSI0dO1YzZsxQWFiYBgwYoMjISO3atcu6AmTnzp117NgxxcTEKCMjQ88884x69Oih2bNnS5JSUlLUsmVLRUREaNKkSdq+fbu6desmf39/9ejR45ptHwAAAICbm4sx+TsHauzYsfleaFZYuloPPfSQgoKCNHXqVKutXbt28vLy0ueffy5jjEJCQvTaa6/p9ddflyQlJycrKChI06dPV8eOHbV7927VqFFDGzduVP369SVJS5cuVatWrfTbb78pJCREH3/8sfr376/ExES5u7tLkvr27auFCxdqz549+RprSkqK/Pz8lJycLF9fX6ds/9XgFDvnop4AAADIr4Jkg3wfIRszZozD8z/++ENnz56Vv7+/JOnUqVPy9vZWYGCg0wLZ3XffrcmTJ2vfvn2qUqWKfvnlF61bt04ffPCBJCkhIUGJiYmKiIiw5vHz81PDhg0VGxurjh07KjY2Vv7+/lYYk6SIiAi5urpq/fr1evTRRxUbG6umTZtaYUySIiMjNWLECJ08eVKlSpXKNra0tDSlpaVZz3O66iQAAAAA5CXfvyFLSEiwHu+++67q1Kmj3bt3KykpSUlJSdq9e7fq1q2roUOHOm1wffv2VceOHVWtWjUVL15cd955p3r37q3OnTtLknXPs6CgIIf5goKCrGmJiYkKDAx0mO7m5qaAgACHPjkt49J1XG7YsGHy8/OzHqGhoVe5tQAAAABuNoW6qMeAAQM0btw4Va1a1WqrWrWqxowZo7fffttpg5s7d65mzZql2bNna8uWLZoxY4bef/99zZgxw2nrKKx+/fopOTnZehw5csTuIQEAAAD4hynURT2OHTumCxcuZGu/ePGijh8/ftWDyvLGG29YR8kkqVatWjp06JCGDRumLl26KDg4WJJ0/PhxlStXzprv+PHjqlOnjiQpODhYJ06ccFjuhQsXlJSUZM0fHBycbdxZz7P6XM7Dw0MeHh5Xv5EAAAAAblqFOkLWokUL9ezZU1u2bLHaNm/erBdeeMHh91xX6+zZs3J1dRxisWLFlJmZKUkKCwtTcHCwVqxYYU1PSUnR+vXrFR4eLkkKDw/XqVOntHnzZqvPypUrlZmZqYYNG1p91q5da93oWpJiYmJUtWrVHH8/BgAAAADOUKhA9tlnnyk4OFj169e3jhQ1aNBAQUFBmjJlitMG9/DDD+vdd9/VkiVLdPDgQS1YsEAffPCBHn30UUmSi4uLevfurXfeeUeLFi3S9u3b9fTTTyskJERt27aVJFWvXl0PPPCAnnvuOW3YsEE//vijevXqpY4dOyokJESS1KlTJ7m7u6t79+7auXOn5syZo48++kh9+vRx2rYAAAAAwOUKdcpi2bJl9e2332rfvn3WZeGrVaumKlWqOHVw48aN04ABA/Tiiy/qxIkTCgkJUc+ePTVw4ECrz5tvvqkzZ86oR48eOnXqlO655x4tXbrUugeZJM2aNUu9evVSixYt5Orqqnbt2jlcxt/Pz0/Lli1TVFSU6tWrpzJlymjgwIHcgwwAAADANZXv+5Ahb9yHLGc3yn2zqCcAAADy65rch+xyv/32mxYtWqTDhw8rPT3dYVrWfcIAAAAAALkrVCBbsWKFHnnkEVWqVEl79uzRHXfcoYMHD8oYo7p16zp7jAAAAABwQyrURT369eun119/Xdu3b5enp6f+97//6ciRI2rWrJn+/e9/O3uMAAAAAHBDKlQg2717t55++mlJkpubm86dOycfHx8NGTJEI0aMcOoAAQAAAOBGVahAVqJECet3Y+XKldOBAwesaX/++adzRgYAAAAAN7hC/YasUaNGWrdunapXr65WrVrptdde0/bt2zV//nw1atTI2WMEAAAAgBtSoQLZBx98oNTUVEnS4MGDlZqaqjlz5qhy5cpcYREAAAAA8qlQgaxSpUrWv0uUKKFJkyY5bUAAAAAAcLMo1G/IAAAAAABXL99HyEqVKiUXF5d89U1KSir0gAAAAADgZpHvQPbhhx9a//7rr7/0zjvvKDIyUuHh4ZKk2NhYff/99xowYIDTBwkAAAAANyIXY4wp6Ezt2rVT8+bN1atXL4f28ePHa/ny5Vq4cKGzxvePkZKSIj8/PyUnJ8vX19fu4WhwPo9mXmvRBd+9iiTqCQAAgPwqSDYo1G/Ivv/+ez3wwAPZ2h944AEtX768MIsEAAAAgJtOoQJZ6dKl9fXXX2dr//rrr1W6dOmrHhQAAAAA3AwKddn7wYMH69lnn9Xq1avVsGFDSdL69eu1dOlSffrpp04dIAAAAADcqAoVyLp27arq1atr7Nixmj9/viSpevXqWrdunRXQAAAAAAB5K1Qgk6SGDRtq1qxZzhwLAAAAANxU8h3IUlJSrCuEpKSk5Nm3KFxlEAAAAACKugLdGPrYsWMKDAyUv79/jjeJNsbIxcVFFy9edOogAQAAAOBGlO9AtnLlSgUEBEiSVq1adc0GBAAAAAA3i3wHsmbNmln/DgsLU2hoaLajZMYYHTlyxHmjAwAAAIAbWKHuQxYWFqY//vgjW3tSUpLCwsKuelAAAAAAcDMoVCDL+q3Y5VJTU+Xp6XnVgwIAAACAm0GBLnvfp08fSZKLi4sGDBggb29va9rFixe1fv161alTx6kDBAAAAIAbVYEC2datWyX9fYRs+/btcnd3t6a5u7urdu3aev311507QgAAAAC4QRUokGVdXfGZZ57RRx99xP3GAAAAAOAqFCiQZZk2bZqzxwEAAAAAN51CBbIzZ85o+PDhWrFihU6cOKHMzEyH6b/++qtTBgcAAAAAN7JCBbJnn31Wa9as0VNPPaVy5crleMVFAAAAAEDeChXIvvvuOy1ZskSNGzd29ngAAAAA4KZRqPuQlSpVSgEBAc4eCwAAAADcVAoVyIYOHaqBAwfq7Nmzzh4PAAAAANw0CnXK4ujRo3XgwAEFBQXp1ltvVfHixR2mb9myxSmDAwAAAIAbWaECWdu2bZ08DAAAAAC4+RQqkEVHRzt7HAAAAABw0ynUb8gAAAAAAFevUEfILl68qDFjxmju3Lk6fPiw0tPTHaYnJSU5ZXAAAAAAcCMr1BGywYMH64MPPlCHDh2UnJysPn366LHHHpOrq6sGDRrk5CECAAAAwI2pUIFs1qxZ+vTTT/Xaa6/Jzc1NTzzxhKZMmaKBAwfq559/dvYYAQAAAOCGVKhAlpiYqFq1akmSfHx8lJycLEl66KGHtGTJEueNDgAAAABuYIUKZOXLl9exY8ckSbfddpuWLVsmSdq4caM8PDycNzoAAAAAuIEVKpA9+uijWrFihSTppZde0oABA1S5cmU9/fTT6tatm1MHCAAAAAA3qkJdZXH48OHWvzt06KAKFSooNjZWlStX1sMPP+y0wQEAAADAjaxQgexy4eHhCg8Pd8aiAAAAAOCmUahTFmfOnJnnw5l+//13PfnkkypdurS8vLxUq1Ytbdq0yZpujNHAgQNVrlw5eXl5KSIiQvHx8Q7LSEpKUufOneXr6yt/f391795dqampDn22bdumJk2ayNPTU6GhoRo5cqRTtwMAAAAALleoI2SvvPKKw/OMjAydPXtW7u7u8vb21tNPP+2UwZ08eVKNGzdW8+bN9d1336ls2bKKj49XqVKlrD4jR47U2LFjNWPGDIWFhWnAgAGKjIzUrl275OnpKUnq3Lmzjh07ppiYGGVkZOiZZ55Rjx49NHv2bElSSkqKWrZsqYiICE2aNEnbt29Xt27d5O/vrx49ejhlWwAAAADgcoUKZCdPnszWFh8frxdeeEFvvPHGVQ8qy4gRIxQaGqpp06ZZbWFhYda/jTH68MMP9fbbb6tNmzaS/j56FxQUpIULF6pjx47avXu3li5dqo0bN6p+/fqSpHHjxqlVq1Z6//33FRISolmzZik9PV2fffaZ3N3dVbNmTcXFxemDDz4gkAEAAAC4Zgp1ymJOKleurOHDh2c7enY1Fi1apPr16+vf//63AgMDdeedd+rTTz+1pickJCgxMVERERFWm5+fnxo2bKjY2FhJUmxsrPz9/a0wJkkRERFydXXV+vXrrT5NmzaVu7u71ScyMlJ79+7NMXxKUlpamlJSUhweAAAAAFAQTgtkkuTm5qajR486bXm//vqrPv74Y1WuXFnff/+9XnjhBb388suaMWOGpL9vUC1JQUFBDvMFBQVZ0xITExUYGJhtnAEBAQ59clrGpeu43LBhw+Tn52c9QkNDr3JrAQAAANxsCnXK4qJFixyeG2N07NgxjR8/Xo0bN3bKwCQpMzNT9evX13vvvSdJuvPOO7Vjxw5NmjRJXbp0cdp6CqNfv37q06eP9TwlJYVQBuTTYBcXu4cgSYo2xu4hAACAm1yhAlnbtm0dnru4uKhs2bK67777NHr0aGeMS5JUrlw51ahRw6GtevXq+t///idJCg4OliQdP35c5cqVs/ocP35cderUsfqcOHHCYRkXLlxQUlKSNX9wcLCOHz/u0CfreVafy3l4eMjDw6OQWwYAAAAAhTxlMTMzU5mZmTp+/LhOnjypixcvKjExUbNnz3YIRlercePG2rt3r0Pbvn37VLFiRUl/X+AjODhYK1assKanpKRo/fr11n3RwsPDderUKW3evNnqs3LlSmVmZqphw4ZWn7Vr1yojI8PqExMTo6pVqzpc0REAAAAAnKnAgezUqVOKiopSmTJlFBwcrICAAAUHB6tfv346e/asUwf36quv6ueff9Z7772n/fv3a/bs2Zo8ebKioqIk/X1krnfv3nrnnXe0aNEibd++XU8//bRCQkKso3jVq1fXAw88oOeee04bNmzQjz/+qF69eqljx44KCQmRJHXq1Enu7u7q3r27du7cqTlz5uijjz5yOCURAAAAAJytQKcsJiUlKTw8XL///rs6d+6s6tWrS5J27dqlcePGKSYmRuvWrdO2bdv0888/6+WXX76qwd11111asGCB+vXrpyFDhigsLEwffvihOnfubPV58803debMGfXo0UOnTp3SPffco6VLl1r3IJOkWbNmqVevXmrRooVcXV3Vrl07jR071pru5+enZcuWKSoqSvXq1VOZMmU0cOBALnkPAAAA4JpyMSb/v2rv3bu3VqxYoeXLl2e7KmFiYqJatmypqlWratmyZRo7dqztF964nlJSUuTn56fk5GT5+vraPRwumuBk1NO5qCcAALiRFSQbFOgI2cKFC/XJJ59kC2PS3xe/GDlypFq1aqXo6OibKowBAAAAQGEU6Ddkx44dU82aNXOdfscdd8jV1VXR0dFXPTAAAAAAuNEVKJCVKVNGBw8ezHV6QkJCtpswAwAAAAByVqBAFhkZqf79+ys9PT3btLS0NA0YMEAPPPCA0wYHAAAAADeyAv2GbMiQIapfv74qV66sqKgoVatWTcYY7d69WxMnTlRaWppmzpx5rcYKAAAAADeUAgWy8uXLKzY2Vi+++KL69eunrAs0uri46P7779f48eNVoUKFazJQAAAAALjRFCiQSVJYWJi+++47nTx5UvHx8ZKk22+/XQEBAU4fHAAAAADcyAocyLKUKlVKDRo0cOZYAAAAAOCmUqCLegAAAAAAnIdABgAAAAA2IZABAAAAgE0IZAAAAABgEwIZAAAAANiEQAYAAAAANiGQAQAAAIBNCGQAAAAAYBMCGQAAAADYhEAGAAAAADYhkAEAAACATQhkAAAAAGATAhkAAAAA2IRABgAAAAA2IZABAAAAgE0IZAAAAABgEwIZAAAAANjEze4BAACuzmAXF7uHIEmKNsbuIQAA8I/DETIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbPKPCmTDhw+Xi4uLevfubbWdP39eUVFRKl26tHx8fNSuXTsdP37cYb7Dhw+rdevW8vb2VmBgoN544w1duHDBoc/q1atVt25deXh46Pbbb9f06dOvwxYBAAAAuJn9YwLZxo0b9cknn+hf//qXQ/urr76qb775RvPmzdOaNWt09OhRPfbYY9b0ixcvqnXr1kpPT9dPP/2kGTNmaPr06Ro4cKDVJyEhQa1bt1bz5s0VFxen3r1769lnn9X3339/3bYPAAAAwM3nHxHIUlNT1blzZ3366acqVaqU1Z6cnKypU6fqgw8+0H333ad69epp2rRp+umnn/Tzzz9LkpYtW6Zdu3bp888/V506dfTggw9q6NChmjBhgtLT0yVJkyZNUlhYmEaPHq3q1aurV69eevzxxzVmzBhbthcAAADAzeEfEciioqLUunVrRUREOLRv3rxZGRkZDu3VqlVThQoVFBsbK0mKjY1VrVq1FBQUZPWJjIxUSkqKdu7cafW5fNmRkZHWMnKSlpamlJQUhwcAAAAAFISb3QO4ki+//FJbtmzRxo0bs01LTEyUu7u7/P39HdqDgoKUmJho9bk0jGVNz5qWV5+UlBSdO3dOXl5e2dY9bNgwDR48uNDbBQAAAABF+gjZkSNH9Morr2jWrFny9PS0ezgO+vXrp+TkZOtx5MgRu4cEAAAA4B+mSAeyzZs368SJE6pbt67c3Nzk5uamNWvWaOzYsXJzc1NQUJDS09N16tQph/mOHz+u4OBgSVJwcHC2qy5mPb9SH19f3xyPjkmSh4eHfH19HR4AAAAAUBBFOpC1aNFC27dvV1xcnPWoX7++OnfubP27ePHiWrFihTXP3r17dfjwYYWHh0uSwsPDtX37dp04ccLqExMTI19fX9WoUcPqc+kysvpkLQMAAAAAroUi/RuykiVL6o477nBoK1GihEqXLm21d+/eXX369FFAQIB8fX310ksvKTw8XI0aNZIktWzZUjVq1NBTTz2lkSNHKjExUW+//baioqLk4eEhSXr++ec1fvx4vfnmm+rWrZtWrlypuXPnasmSJdd3gwEAAADcVIp0IMuPMWPGyNXVVe3atVNaWpoiIyM1ceJEa3qxYsW0ePFivfDCCwoPD1eJEiXUpUsXDRkyxOoTFhamJUuW6NVXX9VHH32k8uXLa8qUKYqMjLRjkwAAAADcJFyMMcbuQdwIUlJS5Ofnp+Tk5CLxe7LBLi52D0GSFH2D7F7U07mop3NRTwAAipaCZIMi/RsyAAAAALiREcgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALCJm90DAACgKBns4mL3EBRtjN1DAABcJxwhAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJu42T0AAABw4xrs4mL3EBRtjN1DAIBccYQMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbuNk9AAAAAOTPYBcXu4egaGPsHgJwQ+EIGQAAAADYhEAGAAAAADYhkAEAAACATQhkAAAAAGATAhkAAAAA2IRABgAAAAA2IZABAAAAgE0IZAAAAABgEwIZAAAAANiEQAYAAAAANiGQAQAAAIBNinQgGzZsmO666y6VLFlSgYGBatu2rfbu3evQ5/z584qKilLp0qXl4+Ojdu3a6fjx4w59Dh8+rNatW8vb21uBgYF64403dOHCBYc+q1evVt26deXh4aHbb79d06dPv9abBwAAAOAmV6QD2Zo1axQVFaWff/5ZMTExysjIUMuWLXXmzBmrz6uvvqpvvvlG8+bN05o1a3T06FE99thj1vSLFy+qdevWSk9P108//aQZM2Zo+vTpGjhwoNUnISFBrVu3VvPmzRUXF6fevXvr2Wef1ffff39dtxcAAADAzcXN7gHkZenSpQ7Pp0+frsDAQG3evFlNmzZVcnKypk6dqtmzZ+u+++6TJE2bNk3Vq1fXzz//rEaNGmnZsmXatWuXli9frqCgINWpU0dDhw7VW2+9pUGDBsnd3V2TJk1SWFiYRo8eLUmqXr261q1bpzFjxigyMvK6bzcAAACAm0ORPkJ2ueTkZElSQECAJGnz5s3KyMhQRESE1adatWqqUKGCYmNjJUmxsbGqVauWgoKCrD6RkZFKSUnRzp07rT6XLiOrT9YycpKWlqaUlBSHBwAAAAAUxD8mkGVmZqp3795q3Lix7rjjDklSYmKi3N3d5e/v79A3KChIiYmJVp9Lw1jW9KxpefVJSUnRuXPnchzPsGHD5OfnZz1CQ0OvehsBAAAA3Fz+MYEsKipKO3bs0Jdffmn3UCRJ/fr1U3JysvU4cuSI3UMCAAAA8A9TpH9DlqVXr15avHix1q5dq/Lly1vtwcHBSk9P16lTpxyOkh0/flzBwcFWnw0bNjgsL+sqjJf2ufzKjMePH5evr6+8vLxyHJOHh4c8PDyuetsAAABgj8EuLnYPQdHG2D0E2KxIHyEzxqhXr15asGCBVq5cqbCwMIfp9erVU/HixbVixQqrbe/evTp8+LDCw8MlSeHh4dq+fbtOnDhh9YmJiZGvr69q1Khh9bl0GVl9spYBAAAAANdCkT5CFhUVpdmzZ+vrr79WyZIlrd98+fn5ycvLS35+furevbv69OmjgIAA+fr66qWXXlJ4eLgaNWokSWrZsqVq1Kihp556SiNHjlRiYqLefvttRUVFWUe4nn/+eY0fP15vvvmmunXrppUrV2ru3LlasmSJbdsOAAAA4MZXpI+Qffzxx0pOTta9996rcuXKWY85c+ZYfcaMGaOHHnpI7dq1U9OmTRUcHKz58+db04sVK6bFixerWLFiCg8P15NPPqmnn35aQ4YMsfqEhYVpyZIliomJUe3atTV69GhNmTKFS94DAAAAuKaK9BEyk49zaj09PTVhwgRNmDAh1z4VK1bUt99+m+dy7r33Xm3durXAYwQAAACAwirSR8gAAAAA4EZGIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsU6cveAwAAACj6Bru42D0ESVJ0Pm6bVdRwhAwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgu8yECRN06623ytPTUw0bNtSGDRvsHhIAAACAGxSB7BJz5sxRnz59FB0drS1btqh27dqKjIzUiRMn7B4aAAAAgBsQgewSH3zwgZ577jk988wzqlGjhiZNmiRvb2999tlndg8NAAAAwA3Ize4BFBXp6enavHmz+vXrZ7W5uroqIiJCsbGx2fqnpaUpLS3Nep6cnCxJSklJufaDzYfzdg/g/xSVelwt6ulc1NO5qKdzFYV63ii1lKins1FP56KezlMUaikVnXpmjcMYc8W+LiY/vW4CR48e1S233KKffvpJ4eHhVvubb76pNWvWaP369Q79Bw0apMGDB1/vYQIAAAD4hzhy5IjKly+fZx+OkBVSv3791KdPH+t5ZmamkpKSVLp0abm4uNg4MudISUlRaGiojhw5Il9fX7uH849HPZ2LejoX9XQu6ulc1NN5qKVzUU/nutHqaYzR6dOnFRIScsW+BLL/U6ZMGRUrVkzHjx93aD9+/LiCg4Oz9ffw8JCHh4dDm7+//7Ucoi18fX1viDdFUUE9nYt6Ohf1dC7q6VzU03mopXNRT+e6kerp5+eXr35c1OP/uLu7q169elqxYoXVlpmZqRUrVjicwggAAAAAzsIRskv06dNHXbp0Uf369dWgQQN9+OGHOnPmjJ555hm7hwYAAADgBkQgu0SHDh30xx9/aODAgUpMTFSdOnW0dOlSBQUF2T20687Dw0PR0dHZTstE4VBP56KezkU9nYt6Ohf1dB5q6VzU07lu5npylUUAAAAAsAm/IQMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiArwv766y8FBgbq4MGD+Z5n6dKlqlOnjjIzM6/dwP7hClPXSZMm6eGHH752g/oHo57ORT2vLerrXHxOORf7p3OxfzoX9byGDIqsV1991Tz77LMObS+99JKpW7eucXd3N7Vr185xvvr165uZM2cWaF1//fWX6dWrl6lSpYrx9PQ0oaGh5qWXXjKnTp1y6Ld8+XITHh5ufHx8TFBQkHnzzTdNRkZGnss+duyYefLJJ01QUJDx9vY2d955p/nqq68c+mzevNlEREQYPz8/ExAQYJ577jlz+vTpAm1Dfl1e17i4ONOxY0dTvnx54+npaapVq2Y+/PBDh3nS0tJMSEiIWbt2bZ7LXrNmjXnooYdMuXLljCSzYMGCbH1Onz5toqKizC233GI8PT1N9erVzccff5zncidPnmzuuece4+/vb/z9/U2LFi3M+vXrHfokJiaaLl26mHLlyhkvLy8TGRlp9u3bd4VqXL3L6/nnn3+ayMhIU65cOePu7m7Kly9voqKiTHJystXHmfWMjo42VatWNd7e3lZtfv755zyXO3HiRFOrVi1TsmRJU7JkSdOoUSPz7bffOvTJz357LeT0vs/y559/mltuucVIMidPnrTanVnPzMxMM2DAABMcHGw8PT1NixYtrrgfXbhwwbz99tvm1ltvNZ6enqZSpUpmyJAhJjMz0+pTmNfpWsipvpKyPb744gtren7rW7FixRyX9eKLL+Y6z7Rp07L19/DwcOhTmNfkesltf502bZqpVauW8fDwMGXLls1Wg/x+Tp08edK8+OKLJjg42Li7u5vKlSubJUuW5DlPZmamGTVqlKlcubJxd3c3ISEh5p133smx77p160yxYsVy/Ty93i6vZ077R9bj+PHjxpj875/R0dHZllG1atU852nWrFmO627VqpVDv127dpmHH37Y+Pr6Gm9vb1O/fn1z6NChQlbBeXLaPzds2GDuu+8+4+fnZ/z9/U3Lli1NXFycQ5+Cfo/64osvjCTTpk2bPPv973//MxEREaZMmTLWZ8/SpUsd+qSkpJhXXnnFVKhQwXh6eprw8HCzYcOGfI/lWsqpnvn5Xpifev7vf/8z9erVM35+fsbb29vUrl27QK9Bbu/l/HzuFQUEsiLqzJkzxtfX18TGxjq0v/TSS2b8+PHmqaeeyvUDZPz48aZ+/foFWt/27dvNY489ZhYtWmT2799vVqxYYSpXrmzatWtn9YmLizPu7u5m8ODBJj4+3qxevdpUq1bNvPbaa3ku+/777zd33XWXWb9+vTlw4IAZOnSocXV1NVu2bDHGGPP777+bUqVKmeeff97s2bPHbNiwwdx9990O63aWnOo6depU8/LLL5vVq1ebAwcOmP/+97/Gy8vLjBs3zmHe119/3Tz++ON5Lv/bb781/fv3N/Pnz8/1jf/cc8+Z2267zaxatcokJCSYTz75xBQrVsx8/fXXuS63U6dOZsKECWbr1q1m9+7dpmvXrsbPz8/89ttvxpi/v4A0atTINGnSxGzYsMHs2bPH9OjRw1SoUMGkpqYWoEIFk1M9k5KSzMSJE83GjRvNwYMHzfLly03VqlXNE0884TCvs+o5a9YsExMTYw4cOGB27Nhhunfvbnx9fc2JEydyXe6iRYvMkiVLzL59+8zevXvNf/7zH1O8eHGzY8cOq8+V9ttrIbf3fZY2bdqYBx98MFsgM8Z59Rw+fLjx8/MzCxcuNL/88ot55JFHTFhYmDl37lyuy3333XdN6dKlzeLFi01CQoKZN2+e8fHxMR999JHVpzCvk7PlVl9JZtq0aebYsWPW4/LtzU99T5w44bCMmJgYI8msWrUq13mmTZtmfH19HeZLTEx06FOY1+R6yK2eo0ePNiEhIWbWrFlm//795pdffsn2/1t+PqfS0tJM/fr1TatWrcy6detMQkKCWb16dbYvz5d76aWXTNWqVc3XX39tfv31V7Np0yazbNmybP1OnjxpKlWqZFq2bFkkAllO9Tx79qzDvnHs2DETGRlpmjVr5jBvfvbP6OhoU7NmTYdl/fHHH3nO89dffzn037FjhylWrJiZNm2a1Wf//v0mICDAvPHGG2bLli1m//795uuvv7YCo11yqufp06dNQECA6dq1q9mzZ4/ZsWOHadeunQkKCjLp6elWv4J8j0pISDC33HKLadKkyRUD2SuvvGJGjBhhNmzYYPbt22f69etnihcv7vC50r59e1OjRg2zZs0aEx8fb6Kjo42vr6/1eW+XnOqZ3++F+annqlWrzPz5882uXbvM/v37zYcffmiKFSuWLbDmJK/3cn4+94oCAlkRNW/ePFO2bNlcp0dHR+f6AXLo0CEjyezfv/+qxjB37lzj7u5u/aWjX79+2d5QixYtMp6eniYlJSXX5ZQoUSLbXzkCAgLMp59+aowx5pNPPjGBgYHm4sWL1vRt27YZSSY+Pv6qtuFyV6prlhdffNE0b97coW3NmjXG3d3dnD17Nl/ryu2NX7NmTTNkyBCHtrp165r+/fvna7nG/H1EomTJkmbGjBnGGGP27t1rJDkEiosXL5qyZctadb4W8lvPjz76yJQvX96hzVn1vFxycrKRZJYvX56v5WYpVaqUmTJlivX8SvvttZBXPSdOnGiaNWtmVqxYkWMgc0Y9MzMzTXBwsBk1apTVdurUKePh4eFwxOhyrVu3Nt26dXNoe+yxx0znzp1znaewr9PVyK2++dm3ClpfY/7+8nXbbbc5HCm83LRp04yfn1+u0wv7mlwPOdUzKSnJeHl5XfF1zc/n1Mcff2wqVark8EX5Snbt2mXc3NzMnj17rti3Q4cO5u23387z8/R6ys//pydOnDDFixfP9n9TfvZPZ2znmDFjTMmSJR3+0NehQwfz5JNPXtVyr4Wc6rlx40YjyRw+fNhqy+n7Rn6/R124cMHcfffdZsqUKaZLly5XDGQ5qVGjhhk8eLAx5u8AXqxYMbN48WKHPgX9jnAt5FTP/H4vLOz30jvvvNO8/fbbV+yX3/dyUQ5k/IasiPrhhx9Ur169Qs1boUIFBQUF6YcffrDaunbtqnvvvbdAy0lOTpavr6/c3NwkSWlpafL09HTo4+XlpfPnz2vz5s25Lufuu+/WnDlzlJSUpMzMTH355Zc6f/68NZ60tDS5u7vL1fX/745eXl6SpHXr1hVozFeS37omJycrICDAoa1+/fq6cOGC1q9ff1VjuPvuu7Vo0SL9/vvvMsZo1apV2rdvn1q2bJnvZZw9e1YZGRnWGNPS0iTJ4fVxdXWVh4eH02t4qfzU8+jRo5o/f76aNWvm0O6sel4qPT1dkydPlp+fn2rXrp2veS5evKgvv/xSZ86cUXh4uNV+pf32Wsitnrt27dKQIUM0c+ZMh/fJpZxRz4SEBCUmJioiIsJq8/PzU8OGDRUbG5vrfHfffbdWrFihffv2SZJ++eUXrVu3Tg8++GCO/QvzOjlDXvtrVFSUypQpowYNGuizzz6TMcZhekHrm56ers8//1zdunWTi4tLnn1TU1NVsWJFhYaGqk2bNtq5c6c1rbCvyfWQUz1jYmKUmZmp33//XdWrV1f58uXVvn17HTlyxKFfTp9Tl1u0aJHCw8MVFRWloKAg3XHHHXrvvfd08eLFXOf55ptvVKlSJS1evFhhYWG69dZb9eyzzyopKcmh37Rp0/Trr78qOjq6EFt+beTn/9OZM2fK29tbjz/+uEN7fvfP+Ph4hYSEqFKlSurcubMOHz5coDFOnTpVHTt2VIkSJSRJmZmZWrJkiapUqaLIyEgFBgaqYcOGWrhwYYGWey3kVM+qVauqdOnSmjp1qtLT03Xu3DlNnTpV1atX16233mr1y8/+KUlDhgxRYGCgunfvXqgxZmZm6vTp09Zn+YULF3Tx4sUcv2tdy8/y/Mipnvn9XpjfemYxxmjFihXau3evmjZtmmffovheLgwCWRF16NAhhYSEFHr+kJAQHTp0yHperlw5VahQId/z//nnnxo6dKh69OhhtUVGRuqnn37SF198oYsXL+r333/XkCFDJEnHjh3LdVlz585VRkaGSpcuLQ8PD/Xs2VMLFizQ7bffLkm67777lJiYqFGjRik9PV0nT55U3759r7jcwshPXX/66SfNmTPHYdslydvbW35+fg51LYxx48apRo0aKl++vNzd3fXAAw9owoQJV/xP51JvvfWWQkJCrC9p1apVU4UKFdSvXz+dPHlS6enpGjFihH777Ten1/BSedXziSeekLe3t2655Rb5+vpqypQpDtOdVU9JWrx4sXx8fOTp6akxY8YoJiZGZcqUyXOe7du3y8fHRx4eHnr++ee1YMEC1ahRw5p+pf32WsipnmlpaXriiSc0atSoPN/DzqhnYmKiJCkoKMihPSgoyJqWk759+6pjx46qVq2aihcvrjvvvFO9e/dW586dHfoV5nVyptz21yFDhmju3LmKiYlRu3bt9OKLL2rcuHEOfQpa34ULF+rUqVPq2rVrnv2qVq2qzz77TF9//bU+//xzZWZm6u6779Zvv/0mqfCvyfWQUz1//fVXZWZm6r333tOHH36or776SklJSbr//vuVnp7u0Pfyz6nL/frrr/rqq6908eJFffvttxowYIBGjx6td955J895Dh06pHnz5mnmzJmaPn26Nm/e7BBg4uPj1bdvX33++efWHxyLgvx8Pk2dOlWdOnWy/miZJT/7Z8OGDTV9+nQtXbpUH3/8sRISEtSkSROdPn06X+PbsGGDduzYoWeffdZqO3HihFJTUzV8+HA98MADWrZsmR599FE99thjWrNmTb6We63kVM+SJUtq9erV+vzzz+Xl5SUfHx8tXbpU3333XbZ94Ur757p16zR16lR9+umnhR7j+++/r9TUVLVv394aX3h4uIYOHaqjR4/q4sWL+vzzzxUbG3tNP8vzI6d6FuR74ZXqKf39x3AfHx+5u7urdevWGjdunO6///5c+xfV93JhEMiKqHPnzmX7q0NBeHl56ezZs9bzYcOGaebMmfmaNyUlRa1bt1aNGjU0aNAgq71ly5YaNWqUnn/+eXl4eKhKlSpq1aqVJOX6V3tJGjBggE6dOqXly5dr06ZN6tOnj9q3b6/t27dLkmrWrKkZM2Zo9OjR8vb2VnBwsMLCwhQUFJTncgvjSnXdsWOH2rRpo+jo6ByPWF1e18IYN26cfv75Zy1atEibN2/W6NGjFRUVpeXLl+dr/uHDh+vLL7/UggULrG0pXry45s+fr3379ikgIEDe3t5atWqVHnzwQafX8FJ51XPMmDHasmWLvv76ax04cEB9+vTJ1scZ9ZSk5s2bKy4uTj/99JMeeOABtW/fXidOnMhznqpVqyouLk7r16/XCy+8oC5dumjXrl3W9Cvtt9dCTvXs16+fqlevrieffPKK8zurngU1d+5czZo1S7Nnz9aWLVs0Y8YMvf/++5oxY4ZDv8K8Ts6U2/46YMAANW7cWHfeeafeeustvfnmmxo1alS2fgWp79SpU/Xggw9e8Qt2eHi4nn76adWpU0fNmjXT/PnzVbZsWX3yySf52ygb5VTPzMxMZWRkaOzYsYqMjFSjRo30xRdfKD4+XqtWrXLoe6V6ZmZmKjAwUJMnT1a9evXUoUMH9e/fX5MmTcpznrS0NM2cOVNNmjTRvffeq6lTp2rVqlXau3evLl68qE6dOmnw4MGqUqXK1RXAya70+RQbG6vdu3fnejTmSvV88MEH9e9//1v/+te/FBkZqW+//VanTp3S3Llz8zW+qVOnqlatWmrQoIHVlnXlvDZt2ujVV19VnTp11LdvXz300EN5vk7XQ071PHfunLp3767GjRvr559/1o8//qg77rhDrVu31rlz5xz65lXP06dP66mnntKnn35a6D8qzZ49W4MHD9bcuXMVGBhotf/3v/+VMUa33HKLPDw8NHbsWD3xxBPX9LM8P3KqZ0G+F+bn/8+SJUsqLi5OGzdu1Lvvvqs+ffpo9erVOfYtyu/lQrH3jEnkplOnTtkugnCpK50nW61aNYffHORXSkqKCQ8PNy1atMj1B+OZmZnm999/N2fPnjW7du0yknK9AtD+/fuz/bbJGGNatGhhevbsma1/YmKiOX36tElNTTWurq5m7ty5Bd6GvORV1507d5rAwEDzn//8J9f5PT09zbx58/K1LuVwrvLZs2dN8eLFs50f3r17dxMZGXnFZY4aNcr4+fmZjRs35trn1KlT1oUSGjRokOcV3q7WlfbTLD/88IORZI4ePerQfrX1zM3tt99u3nvvvXz1zdKiRQvTo0cPY0zB91tnyametWvXNq6urqZYsWKmWLFixtXV1UgyxYoVMwMHDnToe7X1PHDggJFktm7d6tDetGlT8/LLL+e6rPLly5vx48c7tA0dOvSKV3ArzOt0NfK7vy5evNhIMufPn3doz299Dx48aFxdXc3ChQsLNc7HH3/cdOzY0RhT+Nfkesipnp999pmRZI4cOeLQHhgYaCZPnuzQdqXPqaZNm5oWLVo4tH377bdGkklLS8txnoEDBxo3NzeHtrNnzxpJZtmyZebkyZPW+yfr4eLiYrWtWLHiitt9rVxp/+zWrZupU6dOrtML8v7PUr9+fdO3b98r9ktNTTW+vr45XoHYzc3NDB061KH9zTffNHfffXeBxuJsOdVzypQp2X6znpaWZry9vbP9JjOv/XPr1q057kcuLi6mWLFiV/yt1BdffGG8vLyyfRe4VGpqqvWZ2b59+2xXtrze8to/8/O9sDDfS7t3725atmyZ47TCvJcL8j3ieuMIWRF15513Ovy1viDOnz+vAwcO6M477yzQfCkpKWrZsqXc3d21aNGiXP9S5+LiopCQEHl5eemLL75QaGio6tatm2PfrL+GXP6XkmLFiuV4T4qgoCD5+Phozpw58vT0zPNQdWHkVtedO3eqefPm6tKli959990c5z1w4IDOnz9f4LpeKiMjQxkZGfmux6VGjhypoUOHaunSpapfv36u/fz8/FS2bFnFx8dr06ZNatOmTaHHeyX53U+zti3rt26Sc+qZ1/ouXVdB5ynofussOdXzf//7n3755RfFxcUpLi7OOvXzhx9+UFRUlNXPGfUMCwtTcHCwVqxYYbWlpKRo/fr1Dr+vu9zZs2cLVavCvE5XI7/7a1xcnEqVKiUPDw+rrSD1nTZtmgIDA9W6desCj/HixYvavn27ypUrJ6nwr8n1kFM9GzduLEnau3ev1ZaUlKQ///xTFStWtNry8znVuHFj7d+/32E/2rdvn8qVKyd3d/dc57lw4YIOHDjgMI8kVaxYUb6+vtq+fbv1foqLi9Pzzz9vHTFv2LBhASrgXHntn6mpqZo7d26uR8cK8/5PTU3VgQMHrH0tL/PmzVNaWlq2I/Xu7u666667HF5v6e+aX/p62yGnemb9X3Xp7zqznl+6n11p/6xWrVq2/eiRRx6xzgIIDQ3NdVxffPGFnnnmGX3xxRd5/h9RokQJlStXTidPntT3339/TT/L8yOv/fNK3wsL+700r8+IovxeLhS7EyFytm3bNuPm5maSkpIc2uPj483WrVtNz549TZUqVczWrVvN1q1bHf5auGrVKuPj42POnDljtfXt29c89dRTua4vOTnZNGzY0NSqVcvs37/f4TK3Fy5csPqNHDnSbNu2zezYscMMGTLEFC9e3OGvDb/99pupWrWqdY+s9PR0c/vtt5smTZqY9evXm/3795v333/fuLi4ONxLZty4cWbz5s1m7969Zvz48cbLy8vhktnOklNdt2/fbsqWLWuefPJJh+2+/HLc06ZNM5UqVcpz+adPn7ZeE0nmgw8+MFu3bnW4H0uzZs1MzZo1zapVq8yvv/5qpk2bZjw9Pc3EiROtPk899ZTDXy2HDx9u3N3dzVdffeUwxkvv1TZ37lyzatUqc+DAAbNw4UJTsWJF89hjjxW6VvmRUz2XLFliPvvsM7N9+3aTkJBgFi9ebKpXr24aN27sMK8z6pmammr69etnYmNjzcGDB82mTZvMM888Yzw8PByObt13330OtzHo27evWbNmjUlISDDbtm0zffv2NS4uLtalsfO73zpbbu/7S61atSrHqyw6a/8cPny48ff3N19//bXZtm2badOmTbZLrF9ezy5duphbbrnFuuz9/PnzTZkyZcybb75pjMn/63St5VTfRYsWmU8//dRs377dxMfHm4kTJxpvb+9sRx/zU19j/r66aYUKFcxbb72V4/TL39uDBw8233//vTlw4IDZvHmz6dixo/H09DQ7d+60+uTnNbFDbvtrmzZtTM2aNc2PP/5otm/fbh566CFTo0YNh6sl5vQ5dbnDhw+bkiVLml69epm9e/eaxYsXm8DAQId7io0bN87cd9991vOLFy+aunXrmqZNm5otW7aYTZs2mYYNG5r7778/1/UUlass5vX+nzJlivH09Mz2vs+Sn/3ztddeM6tXrzYJCQnmxx9/tO6Hdeln3eX7Z5Z77rnHdOjQIcflzp8/3xQvXtxMnjzZxMfHm3HjxplixYqZH374Ic/xXGs51XP37t3Gw8PDvPDCC2bXrl1mx44d5sknnzR+fn4OZ3DkZ/+8XE5XWbz8u9esWbOMm5ubmTBhgsNn+aX3fF26dKn57rvvzK+//mqWLVtmateubRo2bFigq41eC7ntn1f6XmhM/ur53nvvmWXLlpkDBw6YXbt2mffff9+4ubk5XNn4St9lc3ov5+dzryggkBVhDRo0MJMmTXJoy+0mjQkJCVafHj16ZDutqkuXLtnuW3KprC95V1p28+bNjZ+fn/H09DQNGzbMdjPdhISEbPfd2bdvn3nsscdMYGCg8fb2Nv/617+yXbL3qaeeMgEBAcbd3T3H6c50eV1zulmmJFOxYkWH+Vq2bGmGDRuW57Jzq2OXLl2sPseOHTNdu3Y1ISEhxtPT01StWtWMHj3a4dLYzZo1c5gntxvORkdHW32yLi1fvHhxU6FCBfP222/nelqPM11ez5UrV5rw8HBrP6lcubJ56623sn2RcEY9z507Zx599FETEhJi3N3dTbly5cwjjzyS7VSJihUrOtSqW7dupmLFisbd3d2ULVvWtGjRItt9ivKz314LOb3vL5VbIHPW/pl1E+KgoCDj4eFhWrRoYfbu3euwnMvrefmNTCtVqmT69+9v7X/5fZ2uh8vr+91335k6deoYHx8fU6JECVO7dm0zadIkh1OajMlffY0x5vvvvzeSstUsy+Xv7d69e5sKFSoYd3d3ExQUZFq1apXtXnf5eU3sktP+mpycbLp162b8/f1NQECAefTRRx0uM25Mzp9TOfnpp59Mw4YNjYeHh6lUqZJ59913Hf5IGB0dne3/6t9//9089thj1o1qu3btav76669c11FUApkxub//w8PDTadOnXKdLz/7Z4cOHUy5cuWMu7u7ueWWW0yHDh2ynVp3+f5pjDF79uyxTvnMzdSpU83tt99uPD09Te3atQt9uq6z5VTPZcuWmcaNGxs/Pz9TqlQpc99992W7l15+989L5RTILv/uldt3uEtrPmfOHFOpUiXj7u5ugoODTVRUlENgs1NO9bzS90Jj8lfP/v37W/tQqVKlTHh4uPnyyy8d+lzpu2xO7+X8fO4VBQSyIizryMLlXwzy8scff5iAgADz66+/XsOR/bMVpq47duwwgYGBReY/xaKEejoX9by2qK9z8TnlXOyfzsX+6VzU89r5Z18j8gbXunVrxcfH6/fff8/zfORLHTx4UBMnTlRYWNg1Ht0/V2HqeuzYMc2cOVN+fn7XeHT/PNTTuajntUV9nYvPKedi/3Qu9k/nop7Xjosxl939EgAAAABwXXCVRQAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAC6xYMECzZ071+5hAABuEgQyAAD+z4YNG9S7d281atTI7qEAAG4SBDIAwA2ra9eucnFx0fDhwx3aFy5cKBcXF4e25ORkPfvss1qwYIEqVKhwPYcJALiJEcgAADc0T09PjRgxQidPnsyzn5+fn7Zt26a6detep5Fll56ebtu6AQD2IJABAG5oERERCg4O1rBhw3KcPmjQINWpU8eh7cMPP9Stt95qPe/atavatm2r9957T0FBQfL399eQIUN04cIFvfHGGwoICFD58uU1bdo0h+UcOXJE7du3l7+/vwICAtSmTRsdPHgw23LfffddhYSEqGrVqpKk7du367777pOXl5dKly6tHj16KDU11Zpv9erVatCggUqUKCF/f381btxYhw4durpCAQBsQSADANzQihUrpvfee0/jxo3Tb7/9VujlrFy5UkePHtXatWv1wQcfKDo6Wg899JBKlSql9evX6/nnn1fPnj2tdWRkZCgyMlIlS5bUDz/8oB9//FE+Pj564IEHHI6ErVixQnv37lVMTIwWL16sM2fOKDIyUqVKldLGjRs1b948LV++XL169ZIkXbhwQW3btlWzZs20bds2xcbGqkePHtlOwQQA/DO42T0AAACutUcffVR16tRRdHS0pk6dWqhlBAQEaOzYsXJ1dVXVqlU1cuRInT17Vv/5z38kSf369dPw4cO1bt06dezYUXPmzFFmZqamTJlihaVp06bJ399fq1evVsuWLSVJJUqU0JQpU+Tu7i5J+vTTT3X+/HnNnDlTJUqUkCSNHz9eDz/8sEaMGKHixYsrOTlZDz30kG677TZJUvXq1a+qPgAA+3CEDABwUxgxYoRmzJih3bt3F2r+mjVrytX1/39sBgUFqVatWtbzYsWKqXTp0jpx4oQk6ZdfftH+/ftVsmRJ+fj4yMfHRwEBATp//rwOHDhgzVerVi0rjEnS7t27Vbt2bSuMSVLjxo2VmZmpvXv3KiAgQF27dlVkZKQefvhhffTRRzp27FihtgkAYD8CGQDgptC0aVNFRkaqX79+Du2urq4yxji0ZWRkZJu/ePHiDs9dXFxybMvMzJQkpaamql69eoqLi3N47Nu3T506dbLmuTR45de0adMUGxuru+++W3PmzFGVKlX0888/F3g5AAD7ccoiAOCmMXz4cNWpU8e6eIYklS1bVomJiTLGWKcWxsXFXfW66tatqzlz5igwMFC+vr75nq969eqaPn26zpw5Y4W1H3/80TpVMsudd96pO++8U/369VN4eLhmz57N/dMA4B+II2QAgJtGrVq11LlzZ40dO9Zqu/fee/XHH39o5MiROnDggCZMmKDvvvvuqtfVuXNnlSlTRm3atNEPP/yghIQErV69Wi+//HKeFxfp3LmzPD091aVLF+3YsUOrVq3SSy+9pKeeekpBQUFKSEhQv379FBsbq0OHDmnZsmWKj4/nd2QA8A9FIAMA3FSGDBlinVYo/X1EauLEiZowYYJq166tDRs26PXXX7/q9Xh7e2vt2rWqUKGCHnvsMVWvXl3du3fX+fPn8zxi5u3tre+//15JSUm666679Pjjj6tFixYaP368NX3Pnj1q166dqlSpoh49eigqKko9e/a86jEDAK4/F3P5ifMAAAAAgOuCI2QAAAAAYBMCGQAAAADYhEAGAAAAADYhkAEAAACATQhkAAAAAGATAhkAAAAA2IRABgAAAAA2IZABAAAAgE0IZAAAAABgEwIZAAAAANiEQAYAAAAANvl/GWnyAQb/1oQAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(df_pop_municipios[1].size)\n",
        "print(df_pop_municipios[2].size)\n",
        "print(df_pop_municipios[3].size)\n",
        "print(df_pop_municipios[4].size)\n",
        "print(df_pop_municipios[5].size)\n",
        "print(df_pop_municipios[6].size)\n",
        "print(df_pop_municipios[7].size)\n",
        "print(df_pop_municipios[8].size)\n",
        "print(df_pop_municipios[9].size)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8xneQ-dlRpfx",
        "outputId": "a1725c55-56da-4c32-b862-b98c0ec3da1b"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "13320\n",
            "8152\n",
            "5960\n",
            "4824\n",
            "3344\n",
            "2960\n",
            "2568\n",
            "1912\n",
            "1520\n"
          ]
        }
      ]
    }
  ]
}