Bilhetagem_Eletrônica-2019-Analitico.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Datasets Portal da Transparência da Mobilidade Urbana de Natal/RN\n",
    "\n",
    "## Dataset Bilhetagem Eletrônica Analítico 2019\n",
    "\n",
    "http://dados.natal.br/dataset/bilhetagem-eletronica\n",
    "\n",
    "Dados BE 2019 - Analitico\n",
    "http://dados.natal.br/dataset/4fad551d-4d3b-4597-b8d3-7e887e22332e/resource/0d4a0f0f-b8a5-46a0-acfe-bb9138c8eb9e/download/dados-be-2019-analitico.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Download do arquivo csv\n",
    "Vamos baixar o arquivo de 2018 com o comando wget\n",
    "comando abaixo esta comentando em função do Windows 10 não possuir o comando."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#wget -c http://dados.natal.br/dataset/4fad551d-4d3b-4597-b8d3-7e887e22332e/resource/0d4a0f0f-b8a5-46a0-acfe-bb9138c8eb9e/download/dados-be-2019-analitico.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Verificar o arquivo baixado com o comando\n",
    "*ls -lah dados-be**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ls -lah dados-be*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Carregar o arquivo CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"data\\dados-be-2019-analitico.csv\", encoding='iso-8859-1', sep=';', thousands=r'.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Checar se o arquivo foi carregado exibindo os primeiros registros"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mês</th>\n",
       "      <th>Empresa</th>\n",
       "      <th>Linha</th>\n",
       "      <th>Estudante_Cartao</th>\n",
       "      <th>Estudante_BT</th>\n",
       "      <th>Vale_Transporte</th>\n",
       "      <th>Integracao_Plena</th>\n",
       "      <th>Integracao_Complementar</th>\n",
       "      <th>Gratuito_Cartao</th>\n",
       "      <th>Gratuito_BT</th>\n",
       "      <th>Inteira_Cartao</th>\n",
       "      <th>Inteira_Especie</th>\n",
       "      <th>Tarifa_Social</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>CONCEIÇÃO</td>\n",
       "      <td>21</td>\n",
       "      <td>14433</td>\n",
       "      <td>4640</td>\n",
       "      <td>36604</td>\n",
       "      <td>8347</td>\n",
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       "      <td>3401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>CONCEIÇÃO</td>\n",
       "      <td>22</td>\n",
       "      <td>2099</td>\n",
       "      <td>842</td>\n",
       "      <td>5175</td>\n",
       "      <td>1006</td>\n",
       "      <td>0</td>\n",
       "      <td>3730</td>\n",
       "      <td>1788</td>\n",
       "      <td>1032</td>\n",
       "      <td>7345</td>\n",
       "      <td>0</td>\n",
       "      <td>643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>CONCEIÇÃO</td>\n",
       "      <td>30</td>\n",
       "      <td>10095</td>\n",
       "      <td>2912</td>\n",
       "      <td>21823</td>\n",
       "      <td>5746</td>\n",
       "      <td>0</td>\n",
       "      <td>6975</td>\n",
       "      <td>3403</td>\n",
       "      <td>5200</td>\n",
       "      <td>21659</td>\n",
       "      <td>858</td>\n",
       "      <td>2356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>CONCEIÇÃO</td>\n",
       "      <td>31</td>\n",
       "      <td>10282</td>\n",
       "      <td>3142</td>\n",
       "      <td>22424</td>\n",
       "      <td>7351</td>\n",
       "      <td>0</td>\n",
       "      <td>6589</td>\n",
       "      <td>3202</td>\n",
       "      <td>5132</td>\n",
       "      <td>23757</td>\n",
       "      <td>64</td>\n",
       "      <td>2264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>CONCEIÇÃO</td>\n",
       "      <td>41</td>\n",
       "      <td>7218</td>\n",
       "      <td>1673</td>\n",
       "      <td>18788</td>\n",
       "      <td>7473</td>\n",
       "      <td>0</td>\n",
       "      <td>5229</td>\n",
       "      <td>3065</td>\n",
       "      <td>4256</td>\n",
       "      <td>13547</td>\n",
       "      <td>0</td>\n",
       "      <td>2164</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   Mês    Empresa  Linha  Estudante_Cartao  Estudante_BT  Vale_Transporte  \\\n",
       "0    1  CONCEIÇÃO     21             14433          4640            36604   \n",
       "1    1  CONCEIÇÃO     22              2099           842             5175   \n",
       "2    1  CONCEIÇÃO     30             10095          2912            21823   \n",
       "3    1  CONCEIÇÃO     31             10282          3142            22424   \n",
       "4    1  CONCEIÇÃO     41              7218          1673            18788   \n",
       "\n",
       "   Integracao_Plena  Integracao_Complementar  Gratuito_Cartao  Gratuito_BT  \\\n",
       "0              8347                        0            16427         8330   \n",
       "1              1006                        0             3730         1788   \n",
       "2              5746                        0             6975         3403   \n",
       "3              7351                        0             6589         3202   \n",
       "4              7473                        0             5229         3065   \n",
       "\n",
       "   Inteira_Cartao  Inteira_Especie  Tarifa_Social  Qtd_Viagens  \n",
       "0            6260            41213           3119         3401  \n",
       "1            1032             7345              0          643  \n",
       "2            5200            21659            858         2356  \n",
       "3            5132            23757             64         2264  \n",
       "4            4256            13547              0         2164  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Exibir 10 registros aleatórios"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mês</th>\n",
       "      <th>Empresa</th>\n",
       "      <th>Linha</th>\n",
       "      <th>Estudante_Cartao</th>\n",
       "      <th>Estudante_BT</th>\n",
       "      <th>Vale_Transporte</th>\n",
       "      <th>Integracao_Plena</th>\n",
       "      <th>Integracao_Complementar</th>\n",
       "      <th>Gratuito_Cartao</th>\n",
       "      <th>Gratuito_BT</th>\n",
       "      <th>Inteira_Cartao</th>\n",
       "      <th>Inteira_Especie</th>\n",
       "      <th>Tarifa_Social</th>\n",
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       "  </thead>\n",
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       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1</td>\n",
       "      <td>DUNAS - URB</td>\n",
       "      <td>57</td>\n",
       "      <td>1003</td>\n",
       "      <td>251</td>\n",
       "      <td>1654</td>\n",
       "      <td>700</td>\n",
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       "      <td>384</td>\n",
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       "      <td>347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>1</td>\n",
       "      <td>GUANABARA - URB</td>\n",
       "      <td>593</td>\n",
       "      <td>2772</td>\n",
       "      <td>466</td>\n",
       "      <td>2524</td>\n",
       "      <td>683</td>\n",
       "      <td>0</td>\n",
       "      <td>988</td>\n",
       "      <td>424</td>\n",
       "      <td>593</td>\n",
       "      <td>2989</td>\n",
       "      <td>170</td>\n",
       "      <td>968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>2</td>\n",
       "      <td>CONCEIÇÃO</td>\n",
       "      <td>63</td>\n",
       "      <td>40701</td>\n",
       "      <td>9842</td>\n",
       "      <td>43915</td>\n",
       "      <td>20553</td>\n",
       "      <td>0</td>\n",
       "      <td>15472</td>\n",
       "      <td>6381</td>\n",
       "      <td>7950</td>\n",
       "      <td>40626</td>\n",
       "      <td>0</td>\n",
       "      <td>3636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>1</td>\n",
       "      <td>SANTA MARIA - URB</td>\n",
       "      <td>34</td>\n",
       "      <td>4761</td>\n",
       "      <td>1418</td>\n",
       "      <td>8867</td>\n",
       "      <td>2383</td>\n",
       "      <td>0</td>\n",
       "      <td>7476</td>\n",
       "      <td>4569</td>\n",
       "      <td>2233</td>\n",
       "      <td>12728</td>\n",
       "      <td>0</td>\n",
       "      <td>1530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>CONCEIÇÃO</td>\n",
       "      <td>71</td>\n",
       "      <td>10033</td>\n",
       "      <td>3718</td>\n",
       "      <td>24365</td>\n",
       "      <td>4570</td>\n",
       "      <td>0</td>\n",
       "      <td>14472</td>\n",
       "      <td>6197</td>\n",
       "      <td>4788</td>\n",
       "      <td>31456</td>\n",
       "      <td>3354</td>\n",
       "      <td>2925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>1</td>\n",
       "      <td>REUNIDAS</td>\n",
       "      <td>26</td>\n",
       "      <td>16291</td>\n",
       "      <td>5699</td>\n",
       "      <td>50106</td>\n",
       "      <td>12882</td>\n",
       "      <td>250</td>\n",
       "      <td>7235</td>\n",
       "      <td>4809</td>\n",
       "      <td>8498</td>\n",
       "      <td>42178</td>\n",
       "      <td>4320</td>\n",
       "      <td>3209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>1</td>\n",
       "      <td>GUANABARA - URB</td>\n",
       "      <td>76</td>\n",
       "      <td>2825</td>\n",
       "      <td>861</td>\n",
       "      <td>7002</td>\n",
       "      <td>1448</td>\n",
       "      <td>42</td>\n",
       "      <td>3279</td>\n",
       "      <td>1016</td>\n",
       "      <td>1404</td>\n",
       "      <td>8065</td>\n",
       "      <td>337</td>\n",
       "      <td>605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>1</td>\n",
       "      <td>REUNIDAS</td>\n",
       "      <td>27</td>\n",
       "      <td>10410</td>\n",
       "      <td>3112</td>\n",
       "      <td>23687</td>\n",
       "      <td>3513</td>\n",
       "      <td>111</td>\n",
       "      <td>9888</td>\n",
       "      <td>5329</td>\n",
       "      <td>5152</td>\n",
       "      <td>30294</td>\n",
       "      <td>3061</td>\n",
       "      <td>2948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>2</td>\n",
       "      <td>CONCEIÇÃO</td>\n",
       "      <td>7601</td>\n",
       "      <td>102</td>\n",
       "      <td>37</td>\n",
       "      <td>243</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>149</td>\n",
       "      <td>68</td>\n",
       "      <td>43</td>\n",
       "      <td>367</td>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>2</td>\n",
       "      <td>REUNIDAS</td>\n",
       "      <td>7847</td>\n",
       "      <td>19359</td>\n",
       "      <td>5983</td>\n",
       "      <td>29761</td>\n",
       "      <td>5649</td>\n",
       "      <td>57</td>\n",
       "      <td>9668</td>\n",
       "      <td>5201</td>\n",
       "      <td>8080</td>\n",
       "      <td>33094</td>\n",
       "      <td>0</td>\n",
       "      <td>2277</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "     Mês            Empresa  Linha  Estudante_Cartao  Estudante_BT  \\\n",
       "21     1        DUNAS - URB     57              1003           251   \n",
       "48     1    GUANABARA - URB    593              2772           466   \n",
       "100    2          CONCEIÇÃO     63             40701          9842   \n",
       "74     1  SANTA MARIA - URB     34              4761          1418   \n",
       "7      1          CONCEIÇÃO     71             10033          3718   \n",
       "62     1           REUNIDAS     26             16291          5699   \n",
       "40     1    GUANABARA - URB     76              2825           861   \n",
       "63     1           REUNIDAS     27             10410          3112   \n",
       "112    2          CONCEIÇÃO   7601               102            37   \n",
       "166    2           REUNIDAS   7847             19359          5983   \n",
       "\n",
       "     Vale_Transporte  Integracao_Plena  Integracao_Complementar  \\\n",
       "21              1654               700                        0   \n",
       "48              2524               683                        0   \n",
       "100            43915             20553                        0   \n",
       "74              8867              2383                        0   \n",
       "7              24365              4570                        0   \n",
       "62             50106             12882                      250   \n",
       "40              7002              1448                       42   \n",
       "63             23687              3513                      111   \n",
       "112              243                54                        0   \n",
       "166            29761              5649                       57   \n",
       "\n",
       "     Gratuito_Cartao  Gratuito_BT  Inteira_Cartao  Inteira_Especie  \\\n",
       "21               894          384             467             1648   \n",
       "48               988          424             593             2989   \n",
       "100            15472         6381            7950            40626   \n",
       "74              7476         4569            2233            12728   \n",
       "7              14472         6197            4788            31456   \n",
       "62              7235         4809            8498            42178   \n",
       "40              3279         1016            1404             8065   \n",
       "63              9888         5329            5152            30294   \n",
       "112              149           68              43              367   \n",
       "166             9668         5201            8080            33094   \n",
       "\n",
       "     Tarifa_Social  Qtd_Viagens  \n",
       "21               0          347  \n",
       "48             170          968  \n",
       "100              0         3636  \n",
       "74               0         1530  \n",
       "7             3354         2925  \n",
       "62            4320         3209  \n",
       "40             337          605  \n",
       "63            3061         2948  \n",
       "112              0           41  \n",
       "166              0         2277  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizar o descritivo da estrtura de dados com o número de linhas e colunas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(189, 14)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizar informações básicas do dataset como colunas, tamanho, tipo de valores, etc.."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 189 entries, 0 to 188\n",
      "Data columns (total 14 columns):\n",
      "Mês                        189 non-null int64\n",
      "Empresa                    189 non-null object\n",
      "Linha                      189 non-null int64\n",
      "Estudante_Cartao           189 non-null int64\n",
      "Estudante_BT               189 non-null int64\n",
      "Vale_Transporte            189 non-null int64\n",
      "Integracao_Plena           189 non-null int64\n",
      "Integracao_Complementar    189 non-null int64\n",
      "Gratuito_Cartao            189 non-null int64\n",
      "Gratuito_BT                189 non-null int64\n",
      "Inteira_Cartao             189 non-null int64\n",
      "Inteira_Especie            189 non-null int64\n",
      "Tarifa_Social              189 non-null int64\n",
      "Qtd_Viagens                189 non-null int64\n",
      "dtypes: int64(13), object(1)\n",
      "memory usage: 20.8+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exibir informações estatísticas das colunas numéricas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>Mês</th>\n",
       "      <th>Linha</th>\n",
       "      <th>Estudante_Cartao</th>\n",
       "      <th>Estudante_BT</th>\n",
       "      <th>Vale_Transporte</th>\n",
       "      <th>Integracao_Plena</th>\n",
       "      <th>Integracao_Complementar</th>\n",
       "      <th>Gratuito_Cartao</th>\n",
       "      <th>Gratuito_BT</th>\n",
       "      <th>Inteira_Cartao</th>\n",
       "      <th>Inteira_Especie</th>\n",
       "      <th>Tarifa_Social</th>\n",
       "      <th>Qtd_Viagens</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>189.000000</td>\n",
       "      <td>189.000000</td>\n",
       "      <td>189.000000</td>\n",
       "      <td>189.000000</td>\n",
       "      <td>189.000000</td>\n",
       "      <td>189.000000</td>\n",
       "      <td>189.000000</td>\n",
       "      <td>189.000000</td>\n",
       "      <td>189.000000</td>\n",
       "      <td>189.000000</td>\n",
       "      <td>189.000000</td>\n",
       "      <td>189.000000</td>\n",
       "      <td>189.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.502646</td>\n",
       "      <td>1095.338624</td>\n",
       "      <td>10124.253968</td>\n",
       "      <td>3087.497354</td>\n",
       "      <td>20140.910053</td>\n",
       "      <td>5341.021164</td>\n",
       "      <td>67.634921</td>\n",
       "      <td>6653.238095</td>\n",
       "      <td>3498.375661</td>\n",
       "      <td>4273.582011</td>\n",
       "      <td>20416.206349</td>\n",
       "      <td>712.534392</td>\n",
       "      <td>1827.703704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.501321</td>\n",
       "      <td>2229.940501</td>\n",
       "      <td>9284.993264</td>\n",
       "      <td>2935.074385</td>\n",
       "      <td>18595.009652</td>\n",
       "      <td>5456.010165</td>\n",
       "      <td>149.063420</td>\n",
       "      <td>5867.607666</td>\n",
       "      <td>3098.381922</td>\n",
       "      <td>3624.894456</td>\n",
       "      <td>17619.509801</td>\n",
       "      <td>1377.640650</td>\n",
       "      <td>1235.652777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>3105.000000</td>\n",
       "      <td>861.000000</td>\n",
       "      <td>5533.000000</td>\n",
       "      <td>1228.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2192.000000</td>\n",
       "      <td>985.000000</td>\n",
       "      <td>1278.000000</td>\n",
       "      <td>7031.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>737.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>7246.000000</td>\n",
       "      <td>2226.000000</td>\n",
       "      <td>15226.000000</td>\n",
       "      <td>3512.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5253.000000</td>\n",
       "      <td>2800.000000</td>\n",
       "      <td>3437.000000</td>\n",
       "      <td>16665.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1675.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>599.000000</td>\n",
       "      <td>14718.000000</td>\n",
       "      <td>4518.000000</td>\n",
       "      <td>30168.000000</td>\n",
       "      <td>8241.000000</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>9483.000000</td>\n",
       "      <td>5201.000000</td>\n",
       "      <td>6334.000000</td>\n",
       "      <td>29753.000000</td>\n",
       "      <td>776.000000</td>\n",
       "      <td>2796.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>9018.000000</td>\n",
       "      <td>48043.000000</td>\n",
       "      <td>17162.000000</td>\n",
       "      <td>109827.000000</td>\n",
       "      <td>29590.000000</td>\n",
       "      <td>963.000000</td>\n",
       "      <td>31929.000000</td>\n",
       "      <td>16846.000000</td>\n",
       "      <td>17130.000000</td>\n",
       "      <td>88472.000000</td>\n",
       "      <td>8935.000000</td>\n",
       "      <td>5315.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Mês        Linha  Estudante_Cartao  Estudante_BT  \\\n",
       "count  189.000000   189.000000        189.000000    189.000000   \n",
       "mean     1.502646  1095.338624      10124.253968   3087.497354   \n",
       "std      0.501321  2229.940501       9284.993264   2935.074385   \n",
       "min      1.000000     2.000000          0.000000      0.000000   \n",
       "25%      1.000000    39.000000       3105.000000    861.000000   \n",
       "50%      2.000000    73.000000       7246.000000   2226.000000   \n",
       "75%      2.000000   599.000000      14718.000000   4518.000000   \n",
       "max      2.000000  9018.000000      48043.000000  17162.000000   \n",
       "\n",
       "       Vale_Transporte  Integracao_Plena  Integracao_Complementar  \\\n",
       "count       189.000000        189.000000               189.000000   \n",
       "mean      20140.910053       5341.021164                67.634921   \n",
       "std       18595.009652       5456.010165               149.063420   \n",
       "min           0.000000          0.000000                 0.000000   \n",
       "25%        5533.000000       1228.000000                 0.000000   \n",
       "50%       15226.000000       3512.000000                 0.000000   \n",
       "75%       30168.000000       8241.000000                54.000000   \n",
       "max      109827.000000      29590.000000               963.000000   \n",
       "\n",
       "       Gratuito_Cartao   Gratuito_BT  Inteira_Cartao  Inteira_Especie  \\\n",
       "count       189.000000    189.000000      189.000000       189.000000   \n",
       "mean       6653.238095   3498.375661     4273.582011     20416.206349   \n",
       "std        5867.607666   3098.381922     3624.894456     17619.509801   \n",
       "min           0.000000      0.000000        0.000000         0.000000   \n",
       "25%        2192.000000    985.000000     1278.000000      7031.000000   \n",
       "50%        5253.000000   2800.000000     3437.000000     16665.000000   \n",
       "75%        9483.000000   5201.000000     6334.000000     29753.000000   \n",
       "max       31929.000000  16846.000000    17130.000000     88472.000000   \n",
       "\n",
       "       Tarifa_Social  Qtd_Viagens  \n",
       "count     189.000000   189.000000  \n",
       "mean      712.534392  1827.703704  \n",
       "std      1377.640650  1235.652777  \n",
       "min         0.000000     1.000000  \n",
       "25%         0.000000   737.000000  \n",
       "50%         0.000000  1675.000000  \n",
       "75%       776.000000  2796.000000  \n",
       "max      8935.000000  5315.000000  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calcular Quantidade de Passageiros"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Qtd_Passageiros'] = df.Estudante_Cartao + df.Estudante_BT + df.Vale_Transporte + df.Integracao_Plena + df.Integracao_Complementar + df.Gratuito_Cartao + df.Gratuito_BT + df.Inteira_Cartao + df.Inteira_Especie + df.Tarifa_Social"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exibir a quantidade de empresas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "empresas = df['Empresa'].unique()\n",
    "len(empresas)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['CONCEIÇÃO' 'DUNAS - URB' 'GUANABARA - URB' 'REUNIDAS'\n",
      " 'SANTA MARIA - URB' 'VIA SUL - URB']\n"
     ]
    }
   ],
   "source": [
    "print(df.Empresa.unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exibir a quantidade de linhas de ônibus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "84"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "linhas = df['Linha'].unique()\n",
    "len(linhas)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[  21   22   30   31   41   59   63   71   76   83  411  587  599  905\n",
      " 2369 3001 3101 6301 7601   33   40   57  331  332    2    4    5    8\n",
      "   13   18   19   20   25   60   64   67   70   72   75   77   79   81\n",
      "   84  101  102  592  593 1029 1214 1301 1302 1516 1778 6162 6443 7501\n",
      " 7502    7   26   27   35   68   73   85 7847 9018   24   34   36   37\n",
      "   38   39   44   46   48   54   56   66  561   50   51   52   65   29]\n"
     ]
    }
   ],
   "source": [
    "print(df.Linha.unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Gráficos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quantidade de Viagens por Empresa anual"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "new_df = df.groupby(['Empresa']).sum()\n",
    "new_df['Qtd_Viagens'].sort_values(ascending=False).plot.bar(grid=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quantidade de Passageiros por Empresa Anual"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.groupby(['Empresa'])['Qtd_Viagens'].sum().sort_values().plot.pie(autopct='%.1f%%', title='Quantidade de Viagens')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quantidade de Passageiros por Empresa Anual"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "new_df = df.groupby(['Empresa']).sum()\n",
    "new_df['Qtd_Passageiros'].sort_values(ascending=False).plot.bar(grid=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quantidade de Viagens anual por Linha"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "new_df = df.groupby(['Linha']).sum()\n",
    "plt.figure(figsize=(25,6))\n",
    "new_df['Qtd_Viagens'].sort_values(ascending=False).plot.bar(grid=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quantidade de Passageiros anual por Linha"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "new_df = df.groupby(['Linha']).sum()\n",
    "plt.figure(figsize=(25,6))\n",
    "new_df['Qtd_Passageiros'].sort_values(ascending=False).plot.bar(grid=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quantidade de Viagens por Mês"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "new_df = df.groupby(['Mês']).sum()\n",
    "new_df['Qtd_Viagens'].plot.bar(grid=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quantidade de Passageiros por mês"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "new_df = df.groupby(['Mês']).sum()\n",
    "new_df['Qtd_Passageiros'].plot.bar(grid=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tipo de Passagem por mês"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.groupby(['Mês'])[['Estudante_Cartao', 'Estudante_BT', 'Vale_Transporte', 'Integracao_Plena', 'Integracao_Complementar', 'Gratuito_Cartao', 'Gratuito_BT', 'Inteira_Cartao', 'Inteira_Especie','Tarifa_Social']].max().plot(grid=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tipo de Passagem por Empresa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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HDnx9ffHz88Pf35/79+8TFhZGmzZt6NmzJ3Xq1GHMmDEkPxz72Wef4e3tTb169Zg6dSpgWNiyVKlSTJs2jUaNGjF37lxu3rxJy5Ytad++PQBbtmyhadOm+Pv7079/f+7fv5/j4xVC5B4JJnZUtmxZGjVqxI8//ggYRiX9+/fH3d2db7/9liNHjhAeHs6kSZNIu1LB1q1bOX/+PAcPHiQyMpKIiAiLFlE8ffo0L7/8MkePHqVy5crMmTOHw4cPc+zYMbZt25YqGVfFihU5evQow4cPNz1DMm/ePJYtW0ZkZCS7d+82TUsdOHCAkJAQTpw4wZkzZ9i4cSNRUVFMmzaN8PBwjh49yt69e9m8eTMAd+/exd/fn4MHDzJlyhQqVKjAzz//TFhYGDdv3mTOnDls376dI0eO4OPjk+65FiGEfUkwsbOUU13JU1xaa6ZOnYqPjw/t27fnjz/+4MaN1Et7bN26la1bt1K/fn38/f05e/asabSQE08++SQNGzY0vf/iiy/w9/fH39+fM2fOpAomvXv3BqBBgwb89ttvgOHhxNdee41FixZx7949nJ2dAWjSpAleXl44OzszYMAA9uzZw4EDB2jbti3lypXDxcWF559/3hQAXV1d6dWrV4Z9/OWXXzh9+jTNmjXDz8+PNWvWcOXKlRwfqxAi98gFeDvr2bMnEydO5MiRI8TFxeHv78+qVav466+/iIiIwMXFBS8vr3TXD7TWTJkyhVdeecWq9osXL256ff78ed5//30OHjxIqVKleOGFFzJdov7Ro0cATJs2jR49evD999/TsGFDU9KetEvgK6XSja5Scnd3z3DZfDAca6dOnfj0008tOkYhRO6TkYmdeXh4EBgYyLBhw0wX3u/evUuFChVwcXEhPDzcNApI6ZlnnmHFihWmO7v++OMPbt68aVVf7t27h6enJyVKlOD69ev89NNP2da5ePEiPj4+TJkyhfr163Pu3DkA9u/fz9WrV3n06BFffvklLVq0oEmTJoSHh3P79m0SExNZu3YtrVu3znC/KZe+b9asGbt27eLSpUsA3L9/36JRmBAi98jIJIXsbuXNiZykbx04cCC9e/c2TXcNGjSI7t27ExAQgJ+fH7Vq1UpXp2PHjpw5c4amTZsChqD02WefUaFCBYv77O/vT506dahXr57ZS9TPnz+fn3/+GScnJ3x8fOjYsSO7d++mWbNmTJo0iVOnThEYGEiPHj1QSjFjxgwCAwPRWtO9e3e6du2aYSKuoKAg2rdvT9WqVQkLC+Pjjz+mf//+PHz4EIDZs2dTo0YNi49VCGFbsgS9LEFvkayOLywsjMWLF7Nhw4Y87lV6sgR9erJEe8EmS9ALIYRwWDLN5UBSPu2e0vbt2ylbtmye9aN9+/am50OEEIWDBBMHkvy0uxBC5DWZ5hJCCGE1CSZCCCGsJsFECCGE1SSYCCGEsJpcgE/hTC3b3s9f++yZbLcxJz9JSEgIQUFBFCtWzFZdy3PTp0/no48+onz58iQmJjJ79mx69OjB9OnT8fDw4PXXX7d3F4UQVpCRSQEQEhJCbGysTfaV0dPmeSU5l8r69esZNmxYvsmfIoSwngSTfCL5qda+fftSq1YtBg0ahNaa0NBQrl27Rps2bWjTpg1gWDE4ObdHv379TCObH374gVq1atGiRQvGjx9Pt27dAMOoICgoiI4dO/LSSy9x5coVWrZsaVod+JdffjH1Y+7cuXh7e+Pr60twcDAAH330EQ0bNsTX15c+ffqYAttvv/1Gu3bt8PHxoV27dly9etWsY61duzZFihTh1q1bqcovXrxIp06daNCgAS1btuTs2bMADBkyhPHjx9OsWTOeeOIJvvrqKwBiYmLMyvsihMh9EkzykaNHjxISEsLp06e5dOkSe/fuZfz48Tz++OOEh4cTHh7OrVu3mDlzJmFhYRw5coSAgABTVsJXXnmFLVu2sGfPHv76669U+46IiGDjxo18/vnnVKhQgW3btnHkyBHWrVvH+PHjAUMCqg0bNnDgwAGOHTvGG2+8ARiWnj906BDHjh2jdu3afPzxxwCMHTuWl156iePHjzNo0CDTfrJz4MABnJycTOmDkwUFBbFo0SIiIiKYP38+o0ePNn12/fp19uzZw+bNm01Bzs3NLdu8L0KIvCHXTPKRRo0aUaVKFQD8/Py4cuUKLVq0SLXN/v37OX36tGkRxocPH9K0aVPOnj3LE088QfXq1QHD4pHLli0z1evRowfu7u4AJCQkMHbsWCIjI3F2dubXX38FDGtqDR061HRtpkyZMgCcPHmSadOm8c8//xATE2PKWb9v3z6++eYbAF588UVT8MnMwoUL+eyzz/D09GTdunWplpyPiYnhl19+oV+/fqay5AyUYFiq38nJiTp16phyuyTnfdm9ezdOTk6mvC+PPfZY9t9sIYRNSTDJR5LzhYAhZ0hG1ze01nTo0IEvvvgiVfnRo0ez3HfKvCULFy6kYsWKHDt2jKSkJFN2RK11hjlFhgwZwoYNG/D19WXVqlWmnCVpZZaPJNmECRMyvdCelJREqVKlMn2CP+X3Jnn0sWbNmmzzvggh8oZMcxUAKXN7NGnShL1793LhwgUAYmNj+fXXX6lVqxaXLl0yZSBct25dpvu7e/culSpVwsnJiU8//dSU6Kpjx46sWLHCdE3kzp07gGGF4EqVKpGQkMCaNWtM+2nWrJlp2fw1a9akG0XlRIkSJahevTrr168HDAHj2LFjWdYxJ++LECJvyMgkBXNu5TVXTvKZZCcoKIjOnTtTqVIlwsPDWbVqFQMHDjRNA82cOZOaNWuyZMkSOnXqRLly5WjUqFGm+xs9ejR9+vRh/fr1tGnTxjRq6dSpE5GRkQQEBODq6kqXLl2YPXs2//vf/2jcuDHVqlXD29vbdGyhoaEMGzaMefPmUb58eVauXGnVca5Zs4ZRo0Yxc+ZMEhISGDBgAL6+vplub07eFyFE3pB8Jg6UzyQmJgYPDw+01owZM4YaNWowYcKEXGmroORrkXwm6Um+j4JN8pmIXPfRRx/h5+dH3bp1uXv3rtX54YUQwlwyzeVAJkyYkGsjEXPNmjXLdN0jWb9+/Xjrrbfs1CMhRF6QYCJs6q233pLAIUQhJNNcQgghrCYjE+HQYmIsS1dctKgzsbE5r1uihEXNCVHgychECCGE1bINJkopN6XUQaXUMaXUKaXUf43l1ZVSB5RS55VS65RSrsbyosb3F4yfe6XY1xRj+Tml1DMpyjsZyy4opYJTlOe4DSGEEHnPnGmuB0BbrXWMUsoF2KOU2gJMBBZqrdcqpZYCLwMfGv/9W2v9lFJqAPAu0F8pVQcYANQFHgfClFI1jW18AHQAooBDSqlNWuvTxrpmt2HtN+ODkTus3UUqY5a2zXabwpLPBOCTTz5h7ty5aK3RWjNs2LBczWMSGBjIm2++meWDj7ll1apVdOzYkccffzzP2xbCHrIdmWiD5N92LsYvDbQFvjKWrwZ6Gl8/a3yP8fN2yrBo07PAWq31A631ZeAC0Mj4dUFrfUlr/RBYCzxrrJPTNhySI+Qz2bJlCyEhIWzdupVTp05x5MgRSpYsaZe+5IVVq1Zx7dq1HNWxZ64ZIaxl1jUTpZSzUioSuAlsAy4C/2itk8/+KKCy8XVl4HcA4+d3gbIpy9PUyay8rAVtFFiOns/knXfeYf78+aa/1N3c3BgxYgQAkZGRNGnSBB8fH3r16sXff/8NGEYWEyZMoFWrVtSuXZtDhw7Ru3dvatSowbRp0wC4cuUKtWrVYvDgwfj4+NC3b98MA++uXbvo3r07zzzzDEFBQdy/fx+Axo0b884779C9e3c6d+7MiRMneP755wkICOCTTz4x1f/www/p0qUL7du3Z/78+QD8/vvvtG7dmsmTJ9OmTRsGDhxIXFwcX331FYcPH2bQoEH4+fkRFxfHjBkzaNiwIfXq1SMoKMi0WGVgYCBTp06ldevWvP/+++afMELkM2bdzaW1fgT4KaVKAd8CGa3vkLwuS0YjBJ1FeUYBLavts2ojFaVUEBAEULFixXSr3ZYsWdKma2ilZe6+o6OjiY2N5ejRoxw4cIBKlSrRoUMHtm3bxtChQ3nvvff47rvvKFu2LFeuXOG///0v3377LcWLF2fhwoW88847vPbaawQFBbFlyxa8vLwYOnQoiYmJREdH8+DBAw4dOsRPP/2Eu7s7sbGxfPPNN7i5uXHhwgVefvlldu3axdatW/n6668JCwujWLFi3Llzh+joaDp06MCAAQMAmDFjBh988AEjRoxg5MiR9OvXj0GDBvHpp58yevTodKsZJztx4gQ1a9bM8HvywgsvMG/ePFq0aMHMmTN56623ePfdd00LUH7//fcsWbKEHj16sHv3bkqXLo2vry/Dhw8nJiaGc+fOsWjRIhYvXszo0aNZuHAh48eP59GjR7i4uBATE0NoaKjpexYaGsrHH3/M5MmTUUrxr3/9i+nTp/PWW28xceJEvv/+exISEmjWrBkjRowwLSIZFhaG1ppBgwYRERFBlSpVuHz5Mh999BGhoaG8/PLLfPbZZwwYMID69eszc+ZM/P39SUxMZPDgwaYHSkeMGMH69evp3Lkzjx494ubNm2zevDnDcyY+Pj7TVZotFRMTY/N95idyfPaRo1uDtdb/KKV2Ak2AUkqpIsaRQRUgeUwfBVQFopRSRYCSwJ0U5clS1smo/JYFbaTt7zJgGRjW5kq7ns2ZM2dydX0pc/ft6elJsWLFaNSokWmxwgYNGnDz5k08PT1RSuHh4YGnpye7du3i3LlzdOrUCfi/fCZ//PEHTz75JN7ehrWhXnrpJZYtW4anpydFixalZ8+eVKhQATAs9542n4mnpye//PILw4cPp2LFiqn6f+TIEV588cVU+UycnZ05dOgQmzZtwsXFhREjRvD2229nesxKKTw9PdN9fvfuXe7du0fnzp0Bw6KW/fr1w9PTE2dnZ/r27Yunp6fpr/oaNWoA8OSTT/LPP/9QqlQpqlatSocOHQAYOnQooaGhpvoJCQns27ePc+fOmdpISEigQYMGPHjwAK01bdu25cGDB6Zg5+rqiqenJ66urty8eZOwsDDCw8Np3bo18H8rNVeoUIGqVatSs2ZNHjx4QN26dblx44ap7eLFi5uOd+vWrcydO5fY2Fju3LmDn5+fabsXX3wx0++bm5sb9evXN+s8MpesXVWw5dfjyzaYKKXKAwnGQOIOtMdwwTsc6IvhGsdgIDln6ibj+33Gz3dorbVSahPwuVJqAYYL8DWAgxhGGTWUUtWBPzBcpH/eWCdHbVj1ncgHHDmfSd26dYmIiKBt2+xvSkgp+Xvi5OSU6vvj5ORk+v6kbTfte601rVq1YsmSJVm2oZTC1dU1VRuPHj1Ca83YsWN58cUXU9X7/fffzfqZxcfHM3r0aA4fPkzVqlWZPn16qrwrKX82QhRU5lwzqQSEK6WOA4eAbVrrzcCbwESl1AUM1ys+Nm7/MVDWWD4RCAbQWp8CvgROAz8CY7TWj4yjjrHAT8AZ4EvjtuS0DUflCPlMpkyZwhtvvMGff/4JGLIohoaGUrJkSUqXLs3PP/8MwKeffmoaAZjr6tWr7Nu3D4AvvvgiXT8aNGjAoUOHuHz5MgBxcXFcvHjR7P0HBgaybt0603WW69evp8tfn1bKn1ly4ChXrhwxMTGmHPZCOJJsRyZa6+NAunG21voShjux0pbHA/3Slhs/mwXMyqD8B+AHW7RhDXNu5TWX5DNJrUuXLty4cYP27dubRkDDhg0DYPXq1YwcOZLY2FieeOKJHOdFqV27NqtXr+aVV16hRo0ajBo1KtXnZcuWZeHChYwZM4aHDx8C8MYbb/Dkk0+atf/WrVtz/vx5evToAUCxYsVYtGgRzs7OmdYZMmQII0eOxN3dnX379jFixAi8vb3x8vKiYcOGOTo+IQoCyWci+Uwskl/ymVy5coVu3bpx8uTJDD9/GGVZUI93f4RbXObBIjOuVWz7PZF8Jjknx2dbks+kEJJ8JkIIe5GFHh1IYcxn4uXllemoRAiRdySYCJuSfCZCFE4STIQQ+dJj4ZEW1ZsaE8cAC+r+2cbPovaEgQQTIUS+tEb3saheLBNYo8daUNNwpjWSAAAgAElEQVT828VFenIBXgghhNUkmAghhLCaTHOl8F7/bjbd36R1m83a7saNG0yYMIH9+/dTunRpXF1deeONN+jVq5dZ9f/55x8+//xzRo8ene22w4cPZ+LEidSpU4fZs2czdepUs9rIqM8jRozg0KFDFC1aFC8vL0JCQqhZs2b2lY2saV8Ikb/IyMTOtNb07NmTVq1acenSJSIiIli7di1RUVGptssq18U///yT6bpTaS1fvpw6deoAhl/mlvb5+eefJzAwkIsXL3L69Glmz57NjRs3zK6flJRkcftCiPxHgomd7dixA1dXV0aOHGkqq1atGuPGjWPVqlX069eP7t2707FjR2JiYmjXrh3+/v54e3uzcaNh3cvg4GAuXryIn58fkydPZufOnaZcJgBjx45l1apVgGGdqcOHDxMcHExcXBx+fn4MGjQIgAULFlCvXj3q1atHSEhIpn0ODw/HxcUlVZ/9/Pxo2bJlpn28cuUKtWvXZvTo0fj7+/Pyyy+na79nz540aNCAunXrsmzZMtO+v/jiC7y9valXrx5vvvlmjr6/dx78adFXok6wqJ4QhZVMc9nZqVOn8Pf3z/Tzffv2cfz4ccqUKUNiYiLffvstJUqU4NatWzRp0oQePXowZ84cTp48SWSk4XZIc3IdzJkzh8WLF5vqREREsHLlSg4cOIDWmsaNG9O6desMlz8/efIkfn4Z30bp5uaWYR8Bzp07x8qVK02jqPXr15vaB1ixYgVlypQhLi6Ohg0b0qdPHx48eMCbb75JREQEpUuXpmPHjmzYsIGePXtm2L4Qwj5kZJLPjBkzBl9fX9NigB06dKBMmTKAYXpo6tSp+Pj40L59e/744w+zp5ays2fPHnr16kXx4sXx8PCgd+/eppV8cyKrPlarVo0mTZpkWjc0NBRfX1+aNGnC77//zvnz5zl06BCBgYGUL1+eIkWKMGjQIHbv3m3xcQohcoeMTOysbt26fP3116b3H3zwAbdu3SIgwLCuWspcF2vWrOGvv/4iIiICFxcXvLy8UuXFSFakSBGSkpJM7zPaJq2cLPhZt27dTJe4z6qPWeXt2LlzJ2FhYezbt49ixYoRGBhIfHx8jvpV2MhDfSI/kWBiZ23btmXq1Kl8+OGHpqXTM8phDoY8JBUqVMDFxcWUShZS584Awwjg9OnTPHjwgPj4eLZv355hrhEXFxcSEhJwcXGhVatWDBkyhODgYLTWfPvtt3z66aeZ9vnNN9/ko48+MuVxP3ToELGxsZn2MSMp27979y6lS5emWLFinD17lv379wOGHO2vvvoqt27donTp0nzxxReMGzfOjO+s45OH+kR+IsEkBXNv5TWHuflMlFJs2LCBCRMmMHfuXMqXL0/x4sV59913iYuLS7XtoEGD6N69OwEBAfj5+ZlS/JYtW5bmzZtTr149OnfuzLx583juuefw8fGhRo0amaZ9DQoKwsfHB39/f9asWcOQIUNMeVCGDx+eaT2lFJ9//jnTpk1jzpw5uLm5mW4Nrlu3boZ9zK79FStWsHTpUnx8fHj66adN02GVKlXinXfeoU2bNmit6dKlC88++6xZ31shRN6RfCYOlM8kLxWU4/vz4nmL6rmWLMXDu//kuN5jT9awqL3MZHWObt9hXnKvtGLvT6BY8YU5rteubd6OTBz9+Cwl+UyEEEI4LJnmEpm6ffs27dq1S1e+fft2XF1d7dAjIUR+JcFEZKps2bKpngNJyZY57oUQBZ9McwkhhLCaBBMhhBBWk2AihBDCahJMhBBCWE0uwKcQFZzztaiy4jmnpVnbFcR8JqVKlcLb2xutNc7OzixevBhPT09efPFFAK5evUrJkiUpWbIk5cqVIywszKJ2hBAFg4xM7Kwg5jMBcHd3JzIykmPHjvHOO+8wZcoUvL29iYyMJDIykh49ejBv3jwiIyMlkAhRCEgwsbOCmM8krXv37lG6dGkbfDeEEAWVTHPZWUHMZwKYAlF8fDzXr19nx44dOT94IYTDkJFJPlNQ8pkkT3OdPXuWH3/8kZdeekmWixeiEJORiZ0VxHwmaTVt2pRbt27x119/UaFCBYv3kxucilS0sGaSFXWFKHwkmNhZQcxnktbZs2d59OgRZcuWzenh5zrP6KsW1XvoXgH36JsW1KxnUXtCFHQSTFKoYuatvOZw5Hwm8H/XTMAwqlm9ejXOzs5mHbMQwvFIPhPJZ2KRgnJ8cSdPWlTvYYUKuN7M+cjEvZ5tRyaSzyTnCsrxWUrymQghhHBYMs0lMiX5TIQQ5pJgIjIl+UyEEOaSaS4hhBBWk2AihBDCatkGE6VUVaVUuFLqjFLqlFLqVWN5GaXUNqXUeeO/pY3lSikVqpS6oJQ6rpTyT7GvwcbtzyulBqcob6CUOmGsE6qUUpa2IYQQIu+ZMzJJBCZprWsDTYAxSqk6QDCwXWtdA9hufA/QGahh/AoCPgRDYAD+AzQGGgH/SQ4Oxm2CUtTrZCzPURtCCCHsI9sL8Frr68B14+topdQZoDLwLBBo3Gw1sBN401j+iTY8wLJfKVVKKVXJuO02rfUdAKXUNqCTUmonUEJrvc9Y/gnQE9iS0zaMfbXY9OnTralu0f48PDyIiYnJcpuQkBCCgoIoVqxYltulzFVirfnz57N8+XKKFCmCs7MzkyZN4qWXXjK7/oYNG6hZs6ZN+iKEyP9ydDeXUsoLqA8cACom//LWWl9XSiUvylQZ+D1FtShjWVblURmUY0EbVgUTWzt2L+NlUVJKSrOdb4n0ASMkJIQXXngh22CyfPnyDMsfPXqUo6fTly5dyrZt2zh48CAlSpTg7t27bNiwwez6iYmJbNiwgW7dukkwEaKQMDuYKKU8gK+B17TW94yXNTLcNIMybUF5lt0xp45SKgjDNBgVK1ZMtzR7yZIlc/UW12pJWY84AJzQVEuKYc+evcyZM59y5cpz+vRp/Pz8WL58OUuXLuXatWu0bt2asmXL8v3337N9+3Zmz57Nw4cPqV69OkuWLMHDw4MuXbowc+ZM/P39qVSpEmPGjDFtu2vXLrZs2UJ8fDyNGzfm/fffJ7Of4axZs9i8eTNKKaKjo3FycqJ3795ER0czZ84ctmzZQlxcHE2aNDHtp0uXLjRu3Jj9+/fTtm1bNm7cyM6dO5kxYwaffvopu3fvZuXKlSQkJPDEE0+wbNkyihUrxtWrVxkzZgy3bt2iXLlyLFmyhKpVq9rsZxBX2bKFJ4tQhGgL6iba+HyKj4/PNKVA7P0JFu0zKamiRXXNSW1gSzdvzLSoXtGiRS2qm9fHZ6mYmJh82VezgolSygVDIFmjtf7GWHwjeWrJOI2VvPZEFJDyt0EV4JqxPDBN+U5jeZUMtrekjVS01suAZWBYTiXtEgRnzpzJ1SVBnJzMWR5e4+R0A6X+5sSJ45w6dYbHH3+c5s2bc/z4cd544w2WLFnCrl27KFeuHLdu3WLBggWEh4eb1vD66KOPePvtt3F2dqZ48eJ4enpy//59GjRowLvvvgtAQEAAs2bNAuDFF19k165ddO/ePV1voqOjiYmJwdfXN8PeTpo0iVmzZhEdHc3o0aNN+3F2diY2NpY9e/YAhrS93bp1o2/fvgBUqVKFcePGATBt2jS+/PJLxo0bR3BwMEOHDmXw4MGsWLGCqVOn5mgUlJ2rtyxb6LG8c3n+evRXjuvVLV3XovYy4+bmlukaadt3vGzRPi1dbiQwMG+XG7F02vnpp5/m3LlzOa43cOBAi9rLa3m9nIq5zLmbSwEfA2e01gtSfLQJSL4jazCwMUX5S8Y7rpoAd41TVT8BHZVSpY0X3jsCPxk/i1ZKNTG29VKafeWkjQLN378eVapUwcnJCT8/P65cuZJum/3793P69GmaN2+On58fq1evNq0enJKzszN9+vQxvQ8PD6dx48Z4e3uzY8cOTp06lWEftNaZjlhS7qdJkybp9tO/f/9M6508eZKWLVvi7e3NmjVrTPX27dvH888/DxiCXHIwEkIULOaMTJoDLwInlFLJj0NPBeYAXyqlXgauAv2Mn/0AdAEuALHAUACt9R2l1P+AQ8btZiRfjAdGAasAdwwX3rcYy3PURkFXtOj/LVHi7OycYd53rTUdOnTgiy++yHJfbm5upusk8fHxjB49msOHD1O1alWmT5+eaY6TEiVKULx4cS5dusQTTzyR6rOU+ylVqhTvvfdeqv2kzL2S1pAhQ9iwYQO+vr6sWrUq02F6VoFMCJF/ZTsy0Vrv0VorrbWP1trP+PWD1vq21rqd1rqG8d87xu211nqM1vpJrbW31vpwin2t0Fo/ZfxamaL8sNa6nrHOWONdWljShiNKma+kSZMm7N27lwsXLgCG3Ce//vprlvWTf+GXK1eOmJgYvvrqqyy3nzJlCmPGjOHevXuAIcf7smXLcrSftDlWoqOjqVSpEgkJCaxZs8ZU3qxZM9auXQsYkn9llHdFCJH/ydpcKWQ0R3vv3gmL9pWUVBGwTUrdoKAgOnfuTKVKlQgPD2fVqlUMHDiQBw8eADBz5kxq1qyZaf1SpUoxYsQIvL298fLyMqUEzsyoUaOIiYmhYcOGuLi44OLiwqRJk1Ltp2rVqlnuZ8CAAYwYMYLQ0FC++uor/ve//9G4cWOqVauGt7e3KdCEhoYybNgw5s2bR/ny5Vm5cmWm+xRC5F+SzySbfCbWBBPzLsCnVqKEt0Xt5bWCks/k1K2Mrw1lx+IL8OVsewE+q3M0ry9Q2/o5rNxqr6Acn6Ukn4kQQgiHJdNchdiYMWPYu3dvqrJXX32VoUMd4n4GUcANj0+fS8ccZ5Lu0tLCusJyEkwKsQ8++MDeXRBCOAiZ5hJCCGE1CSZCCCGsJsFECCGE1eSaiRAFlFygFvmJBJMUtu940qb7axiQ/YKFjz/emGvXDmS5TV7nMxkyZAi7du2iZMmSABQrVoxffvnFqn1m5/Dhw3zyySeEhobmajtCiNwhwaQAyOt8JgDz5s0zrfibFwICAggIyPa5KFGIrLv8rkX1qtTsybrLS3NcbxItLWpPGMg1k3zi558P0bXrMPr27UutWrUYNGgQWmtCQ0O5du0abdq0oU2bNgBs3bqVpk2b4u/vT79+/UyZGgMDA0l+yt/Dw4O3336bxo0bs2/fPmbMmEHDhg2pV68eQUFBWLLywa5du/Dz88PPz48WLVoQHR3Nzp07adWqFb169aJOnTqMHDmSpKSkLPt56NAhmjVrhq+vL40aNTLtp1u3bgDcv3+fYcOG0bBhQ+rXr8/GjRsz7ZMQIn+QYJKPHD9+lpCQEE6fPs2lS5fYu3cv48eP5/HHHyc8PJzw8HBu3brFzJkzCQsL48iRIwQEBLBgwYJ0+7p//z716tXjwIEDtGjRgrFjx3Lo0CFOnjxJXFwcmzdvzrIvkydPNgWOQYMGAYZUvh988AGRkZH8+OOPuLu7A3Dw4EHee+89Tpw4wcWLF/nmm28y7efDhw/p378/77//PseOHSMsLMy0n2SzZs2ibdu2HDp0iPDwcCZPnsz9+/dt9F0WQuQGmebKR5LzmQCmfCZpV9FNmc8E4OHDhzRt2jTdvjLKZzJ37lxiY2O5c+cOdevWzTA5VrKMprmaN2/OxIkTGTRoEB07dqRSpUoANGrUyLRc/cCBA9mzZw9ubm4Z9vPcuXNUqlTJtEhkiRIl0rW9detWNm3axPz58wHDqsdXr17Ndh21wkamgUR+IsEkH8kP+UyyEhwcTNeuXfnhhx9o164d27dvB9LnIFFKZdrP48ePZ5uzRGvN119/zdNPP53jPgoh7EOmuQqAvM5nkpmLFy/i7e3Nm2++Sf369Tl79ixgmOa6fPkySUlJrFu3jhYtWmTaz1q1anHt2jUOHTLkSIuOjk4XNJ955hkWLVpkuq5z9OhRi/orhMg7MjJJoV3b9DmuC2M+EzBcM5k5c6bp/cGDBwkJCSE8PBxnZ2dq1KhB586d2bdvH02bNiU4OJgTJ06YLsY7OTll2s9169Yxbtw44uLicHd3JywsLFXb//73v3nttdfw8fFBa42Xl1e213iEEPYl+Uwkn4lFkvOZ7Ny5k/nz5+fbX/aOnM/kvf7dLNpnlWd6EvVT9s9ApTVpXd7+jB39+Cwl+UyEEEI4LJnmKsRskc8kMDAwT/9KEkLkTxJMshETU9aiekWLOhMbm/O6Gdwpm2skn4kQwlZkmksIIYTVZGQiRAHV5Vj6uw/N8VurB/hYWDcvOfrxORoZmQghhLCaBBMhhBBWk2muFB4Lj7Tp/q7WyDo/yu2/b9NpQA8Abvx1A2cnZ8o/VgEwPCTo6uqaVXUAhg4dSnBwME8//TRr167lv//9L5UrV073IGBWHj16xPjx49m1axdKKdzd3Vm/fj3VqlUzex8A3377LRcuXGDy5MmZbrN8+XJOnjxJSEhIjvYthMjfJJjYUdnSZTn0k+HW3P8tmE3xYh4Ez3zL7PqPHj1i5cqVpvfLly9n2bJltGyZswX5Pv/8c27fvs3x48dxcnLi6tWrGS7AmJ1evXrluI4QwjHINFc+1b17dxo0aEDdunVNSa8SExMpVaoU06ZNo1GjRhw8eJAWLVoQGRnJ22+/zf79+xk+fDjBwcFcvHiRli1bUr9+fRo0aMCBA5lnc7x+/TqVKlXCyclwOvzrX/+iVKlSAHz22Wd4e3tTr149pk6daqrz448/4u/vj6+vLx07dgQMwey1114DYOPGjTRu3Jj69evTsWNHbt68mSvfJyFE/iAjk3xq9erVlClThtjYWAICAujTpw+enp7cvXsXf3//VOtmAcyYMYMdO3awePFi/Pz8iI2NZdu2bbi5uXH27FkGDx6caUAZMGAALVu2ZOfOnbRr144XXngBPz8/oqKimDZtGocPH6ZkyZK0b9+ezZs3ExAQwMSJE9mzZw/VqlXjzp076fbZqlUrevTogVKKpUuX8t577/Huu5YtmS6EyP8kmORTCxcuZNOmTQBERUVx8eJF/Pz8cHV1NWs66cGDB4wdO5Zjx45RpEgRLl7M/FbJf/3rX5w7d44dO3awY8cO2rRpw7fffsvt27dp27Yt5cqVA+D5559n9+7dJCQk0LJlS9M1lTJlyqTb59WrV3nuuef4888/efDgQZYLUQohCj4JJrnozoM/zd42LjEGp0eGRTfDwsLYvXs3+/fvx93dnRYtWpiWkXd3d882HwjAe++9R9WqVfnss89ISEjAw8Mjy+3d3Nzo0qULXbp0oVy5cmzcuNGU2CotrXW2fRgzZgxTp06lS5cuhIWFMWfOnGz7LIQouCSY5EN3796lTJkyuLu7c+rUKVPuj5zu46mnnkIpxerVq7PM+R4REcHjjz9OpUqVSEpK4sSJEzRs2JAmTZowefJkbt++TcmSJVm7di2vv/46AQEBvPrqq/z222+maa60o5O7d+9SuXJltNasXr06x/0X2XtuimX/fUd5KCZbUNey9bNFYSHBJIU/2/ilL7t43qJ9uZYsxcO7/1hUt2vXrixbtgxfX19q1apF48aNc7yPsWPH0rdvX7744gvat29P0aJFM932zz//ZMSIETx8+BCtNU2bNmXUqFEULVqUGTNmEBgYiNaa7t2707VrVwAWLFjAs88+i9aaxx9/nC1btqTa5/Tp0+nVqxdVqlShUaNGXL9+PcfHIAo3CZYFi+QzySafSV4Hk8eerGFRe5Zy9HwtjpzPxHu1Zd/LUR6j+DDmwxzXOzE4b3/dOvrxWUrymQghhHBYMs1ViERGRjJkyJBUZUWLwrZtn9qnQ0IIhyHBpBDx8/MjMjL1kjGWTnMJIURKhX6aq7BcMxIFj5yboiDJNpgopVYopW4qpU6mKCujlNqmlDpv/Le0sVwppUKVUheUUseVUv4p6gw2bn9eKTU4RXkDpdQJY51QZXyAwZI2csrNzY3bt2/Lf1qR72ituX37Nm5ubvbuihBmMWeaaxWwGPgkRVkwsF1rPUcpFWx8/ybQGahh/GoMfAg0VkqVAf4DBAAaiFBKbdJa/23cJgjYD/wAdAK25LQNSw6+SpUqREVF8ddfmd+1c+8vy9aUcr7zN4/i4nJc7++HiRa1Z6n4+JzfkQWQlBSHk9O9HNdzc8vbmdU/Y8x/cDSl+073iU6KznE9p79sN9h3c3OjSpUqNtufELkp2//ZWuvdSimvNMXPAoHG16uBnRh+0T8LfKINf+rvV0qVUkpVMm67TWt9B0AptQ3opJTaCZTQWu8zln8C9MQQTHLUhtY6xw8yuLi4UL169Sy3OdOrd053C8Bv48ZSbdHiHNerffaMRe1ZavuObhbVi70/gWLFF+a4Xru2eZsB77nVz1lUz9FvLxXC1iz9M6pi8i9v478VjOWVgd9TbBdlLMuqPCqDckvaEEIIYSe2nnPIaMEmbUG5JW2k31CpIAxTaFSsWJGdO3dms+v04seNzXEdgIcVKvCbBXVvWNBHa8Ten2BRvaSkihbVteRnYI1RHqMsqlfeubxFdfPy+Bz52MDxj89SMTEx+bKvlgaTG8lTS8ZprOQLC1FA1RTbVQGuGcsD05TvNJZXyWB7S9pIR2u9DFgGhifgLXlq9MxIy07ogjPN9bJF9Syd5goMzNtprnGrx1lUz+Jprj55N83lyMcGjn98lsrrJ+DNZWkw2QQMBuYY/92YonysUmothovid43B4CdgdvIdWUBHYIrW+o5SKlop1QQ4ALwELLKkDQuPQwgh7GL7jqzTemcm9v4Ei/4IzO3rldkGE6XUFxhGFeWUUlEY7sqaA3yplHoZuAr0M27+A9AFuADEAkMBjEHjf0Dy8rczki/GA6Mw3DHmjuHCe/KKgTlqQwghhP2YczfXwEw+apfBthoYk8l+VgArMig/DNTLoPx2TtsQQghhH7KcSjZkGWwhhMheoV9ORQghhPVkZFLI/bz7RYvqPf10WSIicl63XVuLmhNC5HMyMhFCCGE1CSZCCCGsJtNchdzw+HQ3zJnlTNJdWlpYVwjheGRkIoQQwmoSTIQQQlhNprkKuXWX37WoXpWaPVl3eWmO602ipUXtWerE5asW1dv59EOL6wpRGEkwEUIIO3C02/JlmksIIYTVJJgIIYSwmkxzCSGEHTjabfkSTAq5Lscsy3HwW6sH+FhYVwjheCSYCCGEHTjanZRyzUQIIYTVZGQiHJpX/OcW1ZuUlMgQC+pesag1IQo+CSaFnCT/EvmVPHBasEgwEUIIO3C0m1/kmokQQgirSTARQghhNZnmEqKAkmsKBZujXa+UkYkQQgirychECJEvyW3dBYuMTIQQQlhNRibZkHlpIYTIngQTIQoomQYS+YlMcwkhhLCajEyyIX/9CSFE9mRkIoQQwmoSTIQQQlhNgokQQgiryTWTQk5ufRZC2IIEEyGEsANH+0NOgkkhJ3erCSFsQYKJEELYgaP9IScX4IUQQlhNgokQQgirFdhgopTqpJQ6p5S6oJQKtnd/hBCiMCuQwUQp5Qx8AHQG6gADlVJ17NsrIYQovApkMAEaARe01pe01g+BtcCzdu6TEEIUWgU1mFQGfk/xPspYJoQQwg6U1trefcgxpVQ/4Bmt9XDj+xeBRlrrcWm2CwKCjG+fBs7lYTfLAbfysL28JsdXcDnysYEcn61V01qXz26jgvqcSRRQNcX7KsC1tBtprZcBy/KqUykppQ5rrQPs0XZekOMruBz52ECOz14K6jTXIaCGUqq6UsoVGABssnOfhBCi0CqQIxOtdaJSaizwE+AMrNBan7Jzt4QQotAqkMEEQGv9A/CDvfuRBbtMr+UhOb6Cy5GPDeT47KJAXoAXQgiRvxTUayZCCCHyEQkmQgghrCbBRIg0lFLllFLK3v0QIq38fG5KMLExpZSHUqq4vfthK0qpGkqpVUqpBUqpKkqpLUqp+0qpY0qphvbun7WUUk2UUjuVUt8opeorpU4CJ4EbSqlO9u6frSmlXIzHWcHefbGWnJv5iwQTG1FKjVZKXQV+A35XSv2mlBpt737ZwErgFwwPhR4AVgBlgdeBxXbsl60sBmYDXwA7gOFa68eAVsA79uyYLSilliql6hpflwSOAZ8AR5VSA+3aOevJuZmPyN1cNqCUmgY0A8ZqrS8Zy54A3gcOaK1n2rN/1lBKRWqt/YyvL2itn8ros4IqzfGd0VrXTvHZUa11ffv1znpKqVNa6+Rg8hoQqLXuqZR6DNhSkI9Pzs389bOTkYltvAj0Tg4kAMbXzwEv2a1XtpGU4vW9LD4rqFIeQ1yazxzhL62HKV53ADYAaK3/tE93bErOzXykwD60mN9oreMzKItTShX0k7qWUuo4oIAnja8xvn/Cft2yGV+l1D0Mx+NufI3xvZv9umUz/yilugF/AM2BlwGUUkUAd3t2zAbk3MxHJJjYRpRSqp3WenvKQqVUW+C6nfpkK7Wz36Tg0lo727sPuewVIBR4DHgtxYikHfC93XplG3Ju5iNyzcQGjBc4NwJ7gAgMQ9CGGP4SfNYR1w0zZrscoLVeY+++5AalVClgjNZ6lr37kluUUg211ofs3Q9bk3PTPuSaiQ0Yg0U9YDfghWGIvRuoV9ADiVKqhFJqilJqsVKqozIYByRfEyrQlFJVlVLLlFKblVLDlVLFlFLvAeeBAn/7bFpKqTpKqRlKqfPAh/bujzXk3MxfZGSSi5RSzYHntdZj7N0XSymlNgJ/A/swTI2UBlyBV7XWkfbsmy0opcKBXRiOrxOGYzwFTHCQi9QopaoBA41fiUA1IEBrfcWe/bKWnJv5iwQTG1NK+WH4T9sfuAx8o7VeZN9eWU4pdUJr7W187Ywhw9u/tNbR9u2ZbSiljmmtfVO8v4Hh+B7YsVs2o5T6BSgJrAXWaq3PK6Uua62r27lrVpNzM3+RC/BWUEpN11pPV0rVxJCgayBwG1iHIVC3sWsHbSMh+YXW+pHxF5FD/GdNppQqjeEOGYA/gWLKuIqB1vqO3TpmG+U+HQAAABTZSURBVH9hyERaESiPYYrEUf6ClHMzH5GRiRWUUp9qrV803v77M/Cy1vqC8bNLWusCf3uiUuoRcD/5LYbbSWONr7XWuoS9+mYLSqkrGO7nz2i9I+0gP8OSQB8Mf+w8BZQCntFaH7Rrx6wk52b+OjdlZGKd5L+M+mAYmYQrpX7EMKWQLxdjy6mCdntiTmmtvezdh9ymtb6LYamRFUqpihimYEOUUlW11lXt2zvLybmZv8jIxApKKbeUDysah589MfwF2BZYDXyrtd5qpy5aTSlVJk2RBv7RDnLiKKX80xRp4JbW+nd79CcvKaWqaa1/s3c/LCXnZv4iwSSXGE/0vhjud29r7/5YSil1GcNJnHKk5QlEYlh47oo9+mUrxjtm0iqD4a6ggQ5yV9Bg4FWgFoaf5RkgVGv9iV07ZiU5N/PXuSnBxAaUYbnrclrrLWnKewB/aK0j7NOz3KOU6g0Eaa3z3VLYtqCUCgAWaK1b2bsv1lBKvQRMACYCRzD84vUH5gHvF/SAkhE5N+1DgokNKKV2AkPS/iWklHoKWFaQRyZZUUod0VqnHYo7DEc4PqXUfgyj4ytpyr0w3CrcxA7dynWO8LPLSn48PnkC3jbKZjSkNt7Z5aWUWqmU2pP33co9SikPHPj8MV6odoS/tEpkcm5eAQr03U6ZkXPTPuRuLtvIcvVVrfVQpdTRvOqMLSmlJmZQXBrogQMkIFJKLSL9f8wyGPLTvJr3PbK5tEuXm/tZvifnZv4iwcQ2wpRSs4BpKe8kUUr9Fwgzvm1hl55ZzzPNe43h4akXtNYn7NAfWzuc5r3G8ODpRK31TTv0x9Zqp1iaPSVHWKZdzs18RK6Z2IDxluDlQCMMd5IA+GI4GYZrrWPs1TdRuBnX5cpUQb41WOQvEkxsSBlS9dY1vj2VMvOiEEI4MgkmNpDBw0WpaK2P5FVfhEhJKRVNxhdrHWLJEZF/SDCxgUweLkqmHfXWYEellHosPy7xLUR+PjclmIgcy4/3uNuSox+fI3P0n11+Pj6HvRc7Lyml3kjxul+az2bnfY9ynUMsYpkFhzk+pVS0Uuqe8d/oFO9jlVKJ9u5fLnCYn10m8u3xSTCxjQEpXk9J85kjLunwvb07kMs+sncHbEVr7am1LmH81xN4HJiF4Rba9+3bu1wh56adyDSXDSiljmqt66d9ndF7IexBKVUKeA14CfgcWKi1vm3fXglHIg8t2obO5HVG74XIM0qpcsAkDDlMVgD1jflNhLApGZnYQIqMbymzvWF876a1drFX30ThppS6jyF170ogXUpbrfWCPO+UcEhyzcQGtNbOKealixhfJ793qECilHJRStVX/7+9+46Sq7zPOP59UEToCNkgsBG9mN4EMSU6dIgNpgeEHVs2xsEHjCEBnxwwpvkYMM02IRByXIgpoojiEgMmYIGAIDAICL0J00EUhy4jnvzxvgPDMLvaZe7OO+X3OWeP5t7ZlZ7R7s7v3rdKS5XOMpIkbS7pzNI5KnAyqZBAWn6k8aPnSBov6fDSOUaSpJtKZ2gUzVwVGGQ/k52BZ7p5PxNJZwNn2L437yV+CzAXGCvpMNsXlk1YHUnrA/sCfw88DlxWNlHrbB9TOkM75Oa8vUi7nH4auLxsohG3XOkAjaKYVONkYHKT8/cD55C28O1Wf2v7gPz4q8BDtneVtDTwO6Cri4mk1Uij8SaRFtG7iNT8u1XRYBWR9JOGUwZmA9fb7uptESQtCuxGugBYjVRAVrK9bNFg7dFx/RNRTKox4H4mkj5RIE+V5tQ93g64BMD2c1LHDnkfjgeAG4Gd8/4zSDq0bKRKNbsrHgucLOki2z9qd6AKvQDMAL4LTLdtSbsVzlSZvGNk06eYx7YXJUQxqcZg39iF25ZiZLwqaSfgaWBzYD8ASX9FB/5Afwx7kO5Mrpd0FTCFDp4YNly2z212Pjdf3gx0czE5gvS9Owu4QNJFhfNUbedBnvtN21IMUYzmqkD+xXyJ5vuZLGP7G8XCtSg3A/0EWBr4ke1f5PM7ANvb/ueC8SqTtxHYldTctTVwLnC57WuKBhtBvTIHKq/WPYlUWFYFjiZ97x4qGqzPRDGpQL/uZyJpY9u3lc5RNUljSZ25e/fiIp35rvIfgN1tD3b123UkrUMeRGF75dJ5WtFkJ8laf9d0248XiDSoKCYV6of9TCStyQcd1n+2PaFwpBGRZ4wfZPv7pbO0YoAl6N8CpgGH2H6m/anCUEg6usnpscAOwDG2p7Q50qCimFRA0qDD9Gz/qV1ZRkLerW9S/ngXWB6Y0GzQQbeRNB44irRm1RWkpUaOJ125X2i74/baDkm/7tWS75yv7bTVg6MDvhq/Jf1Q13fcGlgSWAoYVSJUFSTdDCxO6pje0/bDkh7vhUKS/SfpKn0qaVHO/wHuBdbt1H0jhkPSl2yflx9vbvumuucOsv2v5dK1Ji9c2Xdsv6wOHEoZM+ArYHsd2+vmP9chjcK4CXidtLheN3uRNFN6HKk4QgeOcW/BWNvH2L7a9qGk1zm5FwpJVt/ufkbDc19rZ5B2kTRG0pGlc4wUSVsDr5TO0SjuTCokaVXgSOBvgFOBg23/pWyq1tjeJc983wM4VtIqwBhJm9ieUTheJSQtwQd3lc8BC+VBFdh+uViwamiAx82Ou8ogTZS1lZG7mqR7+OiF21jgGdJr7CjRZ1IBSWuTishawA9Jbe1zy6YaGZLGkVag3QcYb3t84UgtkTQLeI/mb6y2vVJ7E1Wrfme+xl36OnnXvqHI22VPIy3xsyOwDamJ8tBeuLPMfZX1DLxk+40SeeYlikkF8qrBT5L6Tj5SRGwf3PZQbSBpedtPlM4RBibpTeARUrFcOT8mH69ku2sn1Uq6y/Z6dcfPA8vZfqdgrMpIWgj4S611Q9LqwOeAWbY7bu2xaOaqRk+2PQNI+jkD95GYPCO+l0hamTz82fbapfO0aI3SAUZSjzdRXkX6/Xo4Ny/fApwP7JSbmRt3dS0q7kwqJmkRUvNIR96KDpekPZqcXo40sGBUryyqJ2kZUvPdvsC6wAnAZbbvKRpshEgaBexj+/zSWT6uPmiivCcP6EHS8aTBIgdKmh/4Y+25ThF3JhWR9E3S/u8L5+PXgZNs/1vRYC2yPbX2OE/KPAKYCJwI/LRUrqpI2p80f2ZZ4GLg68CVto8tGqwikhYDDiQty/4r4PfAQcBhpNUauraY2F6hdIYRVn+lvzVpdXJsz5H0XplIA4tiUgFJ3wU2A7aszXrPb7w/ljS2B2ZRr0EaYLAB6Qf6ANvvlk1VmTNJzQf72r4dQFIv3a7/kjSM9BZSoTwcmB/YxfbMwb6wG/VYE+Xdkk4hLbK6CnANvL86Q8eJZq4KSHoQWM/22w3nFwTusr1amWStk3QJMAE4hXTl/qEBBt3eLt2wqdI40muc3O2j1GoamkpGkdZ2Ws72R7bw7Va92kSZ3z++DSwD/Mz2Xfn8ZsDKtn9ZMl+jKCYVkPSg7dUHeO4B259pd6aq5Hbp2g/JR2b5d3u7dD1Jy/LBumMLkVaePaJsqtb02nDgek2aKC8mNVGuWDRYn4pmrmo8JWkb2/9df1LSNsCzhTJVog/apd9n+ynSHdgpeen9SYUjVWE9Sf+XHwtYMB/3wvpVvd5E2VWimFTjYOBKSdNJO9sZ2Ji0mdQuJYO1SlLjVayB2bafLJFnJOTJYW/Yni3ps8AWwKO90Alvu2vXhRuCT5GaKE/Lk2kvBkaXjdS/opmrAnkM+NKkfajXIl313Qs8DDxt+9GC8VqSZxk3GkvqxJ3U7Z24ko4CJpOK5BRgW+APpCVx7rLd7Wur9YVebKIciKQFSNtMX1I6S70oJhWQ9BvgCNt3N5yfABzdaxsQwfuv7TTbE0tnaYWk+4D1SW9AfwKWtv1m3kBqZg+MCOo7tSbKXrizrMmDJ7YnFcsdgBtt71k21YdFM1c1VmgsJAC2b5e0QvvjjLz82hYpnaMCb9ueA8yR9KjtNwFsvytpTuFsYRCSdh/k6a4eyVUjaSJplNrngRmkpvMVaz+nnSSKSTUWGOS5BduWoo1yG3Uv3NaOyW9KAhare4MSaR+X0LkuJU28rDW1Nu4ndFnbE1VI0lOku+WzgMNtv5b3Euq4QgJRTKpym6T9bf9H/UlJ+5E65LuWpDNovgz2ZqQx8N1uGmn/GYAb6h7XjkPn2oM0v2Rd4ErSat2PDP4lXWUqsCvpNc6VdCUdfAEXfSYVyFfplwNz+KB4TCB1Uu/WzcthS/pKwykDLwG32X6hQKS2kTTO9vOlc4TB5YUddyG96X4CONL2tLKpqpF3VNyK1FfyOWAx0uKP/2X79ZLZGkUxqZCkrYBah+29tq8rmadqkpYEsP1i6SwjpW4jsH2BNWx/unCkMA+5c3pH0miutYF/sX112VTVkzQa+DvS69ze9icLR/qQKCZhniQdDXyL1CY9H/AucIbt44oGq0hetuILpAKyIWmb4l2BG2x33IJ6IckXb5OATYBrgSm1yYu9TtKCtt8qnaNeFJMwKEmHkm6vv2H78XxuJVKn4FW2Ty+Zr1WSzietgnwNaZ7JdcAjsSRH58sr594NTCc1v37ozazbN6UbYNve99let41x5ik64MO8fBnYzvbs2gnbj0n6EukNuKuLCalZ5BXgfuAB23NjSY6u8dXSAUbYTqUDDEcUkzAvo+sLSY3tF3MbblezvZ6kz5CauK6V9AKwqKSlu3ngRD+wfW7pDCPscOAC2zeXDjIU85UOEDreYBP3emJSn+0HbH8vr/x8KGkPkBmSuuKXOPSsh4FTJc2SdJKk9UsHGkz0mYRBSZoLNNuCWMACtrv+7qSZPCRzYq8MMQ3dKy9Euk/+WAC4kDTY4KGiwRpEMQl9TdL3Bnu+V0as9RtJG9u+rXSOqknaAPgZsG6nrQgdzVyh373R5APSxLDvlAoVhk/SmpKOk/QwabRhT5A0WtLOeeTh74CHSHOhOkrcmYSQSVqUtETMfqS9MU7t9Vn+3S43AU3KH+8CywMTbM8qmasKkrYjva7aIo9TgCtsN2t2Li6KSeh7ksYC/wR8ETgX+LHtV8qmCvOSB0gsTnqTnWL74bwQYk/MEcp7CV0ATLX9cuk88xJDg0Nfk3QysDtwDrBOp613FAb1Imn/93HAkqTRTz1zdWx7q9IZhiPuTEJfy7Oo3yE1kdT/MvTCHuk9r24ttUnAKsAYYAfbM4oG60NRTEIIPUHSUqSVgycB422PLxypr8RorhAaSFpY0hcl/bZ0ljAwST+oP7b9gu0zbG8GbFEoVt+KYhICIGl+SbtKuhh4FtgWOLtwrDC4HQd6wvYT7QwSogM+9Lm64Zc7ANeTllLZxHavLyLYC0ZJWoIPb9f7vm4YAdVLos8k9LXcAX8jMLluif3HbK9UNlmYF0nvAE/TvJg4voftFXcmod9tRFrz6FpJj5HmLHTUMhVhQPfZ3qB0iJDEnUkImaTNSU1eewAzgcttn1M2VRiIpDujmHSOKCYhNJA0H7AdsE/0nXQuSZNt/6J0jpBEMQl9TdKGDacMzLb9ZIk8Yegk/ZyBZ7zb9n7tzNPvopiEvpbXP2o0FpifdGdyV5sjhSGS1Gzl3OWAQ4BRtpdtc6S+FsUkhCYkTQBOsz2xdJYwb5JWAo4AJgKnAz+13RM7gXaLmLQYQhO2bwcWKZ0jDE7SGpLOA34NTAfWtH1WFJL2i6HBITQhaRw9tAJtL5J0CTABOAU4FJgLLJZ2XI5Ji+0WzVyhr0k6g48WjbHAZsC3bf+6/anCUEiaxQffu9qftQmMMWmxzaKYhL4m6SsNpwy8BNwWuyyGMHRRTEIIPUPSyqQVDSbZXrt0nn4SHfChr0naRdKBdce3Snosf+xVMlsYGknLSDpE0gzgXlJf8KTCsfpOFJPQ774D/Kru+K+BjYEtgQNKBApDI2l/SdcB04BPAl8HnrV9rO17yqbrPzGaK/S7+Rtmu0+3/RLwkqSFS4UKQ3ImcAuwbx7KjaRoty8kiknod0vUH9g+qO5wyTZnCcPzKWAv4LQ8lPtiYHTZSP0rmrlCv7tV0v6NJyX9IzCjQJ4wRLZn5wmKE4FtgD8DL0i6v3FL3zDyYjRX6GuSlgKuAN4B7sinNyL1nexq+/lS2cLHI2k10miuY0tn6SdRTEIAJG0NrJUP77V9Xck8Yd4kbQw8afu5fPxl0l40TwDHxAz49opiEkLoSpLuALa1/bKkiaRdMr8FrA+sYXvPogH7THTAhxC61ai6u4+9gXNsTwWmSppZMFdfig74EEK3GiWpdkG8DVDfNBkXym0W/+EhhG51ITBN0mzgLeBGAEmrkEZ2hTaKPpMQQteS9FlgGeAa22/kc6sBi9i+Y9AvDpWKYhJCCKFl0WcSQgihZVFMQgghtCw64EMYJklzgfpVaafYPrFUnhA6QfSZhDBMkl63vcgI/xujbM8dyX8jhCpFM1cIFZE0S9IPJN0i6XZJG0q6WtKjkg7In7OlpBskXS7pPklnS5ovP/e6pOMk3QpsKmkjSdMk/TH/Pcvkzzs4f+3dkqbkc5tIulnSnfnP1Yv9R4S+FHcmIQxTk2auE2xfJGkWcJLtsySdTppItzmwAGm9r6UkbQlcBaxJWkPqKuDfbV+a9+LY2/bFkkaTNn3axfaLkvYGdrD9NUnPACvafkfSGNuvSloMeNP2u5K2Bb5pe4+2/IeEQPSZhPBxvGV7/QGeq+3aeA9prsNrwGuS3pY0Jj83w/ZjAJIuBLYALgXmAlPz56wOrA38XhLAKODZ/NzdwPmSriCteAywOHCupFUBE/t6hDaLYhJCtd7Jf75X97h2XPt9a2wOqB2/XddPItLdzKZN/o3PAxOBLwBHSVoLOB643vZuklYA/tDCawhh2KLPJIT220TSirmvZG9gepPPeRBYUtKmAJJGS1orf81429eT9q8fAyxCujN5On/t5JF+ASE0imISwvAtKGlm3cdwhwXfApwI/C/wOHB54yfYngPsCZwk6S5gJrAZqbnrPEn3AHcCp9t+FfghcIKkm/LnhNBW0QEfQhvlDvjDbO9UOksIVYo7kxBCCC2LO5MQQggtizuTEEIILYtiEkIIoWVRTEIIIbQsikkIIYSWRTEJIYTQsigmIYQQWvb/LV8M4EbJo+0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "new_df = df.groupby(['Empresa']).sum()\n",
    "new_df[['Estudante_Cartao', 'Estudante_BT', 'Vale_Transporte', 'Integracao_Plena', 'Integracao_Complementar', 'Gratuito_Cartao', 'Gratuito_BT', 'Inteira_Cartao', 'Inteira_Especie','Tarifa_Social']].plot.bar(grid=True, stacked=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}