eusoubrasileiro/tse_hell.ipynb

## tse_hell.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DISCLAIMER\n",
    "### Na estatística, viés, pressuposições erradas e pressa nos levam a conclusões erradas!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/media/andre/LxData/tse-2022/csvs/turno2\n"
     ]
    }
   ],
   "source": [
    "%cd /media/andre/LxData/tse-2022/csvs/turno2/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "from pathlib import Path \n",
    "from matplotlib import pyplot as plt \n",
    "import seaborn as sns \n",
    "from tqdm import tqdm\n",
    "sns.set_theme()\n",
    "%matplotlib inline "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sample testing file\n",
    "#### Selecting usefull columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DS_ELEICAO</th>\n",
       "      <th>SG_UF</th>\n",
       "      <th>NM_MUNICIPIO</th>\n",
       "      <th>NR_ZONA</th>\n",
       "      <th>NR_SECAO</th>\n",
       "      <th>NR_LOCAL_VOTACAO</th>\n",
       "      <th>DS_CARGO_PERGUNTA</th>\n",
       "      <th>NR_PARTIDO</th>\n",
       "      <th>SG_PARTIDO</th>\n",
       "      <th>QT_APTOS</th>\n",
       "      <th>QT_COMPARECIMENTO</th>\n",
       "      <th>QT_ABSTENCOES</th>\n",
       "      <th>CD_TIPO_URNA</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_FLASHCARD_URNA_EFETIVADA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Eleição Geral Federal 2022</td>\n",
       "      <td>AC</td>\n",
       "      <td>RIO BRANCO</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1279</td>\n",
       "      <td>Presidente</td>\n",
       "      <td>13</td>\n",
       "      <td>PT</td>\n",
       "      <td>185</td>\n",
       "      <td>147</td>\n",
       "      <td>38</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>LULA</td>\n",
       "      <td>48</td>\n",
       "      <td>2046404</td>\n",
       "      <td>90FF9DFC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Eleição Geral Federal 2022</td>\n",
       "      <td>AC</td>\n",
       "      <td>RIO BRANCO</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1279</td>\n",
       "      <td>Presidente</td>\n",
       "      <td>-1</td>\n",
       "      <td>#NULO#</td>\n",
       "      <td>185</td>\n",
       "      <td>147</td>\n",
       "      <td>38</td>\n",
       "      <td>1</td>\n",
       "      <td>96</td>\n",
       "      <td>Nulo</td>\n",
       "      <td>1</td>\n",
       "      <td>2046404</td>\n",
       "      <td>90FF9DFC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Eleição Geral Federal 2022</td>\n",
       "      <td>AC</td>\n",
       "      <td>RIO BRANCO</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1279</td>\n",
       "      <td>Presidente</td>\n",
       "      <td>22</td>\n",
       "      <td>PL</td>\n",
       "      <td>185</td>\n",
       "      <td>147</td>\n",
       "      <td>38</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>JAIR BOLSONARO</td>\n",
       "      <td>96</td>\n",
       "      <td>2046404</td>\n",
       "      <td>90FF9DFC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Eleição Geral Federal 2022</td>\n",
       "      <td>AC</td>\n",
       "      <td>RIO BRANCO</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1279</td>\n",
       "      <td>Presidente</td>\n",
       "      <td>-1</td>\n",
       "      <td>#NULO#</td>\n",
       "      <td>185</td>\n",
       "      <td>147</td>\n",
       "      <td>38</td>\n",
       "      <td>1</td>\n",
       "      <td>95</td>\n",
       "      <td>Branco</td>\n",
       "      <td>2</td>\n",
       "      <td>2046404</td>\n",
       "      <td>90FF9DFC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Eleição Geral Federal 2022</td>\n",
       "      <td>AC</td>\n",
       "      <td>RIO BRANCO</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1139</td>\n",
       "      <td>Presidente</td>\n",
       "      <td>22</td>\n",
       "      <td>PL</td>\n",
       "      <td>339</td>\n",
       "      <td>259</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>JAIR BOLSONARO</td>\n",
       "      <td>167</td>\n",
       "      <td>2048249</td>\n",
       "      <td>90FF9DFC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   DS_ELEICAO SG_UF NM_MUNICIPIO  NR_ZONA  NR_SECAO  \\\n",
       "0  Eleição Geral Federal 2022    AC   RIO BRANCO        1         3   \n",
       "1  Eleição Geral Federal 2022    AC   RIO BRANCO        1         3   \n",
       "2  Eleição Geral Federal 2022    AC   RIO BRANCO        1         3   \n",
       "3  Eleição Geral Federal 2022    AC   RIO BRANCO        1         3   \n",
       "4  Eleição Geral Federal 2022    AC   RIO BRANCO        1         4   \n",
       "\n",
       "   NR_LOCAL_VOTACAO DS_CARGO_PERGUNTA  NR_PARTIDO SG_PARTIDO  QT_APTOS  \\\n",
       "0              1279        Presidente          13         PT       185   \n",
       "1              1279        Presidente          -1     #NULO#       185   \n",
       "2              1279        Presidente          22         PL       185   \n",
       "3              1279        Presidente          -1     #NULO#       185   \n",
       "4              1139        Presidente          22         PL       339   \n",
       "\n",
       "   QT_COMPARECIMENTO  QT_ABSTENCOES  CD_TIPO_URNA  NR_VOTAVEL      NM_VOTAVEL  \\\n",
       "0                147             38             1          13            LULA   \n",
       "1                147             38             1          96            Nulo   \n",
       "2                147             38             1          22  JAIR BOLSONARO   \n",
       "3                147             38             1          95          Branco   \n",
       "4                259             80             1          22  JAIR BOLSONARO   \n",
       "\n",
       "   QT_VOTOS  NR_URNA_EFETIVADA CD_FLASHCARD_URNA_EFETIVADA  \n",
       "0        48            2046404                    90FF9DFC  \n",
       "1         1            2046404                    90FF9DFC  \n",
       "2        96            2046404                    90FF9DFC  \n",
       "3         2            2046404                    90FF9DFC  \n",
       "4       167            2048249                    90FF9DFC  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "votos = pd.read_csv('bweb_2t_AC_311020221535.csv', encoding='cp1252', sep=';')\n",
    "votos.head(1)\n",
    "selected = \"\"\"DS_ELEICAO SG_UF NM_MUNICIPIO NR_ZONA\tNR_SECAO\tNR_LOCAL_VOTACAO DS_CARGO_PERGUNTA NR_PARTIDO SG_PARTIDO QT_APTOS QT_COMPARECIMENTO QT_ABSTENCOES CD_TIPO_URNA NR_VOTAVEL NM_VOTAVEL QT_VOTOS NR_URNA_EFETIVADA CD_FLASHCARD_URNA_EFETIVADA\"\"\".replace('\\t', ' ').split(\" \")\n",
    "votos[selected].head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Merging all *csvs boletins de urnas (only selected columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_SC_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_MA_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_PB_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_ES_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_DF_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_GO_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_AP_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_PE_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_RO_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_ZZ_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_RN_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_PA_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_PI_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_AC_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_TO_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_AM_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_SE_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_CE_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_RR_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_RJ_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_RS_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_SP_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_MT_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_AL_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_MG_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_MS_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_BA_311020221535.csv\n",
      "/media/andre/LxData/tse-2022/csvs/turno2/bweb_2t_PR_311020221535.csv\n"
     ]
    }
   ],
   "source": [
    "csvs = []\n",
    "for path in Path('.').glob('*.csv'):\n",
    "    data = pd.read_csv(path.absolute(), encoding='cp1252', sep=';')    \n",
    "    csvs.append(data[selected])\n",
    "    print(str(path.absolute()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2841231\n"
     ]
    }
   ],
   "source": [
    "csvs_todos = pd.concat(csvs, axis=0, ignore_index=True)\n",
    "print(len(csvs_todos))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Criando coluna modelo de urna pela coluna NR_URNA_EFETIVADA e tabela abaixo\n",
    "\n",
    "    2009\t999500\t1220500\n",
    "    2010\t1220501\t1345500\n",
    "    2011\t1368501\t1370500\n",
    "    2011\t1600000\t1650000\n",
    "    2013\t1650001\t1701000\n",
    "    2015\t1750000\t1950000 \n",
    "    2020\t2000000\t2250000\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def label(x):\n",
    "    if x == 1:\n",
    "        return 2009\n",
    "    if x == 2:\n",
    "        return 2010 \n",
    "    if x == 3 or x == 4:\n",
    "        return 2011\n",
    "    if x == 5:\n",
    "        return 2013\n",
    "    if x == 6:\n",
    "        return 2015\n",
    "    if x == 7:\n",
    "        return 2020 \n",
    "    else:\n",
    "        return np.nan \n",
    "\n",
    "import numpy as np \n",
    "csvs_todos['MODELO'] = np.digitize(csvs_todos.NR_URNA_EFETIVADA,bins=[999500,1220500,1345500,1370500,1650000,1701000,1950000,2250000], right=True).astype(int) # 1 is 2009, 2 is 2010 and so on\n",
    "csvs_todos['MODELO'] = csvs_todos['MODELO'].apply(label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DS_ELEICAO</th>\n",
       "      <th>SG_UF</th>\n",
       "      <th>NM_MUNICIPIO</th>\n",
       "      <th>NR_ZONA</th>\n",
       "      <th>NR_SECAO</th>\n",
       "      <th>NR_LOCAL_VOTACAO</th>\n",
       "      <th>DS_CARGO_PERGUNTA</th>\n",
       "      <th>NR_PARTIDO</th>\n",
       "      <th>SG_PARTIDO</th>\n",
       "      <th>QT_APTOS</th>\n",
       "      <th>QT_COMPARECIMENTO</th>\n",
       "      <th>QT_ABSTENCOES</th>\n",
       "      <th>CD_TIPO_URNA</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_FLASHCARD_URNA_EFETIVADA</th>\n",
       "      <th>MODELO</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>626605</th>\n",
       "      <td>Eleição Geral Federal 2022</td>\n",
       "      <td>ZZ</td>\n",
       "      <td>CIUDAD GUAYANA</td>\n",
       "      <td>1</td>\n",
       "      <td>91</td>\n",
       "      <td>1015</td>\n",
       "      <td>Presidente</td>\n",
       "      <td>-1</td>\n",
       "      <td>#NULO#</td>\n",
       "      <td>75</td>\n",
       "      <td>0</td>\n",
       "      <td>75</td>\n",
       "      <td>4</td>\n",
       "      <td>96</td>\n",
       "      <td>Nulo</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>#NULO#</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        DS_ELEICAO SG_UF    NM_MUNICIPIO  NR_ZONA  NR_SECAO  \\\n",
       "626605  Eleição Geral Federal 2022    ZZ  CIUDAD GUAYANA        1        91   \n",
       "\n",
       "        NR_LOCAL_VOTACAO DS_CARGO_PERGUNTA  NR_PARTIDO SG_PARTIDO  QT_APTOS  \\\n",
       "626605              1015        Presidente          -1     #NULO#        75   \n",
       "\n",
       "        QT_COMPARECIMENTO  QT_ABSTENCOES  CD_TIPO_URNA  NR_VOTAVEL NM_VOTAVEL  \\\n",
       "626605                  0             75             4          96       Nulo   \n",
       "\n",
       "        QT_VOTOS  NR_URNA_EFETIVADA CD_FLASHCARD_URNA_EFETIVADA  MODELO  \n",
       "626605         0                 -1                      #NULO#     NaN  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csvs_todos[csvs_todos['MODELO'].isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "csvs_todos.dropna(inplace=True) # ignore above 0 votos "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribuição de boletins de urna por modelo de Urna"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# modelos de urnas \n",
    "plt.figure(figsize=(9,9))\n",
    "csvs_todos.MODELO.hist(bins=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['DS_ELEICAO', 'SG_UF', 'NM_MUNICIPIO', 'NR_ZONA', 'NR_SECAO',\n",
       "       'NR_LOCAL_VOTACAO', 'DS_CARGO_PERGUNTA', 'NR_PARTIDO', 'SG_PARTIDO',\n",
       "       'QT_APTOS', 'QT_COMPARECIMENTO', 'QT_ABSTENCOES', 'CD_TIPO_URNA',\n",
       "       'NR_VOTAVEL', 'NM_VOTAVEL', 'QT_VOTOS', 'NR_URNA_EFETIVADA',\n",
       "       'CD_FLASHCARD_URNA_EFETIVADA', 'MODELO'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csvs_todos.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "csvs_todos.to_csv(\"/media/andre/LxData/tse-2022/csvs/turno2_todos_csvs.csv\", index=False)\n",
    "csvs_todos = pd.read_csv('/media/andre/LxData/tse-2022/csvs/turno2_todos_csvs.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>DS_ELEICAO</th>\n",
       "      <th>SG_UF</th>\n",
       "      <th>NM_MUNICIPIO</th>\n",
       "      <th>NR_ZONA</th>\n",
       "      <th>NR_SECAO</th>\n",
       "      <th>NR_LOCAL_VOTACAO</th>\n",
       "      <th>DS_CARGO_PERGUNTA</th>\n",
       "      <th>NR_PARTIDO</th>\n",
       "      <th>SG_PARTIDO</th>\n",
       "      <th>QT_APTOS</th>\n",
       "      <th>QT_COMPARECIMENTO</th>\n",
       "      <th>QT_ABSTENCOES</th>\n",
       "      <th>CD_TIPO_URNA</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_FLASHCARD_URNA_EFETIVADA</th>\n",
       "      <th>MODELO</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Eleição Geral Federal 2022</td>\n",
       "      <td>SC</td>\n",
       "      <td>ARARANGUÁ</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1015</td>\n",
       "      <td>Presidente</td>\n",
       "      <td>-1</td>\n",
       "      <td>#NULO#</td>\n",
       "      <td>391</td>\n",
       "      <td>318</td>\n",
       "      <td>73</td>\n",
       "      <td>1</td>\n",
       "      <td>95</td>\n",
       "      <td>Branco</td>\n",
       "      <td>2</td>\n",
       "      <td>1282596</td>\n",
       "      <td>009A2C50</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Eleição Geral Federal 2022</td>\n",
       "      <td>SC</td>\n",
       "      <td>ARARANGUÁ</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1015</td>\n",
       "      <td>Presidente</td>\n",
       "      <td>22</td>\n",
       "      <td>PL</td>\n",
       "      <td>391</td>\n",
       "      <td>318</td>\n",
       "      <td>73</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>JAIR BOLSONARO</td>\n",
       "      <td>221</td>\n",
       "      <td>1282596</td>\n",
       "      <td>009A2C50</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Eleição Geral Federal 2022</td>\n",
       "      <td>SC</td>\n",
       "      <td>ARARANGUÁ</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1015</td>\n",
       "      <td>Presidente</td>\n",
       "      <td>-1</td>\n",
       "      <td>#NULO#</td>\n",
       "      <td>391</td>\n",
       "      <td>318</td>\n",
       "      <td>73</td>\n",
       "      <td>1</td>\n",
       "      <td>96</td>\n",
       "      <td>Nulo</td>\n",
       "      <td>2</td>\n",
       "      <td>1282596</td>\n",
       "      <td>009A2C50</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Eleição Geral Federal 2022</td>\n",
       "      <td>SC</td>\n",
       "      <td>ARARANGUÁ</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1015</td>\n",
       "      <td>Presidente</td>\n",
       "      <td>13</td>\n",
       "      <td>PT</td>\n",
       "      <td>391</td>\n",
       "      <td>318</td>\n",
       "      <td>73</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>LULA</td>\n",
       "      <td>93</td>\n",
       "      <td>1282596</td>\n",
       "      <td>009A2C50</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Eleições Gerais Estaduais 2022</td>\n",
       "      <td>SC</td>\n",
       "      <td>ARARANGUÁ</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1015</td>\n",
       "      <td>Governador</td>\n",
       "      <td>-1</td>\n",
       "      <td>#NULO#</td>\n",
       "      <td>391</td>\n",
       "      <td>318</td>\n",
       "      <td>73</td>\n",
       "      <td>1</td>\n",
       "      <td>96</td>\n",
       "      <td>Nulo</td>\n",
       "      <td>4</td>\n",
       "      <td>1282596</td>\n",
       "      <td>009A2C50</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0                      DS_ELEICAO SG_UF NM_MUNICIPIO  NR_ZONA  \\\n",
       "0           0      Eleição Geral Federal 2022    SC    ARARANGUÁ        1   \n",
       "1           1      Eleição Geral Federal 2022    SC    ARARANGUÁ        1   \n",
       "2           2      Eleição Geral Federal 2022    SC    ARARANGUÁ        1   \n",
       "3           3      Eleição Geral Federal 2022    SC    ARARANGUÁ        1   \n",
       "4           4  Eleições Gerais Estaduais 2022    SC    ARARANGUÁ        1   \n",
       "\n",
       "   NR_SECAO  NR_LOCAL_VOTACAO DS_CARGO_PERGUNTA  NR_PARTIDO SG_PARTIDO  \\\n",
       "0         1              1015        Presidente          -1     #NULO#   \n",
       "1         1              1015        Presidente          22         PL   \n",
       "2         1              1015        Presidente          -1     #NULO#   \n",
       "3         1              1015        Presidente          13         PT   \n",
       "4         1              1015        Governador          -1     #NULO#   \n",
       "\n",
       "   QT_APTOS  QT_COMPARECIMENTO  QT_ABSTENCOES  CD_TIPO_URNA  NR_VOTAVEL  \\\n",
       "0       391                318             73             1          95   \n",
       "1       391                318             73             1          22   \n",
       "2       391                318             73             1          96   \n",
       "3       391                318             73             1          13   \n",
       "4       391                318             73             1          96   \n",
       "\n",
       "       NM_VOTAVEL  QT_VOTOS  NR_URNA_EFETIVADA CD_FLASHCARD_URNA_EFETIVADA  \\\n",
       "0          Branco         2            1282596                    009A2C50   \n",
       "1  JAIR BOLSONARO       221            1282596                    009A2C50   \n",
       "2            Nulo         2            1282596                    009A2C50   \n",
       "3            LULA        93            1282596                    009A2C50   \n",
       "4            Nulo         4            1282596                    009A2C50   \n",
       "\n",
       "   MODELO  \n",
       "0  2010.0  \n",
       "1  2010.0  \n",
       "2  2010.0  \n",
       "3  2010.0  \n",
       "4  2010.0  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csvs_todos.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Consolida urnas por MUNICIPIO e MODELO (PRESIDENTE)\n",
    "\n",
    "Cria novo dataframe com cada row correspondendo à 1 urna:  \n",
    "Votos Lula, bolsonaro, cidade, uf, modelo de urna"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 5426/5426 [11:57<00:00,  7.57it/s]  \n"
     ]
    }
   ],
   "source": [
    "votos_presidente = csvs_todos.loc[ csvs_todos['DS_CARGO_PERGUNTA'] == \"Presidente\" ]\n",
    "cidades = [] \n",
    "for name, df in tqdm(votos_presidente.groupby(csvs_todos.NM_MUNICIPIO)):\n",
    "    for urname, udf in df.groupby(df.NR_URNA_EFETIVADA):\n",
    "        bolso = sum(udf.loc[udf.NR_VOTAVEL == 22 ].QT_VOTOS)\n",
    "        lula = sum(udf.loc[udf.NR_VOTAVEL == 13 ].QT_VOTOS)\n",
    "        uf = udf.iloc[0].SG_UF\n",
    "        cidades.append(pd.DataFrame([[bolso, lula, bolso+lula, name, uf, int(udf.iloc[0].MODELO)]], columns=['bolso', 'lula', 'soma', 'cidade', 'UF', 'urna']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bolso</th>\n",
       "      <th>lula</th>\n",
       "      <th>soma</th>\n",
       "      <th>cidade</th>\n",
       "      <th>UF</th>\n",
       "      <th>urna</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>171</td>\n",
       "      <td>116</td>\n",
       "      <td>287</td>\n",
       "      <td>ABADIA DE GOIÁS</td>\n",
       "      <td>GO</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>172</td>\n",
       "      <td>111</td>\n",
       "      <td>283</td>\n",
       "      <td>ABADIA DE GOIÁS</td>\n",
       "      <td>GO</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>148</td>\n",
       "      <td>101</td>\n",
       "      <td>249</td>\n",
       "      <td>ABADIA DE GOIÁS</td>\n",
       "      <td>GO</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>160</td>\n",
       "      <td>96</td>\n",
       "      <td>256</td>\n",
       "      <td>ABADIA DE GOIÁS</td>\n",
       "      <td>GO</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>173</td>\n",
       "      <td>116</td>\n",
       "      <td>289</td>\n",
       "      <td>ABADIA DE GOIÁS</td>\n",
       "      <td>GO</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>176</td>\n",
       "      <td>84</td>\n",
       "      <td>260</td>\n",
       "      <td>ABADIA DE GOIÁS</td>\n",
       "      <td>GO</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>146</td>\n",
       "      <td>92</td>\n",
       "      <td>238</td>\n",
       "      <td>ABADIA DE GOIÁS</td>\n",
       "      <td>GO</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>143</td>\n",
       "      <td>118</td>\n",
       "      <td>261</td>\n",
       "      <td>ABADIA DE GOIÁS</td>\n",
       "      <td>GO</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>150</td>\n",
       "      <td>165</td>\n",
       "      <td>315</td>\n",
       "      <td>ABADIA DE GOIÁS</td>\n",
       "      <td>GO</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>172</td>\n",
       "      <td>113</td>\n",
       "      <td>285</td>\n",
       "      <td>ABADIA DE GOIÁS</td>\n",
       "      <td>GO</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   bolso  lula  soma           cidade  UF  urna\n",
       "0    171   116   287  ABADIA DE GOIÁS  GO  2009\n",
       "1    172   111   283  ABADIA DE GOIÁS  GO  2009\n",
       "2    148   101   249  ABADIA DE GOIÁS  GO  2009\n",
       "3    160    96   256  ABADIA DE GOIÁS  GO  2009\n",
       "4    173   116   289  ABADIA DE GOIÁS  GO  2009\n",
       "5    176    84   260  ABADIA DE GOIÁS  GO  2009\n",
       "6    146    92   238  ABADIA DE GOIÁS  GO  2009\n",
       "7    143   118   261  ABADIA DE GOIÁS  GO  2009\n",
       "8    150   165   315  ABADIA DE GOIÁS  GO  2009\n",
       "9    172   113   285  ABADIA DE GOIÁS  GO  2009"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "urnas_presidente = pd.concat(cidades, axis=0, ignore_index=True)\n",
    "urnas_presidente.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "urnas_presidente.to_csv('/media/andre/LxData/tse-2022/csvs/turno2_urnas_presidente.csv', index=False)                        \n",
    "urnas_presidente = pd.read_csv('/media/andre/LxData/tse-2022/csvs/turno2_urnas_presidente.csv')                        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 792x792 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plt.plot(.bolso, urnas_presidente.lula, 'o', alpha=0.2)\n",
    "# plt.rc('axes', labelsize=18)    # fontsize of the x and y labels\n",
    "# plt.xlabel(\"Bolsonaro\")\n",
    "# plt.ylabel(\"Lula\")\n",
    "# plt.title(\"Soma votos por Urnas (x, y) (Bolsonaro, Lula)\")\n",
    "sns.set_style(\"dark\")\n",
    "# urnas_presidente.query(\"urna == 2020\")\n",
    "g = sns.jointplot(data=urnas_presidente, x=\"bolso\", y=\"lula\", hue=\"urna\", alpha=0.7, kind='hist',\n",
    "                  xlim=(0,400), ylim=(0,400), palette='rainbow',\n",
    "                  marginal_kws=dict(bins=70, fill=True), marginal_ticks=True)\n",
    "#g.fig.set_dpi(200)\n",
    "g.fig.set_size_inches(11,11)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Northeast cities with less than 100,000 voters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Lista de cidades por população de votantes\n",
    "\n",
    "cuttoff 100K "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [],
   "source": [
    "small_cities = urnas_presidente.groupby(urnas_presidente.cidade).agg({\"soma\" : \"sum\"}).query(\"soma < 100e3\").index.to_list()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Pega somente cidades que tenham urnas 2020 AND alguma das outras != 2020"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>urna</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UF</th>\n",
       "      <th>cidade</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">MA</th>\n",
       "      <th>CAXIAS</th>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHAPADINHA</th>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COLINAS</th>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PINHEIRO</th>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SANTA INÊS</th>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SANTA LUZIA DO PARUÁ</th>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         urna\n",
       "UF cidade                    \n",
       "MA CAXIAS                True\n",
       "   CHAPADINHA            True\n",
       "   COLINAS               True\n",
       "   PINHEIRO              True\n",
       "   SANTA INÊS            True\n",
       "   SANTA LUZIA DO PARUÁ  True"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ufs_northeast = \"\"\"MA PI CE RN PB PE AL SE BA\"\"\".split(' ')\n",
    "urnas_presidente_neast = urnas_presidente.query(\"cidade == @small_cities and UF == @ufs_northeast\")\n",
    "def func(x):\n",
    "    return 2020 in x.values and x.nunique() > 1\n",
    "urnas_presidente_neast.groupby(['UF','cidade']).agg({'urna' : func }).query(\"urna == True\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Somente essas cidades do Maranhão tem urnas com esses critérios"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [],
   "source": [
    "cities_neast_ma = urnas_presidente_neast.groupby(['UF','cidade']).agg({'urna' : func }).query(\"urna == True\").index.map(lambda x: x[1]).to_list()\n",
    "urnas_presidente_ma =  urnas_presidente_neast.query(\"UF == 'MA' and cidade == @cities_neast_ma\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### probability density function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import norm\n",
    "\n",
    "def plot_pdf(mean, std, color='k'):\n",
    "    xmin, xmax = plt.xlim()\n",
    "    mu, std = mean, std\n",
    "    x = np.linspace(10, 120, 100)\n",
    "    p = norm.pdf(x, mu, std)\n",
    "    plt.plot(x, p, color=color, linewidth=1)\n",
    "    return mu, std "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean 75.00 std 10.812\n",
      "mean 70.87 std 9.007\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f7807ec8df0>"
      ]
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18,6))\n",
    "plt.rc('axes', labelsize=30)    # fontsize of the x and y labels\n",
    "plt.rc('legend', fontsize=25)    # fontsize of the x and y labels\n",
    "plt.rc('axes', labelsize=30)    # fontsize of the x and y labels\n",
    "perc_lula = 100*urnas_presidente_ma.query('urna == 2020').lula/urnas_presidente_ma.query('urna == 2020').soma\n",
    "perc_lula.hist(bins=20, alpha=0.85, label='Votos Lula Urnas 2020', density=True)\n",
    "mu, std = plot_pdf(perc_lula.mean(), perc_lula.std(), 'b')\n",
    "print(f\"mean {mu:.2f} std {std:.3f}\")\n",
    "perc_lula = 100*urnas_presidente_ma.query('urna != 2020').lula/urnas_presidente_ma.query('urna != 2020').soma\n",
    "perc_lula.hist(bins=10, color='r', alpha=0.6, label='Votos Lula Urnas != 2020', density=True)\n",
    "mu, std  = plot_pdf(perc_lula.mean(), perc_lula.std(), 'r')\n",
    "print(f\"mean {mu:.2f} std {std:.3f}\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## O ERRO!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Se pagarmos urnas de cidades do nordeste misturando modelos de cidades diferentes\n",
    "\n",
    "Ou seja, cidades que só tem 1 ou mais modelo de urna 2013, 2015 etc todos diferentes de 2020 ou qualquer combinação delas.   \n",
    "E toda as que só tem urnas 2020. \n",
    "\n",
    "Isso viola o pressuposto estatístico que é que cada cidade tem uma distribuição estatística específica.  \n",
    "Por exemplo, simplificando. Acabamos comparando urnas do modelo 2020 da cidade A com urnas de modelos 2013, 1015 etc. da cidade B.  \n",
    "Como cidade A e cidade B são ambientes eleitorais diferentes não se pode afirmar que suas urnas devem apresentar mesma distribuição estatística.  \n",
    "\n",
    "Exemplo mais detalhado. Na prática nesse gráfico são comparadas urnas das cidades A, B, C etc. modelo 2020 com urnas das cidades E, F, G, H, I etc... com outros modelos.  \n",
    "Mas as distribuições das cidades A, B, C, D, E, F, G, H, I são inerentemente diferentes entre si.  \n",
    "Só poderiam ser comparadas urnas 2020 de A com urnas != 2020 em A. Urnas 2020 de B com urnas != 2020 de B. E assim sucessivamente.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean 70.25 std 12.100\n",
      "mean 76.04 std 11.498\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f7807a25d90>"
      ]
     },
     "execution_count": 210,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18,6))\n",
    "plt.rc('axes', labelsize=30)    # fontsize of the x and y labels\n",
    "plt.rc('legend', fontsize=25)    # fontsize of the x and y labels\n",
    "plt.rc('axes', labelsize=30)    # fontsize of the x and y labels\n",
    "perc_lula = 100*urnas_presidente_neast.query('urna == 2020').lula/urnas_presidente_neast.query('urna == 2020').soma\n",
    "perc_lula.hist(bins=60, alpha=0.85, label='Votos Lula Urnas 2020', density=True)\n",
    "mu, std = plot_pdf(perc_lula.mean(), perc_lula.std(), 'b')\n",
    "print(f\"mean {mu:.2f} std {std:.3f}\")\n",
    "perc_lula = 100*urnas_presidente_neast.query('urna != 2020').lula/urnas_presidente_neast.query('urna != 2020').soma\n",
    "perc_lula.hist(bins=60, color='r', alpha=0.6, label='Votos Lula Urnas != 2020', density=True)\n",
    "mu, std  = plot_pdf(perc_lula.mean(), perc_lula.std(), 'r')\n",
    "print(f\"mean {mu:.2f} std {std:.3f}\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.8.13 ('venv')",
   "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": "3.8.13"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "ebbbdb4dcc65f109a05ca07877b74b724f0107aa4d6c6ae9e77a0bd67ffa0b43"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}