{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](https://github.com/bigdata-icict/ETL-Dataiku-DSS/raw/master/tutoriais/pcdas_1.5.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Notebook para criação de tabela de indicadores da PNS - módulo O 2013 Acidentes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bibliotecas Utilizadas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lendo pacotes necessários\n",
    "library(survey)\n",
    "library(dplyr)\n",
    "library(tictoc)\n",
    "library(foreign)\n",
    "library(forcats)\n",
    "library(tidyverse)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Carregando microdados da PNS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Carregando banco de dados\n",
    "load(\"<coloque aqui o caminho para o arquivo dos microdados formato RDATA>\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Definição do peso e filtragem de respondentes do questionário"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "     Min.   1st Qu.    Median      Mean   3rd Qu.      Max. \n",
       " 0.004156  0.243959  0.521557  1.000000  1.147413 31.179597 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Selecionando registros válidos para o módulo P e calculando peso amostral - summary de verificação\n",
    "pns2013.1<-pns2013 %>% filter(M001==1)\n",
    "pns2013.1<-pns2013.1 %>% mutate(peso_morador_selec=((V00291*(60202/145572211))))\n",
    "pns2013.1<-pns2013.1 %>% filter(!is.na(peso_morador_selec))\n",
    "summary(pns2013.1$peso_morador_selec)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Criação de variáveis dos indicadores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>Sim</dt><dd>25855</dd><dt>Não</dt><dd>27307</dd><dt>NA's</dt><dd>7040</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Sim] 25855\n",
       "\\item[Não] 27307\n",
       "\\item[NA's] 7040\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Sim\n",
       ":   25855Não\n",
       ":   27307NA's\n",
       ":   7040\n",
       "\n"
      ],
      "text/plain": [
       "  Sim   Não  NA's \n",
       "25855 27307  7040 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>Sim</dt><dd>11780</dd><dt>Não</dt><dd>2547</dd><dt>NA's</dt><dd>45875</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Sim] 11780\n",
       "\\item[Não] 2547\n",
       "\\item[NA's] 45875\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Sim\n",
       ":   11780Não\n",
       ":   2547NA's\n",
       ":   45875\n",
       "\n"
      ],
      "text/plain": [
       "  Sim   Não  NA's \n",
       "11780  2547 45875 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>Sim</dt><dd>24130</dd><dt>Não</dt><dd>5687</dd><dt>NA's</dt><dd>30385</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Sim] 24130\n",
       "\\item[Não] 5687\n",
       "\\item[NA's] 30385\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Sim\n",
       ":   24130Não\n",
       ":   5687NA's\n",
       ":   30385\n",
       "\n"
      ],
      "text/plain": [
       "  Sim   Não  NA's \n",
       "24130  5687 30385 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>Sim</dt><dd>1910</dd><dt>Não</dt><dd>58292</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Sim] 1910\n",
       "\\item[Não] 58292\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Sim\n",
       ":   1910Não\n",
       ":   58292\n",
       "\n"
      ],
      "text/plain": [
       "  Sim   Não \n",
       " 1910 58292 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Usa sempre cinto quando anda no banco de trás de automóvel. - O002P\n",
    "pns2013.1 <- pns2013.1 %>% mutate(O002P=ifelse(O005==1, NA, ifelse(O005==2, 1, 2)))\n",
    "pns2013.1$O002P<-factor(pns2013.1$O002P, levels=c(1,2), labels=c(\"Sim\",\"Não\"))\n",
    "summary(pns2013.1$O002P)\n",
    "\n",
    "#Usa sempre capacete quando dirige motocicleta. - O003P\n",
    "\n",
    "pns2013.1 <- pns2013.1 %>% mutate(O003P= ifelse(O007==1, 1, 2))\n",
    "pns2013.1$O003P<-factor(pns2013.1$O003P, levels=c(1,2), labels=c(\"Sim\",\"Não\"))\n",
    "summary(pns2013.1$O003P)\n",
    "\n",
    "#Usa sempre capacete quando está como passageiro de motocicleta. - O004P\n",
    "pns2013.1 <- pns2013.1  %>% mutate(O004P= ifelse(O008==1,NA,ifelse(O008==2,1,2)))\n",
    "pns2013.1$O004P<-factor(pns2013.1$O004P, levels=c(1,2), labels=c(\"Sim\",\"Não\"))\n",
    "summary(pns2013.1$O004P)\n",
    "\n",
    "#Usa sempre capacete quando está como passageiro de motocicleta. - O006P\n",
    "pns2013.1 <- pns2013.1  %>% mutate(O006P = ifelse(O009==1,1,\n",
    "                                          ifelse(O009==2,2,2)))   \n",
    "pns2013.1$O006P<-factor(pns2013.1$O006P, levels=c(1,2), labels=c(\"Sim\",\"Não\"))\n",
    "summary(pns2013.1$O006P)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Definições de abrangências"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Situação urbana ou rural"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>urbano</dt><dd>49245</dd><dt>rural</dt><dd>10957</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[urbano] 49245\n",
       "\\item[rural] 10957\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "urbano\n",
       ":   49245rural\n",
       ":   10957\n",
       "\n"
      ],
      "text/plain": [
       "urbano  rural \n",
       " 49245  10957 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Situação Urbano ou Rural\n",
    "pns2013.1 <- pns2013.1 %>% rename(Sit_Urbano_Rural=V0026)\n",
    "pns2013.1$Sit_Urbano_Rural<-factor(pns2013.1$Sit_Urbano_Rural, levels=c(1,2), labels=c(\"urbano\", \"rural\"))\n",
    "summary(pns2013.1$Sit_Urbano_Rural)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sexo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>Masculino</dt><dd>25920</dd><dt>Feminino</dt><dd>34282</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Masculino] 25920\n",
       "\\item[Feminino] 34282\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Masculino\n",
       ":   25920Feminino\n",
       ":   34282\n",
       "\n"
      ],
      "text/plain": [
       "Masculino  Feminino \n",
       "    25920     34282 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Sexo\n",
    "pns2013.1 <- pns2013.1 %>% rename(Sexo=C006)\n",
    "pns2013.1$Sexo<-factor(pns2013.1$Sexo, levels=c(1,2), labels=c(\"Masculino\", \"Feminino\"))\n",
    "summary(pns2013.1$Sexo)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### UF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>Rondônia</dt><dd>1694</dd><dt>Acre</dt><dd>1814</dd><dt>Amazonas</dt><dd>2586</dd><dt>Roraima</dt><dd>1591</dd><dt>Pará</dt><dd>2004</dd><dt>Amapá</dt><dd>1332</dd><dt>Tocantins</dt><dd>1515</dd><dt>Maranhão</dt><dd>1774</dd><dt>Piauí</dt><dd>1804</dd><dt>Ceará</dt><dd>2560</dd><dt>Rio Grande do Norte</dt><dd>1691</dd><dt>Paraíba</dt><dd>1943</dd><dt>Pernambuco</dt><dd>2591</dd><dt>Alagoas</dt><dd>1748</dd><dt>Sergipe</dt><dd>1553</dd><dt>Bahia</dt><dd>2641</dd><dt>Minas Gerais</dt><dd>3779</dd><dt>Espírito Santo</dt><dd>1724</dd><dt>Rio de Janeiro</dt><dd>3486</dd><dt>São Paulo</dt><dd>5305</dd><dt>Paraná</dt><dd>3012</dd><dt>Santa Catarina</dt><dd>1623</dd><dt>Rio Grande do Sul</dt><dd>2913</dd><dt>Mato Grosso do Sul</dt><dd>1809</dd><dt>Mato Grosso</dt><dd>1476</dd><dt>Goiás</dt><dd>2423</dd><dt>Distrito Federal</dt><dd>1811</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Rondônia] 1694\n",
       "\\item[Acre] 1814\n",
       "\\item[Amazonas] 2586\n",
       "\\item[Roraima] 1591\n",
       "\\item[Pará] 2004\n",
       "\\item[Amapá] 1332\n",
       "\\item[Tocantins] 1515\n",
       "\\item[Maranhão] 1774\n",
       "\\item[Piauí] 1804\n",
       "\\item[Ceará] 2560\n",
       "\\item[Rio Grande do Norte] 1691\n",
       "\\item[Paraíba] 1943\n",
       "\\item[Pernambuco] 2591\n",
       "\\item[Alagoas] 1748\n",
       "\\item[Sergipe] 1553\n",
       "\\item[Bahia] 2641\n",
       "\\item[Minas Gerais] 3779\n",
       "\\item[Espírito Santo] 1724\n",
       "\\item[Rio de Janeiro] 3486\n",
       "\\item[São Paulo] 5305\n",
       "\\item[Paraná] 3012\n",
       "\\item[Santa Catarina] 1623\n",
       "\\item[Rio Grande do Sul] 2913\n",
       "\\item[Mato Grosso do Sul] 1809\n",
       "\\item[Mato Grosso] 1476\n",
       "\\item[Goiás] 2423\n",
       "\\item[Distrito Federal] 1811\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Rondônia\n",
       ":   1694Acre\n",
       ":   1814Amazonas\n",
       ":   2586Roraima\n",
       ":   1591Pará\n",
       ":   2004Amapá\n",
       ":   1332Tocantins\n",
       ":   1515Maranhão\n",
       ":   1774Piauí\n",
       ":   1804Ceará\n",
       ":   2560Rio Grande do Norte\n",
       ":   1691Paraíba\n",
       ":   1943Pernambuco\n",
       ":   2591Alagoas\n",
       ":   1748Sergipe\n",
       ":   1553Bahia\n",
       ":   2641Minas Gerais\n",
       ":   3779Espírito Santo\n",
       ":   1724Rio de Janeiro\n",
       ":   3486São Paulo\n",
       ":   5305Paraná\n",
       ":   3012Santa Catarina\n",
       ":   1623Rio Grande do Sul\n",
       ":   2913Mato Grosso do Sul\n",
       ":   1809Mato Grosso\n",
       ":   1476Goiás\n",
       ":   2423Distrito Federal\n",
       ":   1811\n",
       "\n"
      ],
      "text/plain": [
       "           Rondônia                Acre            Amazonas             Roraima \n",
       "               1694                1814                2586                1591 \n",
       "               Pará               Amapá           Tocantins            Maranhão \n",
       "               2004                1332                1515                1774 \n",
       "              Piauí               Ceará Rio Grande do Norte             Paraíba \n",
       "               1804                2560                1691                1943 \n",
       "         Pernambuco             Alagoas             Sergipe               Bahia \n",
       "               2591                1748                1553                2641 \n",
       "       Minas Gerais      Espírito Santo      Rio de Janeiro           São Paulo \n",
       "               3779                1724                3486                5305 \n",
       "             Paraná      Santa Catarina   Rio Grande do Sul  Mato Grosso do Sul \n",
       "               3012                1623                2913                1809 \n",
       "        Mato Grosso               Goiás    Distrito Federal \n",
       "               1476                2423                1811 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Estados - UFs\n",
    "pns2013.1 <- pns2013.1 %>% rename(Unidades_da_Federacao=V0001)\n",
    "pns2013.1$Unidades_da_Federacao<-factor(pns2013.1$Unidades_da_Federacao, levels=c(11,12,13,14,15,16,17,21,22,23,24,25,26,27,28,29,31,32,33,35,41,42,43,50,51,52,53),\n",
    "                                       label=c(\"Rondônia\",\"Acre\",\"Amazonas\",\"Roraima\",\"Pará\",\"Amapá\",\"Tocantins\",\"Maranhão\",\"Piauí\",\"Ceará\",\n",
    "                                        \"Rio Grande do Norte\",\"Paraíba\",\"Pernambuco\",\"Alagoas\",\"Sergipe\",\"Bahia\",\n",
    "                                        \"Minas Gerais\",\"Espírito Santo\",\"Rio de Janeiro\",\"São Paulo\",\n",
    "                                        \"Paraná\",\"Santa Catarina\",\"Rio Grande do Sul\", \n",
    "                                        \"Mato Grosso do Sul\",\"Mato Grosso\",\"Goiás\",\"Distrito Federal\"))\n",
    "summary(pns2013.1$Unidades_da_Federacao)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Grandes Regiões"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>Norte</dt><dd>12536</dd><dt>Nordeste</dt><dd>18305</dd><dt>Sudeste</dt><dd>14294</dd><dt>Sul</dt><dd>7548</dd><dt>Centro-Oeste</dt><dd>7519</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Norte] 12536\n",
       "\\item[Nordeste] 18305\n",
       "\\item[Sudeste] 14294\n",
       "\\item[Sul] 7548\n",
       "\\item[Centro-Oeste] 7519\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Norte\n",
       ":   12536Nordeste\n",
       ":   18305Sudeste\n",
       ":   14294Sul\n",
       ":   7548Centro-Oeste\n",
       ":   7519\n",
       "\n"
      ],
      "text/plain": [
       "       Norte     Nordeste      Sudeste          Sul Centro-Oeste \n",
       "       12536        18305        14294         7548         7519 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Grandes Regiões\n",
    "pns2013.1 <- pns2013.1 %>% \n",
    "  mutate(GrandesRegioes = fct_collapse(Unidades_da_Federacao, \n",
    "                                          `Norte` = c(\"Rondônia\",\"Acre\",\"Amazonas\",\"Roraima\",\"Pará\", \"Amapá\",\"Tocantins\"),\n",
    "                                          `Nordeste` = c(\"Maranhão\", \"Piauí\", \"Ceará\", \"Rio Grande do Norte\", \"Paraíba\",\"Pernambuco\", \"Alagoas\",\"Sergipe\",\"Bahia\"),\n",
    "                                          `Sudeste` = c(\"Minas Gerais\", \"Espírito Santo\",\"Rio de Janeiro\", \"São Paulo\"), \n",
    "                                          `Sul` = c(\"Paraná\", \"Santa Catarina\", \"Rio Grande do Sul\"),\n",
    "                                          `Centro-Oeste`= c(\"Mato Grosso do Sul\",\"Mato Grosso\", \"Goiás\", \"Distrito Federal\")))\n",
    "summary(pns2013.1$GrandesRegioes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Faixa Etária"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>18 a 29 anos</dt><dd>14321</dd><dt>30 a 44 anos</dt><dd>20242</dd><dt>45 a 59 anos</dt><dd>14462</dd><dt>60 anos ou mais</dt><dd>11177</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[18 a 29 anos] 14321\n",
       "\\item[30 a 44 anos] 20242\n",
       "\\item[45 a 59 anos] 14462\n",
       "\\item[60 anos ou mais] 11177\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "18 a 29 anos\n",
       ":   1432130 a 44 anos\n",
       ":   2024245 a 59 anos\n",
       ":   1446260 anos ou mais\n",
       ":   11177\n",
       "\n"
      ],
      "text/plain": [
       "   18 a 29 anos    30 a 44 anos    45 a 59 anos 60 anos ou mais \n",
       "          14321           20242           14462           11177 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Faixas Etárias\n",
    "pns2013.1 <-  pns2013.1 %>% mutate(faixa_idade=cut(C008,\n",
    "  breaks = c(18,30, 45, 60,Inf),\n",
    "  labels = c(\"18 a 29 anos\",\"30 a 44 anos\",\"45 a 59 anos\",\"60 anos ou mais\"), \n",
    "  ordered_result = TRUE, right = FALSE))\n",
    "summary(pns2013.1$faixa_idade) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Raça"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>Branca</dt><dd>24106</dd><dt>Preta</dt><dd>5631</dd><dt>Parda</dt><dd>29512</dd><dt>NA's</dt><dd>953</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Branca] 24106\n",
       "\\item[Preta] 5631\n",
       "\\item[Parda] 29512\n",
       "\\item[NA's] 953\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Branca\n",
       ":   24106Preta\n",
       ":   5631Parda\n",
       ":   29512NA's\n",
       ":   953\n",
       "\n"
      ],
      "text/plain": [
       "Branca  Preta  Parda   NA's \n",
       " 24106   5631  29512    953 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Raça\n",
    "pns2013.1 <- pns2013.1 %>% mutate(Raca= ifelse(C009==1, 1, \n",
    "                                        ifelse(C009==2, 2, \n",
    "                                        ifelse(C009==4, 3, 9))))\n",
    "\n",
    "pns2013.1$Raca<-factor(pns2013.1$Raca, levels=c(1,2,3),labels=c(\"Branca\", \"Preta\", \"Parda\"))\n",
    "\n",
    "summary(pns2013.1$Raca)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Renda per capita"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>Até 1/2 SM</dt><dd>14256</dd><dt>1/2 até 1 SM</dt><dd>17504</dd><dt>1 até 2 SM</dt><dd>15493</dd><dt>2 até 3 SM</dt><dd>5335</dd><dt>Mais de 3 SM</dt><dd>7603</dd><dt>NA's</dt><dd>11</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Até 1/2 SM] 14256\n",
       "\\item[1/2 até 1 SM] 17504\n",
       "\\item[1 até 2 SM] 15493\n",
       "\\item[2 até 3 SM] 5335\n",
       "\\item[Mais de 3 SM] 7603\n",
       "\\item[NA's] 11\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Até 1/2 SM\n",
       ":   142561/2 até 1 SM\n",
       ":   175041 até 2 SM\n",
       ":   154932 até 3 SM\n",
       ":   5335Mais de 3 SM\n",
       ":   7603NA's\n",
       ":   11\n",
       "\n"
      ],
      "text/plain": [
       "  Até 1/2 SM 1/2 até 1 SM   1 até 2 SM   2 até 3 SM Mais de 3 SM         NA's \n",
       "       14256        17504        15493         5335         7603           11 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Rendimento domiciliar per capita\n",
    "pns2013.1 <-  pns2013.1  %>% mutate(rend_per_capita=cut(VDF003,\n",
    "  breaks = c(-Inf,339, 678, 1356, 2034,Inf),\n",
    "  labels=c(\"Até 1/2 SM\",\"1/2 até 1 SM\",\"1 até 2 SM\",\"2 até 3 SM\",\"Mais de 3 SM\"), \n",
    "  ordered_result = TRUE, right = TRUE, na.exclude= TRUE))\n",
    "\n",
    "summary(pns2013.1$rend_per_capita)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Escolaridade"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>Fundamental incompleto ou equivalente</dt><dd>24083</dd><dt>Médio incompleto ou equivalente</dt><dd>9215</dd><dt>Superior incompleto ou equivalente</dt><dd>19149</dd><dt>Superior completo</dt><dd>7755</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Fundamental incompleto ou equivalente] 24083\n",
       "\\item[Médio incompleto ou equivalente] 9215\n",
       "\\item[Superior incompleto ou equivalente] 19149\n",
       "\\item[Superior completo] 7755\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Fundamental incompleto ou equivalente\n",
       ":   24083Médio incompleto ou equivalente\n",
       ":   9215Superior incompleto ou equivalente\n",
       ":   19149Superior completo\n",
       ":   7755\n",
       "\n"
      ],
      "text/plain": [
       "Fundamental incompleto ou equivalente       Médio incompleto ou equivalente \n",
       "                                24083                                  9215 \n",
       "   Superior incompleto ou equivalente                     Superior completo \n",
       "                                19149                                  7755 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Escolaridade\n",
    "pns2013.1 <- pns2013.1 %>% mutate(gescol = ifelse(VDD004A %in% 1:2, 1, \n",
    "                        ifelse(VDD004A%in% 3:4, 2, \n",
    "                        ifelse(VDD004A%in% 5:6, 3,4\n",
    "                        ))))\n",
    "\n",
    "pns2013.1$gescol<-factor(pns2013.1$gescol, levels=c(1,2,3,4), \n",
    "                                   labels=c(\"Fundamental incompleto ou equivalente\",\"Médio incompleto ou equivalente\",\n",
    "                                           \"Superior incompleto ou equivalente\",\"Superior completo\"))\n",
    "summary(pns2013.1$gescol)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Capital"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>Porto Velho</dt><dd>1694</dd><dt>Rio Branco</dt><dd>1814</dd><dt>Manaus</dt><dd>2586</dd><dt>Boa Vista</dt><dd>1591</dd><dt>Belém</dt><dd>2004</dd><dt>Macapá</dt><dd>1332</dd><dt>Palmas</dt><dd>1515</dd><dt>São Luís</dt><dd>1774</dd><dt>Teresina</dt><dd>1804</dd><dt>Fortaleza</dt><dd>2560</dd><dt>Natal</dt><dd>1691</dd><dt>João Pessoa</dt><dd>1943</dd><dt>Recife</dt><dd>2591</dd><dt>Maceió</dt><dd>1748</dd><dt>Aracaju</dt><dd>1553</dd><dt>Salvador</dt><dd>2641</dd><dt>Belo Horizonte</dt><dd>3779</dd><dt>Vitória</dt><dd>1724</dd><dt>Rio de Janeiro</dt><dd>3486</dd><dt>São Paulo</dt><dd>5305</dd><dt>Curitiba</dt><dd>3012</dd><dt>Florianópolis</dt><dd>1623</dd><dt>Porto Alegre</dt><dd>2913</dd><dt>Campo Grande</dt><dd>1809</dd><dt>Cuiabá</dt><dd>1476</dd><dt>Goiânia</dt><dd>2423</dd><dt>Brasília</dt><dd>1811</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Porto Velho] 1694\n",
       "\\item[Rio Branco] 1814\n",
       "\\item[Manaus] 2586\n",
       "\\item[Boa Vista] 1591\n",
       "\\item[Belém] 2004\n",
       "\\item[Macapá] 1332\n",
       "\\item[Palmas] 1515\n",
       "\\item[São Luís] 1774\n",
       "\\item[Teresina] 1804\n",
       "\\item[Fortaleza] 2560\n",
       "\\item[Natal] 1691\n",
       "\\item[João Pessoa] 1943\n",
       "\\item[Recife] 2591\n",
       "\\item[Maceió] 1748\n",
       "\\item[Aracaju] 1553\n",
       "\\item[Salvador] 2641\n",
       "\\item[Belo Horizonte] 3779\n",
       "\\item[Vitória] 1724\n",
       "\\item[Rio de Janeiro] 3486\n",
       "\\item[São Paulo] 5305\n",
       "\\item[Curitiba] 3012\n",
       "\\item[Florianópolis] 1623\n",
       "\\item[Porto Alegre] 2913\n",
       "\\item[Campo Grande] 1809\n",
       "\\item[Cuiabá] 1476\n",
       "\\item[Goiânia] 2423\n",
       "\\item[Brasília] 1811\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Porto Velho\n",
       ":   1694Rio Branco\n",
       ":   1814Manaus\n",
       ":   2586Boa Vista\n",
       ":   1591Belém\n",
       ":   2004Macapá\n",
       ":   1332Palmas\n",
       ":   1515São Luís\n",
       ":   1774Teresina\n",
       ":   1804Fortaleza\n",
       ":   2560Natal\n",
       ":   1691João Pessoa\n",
       ":   1943Recife\n",
       ":   2591Maceió\n",
       ":   1748Aracaju\n",
       ":   1553Salvador\n",
       ":   2641Belo Horizonte\n",
       ":   3779Vitória\n",
       ":   1724Rio de Janeiro\n",
       ":   3486São Paulo\n",
       ":   5305Curitiba\n",
       ":   3012Florianópolis\n",
       ":   1623Porto Alegre\n",
       ":   2913Campo Grande\n",
       ":   1809Cuiabá\n",
       ":   1476Goiânia\n",
       ":   2423Brasília\n",
       ":   1811\n",
       "\n"
      ],
      "text/plain": [
       "   Porto Velho     Rio Branco         Manaus      Boa Vista          Belém \n",
       "          1694           1814           2586           1591           2004 \n",
       "        Macapá         Palmas       São Luís       Teresina      Fortaleza \n",
       "          1332           1515           1774           1804           2560 \n",
       "         Natal    João Pessoa         Recife         Maceió        Aracaju \n",
       "          1691           1943           2591           1748           1553 \n",
       "      Salvador Belo Horizonte        Vitória Rio de Janeiro      São Paulo \n",
       "          2641           3779           1724           3486           5305 \n",
       "      Curitiba  Florianópolis   Porto Alegre   Campo Grande         Cuiabá \n",
       "          3012           1623           2913           1809           1476 \n",
       "       Goiânia       Brasília \n",
       "          2423           1811 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Capital\n",
    "pns2013.1<- pns2013.1 %>% mutate(Capital= fct_collapse(Unidades_da_Federacao,\n",
    "                                        `Porto Velho`= \"Rondônia\", \n",
    "                                        `Boa Vista`= \"Roraima\",              \n",
    "                                        `Rio Branco`= \"Acre\", \n",
    "                                        `Manaus` = \"Amazonas\",\n",
    "                                        `Belém` = \"Pará\" ,\n",
    "                                        `Macapá`= \"Amapá\",\n",
    "                                        `Palmas` = \"Tocantins\",\n",
    "                                        `São Luís` = \"Maranhão\",\n",
    "                                        `Teresina`= \"Piauí\" ,\n",
    "                                        `Fortaleza`= \"Ceará\",\n",
    "                                        `Natal`= \"Rio Grande do Norte\",\n",
    "                                        `João Pessoa`= \"Paraíba\",\n",
    "                                        `Recife`= \"Pernambuco\",\n",
    "                                        `Maceió`= \"Alagoas\",\n",
    "                                        `Aracaju`= \"Sergipe\",\n",
    "                                        `Salvador`= \"Bahia\",\n",
    "                                        `Belo Horizonte`= \"Minas Gerais\",\n",
    "                                        `Vitória`= \"Espírito Santo\",\n",
    "                                        `Rio de Janeiro`= \"Rio de Janeiro\",\n",
    "                                        `São Paulo`= \"São Paulo\",\n",
    "                                        `Curitiba`= \"Paraná\",\n",
    "                                        `Florianópolis`= \"Santa Catarina\",\n",
    "                                        `Porto Alegre`= \"Rio Grande do Sul\",\n",
    "                                        `Campo Grande`=  \"Mato Grosso do Sul\",\n",
    "                                        `Cuiabá`= \"Mato Grosso\",\n",
    "                                        `Goiânia` = \"Goiás\",\n",
    "                                        `Brasília`= \"Distrito Federal\"))\n",
    "summary(pns2013.1$Capital)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Criando indicadores"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Filtrando base de indicadores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "     V0024            UPA_PNS        peso_morador_selec   O002P      \n",
       " Min.   :1110011   Min.   :1100001   Min.   : 0.004156   Sim :25855  \n",
       " 1st Qu.:2210013   1st Qu.:2200075   1st Qu.: 0.243959   Não :27307  \n",
       " Median :2951023   Median :2900192   Median : 0.521557   NA's: 7040  \n",
       " Mean   :3035353   Mean   :3007819   Mean   : 1.000000               \n",
       " 3rd Qu.:4110111   3rd Qu.:4100002   3rd Qu.: 1.147413               \n",
       " Max.   :5310220   Max.   :5300180   Max.   :31.179597               \n",
       "                                                                     \n",
       "  O003P        O004P       O006P            C008             C009     \n",
       " Sim :11780   Sim :24130   Sim: 1910   Min.   : 18.00   Min.   :1.00  \n",
       " Não : 2547   Não : 5687   Não:58292   1st Qu.: 30.00   1st Qu.:1.00  \n",
       " NA's:45875   NA's:30385               Median : 41.00   Median :3.00  \n",
       "                                       Mean   : 43.31   Mean   :2.61  \n",
       "                                       3rd Qu.: 55.00   3rd Qu.:4.00  \n",
       "                                       Max.   :101.00   Max.   :9.00  \n",
       "                                                                      \n",
       "     V0031       Sit_Urbano_Rural        Sexo             Unidades_da_Federacao\n",
       " Min.   :1.000   urbano:49245     Masculino:25920   São Paulo        : 5305    \n",
       " 1st Qu.:1.000   rural :10957     Feminino :34282   Minas Gerais     : 3779    \n",
       " Median :2.000                                      Rio de Janeiro   : 3486    \n",
       " Mean   :2.308                                      Paraná           : 3012    \n",
       " 3rd Qu.:4.000                                      Rio Grande do Sul: 2913    \n",
       " Max.   :4.000                                      Bahia            : 2641    \n",
       "                                                    (Other)          :39066    \n",
       "      GrandesRegioes           faixa_idade        Raca      \n",
       " Norte       :12536   18 a 29 anos   :14321   Branca:24106  \n",
       " Nordeste    :18305   30 a 44 anos   :20242   Preta : 5631  \n",
       " Sudeste     :14294   45 a 59 anos   :14462   Parda :29512  \n",
       " Sul         : 7548   60 anos ou mais:11177   NA's  :  953  \n",
       " Centro-Oeste: 7519                                         \n",
       "                                                            \n",
       "                                                            \n",
       "     rend_per_capita                                    gescol     \n",
       " Até 1/2 SM  :14256   Fundamental incompleto ou equivalente:24083  \n",
       " 1/2 até 1 SM:17504   Médio incompleto ou equivalente      : 9215  \n",
       " 1 até 2 SM  :15493   Superior incompleto ou equivalente   :19149  \n",
       " 2 até 3 SM  : 5335   Superior completo                    : 7755  \n",
       " Mais de 3 SM: 7603                                                \n",
       " NA's        :   11                                                \n",
       "                                                                   \n",
       "           Capital     \n",
       " São Paulo     : 5305  \n",
       " Belo Horizonte: 3779  \n",
       " Rio de Janeiro: 3486  \n",
       " Curitiba      : 3012  \n",
       " Porto Alegre  : 2913  \n",
       " Salvador      : 2641  \n",
       " (Other)       :39066  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Selecionando variáveis para cálculo de indicadores no survey\n",
    "pns2013Osurvey<- pns2013.1 %>% select(\"V0024\",\"UPA_PNS\",\"peso_morador_selec\", \"O002P\",\"O003P\",\"O004P\", \"O006P\",\n",
    "                                     \"C008\",\"C009\",\"V0031\",\"Sit_Urbano_Rural\",\"Sexo\",\"Unidades_da_Federacao\", \"GrandesRegioes\",\n",
    "                                     \"faixa_idade\", \"Raca\",\"rend_per_capita\",,\"gescol\",\"Capital\")\n",
    "summary(pns2013Osurvey)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cria plano amostral complexo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Salvando csv para cálculo de indicadores no survey\n",
    "path <- \"../dados\"\n",
    "write.csv(pns2013Osurvey, file.path(path, \"pns2013Osurvey.csv\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "desPNSO=svydesign(id=~UPA_PNS, strat=~V0024, weight=~peso_morador_selec, nest=TRUE, data=pns2013Osurvey)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#survey design -O002P\n",
    "desPNSO002P_18=subset(desPNSO, C008>=18 & !is.na(O002P))\n",
    "desPNSO002P_R18=subset(desPNSO, C008>=18 & !is.na(O002P) & !is.na(Raca))\n",
    "desPNSO002P_C18=subset(desPNSO, C008>=18 & V0031==1 & !is.na(O002P))\n",
    "desPNSO002P_RC18=subset(desPNSO, C008>=18  & !is.na(O002P) & !is.na(rend_per_capita))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "#survey design -O003P\n",
    "desPNSO003P_18=subset(desPNSO, C008>=18 & !is.na(O003P))\n",
    "desPNSO003P_R18=subset(desPNSO, C008>=18 & !is.na(O003P) & !is.na(Raca))\n",
    "desPNSO003P_C18=subset(desPNSO, C008>=18 & V0031==1 & !is.na(O003P))\n",
    "desPNSO003P_RC18=subset(desPNSO, C008>=18  & !is.na(O003P) & !is.na(rend_per_capita))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#survey design -O004P\n",
    "desPNSO004P_18=subset(desPNSO, C008>=18 & !is.na(O004P))\n",
    "desPNSO004P_R18=subset(desPNSO, C008>=18 & !is.na(O004P) & !is.na(Raca))\n",
    "desPNSO004P_C18=subset(desPNSO, C008>=18 & V0031==1 & !is.na(O004P))\n",
    "desPNSO004P_RC18=subset(desPNSO, C008>=18  & !is.na(O004P) & !is.na(rend_per_capita))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "#survey design -O006P\n",
    "desPNSO006P_18=subset(desPNSO, C008>=18)\n",
    "desPNSO006P_R18=subset(desPNSO, C008>=18 & !is.na(Raca))\n",
    "desPNSO006P_C18=subset(desPNSO, C008>=18 & V0031==1)\n",
    "desPNSO006P_RC18=subset(desPNSO, C008>=18 & !is.na(rend_per_capita))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Criação da tabela de indicadores\n",
    "Essa tabela é responsável por unir os indicadores no formato do painel de indicadores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "matrizIndicadores = data.frame()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Definição de variáveis para iteração dos indicadores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "ListaIndicadores = c(~O002P,~O003P,~O004P,~O006P)\n",
    "ListaIndicadoresTexto = c(\"O002P\",\"O003P\",\"O004P\",\"O006P\")\n",
    "ListaDominios = c(~Sexo,~Raca,~rend_per_capita,~faixa_idade,~Sit_Urbano_Rural,~Unidades_da_Federacao,~GrandesRegioes,~gescol,~Capital)\n",
    "ListaDominiosTexto = c(\"sexo\",\"raça\",\"rend_per_capita\",\"fx_idade_acid\",\"urb_rur\",\"uf\",\"região\",\"gescol\",\"capital\")\n",
    "ListaTotais = c('Brasil','Capital')\n",
    "Ano <- \"2013\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Preenchendo a tabela de indicadores\n",
    "Essas iterações rodam por indicador, abrangência e por design"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Cálculo dos indicadores usando o pacote survey \n",
    "i <- 0\n",
    "#Para cada indicador\n",
    "for( indicador in ListaIndicadores){\n",
    "    i <- i + 1\n",
    "    j <- 1\n",
    "    #Para cada dominio\n",
    "    for (dominio in ListaDominios){\n",
    "               #design especifico para capital que é subconjunto do dataframe total\n",
    "               if (ListaDominiosTexto[j]==\"capital\"){\n",
    "                   #designs especificos por variavel que são subconjuntos do dataset total\n",
    "                   if(ListaIndicadoresTexto[i] == \"O002P\"){\n",
    "                     dataframe_indicador<-svyby( indicador , dominio , desPNSO002P_C18 , svymean,vartype= c(\"ci\", \"cv\"))\n",
    "                   }\n",
    "                   else if(ListaIndicadoresTexto[i] == \"O003P\"){\n",
    "                     dataframe_indicador<-svyby( indicador , dominio , desPNSO003P_C18 , svymean,vartype= c(\"ci\", \"cv\"))\n",
    "                   }else if(ListaIndicadoresTexto[i] == \"O004P\"){# cv maior do que o aceitável\n",
    "                     dataframe_indicador<-svyby( indicador , dominio , desPNSO004P_C18 , svymean,vartype= c(\"ci\", \"cv\"))\n",
    "                   }else{\n",
    "                     dataframe_indicador<-svyby( indicador , dominio , desPNSO006P_C18 , svymean,vartype= c(\"ci\", \"cv\"))\n",
    "                   }\n",
    "               #Uso design do subconjunto para raça/cor que inclui preta,branca e parda as outras \n",
    "               #não possuiam dados suficientes para os dominios dos indicadores\n",
    "               }else if (ListaDominiosTexto[j]==\"raça\"){\n",
    "                   if(ListaIndicadoresTexto[i] == \"O002P\"){\n",
    "                     dataframe_indicador<-svyby( indicador , dominio , desPNSO002P_R18 , svymean,vartype= c(\"ci\", \"cv\"))\n",
    "                   }\n",
    "                   else if(ListaIndicadoresTexto[i] == \"O003P\"){\n",
    "                     dataframe_indicador<-svyby( indicador , dominio , desPNSO003P_R18 , svymean,vartype= c(\"ci\", \"cv\"))\n",
    "                   }else if(ListaIndicadoresTexto[i] == \"O004P\"){\n",
    "                     dataframe_indicador<-svyby( indicador , dominio , desPNSO004P_R18 , svymean,vartype= c(\"ci\", \"cv\"))\n",
    "                   }\n",
    "                   else{\n",
    "                       dataframe_indicador<-svyby( indicador , dominio , desPNSO006P_R18 , svymean,vartype= c(\"ci\", \"cv\"))\n",
    "                   }\n",
    "               #design geral para o subconjunto maior que 18 anos\n",
    "               }else if (ListaDominiosTexto[j]==\"rend_per_capita\"){\n",
    "                   if(ListaIndicadoresTexto[i] == \"O002P\"){\n",
    "                     dataframe_indicador<-svyby( indicador , dominio , desPNSO002P_RC18 , svymean,vartype= c(\"ci\", \"cv\"))\n",
    "                   }\n",
    "                   else if(ListaIndicadoresTexto[i] == \"O003P\"){\n",
    "                     dataframe_indicador<-svyby( indicador , dominio , desPNSO003P_RC18 , svymean,vartype= c(\"ci\", \"cv\"))\n",
    "                   }else if(ListaIndicadoresTexto[i] == \"O004P\"){\n",
    "                     dataframe_indicador<-svyby( indicador , dominio , desPNSO004P_RC18 , svymean,vartype= c(\"ci\", \"cv\"))\n",
    "                   }\n",
    "                       else{dataframe_indicador<-svyby( indicador , dominio , desPNSO006P_RC18 , svymean,vartype= c(\"ci\", \"cv\"))}\n",
    "               #design geral para o subconjunto maior que 18 anos\n",
    "               }else {\n",
    "                   if(ListaIndicadoresTexto[i] == \"O002P\"){\n",
    "                     dataframe_indicador<-svyby( indicador , dominio , desPNSO002P_18 , svymean,vartype= c(\"ci\", \"cv\"))\n",
    "                   }\n",
    "                   else if(ListaIndicadoresTexto[i] == \"O003P\"){\n",
    "                     dataframe_indicador<-svyby( indicador , dominio , desPNSO003P_18 , svymean,vartype= c(\"ci\", \"cv\"))\n",
    "                   }else if(ListaIndicadoresTexto[i] == \"O004P\"){\n",
    "                     dataframe_indicador<-svyby( indicador , dominio , desPNSO004P_18 , svymean,vartype= c(\"ci\", \"cv\"))\n",
    "                   }else{\n",
    "                     dataframe_indicador<-svyby( indicador , dominio , desPNSO006P_18 , svymean,vartype= c(\"ci\", \"cv\"))\n",
    "                   }\n",
    "               }\n",
    "               #União do dataframe de indicadores no formato do painel disponibilizado para PNS\n",
    "               \n",
    "               dataframe_indicador<-data.frame(dataframe_indicador)\n",
    "               \n",
    "               colnames(dataframe_indicador) <- c(\"abr_nome\",\"Sim\",\"Nao\",\"LowerS\",\"LowerN\",\"UpperS\",\"UpperN\",\"cvS\",\"cvN\")\n",
    "               dataframe_indicador$Indicador <- ListaIndicadoresTexto[i]\n",
    "               dataframe_indicador$abr_tipo <- ListaDominiosTexto[j]\n",
    "               dataframe_indicador$Ano <- Ano\n",
    "               dataframe_indicador <- dataframe_indicador %>% select(\"abr_tipo\",\"abr_nome\",\"Ano\",\"Indicador\",\"Sim\",\"LowerS\",\"UpperS\",\"cvS\")\n",
    "               matrizIndicadores <-rbind(matrizIndicadores,dataframe_indicador)\n",
    "               j <- j + 1\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Criando a tabela pela abrangência total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "matriz_totais <- data.frame()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Preenchendo a tabela com as abrangencia Brasil e total das capitais"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "i=0\n",
    "#para cada indicador\n",
    "for(indicador in ListaIndicadores){\n",
    "    i <- i+1\n",
    "    #para os totais Brasil e total das capitais\n",
    "    for(total in ListaTotais){\n",
    "        #Uso do design que é subconjunto do dataset para cada Capital\n",
    "        if (total == \"Capital\"){\n",
    "                   #Indicadores que são subconjunto do dataset tot\n",
    "                   if(ListaIndicadoresTexto[i] == \"O002P\"){\n",
    "                           dataframe_indicador <- svymean(indicador,desPNSO002P_C18)\n",
    "                   }else if(ListaIndicadoresTexto[i] == \"O003P\"){\n",
    "                           dataframe_indicador <- svymean(indicador,desPNSO003P_C18)\n",
    "                   }else if(ListaIndicadoresTexto[i] == \"O004P\"){\n",
    "                           dataframe_indicador <- svymean(indicador,desPNSO004P_C18)\n",
    "                   }else{\n",
    "                       dataframe_indicador <- svymean(indicador,desPNSO006P_C18)\n",
    "                   }\n",
    "                   \n",
    "        } else {\n",
    "                   if(ListaIndicadoresTexto[i] == \"O002P\"){\n",
    "                           dataframe_indicador <- svymean(indicador,desPNSO002P_18)\n",
    "                   }else if(ListaIndicadoresTexto[i] == \"O003P\"){\n",
    "                           dataframe_indicador <- svymean(indicador,desPNSO003P_18)\n",
    "                   }else if(ListaIndicadoresTexto[i] == \"O004P\"){\n",
    "                           dataframe_indicador <- svymean(indicador,desPNSO004P_18)\n",
    "                   }else{\n",
    "                       dataframe_indicador <- svymean(indicador,desPNSO006P_18)\n",
    "                   }\n",
    "        }\n",
    "      \n",
    "        intervalo_confianca <- confint(dataframe_indicador)\n",
    "        coeficiente_variacao <- cv(dataframe_indicador)\n",
    "        dataframe_indicador <- cbind(data.frame(dataframe_indicador),data.frame(intervalo_confianca))\n",
    "        dataframe_indicador <- cbind(data.frame(dataframe_indicador),data.frame(coeficiente_variacao))\n",
    "        \n",
    "        dataframe_indicador <- dataframe_indicador %>% \n",
    "                               select('mean','X2.5..','X97.5..',coeficiente_variacao) \n",
    "        dataframe_indicador_S <- dataframe_indicador %>% \n",
    "                                 slice(1)\n",
    "                \n",
    "        colnames(dataframe_indicador_S) <- c('Sim','LowerS','UpperS', 'cvS')\n",
    "        dataframe_indicador_S$Indicador <- ListaIndicadoresTexto[i]\n",
    "        print(ListaIndicadoresTexto[i])\n",
    "        dataframe_indicador_S$abr_tipo <- \"total\"\n",
    "        dataframe_indicador_S$abr_nome <- total\n",
    "        dataframe_indicador_S$Ano <- Ano \n",
    "        print(colnames(dataframe_indicador_S))\n",
    "        dataframe_indicador_S <- dataframe_indicador_S %>% \n",
    "                             select(\"abr_tipo\",\"abr_nome\",\"Ano\",\"Indicador\",\"Sim\",\"LowerS\",\"UpperS\",'cvS')\n",
    "        \n",
    "        matriz_totais <-rbind(matriz_totais,dataframe_indicador_S)\n",
    "        \n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Unindo tabela de indicadores e de totais"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "matrizIndicadores<-rbind(matrizIndicadores,matriz_totais)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Exportando tabela de indicadores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "write.table(matrizIndicadores,file=\"<coloque aqui o caminho para exportação da matriz de indicadores>\",sep = \";\",dec = \",\",row.names = FALSE)"
   ]
  }
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