{
 "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 - S 2019 Pré-natal - Parte 4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bibliotecas Utilizadas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lendo pacotes necessários\n",
    "library(survey)\n",
    "library(ggplot2)\n",
    "library(dplyr)\n",
    "library(tictoc)\n",
    "library(foreign)\n",
    "library(forcats)\n",
    "library(tidyverse)\n",
    "source(\"utils.R\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Carregando microdados da PNS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>293726</li><li>1087</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 293726\n",
       "\\item 1087\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 293726\n",
       "2. 1087\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 293726   1087"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Carregando banco de dados para R versão 3.5.0 ou superior\n",
    "load(\"<coloque aqui o caminho para o arquivo dos microdados formato RDATA PNS 2019>\")\n",
    "\n",
    "#conferindo as dimensões (número de linhas e colunas)\n",
    "dim(\"<Coloque aqui o nome do arquivo RDATA PNS 2019>\")"
   ]
  },
  {
   "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",
       " 0.00562  0.26621  0.54401  1.00000  1.12765 61.09981 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Selecionando registros válidos e calculando peso amostral - summary de verificação\n",
    "pns2019.1<-  <Coloque aqui o nome do arquivo RDATA>  %>% filter(V0025A==1) \n",
    "pns2019.1<-pns2019.1 %>% mutate(peso_morador_selec=((V00291*(90846/168426190))))\n",
    "pns2019.1<-pns2019.1 %>% filter(!is.na(peso_morador_selec))\n",
    "summary(pns2019.1$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>2399</dd><dt>Não</dt><dd>335</dd><dt>NA's</dt><dd>88112</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Sim] 2399\n",
       "\\item[Não] 335\n",
       "\\item[NA's] 88112\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Sim\n",
       ":   2399Não\n",
       ":   335NA's\n",
       ":   88112\n",
       "\n"
      ],
      "text/plain": [
       "  Sim   Não  NA's \n",
       " 2399   335 88112 "
      ]
     },
     "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>2356</dd><dt>Não</dt><dd>378</dd><dt>NA's</dt><dd>88112</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Sim] 2356\n",
       "\\item[Não] 378\n",
       "\\item[NA's] 88112\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Sim\n",
       ":   2356Não\n",
       ":   378NA's\n",
       ":   88112\n",
       "\n"
      ],
      "text/plain": [
       "  Sim   Não  NA's \n",
       " 2356   378 88112 "
      ]
     },
     "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>2179</dd><dt>Não</dt><dd>555</dd><dt>NA's</dt><dd>88112</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Sim] 2179\n",
       "\\item[Não] 555\n",
       "\\item[NA's] 88112\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Sim\n",
       ":   2179Não\n",
       ":   555NA's\n",
       ":   88112\n",
       "\n"
      ],
      "text/plain": [
       "  Sim   Não  NA's \n",
       " 2179   555 88112 "
      ]
     },
     "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>2424</dd><dt>Não</dt><dd>394</dd><dt>NA's</dt><dd>88028</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Sim] 2424\n",
       "\\item[Não] 394\n",
       "\\item[NA's] 88028\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Sim\n",
       ":   2424Não\n",
       ":   394NA's\n",
       ":   88028\n",
       "\n"
      ],
      "text/plain": [
       "  Sim   Não  NA's \n",
       " 2424   394 88028 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Desfechos - Indicadores\n",
    "\n",
    "# 16. Proporção de mulheres que fizeram teste de HIV/AIDS durante o pré-natal - S016P.\n",
    "pns2019.1$S016P <- NA\n",
    "pns2019.1$S016P[pns2019.1$C006==2 & pns2019.1$C008>=18 & pns2019.1$S068==1] <- 2\n",
    "pns2019.1$S016P[pns2019.1$C006==2 & pns2019.1$C008>=18 & pns2019.1$S068==1 & pns2019.1$S091==1] <- 1\n",
    "pns2019.1$S016P<-factor(pns2019.1$S016P, levels=c(1,2), labels=c(\"Sim\",\"Não\"))\n",
    "summary(pns2019.1$S016P)\n",
    "\n",
    "# 17. Proporção de mulheres que fizeram teste de HIV/AIDS durante o pré-natal e receberam o resultado antes do parto - S017P.\n",
    "pns2019.1$S017P <- NA\n",
    "pns2019.1$S017P[pns2019.1$C006==2 & pns2019.1$C008>=18 & pns2019.1$S068==1] <- 2\n",
    "pns2019.1$S017P[pns2019.1$C006==2 & pns2019.1$C008>=18 & pns2019.1$S068==1 & pns2019.1$S092==1] <- 1\n",
    "pns2019.1$S017P<-factor(pns2019.1$S017P, levels=c(1,2), labels=c(\"Sim\",\"Não\"))\n",
    "summary(pns2019.1$S017P)\n",
    "\n",
    "# 18. Proporção de mulheres que receberam indicação da maternidade para o parto durante o pré-natal - S018P.\n",
    "pns2019.1$S018P <- NA\n",
    "pns2019.1$S018P[pns2019.1$C006==2 & pns2019.1$C008>=18 & pns2019.1$S068==1] <- 2\n",
    "pns2019.1$S018P[pns2019.1$C006==2 & pns2019.1$C008>=18 & pns2019.1$S068==1 & pns2019.1$S097==1] <- 1\n",
    "pns2019.1$S018P<-factor(pns2019.1$S018P, levels=c(1,2), labels=c(\"Sim\",\"Não\"))\n",
    "summary(pns2019.1$S018P)\n",
    "\n",
    "# 19. Proporção de mulheres que foram atendidas por médico no último parto - S019P.\n",
    "pns2019.1$S019P <- NA\n",
    "pns2019.1$S019P[pns2019.1$C006==2 & pns2019.1$C008>=18 & pns2019.1$S068>0] <- 2\n",
    "pns2019.1$S019P[pns2019.1$C006==2 & pns2019.1$C008>=18 & pns2019.1$S068>0 & pns2019.1$S111==1] <- 1\n",
    "pns2019.1$S019P<-factor(pns2019.1$S019P, levels=c(1,2), labels=c(\"Sim\",\"Não\"))\n",
    "summary(pns2019.1$S019P)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Definições de abrangências"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Situação urbana ou rural"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>urbano</dt><dd>69873</dd><dt>rural</dt><dd>20973</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[urbano] 69873\n",
       "\\item[rural] 20973\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "urbano\n",
       ":   69873rural\n",
       ":   20973\n",
       "\n"
      ],
      "text/plain": [
       "urbano  rural \n",
       " 69873  20973 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Situação Urbano ou Rural\n",
    "pns2019.1 <- pns2019.1 %>% rename(urb_rur=V0026)\n",
    "pns2019.1$urb_rur<-factor(pns2019.1$urb_rur, levels=c(1,2), labels=c(\"urbano\", \"rural\"))\n",
    "summary(pns2019.1$urb_rur)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### UF"
   ]
  },
  {
   "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>Rondônia</dt><dd>2176</dd><dt>Acre</dt><dd>2380</dd><dt>Amazonas</dt><dd>3479</dd><dt>Roraima</dt><dd>2238</dd><dt>Pará</dt><dd>3853</dd><dt>Amapá</dt><dd>1554</dd><dt>Tocantins</dt><dd>1922</dd><dt>Maranhão</dt><dd>5080</dd><dt>Piauí</dt><dd>2740</dd><dt>Ceará</dt><dd>4265</dd><dt>Rio Grande do Norte</dt><dd>2962</dd><dt>Paraíba</dt><dd>3158</dd><dt>Pernambuco</dt><dd>4083</dd><dt>Alagoas</dt><dd>2987</dd><dt>Sergipe</dt><dd>2610</dd><dt>Bahia</dt><dd>3659</dd><dt>Minas Gerais</dt><dd>5209</dd><dt>Espírito Santo</dt><dd>3541</dd><dt>Rio de Janeiro</dt><dd>4966</dd><dt>São Paulo</dt><dd>6114</dd><dt>Paraná</dt><dd>3967</dd><dt>Santa Catarina</dt><dd>3738</dd><dt>Rio Grande do Sul</dt><dd>3767</dd><dt>Mato Grosso do Sul</dt><dd>2863</dd><dt>Mato Grosso</dt><dd>2468</dd><dt>Goiás</dt><dd>2702</dd><dt>Distrito Federal</dt><dd>2365</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Rondônia] 2176\n",
       "\\item[Acre] 2380\n",
       "\\item[Amazonas] 3479\n",
       "\\item[Roraima] 2238\n",
       "\\item[Pará] 3853\n",
       "\\item[Amapá] 1554\n",
       "\\item[Tocantins] 1922\n",
       "\\item[Maranhão] 5080\n",
       "\\item[Piauí] 2740\n",
       "\\item[Ceará] 4265\n",
       "\\item[Rio Grande do Norte] 2962\n",
       "\\item[Paraíba] 3158\n",
       "\\item[Pernambuco] 4083\n",
       "\\item[Alagoas] 2987\n",
       "\\item[Sergipe] 2610\n",
       "\\item[Bahia] 3659\n",
       "\\item[Minas Gerais] 5209\n",
       "\\item[Espírito Santo] 3541\n",
       "\\item[Rio de Janeiro] 4966\n",
       "\\item[São Paulo] 6114\n",
       "\\item[Paraná] 3967\n",
       "\\item[Santa Catarina] 3738\n",
       "\\item[Rio Grande do Sul] 3767\n",
       "\\item[Mato Grosso do Sul] 2863\n",
       "\\item[Mato Grosso] 2468\n",
       "\\item[Goiás] 2702\n",
       "\\item[Distrito Federal] 2365\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Rondônia\n",
       ":   2176Acre\n",
       ":   2380Amazonas\n",
       ":   3479Roraima\n",
       ":   2238Pará\n",
       ":   3853Amapá\n",
       ":   1554Tocantins\n",
       ":   1922Maranhão\n",
       ":   5080Piauí\n",
       ":   2740Ceará\n",
       ":   4265Rio Grande do Norte\n",
       ":   2962Paraíba\n",
       ":   3158Pernambuco\n",
       ":   4083Alagoas\n",
       ":   2987Sergipe\n",
       ":   2610Bahia\n",
       ":   3659Minas Gerais\n",
       ":   5209Espírito Santo\n",
       ":   3541Rio de Janeiro\n",
       ":   4966São Paulo\n",
       ":   6114Paraná\n",
       ":   3967Santa Catarina\n",
       ":   3738Rio Grande do Sul\n",
       ":   3767Mato Grosso do Sul\n",
       ":   2863Mato Grosso\n",
       ":   2468Goiás\n",
       ":   2702Distrito Federal\n",
       ":   2365\n",
       "\n"
      ],
      "text/plain": [
       "           Rondônia                Acre            Amazonas             Roraima \n",
       "               2176                2380                3479                2238 \n",
       "               Pará               Amapá           Tocantins            Maranhão \n",
       "               3853                1554                1922                5080 \n",
       "              Piauí               Ceará Rio Grande do Norte             Paraíba \n",
       "               2740                4265                2962                3158 \n",
       "         Pernambuco             Alagoas             Sergipe               Bahia \n",
       "               4083                2987                2610                3659 \n",
       "       Minas Gerais      Espírito Santo      Rio de Janeiro           São Paulo \n",
       "               5209                3541                4966                6114 \n",
       "             Paraná      Santa Catarina   Rio Grande do Sul  Mato Grosso do Sul \n",
       "               3967                3738                3767                2863 \n",
       "        Mato Grosso               Goiás    Distrito Federal \n",
       "               2468                2702                2365 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Estados - UFs\n",
    "pns2019.1 <- pns2019.1 %>% rename(uf=V0001)\n",
    "pns2019.1$uf<-factor(pns2019.1$uf, 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(pns2019.1$uf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Grandes Regiões"
   ]
  },
  {
   "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>Norte</dt><dd>17602</dd><dt>Nordeste</dt><dd>31544</dd><dt>Sudeste</dt><dd>19830</dd><dt>Sul</dt><dd>11472</dd><dt>Centro-Oeste</dt><dd>10398</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Norte] 17602\n",
       "\\item[Nordeste] 31544\n",
       "\\item[Sudeste] 19830\n",
       "\\item[Sul] 11472\n",
       "\\item[Centro-Oeste] 10398\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Norte\n",
       ":   17602Nordeste\n",
       ":   31544Sudeste\n",
       ":   19830Sul\n",
       ":   11472Centro-Oeste\n",
       ":   10398\n",
       "\n"
      ],
      "text/plain": [
       "       Norte     Nordeste      Sudeste          Sul Centro-Oeste \n",
       "       17602        31544        19830        11472        10398 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Grandes Regiões\n",
    "pns2019.1 <- pns2019.1 %>% \n",
    "  mutate(região = fct_collapse(uf, \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",
    "        )\n",
    "summary(pns2019.1$região)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Capital"
   ]
  },
  {
   "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>Porto Velho</dt><dd>2176</dd><dt>Rio Branco</dt><dd>2380</dd><dt>Manaus</dt><dd>3479</dd><dt>Boa Vista</dt><dd>2238</dd><dt>Belém</dt><dd>3853</dd><dt>Macapá</dt><dd>1554</dd><dt>Palmas</dt><dd>1922</dd><dt>São Luís</dt><dd>5080</dd><dt>Teresina</dt><dd>2740</dd><dt>Fortaleza</dt><dd>4265</dd><dt>Natal</dt><dd>2962</dd><dt>João Pessoa</dt><dd>3158</dd><dt>Recife</dt><dd>4083</dd><dt>Maceió</dt><dd>2987</dd><dt>Aracaju</dt><dd>2610</dd><dt>Salvador</dt><dd>3659</dd><dt>Belo Horizonte</dt><dd>5209</dd><dt>Vitória</dt><dd>3541</dd><dt>Rio de Janeiro</dt><dd>4966</dd><dt>São Paulo</dt><dd>6114</dd><dt>Curitiba</dt><dd>3967</dd><dt>Florianópolis</dt><dd>3738</dd><dt>Porto Alegre</dt><dd>3767</dd><dt>Campo Grande</dt><dd>2863</dd><dt>Cuiabá</dt><dd>2468</dd><dt>Goiânia</dt><dd>2702</dd><dt>Brasília</dt><dd>2365</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Porto Velho] 2176\n",
       "\\item[Rio Branco] 2380\n",
       "\\item[Manaus] 3479\n",
       "\\item[Boa Vista] 2238\n",
       "\\item[Belém] 3853\n",
       "\\item[Macapá] 1554\n",
       "\\item[Palmas] 1922\n",
       "\\item[São Luís] 5080\n",
       "\\item[Teresina] 2740\n",
       "\\item[Fortaleza] 4265\n",
       "\\item[Natal] 2962\n",
       "\\item[João Pessoa] 3158\n",
       "\\item[Recife] 4083\n",
       "\\item[Maceió] 2987\n",
       "\\item[Aracaju] 2610\n",
       "\\item[Salvador] 3659\n",
       "\\item[Belo Horizonte] 5209\n",
       "\\item[Vitória] 3541\n",
       "\\item[Rio de Janeiro] 4966\n",
       "\\item[São Paulo] 6114\n",
       "\\item[Curitiba] 3967\n",
       "\\item[Florianópolis] 3738\n",
       "\\item[Porto Alegre] 3767\n",
       "\\item[Campo Grande] 2863\n",
       "\\item[Cuiabá] 2468\n",
       "\\item[Goiânia] 2702\n",
       "\\item[Brasília] 2365\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Porto Velho\n",
       ":   2176Rio Branco\n",
       ":   2380Manaus\n",
       ":   3479Boa Vista\n",
       ":   2238Belém\n",
       ":   3853Macapá\n",
       ":   1554Palmas\n",
       ":   1922São Luís\n",
       ":   5080Teresina\n",
       ":   2740Fortaleza\n",
       ":   4265Natal\n",
       ":   2962João Pessoa\n",
       ":   3158Recife\n",
       ":   4083Maceió\n",
       ":   2987Aracaju\n",
       ":   2610Salvador\n",
       ":   3659Belo Horizonte\n",
       ":   5209Vitória\n",
       ":   3541Rio de Janeiro\n",
       ":   4966São Paulo\n",
       ":   6114Curitiba\n",
       ":   3967Florianópolis\n",
       ":   3738Porto Alegre\n",
       ":   3767Campo Grande\n",
       ":   2863Cuiabá\n",
       ":   2468Goiânia\n",
       ":   2702Brasília\n",
       ":   2365\n",
       "\n"
      ],
      "text/plain": [
       "   Porto Velho     Rio Branco         Manaus      Boa Vista          Belém \n",
       "          2176           2380           3479           2238           3853 \n",
       "        Macapá         Palmas       São Luís       Teresina      Fortaleza \n",
       "          1554           1922           5080           2740           4265 \n",
       "         Natal    João Pessoa         Recife         Maceió        Aracaju \n",
       "          2962           3158           4083           2987           2610 \n",
       "      Salvador Belo Horizonte        Vitória Rio de Janeiro      São Paulo \n",
       "          3659           5209           3541           4966           6114 \n",
       "      Curitiba  Florianópolis   Porto Alegre   Campo Grande         Cuiabá \n",
       "          3967           3738           3767           2863           2468 \n",
       "       Goiânia       Brasília \n",
       "          2702           2365 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Capital\n",
    "pns2019.1<- pns2019.1 %>% mutate(capital= fct_collapse(uf,\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(pns2019.1$capital)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Faixa Etária"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>18 a 24 anos</dt><dd>8145</dd><dt>25 a 29 anos</dt><dd>7249</dd><dt>30 a 39 anos</dt><dd>18150</dd><dt>40 anos ou mais</dt><dd>54987</dd><dt>NA's</dt><dd>2315</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[18 a 24 anos] 8145\n",
       "\\item[25 a 29 anos] 7249\n",
       "\\item[30 a 39 anos] 18150\n",
       "\\item[40 anos ou mais] 54987\n",
       "\\item[NA's] 2315\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "18 a 24 anos\n",
       ":   814525 a 29 anos\n",
       ":   724930 a 39 anos\n",
       ":   1815040 anos ou mais\n",
       ":   54987NA's\n",
       ":   2315\n",
       "\n"
      ],
      "text/plain": [
       "   18 a 24 anos    25 a 29 anos    30 a 39 anos 40 anos ou mais            NA's \n",
       "           8145            7249           18150           54987            2315 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Faixas Etárias\n",
    "\n",
    "pns2019.1 <- pns2019.1 %>% mutate(fx_idade_S=cut(C008,\n",
    "  breaks = c(18,25,30,40,120),\n",
    "  labels = c(\"18 a 24 anos\", \"25 a 29 anos\", \"30 a 39 anos\", \"40 anos ou mais\"), \n",
    "  ordered_result = TRUE, right = FALSE))\n",
    "summary(pns2019.1$fx_idade_S)"
   ]
  },
  {
   "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>33133</dd><dt>Preta</dt><dd>10345</dd><dt>Parda</dt><dd>45994</dd><dt>NA's</dt><dd>1374</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Branca] 33133\n",
       "\\item[Preta] 10345\n",
       "\\item[Parda] 45994\n",
       "\\item[NA's] 1374\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Branca\n",
       ":   33133Preta\n",
       ":   10345Parda\n",
       ":   45994NA's\n",
       ":   1374\n",
       "\n"
      ],
      "text/plain": [
       "Branca  Preta  Parda   NA's \n",
       " 33133  10345  45994   1374 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Raça\n",
    "pns2019.1 <- pns2019.1 %>% mutate(raça= ifelse(C009==1, 1, \n",
    "                                               ifelse(C009==2, 2, \n",
    "                                                      ifelse(C009==4, 3, 9))))\n",
    "pns2019.1$raça<-factor(pns2019.1$raça, levels=c(1,2,3),labels=c(\"Branca\", \"Preta\", \"Parda\"))\n",
    "summary(pns2019.1$raça)"
   ]
  },
  {
   "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>23697</dd><dt>1/2 até 1 SM</dt><dd>26406</dd><dt>1 até 2 SM</dt><dd>22466</dd><dt>2 até 3 SM</dt><dd>7612</dd><dt>Mais de 3 SM</dt><dd>10643</dd><dt>NA's</dt><dd>22</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Até 1/2 SM] 23697\n",
       "\\item[1/2 até 1 SM] 26406\n",
       "\\item[1 até 2 SM] 22466\n",
       "\\item[2 até 3 SM] 7612\n",
       "\\item[Mais de 3 SM] 10643\n",
       "\\item[NA's] 22\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Até 1/2 SM\n",
       ":   236971/2 até 1 SM\n",
       ":   264061 até 2 SM\n",
       ":   224662 até 3 SM\n",
       ":   7612Mais de 3 SM\n",
       ":   10643NA's\n",
       ":   22\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",
       "       23697        26406        22466         7612        10643           22 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Rendimento domiciliar per capita\n",
    "pns2019.1 <- pns2019.1 %>% mutate(rend_per_capita = ifelse(VDF004 %in% 1:2, 1, \n",
    "                        ifelse(VDF004%in% 3, 2, \n",
    "                        ifelse(VDF004%in% 4, 3,\n",
    "                        ifelse(VDF004%in% 5, 4, \n",
    "                        ifelse(is.na(VDF004)==TRUE, NA_real_, 5))))))\n",
    "pns2019.1$rend_per_capita<-factor(pns2019.1$rend_per_capita, levels=c(1,2,3,4,5), labels=c(\"Até 1/2 SM\",\"1/2 até 1 SM\",\"1 até 2 SM\",\n",
    "                                                                                   \"2 até 3 SM\",\"Mais de 3 SM\"))\n",
    "summary(pns2019.1$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>36276</dd><dt>Médio incompleto ou equivalente</dt><dd>13520</dd><dt>Superior incompleto ou equivalente</dt><dd>27433</dd><dt>Superior completo</dt><dd>13617</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Fundamental incompleto ou equivalente] 36276\n",
       "\\item[Médio incompleto ou equivalente] 13520\n",
       "\\item[Superior incompleto ou equivalente] 27433\n",
       "\\item[Superior completo] 13617\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Fundamental incompleto ou equivalente\n",
       ":   36276Médio incompleto ou equivalente\n",
       ":   13520Superior incompleto ou equivalente\n",
       ":   27433Superior completo\n",
       ":   13617\n",
       "\n"
      ],
      "text/plain": [
       "Fundamental incompleto ou equivalente       Médio incompleto ou equivalente \n",
       "                                36276                                 13520 \n",
       "   Superior incompleto ou equivalente                     Superior completo \n",
       "                                27433                                 13617 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Escolaridade\n",
    "pns2019.1 <- pns2019.1 %>% 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",
    "pns2019.1$gescol<-factor(pns2019.1$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(pns2019.1$gescol)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Criando indicadores"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Filtrando base de indicadores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "     V0024            UPA_PNS      peso_morador_selec      C008       \n",
       " 1210010: 1167   140001681:   18   Min.   : 0.00562   Min.   : 15.00  \n",
       " 1410011:  792   140003815:   18   1st Qu.: 0.26621   1st Qu.: 32.00  \n",
       " 2710111:  779   140005777:   18   Median : 0.54401   Median : 45.00  \n",
       " 2410011:  745   140006746:   18   Mean   : 1.00000   Mean   : 46.39  \n",
       " 5010011:  738   140007081:   18   3rd Qu.: 1.12765   3rd Qu.: 60.00  \n",
       " 3210011:  711   140007715:   18   Max.   :61.09981   Max.   :107.00  \n",
       " (Other):85914   (Other)  :90738                                      \n",
       "      C006            C009           V0031         urb_rur     \n",
       " Min.   :1.000   Min.   :1.000   Min.   :1.000   urbano:69873  \n",
       " 1st Qu.:1.000   1st Qu.:1.000   1st Qu.:1.000   rural :20973  \n",
       " Median :2.000   Median :4.000   Median :2.000                 \n",
       " Mean   :1.529   Mean   :2.679   Mean   :2.605                 \n",
       " 3rd Qu.:2.000   3rd Qu.:4.000   3rd Qu.:4.000                 \n",
       " Max.   :2.000   Max.   :9.000   Max.   :4.000                 \n",
       "                                                               \n",
       "              uf                 região                capital     \n",
       " São Paulo     : 6114   Norte       :17602   São Paulo     : 6114  \n",
       " Minas Gerais  : 5209   Nordeste    :31544   Belo Horizonte: 5209  \n",
       " Maranhão      : 5080   Sudeste     :19830   São Luís      : 5080  \n",
       " Rio de Janeiro: 4966   Sul         :11472   Rio de Janeiro: 4966  \n",
       " Ceará         : 4265   Centro-Oeste:10398   Fortaleza     : 4265  \n",
       " Pernambuco    : 4083                        Recife        : 4083  \n",
       " (Other)       :61129                        (Other)       :61129  \n",
       "           fx_idade_S        raça           rend_per_capita \n",
       " 18 a 24 anos   : 8145   Branca:33133   Até 1/2 SM  :23697  \n",
       " 25 a 29 anos   : 7249   Preta :10345   1/2 até 1 SM:26406  \n",
       " 30 a 39 anos   :18150   Parda :45994   1 até 2 SM  :22466  \n",
       " 40 anos ou mais:54987   NA's  : 1374   2 até 3 SM  : 7612  \n",
       " NA's           : 2315                  Mais de 3 SM:10643  \n",
       "                                        NA's        :   22  \n",
       "                                                            \n",
       "                                   gescol       S016P        S017P      \n",
       " Fundamental incompleto ou equivalente:36276   Sim : 2399   Sim : 2356  \n",
       " Médio incompleto ou equivalente      :13520   Não :  335   Não :  378  \n",
       " Superior incompleto ou equivalente   :27433   NA's:88112   NA's:88112  \n",
       " Superior completo                    :13617                            \n",
       "                                                                        \n",
       "                                                                        \n",
       "                                                                        \n",
       "  S018P        S019P            S068      \n",
       " Sim : 2179   Sim : 2424   Min.   :1.00   \n",
       " Não :  555   Não :  394   1st Qu.:1.00   \n",
       " NA's:88112   NA's:88028   Median :1.00   \n",
       "                           Mean   :1.03   \n",
       "                           3rd Qu.:1.00   \n",
       "                           Max.   :2.00   \n",
       "                           NA's   :87936  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Selecionando variáveis para cálculo de indicadores no survey\n",
    "pns2019Ssurvey<- pns2019.1 %>% select(\"V0024\",\"UPA_PNS\",\"peso_morador_selec\", \"C008\", \"C006\", \"C009\", \"V0031\", \n",
    "                                      \"urb_rur\", \"uf\", \"região\",  \"capital\", \"fx_idade_S\", \"raça\", \"rend_per_capita\", \"gescol\",\n",
    "                                      \"S016P\", \"S017P\", \"S018P\", \"S019P\", \"S068\") \n",
    "summary(pns2019Ssurvey)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exporta tabela filtrada com os dados específicos - Módulo S - Parte 4 2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Salvando csv para cálculo de indicadores no survey\n",
    "diretorio_saida <- \"<coloque aqui o diretório>\"\n",
    "write.csv(pns2019Ssurvey, file.path(diretorio_saida, \"pns2019Ssurvey.csv\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cria plano amostral complexo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "desPNS=svydesign(id=~UPA_PNS, \n",
    "                 strat=~V0024,\n",
    "                 weight=~peso_morador_selec,\n",
    "                 nest=TRUE, \n",
    "                 data=pns2019Ssurvey)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#survey design S016P a S018P\n",
    "desPNSS=subset(desPNS, C006==2 & C008>=18 & S068==1)\n",
    "desPNSS_C=subset(desPNS, C006==2 & C008>=18 & S068==1 & V0031==1)\n",
    "desPNSS_R=subset(desPNS, C006==2 & C008>=18 & S068==1 & !is.na(raça))\n",
    "desPNSS_Rend=subset(desPNS, C006==2 & C008>=18 & S068==1 & !is.na(rend_per_capita))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#survey design S019P\n",
    "desPNSS_S019P=subset(desPNS, C006==2 & C008>=18 & S068>0)\n",
    "desPNSS_S019P_C=subset(desPNS, C006==2 & C008>=18 & S068>0 & V0031==1)\n",
    "desPNSS_S019P_R=subset(desPNS, C006==2 & C008>=18 & S068>0 & !is.na(raça))\n",
    "desPNSS_S019P_Rend=subset(desPNS, C006==2 & C008>=18 & S068>0 & !is.na(rend_per_capita))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Definição de variáveis para iteração dos indicadores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "design_por_abrangencia <- list(\n",
    "    S016P = list(\n",
    "        capital = desPNSS_C,\n",
    "        raça = desPNSS_R,\n",
    "        rend_per_capita = desPNSS_Rend,\n",
    "        default = desPNSS\n",
    "    ),\n",
    "    S017P = list(\n",
    "        capital = desPNSS_C,\n",
    "        raça = desPNSS_R,\n",
    "        rend_per_capita = desPNSS_Rend,\n",
    "        default = desPNSS\n",
    "    ),\n",
    "    S018P = list(\n",
    "        capital = desPNSS_C,\n",
    "        raça = desPNSS_R,\n",
    "        rend_per_capita = desPNSS_Rend,\n",
    "        default = desPNSS\n",
    "    ),\n",
    "    S019P = list(\n",
    "        capital = desPNSS_S019P_C,\n",
    "        raça = desPNSS_S019P_R,\n",
    "        rend_per_capita = desPNSS_S019P_Rend,\n",
    "        default = desPNSS_S019P\n",
    "    )\n",
    ")\n",
    "dominios <- c(\n",
    "    ~raça,\n",
    "    ~rend_per_capita,\n",
    "    ~fx_idade_S,\n",
    "    ~urb_rur,\n",
    "    ~uf,\n",
    "    ~região,\n",
    "    ~capital,\n",
    "    ~gescol\n",
    ") \n",
    "indicadores <- c(~S016P, ~S017P, ~S018P, ~S019P)\n",
    "totais <- c(~Brasil,~Capital)\n",
    "Ano <- \"2019\""
   ]
  },
  {
   "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": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "matriz_indicadores <- popula_indicadores(design_por_abrangencia, dominios, indicadores, Ano)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 308 × 8</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>abr_tipo</th><th scope=col>abr_nome</th><th scope=col>Ano</th><th scope=col>Indicador</th><th scope=col>Sim</th><th scope=col>LowerS</th><th scope=col>UpperS</th><th scope=col>cvS</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Branca</th><td>raça           </td><td>Branca             </td><td>2019</td><td>S016P</td><td>0.8747043</td><td>0.8394447</td><td>0.9099639</td><td>0.02056687</td></tr>\n",
       "\t<tr><th scope=row>Preta</th><td>raça           </td><td>Preta              </td><td>2019</td><td>S016P</td><td>0.9270440</td><td>0.8819540</td><td>0.9721340</td><td>0.02481599</td></tr>\n",
       "\t<tr><th scope=row>Parda</th><td>raça           </td><td>Parda              </td><td>2019</td><td>S016P</td><td>0.8998264</td><td>0.8813427</td><td>0.9183100</td><td>0.01048046</td></tr>\n",
       "\t<tr><th scope=row>Até 1/2 SM</th><td>rend_per_capita</td><td>Até 1/2 SM         </td><td>2019</td><td>S016P</td><td>0.8811666</td><td>0.8556610</td><td>0.9066723</td><td>0.01476830</td></tr>\n",
       "\t<tr><th scope=row>1/2 até 1 SM</th><td>rend_per_capita</td><td>1/2 até 1 SM       </td><td>2019</td><td>S016P</td><td>0.8986344</td><td>0.8672705</td><td>0.9299982</td><td>0.01780731</td></tr>\n",
       "\t<tr><th scope=row>1 até 2 SM</th><td>rend_per_capita</td><td>1 até 2 SM         </td><td>2019</td><td>S016P</td><td>0.9321180</td><td>0.8983597</td><td>0.9658762</td><td>0.01847824</td></tr>\n",
       "\t<tr><th scope=row>2 até 3 SM</th><td>rend_per_capita</td><td>2 até 3 SM         </td><td>2019</td><td>S016P</td><td>0.9131325</td><td>0.8480609</td><td>0.9782041</td><td>0.03635882</td></tr>\n",
       "\t<tr><th scope=row>Mais de 3 SM</th><td>rend_per_capita</td><td>Mais de 3 SM       </td><td>2019</td><td>S016P</td><td>0.8449011</td><td>0.7501941</td><td>0.9396081</td><td>0.05719106</td></tr>\n",
       "\t<tr><th scope=row>18 a 24 anos</th><td>fx_idade_s     </td><td>18 a 24 anos       </td><td>2019</td><td>S016P</td><td>0.8784567</td><td>0.8471783</td><td>0.9097351</td><td>0.01816671</td></tr>\n",
       "\t<tr><th scope=row>25 a 29 anos</th><td>fx_idade_s     </td><td>25 a 29 anos       </td><td>2019</td><td>S016P</td><td>0.9121180</td><td>0.8854396</td><td>0.9387963</td><td>0.01492314</td></tr>\n",
       "\t<tr><th scope=row>30 a 39 anos</th><td>fx_idade_s     </td><td>30 a 39 anos       </td><td>2019</td><td>S016P</td><td>0.8996282</td><td>0.8718667</td><td>0.9273898</td><td>0.01574462</td></tr>\n",
       "\t<tr><th scope=row>40 anos ou mais</th><td>fx_idade_s     </td><td>40 anos ou mais    </td><td>2019</td><td>S016P</td><td>0.8549542</td><td>0.7687697</td><td>0.9411388</td><td>0.05143260</td></tr>\n",
       "\t<tr><th scope=row>urbano</th><td>urb_rur        </td><td>urbano             </td><td>2019</td><td>S016P</td><td>0.9007125</td><td>0.8821043</td><td>0.9193208</td><td>0.01054074</td></tr>\n",
       "\t<tr><th scope=row>rural</th><td>urb_rur        </td><td>rural              </td><td>2019</td><td>S016P</td><td>0.8541637</td><td>0.8152466</td><td>0.8930807</td><td>0.02324614</td></tr>\n",
       "\t<tr><th scope=row>Rondônia</th><td>uf             </td><td>Rondônia           </td><td>2019</td><td>S016P</td><td>0.9657274</td><td>0.9374381</td><td>0.9940167</td><td>0.01494582</td></tr>\n",
       "\t<tr><th scope=row>Acre</th><td>uf             </td><td>Acre               </td><td>2019</td><td>S016P</td><td>0.9341028</td><td>0.8604602</td><td>1.0077454</td><td>0.04022411</td></tr>\n",
       "\t<tr><th scope=row>Amazonas</th><td>uf             </td><td>Amazonas           </td><td>2019</td><td>S016P</td><td>0.9073433</td><td>0.8454635</td><td>0.9692231</td><td>0.03479597</td></tr>\n",
       "\t<tr><th scope=row>Roraima</th><td>uf             </td><td>Roraima            </td><td>2019</td><td>S016P</td><td>0.7734318</td><td>0.6039876</td><td>0.9428759</td><td>0.11177804</td></tr>\n",
       "\t<tr><th scope=row>Pará</th><td>uf             </td><td>Pará               </td><td>2019</td><td>S016P</td><td>0.9134246</td><td>0.8575382</td><td>0.9693110</td><td>0.03121660</td></tr>\n",
       "\t<tr><th scope=row>Amapá</th><td>uf             </td><td>Amapá              </td><td>2019</td><td>S016P</td><td>0.9555542</td><td>0.8885170</td><td>1.0225915</td><td>0.03579421</td></tr>\n",
       "\t<tr><th scope=row>Tocantins</th><td>uf             </td><td>Tocantins          </td><td>2019</td><td>S016P</td><td>0.8106428</td><td>0.6778693</td><td>0.9434163</td><td>0.08356679</td></tr>\n",
       "\t<tr><th scope=row>Maranhão</th><td>uf             </td><td>Maranhão           </td><td>2019</td><td>S016P</td><td>0.8095186</td><td>0.7336835</td><td>0.8853537</td><td>0.04779642</td></tr>\n",
       "\t<tr><th scope=row>Piauí</th><td>uf             </td><td>Piauí              </td><td>2019</td><td>S016P</td><td>0.9391357</td><td>0.8887311</td><td>0.9895403</td><td>0.02738380</td></tr>\n",
       "\t<tr><th scope=row>Ceará</th><td>uf             </td><td>Ceará              </td><td>2019</td><td>S016P</td><td>0.8040217</td><td>0.7193974</td><td>0.8886460</td><td>0.05370064</td></tr>\n",
       "\t<tr><th scope=row>Rio Grande do Norte</th><td>uf             </td><td>Rio Grande do Norte</td><td>2019</td><td>S016P</td><td>0.9353931</td><td>0.8588831</td><td>1.0119032</td><td>0.04173267</td></tr>\n",
       "\t<tr><th scope=row>Paraíba</th><td>uf             </td><td>Paraíba            </td><td>2019</td><td>S016P</td><td>0.8566499</td><td>0.7581708</td><td>0.9551291</td><td>0.05865337</td></tr>\n",
       "\t<tr><th scope=row>Pernambuco</th><td>uf             </td><td>Pernambuco         </td><td>2019</td><td>S016P</td><td>0.8711616</td><td>0.8068706</td><td>0.9354526</td><td>0.03765332</td></tr>\n",
       "\t<tr><th scope=row>Alagoas</th><td>uf             </td><td>Alagoas            </td><td>2019</td><td>S016P</td><td>0.8033046</td><td>0.7070219</td><td>0.8995873</td><td>0.06115329</td></tr>\n",
       "\t<tr><th scope=row>Sergipe</th><td>uf             </td><td>Sergipe            </td><td>2019</td><td>S016P</td><td>0.8516848</td><td>0.7504449</td><td>0.9529247</td><td>0.06064918</td></tr>\n",
       "\t<tr><th scope=row>Bahia</th><td>uf             </td><td>Bahia              </td><td>2019</td><td>S016P</td><td>0.9096653</td><td>0.8455323</td><td>0.9737983</td><td>0.03597093</td></tr>\n",
       "\t<tr><th scope=row>⋮</th><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n",
       "\t<tr><th scope=row>Rio Branco3</th><td>capital</td><td>Rio Branco                           </td><td>2019</td><td>S019P</td><td>0.8528056</td><td>0.73447058</td><td>0.9711407</td><td>7.079706e-02</td></tr>\n",
       "\t<tr><th scope=row>Manaus3</th><td>capital</td><td>Manaus                               </td><td>2019</td><td>S019P</td><td>0.8827997</td><td>0.77794640</td><td>0.9876530</td><td>6.059989e-02</td></tr>\n",
       "\t<tr><th scope=row>Boa Vista3</th><td>capital</td><td>Boa Vista                            </td><td>2019</td><td>S019P</td><td>0.8884627</td><td>0.79679075</td><td>0.9801346</td><td>5.264403e-02</td></tr>\n",
       "\t<tr><th scope=row>Belém3</th><td>capital</td><td>Belém                                </td><td>2019</td><td>S019P</td><td>0.9571920</td><td>0.89676894</td><td>1.0176151</td><td>3.220740e-02</td></tr>\n",
       "\t<tr><th scope=row>Macapá3</th><td>capital</td><td>Macapá                               </td><td>2019</td><td>S019P</td><td>0.4130939</td><td>0.06835764</td><td>0.7578301</td><td>4.257847e-01</td></tr>\n",
       "\t<tr><th scope=row>Palmas3</th><td>capital</td><td>Palmas                               </td><td>2019</td><td>S019P</td><td>1.0000000</td><td>1.00000000</td><td>1.0000000</td><td>0.000000e+00</td></tr>\n",
       "\t<tr><th scope=row>São Luís3</th><td>capital</td><td>São Luís                             </td><td>2019</td><td>S019P</td><td>0.9072290</td><td>0.79492742</td><td>1.0195307</td><td>6.315693e-02</td></tr>\n",
       "\t<tr><th scope=row>Teresina3</th><td>capital</td><td>Teresina                             </td><td>2019</td><td>S019P</td><td>1.0000000</td><td>1.00000000</td><td>1.0000000</td><td>2.414201e-17</td></tr>\n",
       "\t<tr><th scope=row>Fortaleza3</th><td>capital</td><td>Fortaleza                            </td><td>2019</td><td>S019P</td><td>0.8528462</td><td>0.70056621</td><td>1.0051261</td><td>9.110117e-02</td></tr>\n",
       "\t<tr><th scope=row>Natal3</th><td>capital</td><td>Natal                                </td><td>2019</td><td>S019P</td><td>0.9574035</td><td>0.89567915</td><td>1.0191278</td><td>3.289375e-02</td></tr>\n",
       "\t<tr><th scope=row>João Pessoa3</th><td>capital</td><td>João Pessoa                          </td><td>2019</td><td>S019P</td><td>0.8469751</td><td>0.72489071</td><td>0.9690595</td><td>7.354301e-02</td></tr>\n",
       "\t<tr><th scope=row>Recife3</th><td>capital</td><td>Recife                               </td><td>2019</td><td>S019P</td><td>0.7957699</td><td>0.59439109</td><td>0.9971488</td><td>1.291155e-01</td></tr>\n",
       "\t<tr><th scope=row>Maceió3</th><td>capital</td><td>Maceió                               </td><td>2019</td><td>S019P</td><td>0.9052185</td><td>0.82355588</td><td>0.9868812</td><td>4.602799e-02</td></tr>\n",
       "\t<tr><th scope=row>Aracaju3</th><td>capital</td><td>Aracaju                              </td><td>2019</td><td>S019P</td><td>0.8719312</td><td>0.72567301</td><td>1.0181894</td><td>8.558347e-02</td></tr>\n",
       "\t<tr><th scope=row>Salvador3</th><td>capital</td><td>Salvador                             </td><td>2019</td><td>S019P</td><td>0.9772048</td><td>0.93134998</td><td>1.0230596</td><td>2.394149e-02</td></tr>\n",
       "\t<tr><th scope=row>Belo Horizonte3</th><td>capital</td><td>Belo Horizonte                       </td><td>2019</td><td>S019P</td><td>0.8377275</td><td>0.71752331</td><td>0.9579316</td><td>7.320970e-02</td></tr>\n",
       "\t<tr><th scope=row>Vitória3</th><td>capital</td><td>Vitória                              </td><td>2019</td><td>S019P</td><td>1.0000000</td><td>1.00000000</td><td>1.0000000</td><td>0.000000e+00</td></tr>\n",
       "\t<tr><th scope=row>Rio de Janeiro7</th><td>capital</td><td>Rio de Janeiro                       </td><td>2019</td><td>S019P</td><td>0.9813696</td><td>0.94454301</td><td>1.0181962</td><td>1.914613e-02</td></tr>\n",
       "\t<tr><th scope=row>São Paulo6</th><td>capital</td><td>São Paulo                            </td><td>2019</td><td>S019P</td><td>0.9485502</td><td>0.89371537</td><td>1.0033849</td><td>2.949496e-02</td></tr>\n",
       "\t<tr><th scope=row>Curitiba3</th><td>capital</td><td>Curitiba                             </td><td>2019</td><td>S019P</td><td>0.8922268</td><td>0.69385031</td><td>1.0906034</td><td>1.134402e-01</td></tr>\n",
       "\t<tr><th scope=row>Florianópolis3</th><td>capital</td><td>Florianópolis                        </td><td>2019</td><td>S019P</td><td>1.0000000</td><td>1.00000000</td><td>1.0000000</td><td>2.862188e-17</td></tr>\n",
       "\t<tr><th scope=row>Porto Alegre3</th><td>capital</td><td>Porto Alegre                         </td><td>2019</td><td>S019P</td><td>0.9766329</td><td>0.93037992</td><td>1.0228859</td><td>2.416353e-02</td></tr>\n",
       "\t<tr><th scope=row>Campo Grande3</th><td>capital</td><td>Campo Grande                         </td><td>2019</td><td>S019P</td><td>0.9786548</td><td>0.94878671</td><td>1.0085229</td><td>1.557148e-02</td></tr>\n",
       "\t<tr><th scope=row>Cuiabá3</th><td>capital</td><td>Cuiabá                               </td><td>2019</td><td>S019P</td><td>0.9146546</td><td>0.79753409</td><td>1.0317751</td><td>6.533226e-02</td></tr>\n",
       "\t<tr><th scope=row>Goiânia3</th><td>capital</td><td>Goiânia                              </td><td>2019</td><td>S019P</td><td>0.8985256</td><td>0.76221954</td><td>1.0348317</td><td>7.739925e-02</td></tr>\n",
       "\t<tr><th scope=row>Brasília3</th><td>capital</td><td>Brasília                             </td><td>2019</td><td>S019P</td><td>0.8662223</td><td>0.73669275</td><td>0.9957519</td><td>7.629419e-02</td></tr>\n",
       "\t<tr><th scope=row>Fundamental incompleto ou equivalente3</th><td>gescol </td><td>Fundamental incompleto ou equivalente</td><td>2019</td><td>S019P</td><td>0.7421529</td><td>0.68603013</td><td>0.7982757</td><td>3.858315e-02</td></tr>\n",
       "\t<tr><th scope=row>Médio incompleto ou equivalente3</th><td>gescol </td><td>Médio incompleto ou equivalente      </td><td>2019</td><td>S019P</td><td>0.8300336</td><td>0.78011145</td><td>0.8799558</td><td>3.068667e-02</td></tr>\n",
       "\t<tr><th scope=row>Superior incompleto ou equivalente3</th><td>gescol </td><td>Superior incompleto ou equivalente   </td><td>2019</td><td>S019P</td><td>0.9019019</td><td>0.87235022</td><td>0.9314535</td><td>1.671761e-02</td></tr>\n",
       "\t<tr><th scope=row>Superior completo3</th><td>gescol </td><td>Superior completo                    </td><td>2019</td><td>S019P</td><td>0.9757760</td><td>0.95978718</td><td>0.9917647</td><td>8.360210e-03</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 308 × 8\n",
       "\\begin{tabular}{r|llllllll}\n",
       "  & abr\\_tipo & abr\\_nome & Ano & Indicador & Sim & LowerS & UpperS & cvS\\\\\n",
       "  & <chr> & <fct> & <chr> & <chr> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\tBranca & raça            & Branca              & 2019 & S016P & 0.8747043 & 0.8394447 & 0.9099639 & 0.02056687\\\\\n",
       "\tPreta & raça            & Preta               & 2019 & S016P & 0.9270440 & 0.8819540 & 0.9721340 & 0.02481599\\\\\n",
       "\tParda & raça            & Parda               & 2019 & S016P & 0.8998264 & 0.8813427 & 0.9183100 & 0.01048046\\\\\n",
       "\tAté 1/2 SM & rend\\_per\\_capita & Até 1/2 SM          & 2019 & S016P & 0.8811666 & 0.8556610 & 0.9066723 & 0.01476830\\\\\n",
       "\t1/2 até 1 SM & rend\\_per\\_capita & 1/2 até 1 SM        & 2019 & S016P & 0.8986344 & 0.8672705 & 0.9299982 & 0.01780731\\\\\n",
       "\t1 até 2 SM & rend\\_per\\_capita & 1 até 2 SM          & 2019 & S016P & 0.9321180 & 0.8983597 & 0.9658762 & 0.01847824\\\\\n",
       "\t2 até 3 SM & rend\\_per\\_capita & 2 até 3 SM          & 2019 & S016P & 0.9131325 & 0.8480609 & 0.9782041 & 0.03635882\\\\\n",
       "\tMais de 3 SM & rend\\_per\\_capita & Mais de 3 SM        & 2019 & S016P & 0.8449011 & 0.7501941 & 0.9396081 & 0.05719106\\\\\n",
       "\t18 a 24 anos & fx\\_idade\\_s      & 18 a 24 anos        & 2019 & S016P & 0.8784567 & 0.8471783 & 0.9097351 & 0.01816671\\\\\n",
       "\t25 a 29 anos & fx\\_idade\\_s      & 25 a 29 anos        & 2019 & S016P & 0.9121180 & 0.8854396 & 0.9387963 & 0.01492314\\\\\n",
       "\t30 a 39 anos & fx\\_idade\\_s      & 30 a 39 anos        & 2019 & S016P & 0.8996282 & 0.8718667 & 0.9273898 & 0.01574462\\\\\n",
       "\t40 anos ou mais & fx\\_idade\\_s      & 40 anos ou mais     & 2019 & S016P & 0.8549542 & 0.7687697 & 0.9411388 & 0.05143260\\\\\n",
       "\turbano & urb\\_rur         & urbano              & 2019 & S016P & 0.9007125 & 0.8821043 & 0.9193208 & 0.01054074\\\\\n",
       "\trural & urb\\_rur         & rural               & 2019 & S016P & 0.8541637 & 0.8152466 & 0.8930807 & 0.02324614\\\\\n",
       "\tRondônia & uf              & Rondônia            & 2019 & S016P & 0.9657274 & 0.9374381 & 0.9940167 & 0.01494582\\\\\n",
       "\tAcre & uf              & Acre                & 2019 & S016P & 0.9341028 & 0.8604602 & 1.0077454 & 0.04022411\\\\\n",
       "\tAmazonas & uf              & Amazonas            & 2019 & S016P & 0.9073433 & 0.8454635 & 0.9692231 & 0.03479597\\\\\n",
       "\tRoraima & uf              & Roraima             & 2019 & S016P & 0.7734318 & 0.6039876 & 0.9428759 & 0.11177804\\\\\n",
       "\tPará & uf              & Pará                & 2019 & S016P & 0.9134246 & 0.8575382 & 0.9693110 & 0.03121660\\\\\n",
       "\tAmapá & uf              & Amapá               & 2019 & S016P & 0.9555542 & 0.8885170 & 1.0225915 & 0.03579421\\\\\n",
       "\tTocantins & uf              & Tocantins           & 2019 & S016P & 0.8106428 & 0.6778693 & 0.9434163 & 0.08356679\\\\\n",
       "\tMaranhão & uf              & Maranhão            & 2019 & S016P & 0.8095186 & 0.7336835 & 0.8853537 & 0.04779642\\\\\n",
       "\tPiauí & uf              & Piauí               & 2019 & S016P & 0.9391357 & 0.8887311 & 0.9895403 & 0.02738380\\\\\n",
       "\tCeará & uf              & Ceará               & 2019 & S016P & 0.8040217 & 0.7193974 & 0.8886460 & 0.05370064\\\\\n",
       "\tRio Grande do Norte & uf              & Rio Grande do Norte & 2019 & S016P & 0.9353931 & 0.8588831 & 1.0119032 & 0.04173267\\\\\n",
       "\tParaíba & uf              & Paraíba             & 2019 & S016P & 0.8566499 & 0.7581708 & 0.9551291 & 0.05865337\\\\\n",
       "\tPernambuco & uf              & Pernambuco          & 2019 & S016P & 0.8711616 & 0.8068706 & 0.9354526 & 0.03765332\\\\\n",
       "\tAlagoas & uf              & Alagoas             & 2019 & S016P & 0.8033046 & 0.7070219 & 0.8995873 & 0.06115329\\\\\n",
       "\tSergipe & uf              & Sergipe             & 2019 & S016P & 0.8516848 & 0.7504449 & 0.9529247 & 0.06064918\\\\\n",
       "\tBahia & uf              & Bahia               & 2019 & S016P & 0.9096653 & 0.8455323 & 0.9737983 & 0.03597093\\\\\n",
       "\t⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮\\\\\n",
       "\tRio Branco3 & capital & Rio Branco                            & 2019 & S019P & 0.8528056 & 0.73447058 & 0.9711407 & 7.079706e-02\\\\\n",
       "\tManaus3 & capital & Manaus                                & 2019 & S019P & 0.8827997 & 0.77794640 & 0.9876530 & 6.059989e-02\\\\\n",
       "\tBoa Vista3 & capital & Boa Vista                             & 2019 & S019P & 0.8884627 & 0.79679075 & 0.9801346 & 5.264403e-02\\\\\n",
       "\tBelém3 & capital & Belém                                 & 2019 & S019P & 0.9571920 & 0.89676894 & 1.0176151 & 3.220740e-02\\\\\n",
       "\tMacapá3 & capital & Macapá                                & 2019 & S019P & 0.4130939 & 0.06835764 & 0.7578301 & 4.257847e-01\\\\\n",
       "\tPalmas3 & capital & Palmas                                & 2019 & S019P & 1.0000000 & 1.00000000 & 1.0000000 & 0.000000e+00\\\\\n",
       "\tSão Luís3 & capital & São Luís                              & 2019 & S019P & 0.9072290 & 0.79492742 & 1.0195307 & 6.315693e-02\\\\\n",
       "\tTeresina3 & capital & Teresina                              & 2019 & S019P & 1.0000000 & 1.00000000 & 1.0000000 & 2.414201e-17\\\\\n",
       "\tFortaleza3 & capital & Fortaleza                             & 2019 & S019P & 0.8528462 & 0.70056621 & 1.0051261 & 9.110117e-02\\\\\n",
       "\tNatal3 & capital & Natal                                 & 2019 & S019P & 0.9574035 & 0.89567915 & 1.0191278 & 3.289375e-02\\\\\n",
       "\tJoão Pessoa3 & capital & João Pessoa                           & 2019 & S019P & 0.8469751 & 0.72489071 & 0.9690595 & 7.354301e-02\\\\\n",
       "\tRecife3 & capital & Recife                                & 2019 & S019P & 0.7957699 & 0.59439109 & 0.9971488 & 1.291155e-01\\\\\n",
       "\tMaceió3 & capital & Maceió                                & 2019 & S019P & 0.9052185 & 0.82355588 & 0.9868812 & 4.602799e-02\\\\\n",
       "\tAracaju3 & capital & Aracaju                               & 2019 & S019P & 0.8719312 & 0.72567301 & 1.0181894 & 8.558347e-02\\\\\n",
       "\tSalvador3 & capital & Salvador                              & 2019 & S019P & 0.9772048 & 0.93134998 & 1.0230596 & 2.394149e-02\\\\\n",
       "\tBelo Horizonte3 & capital & Belo Horizonte                        & 2019 & S019P & 0.8377275 & 0.71752331 & 0.9579316 & 7.320970e-02\\\\\n",
       "\tVitória3 & capital & Vitória                               & 2019 & S019P & 1.0000000 & 1.00000000 & 1.0000000 & 0.000000e+00\\\\\n",
       "\tRio de Janeiro7 & capital & Rio de Janeiro                        & 2019 & S019P & 0.9813696 & 0.94454301 & 1.0181962 & 1.914613e-02\\\\\n",
       "\tSão Paulo6 & capital & São Paulo                             & 2019 & S019P & 0.9485502 & 0.89371537 & 1.0033849 & 2.949496e-02\\\\\n",
       "\tCuritiba3 & capital & Curitiba                              & 2019 & S019P & 0.8922268 & 0.69385031 & 1.0906034 & 1.134402e-01\\\\\n",
       "\tFlorianópolis3 & capital & Florianópolis                         & 2019 & S019P & 1.0000000 & 1.00000000 & 1.0000000 & 2.862188e-17\\\\\n",
       "\tPorto Alegre3 & capital & Porto Alegre                          & 2019 & S019P & 0.9766329 & 0.93037992 & 1.0228859 & 2.416353e-02\\\\\n",
       "\tCampo Grande3 & capital & Campo Grande                          & 2019 & S019P & 0.9786548 & 0.94878671 & 1.0085229 & 1.557148e-02\\\\\n",
       "\tCuiabá3 & capital & Cuiabá                                & 2019 & S019P & 0.9146546 & 0.79753409 & 1.0317751 & 6.533226e-02\\\\\n",
       "\tGoiânia3 & capital & Goiânia                               & 2019 & S019P & 0.8985256 & 0.76221954 & 1.0348317 & 7.739925e-02\\\\\n",
       "\tBrasília3 & capital & Brasília                              & 2019 & S019P & 0.8662223 & 0.73669275 & 0.9957519 & 7.629419e-02\\\\\n",
       "\tFundamental incompleto ou equivalente3 & gescol  & Fundamental incompleto ou equivalente & 2019 & S019P & 0.7421529 & 0.68603013 & 0.7982757 & 3.858315e-02\\\\\n",
       "\tMédio incompleto ou equivalente3 & gescol  & Médio incompleto ou equivalente       & 2019 & S019P & 0.8300336 & 0.78011145 & 0.8799558 & 3.068667e-02\\\\\n",
       "\tSuperior incompleto ou equivalente3 & gescol  & Superior incompleto ou equivalente    & 2019 & S019P & 0.9019019 & 0.87235022 & 0.9314535 & 1.671761e-02\\\\\n",
       "\tSuperior completo3 & gescol  & Superior completo                     & 2019 & S019P & 0.9757760 & 0.95978718 & 0.9917647 & 8.360210e-03\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 308 × 8\n",
       "\n",
       "| <!--/--> | abr_tipo &lt;chr&gt; | abr_nome &lt;fct&gt; | Ano &lt;chr&gt; | Indicador &lt;chr&gt; | Sim &lt;dbl&gt; | LowerS &lt;dbl&gt; | UpperS &lt;dbl&gt; | cvS &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|\n",
       "| Branca | raça            | Branca              | 2019 | S016P | 0.8747043 | 0.8394447 | 0.9099639 | 0.02056687 |\n",
       "| Preta | raça            | Preta               | 2019 | S016P | 0.9270440 | 0.8819540 | 0.9721340 | 0.02481599 |\n",
       "| Parda | raça            | Parda               | 2019 | S016P | 0.8998264 | 0.8813427 | 0.9183100 | 0.01048046 |\n",
       "| Até 1/2 SM | rend_per_capita | Até 1/2 SM          | 2019 | S016P | 0.8811666 | 0.8556610 | 0.9066723 | 0.01476830 |\n",
       "| 1/2 até 1 SM | rend_per_capita | 1/2 até 1 SM        | 2019 | S016P | 0.8986344 | 0.8672705 | 0.9299982 | 0.01780731 |\n",
       "| 1 até 2 SM | rend_per_capita | 1 até 2 SM          | 2019 | S016P | 0.9321180 | 0.8983597 | 0.9658762 | 0.01847824 |\n",
       "| 2 até 3 SM | rend_per_capita | 2 até 3 SM          | 2019 | S016P | 0.9131325 | 0.8480609 | 0.9782041 | 0.03635882 |\n",
       "| Mais de 3 SM | rend_per_capita | Mais de 3 SM        | 2019 | S016P | 0.8449011 | 0.7501941 | 0.9396081 | 0.05719106 |\n",
       "| 18 a 24 anos | fx_idade_s      | 18 a 24 anos        | 2019 | S016P | 0.8784567 | 0.8471783 | 0.9097351 | 0.01816671 |\n",
       "| 25 a 29 anos | fx_idade_s      | 25 a 29 anos        | 2019 | S016P | 0.9121180 | 0.8854396 | 0.9387963 | 0.01492314 |\n",
       "| 30 a 39 anos | fx_idade_s      | 30 a 39 anos        | 2019 | S016P | 0.8996282 | 0.8718667 | 0.9273898 | 0.01574462 |\n",
       "| 40 anos ou mais | fx_idade_s      | 40 anos ou mais     | 2019 | S016P | 0.8549542 | 0.7687697 | 0.9411388 | 0.05143260 |\n",
       "| urbano | urb_rur         | urbano              | 2019 | S016P | 0.9007125 | 0.8821043 | 0.9193208 | 0.01054074 |\n",
       "| rural | urb_rur         | rural               | 2019 | S016P | 0.8541637 | 0.8152466 | 0.8930807 | 0.02324614 |\n",
       "| Rondônia | uf              | Rondônia            | 2019 | S016P | 0.9657274 | 0.9374381 | 0.9940167 | 0.01494582 |\n",
       "| Acre | uf              | Acre                | 2019 | S016P | 0.9341028 | 0.8604602 | 1.0077454 | 0.04022411 |\n",
       "| Amazonas | uf              | Amazonas            | 2019 | S016P | 0.9073433 | 0.8454635 | 0.9692231 | 0.03479597 |\n",
       "| Roraima | uf              | Roraima             | 2019 | S016P | 0.7734318 | 0.6039876 | 0.9428759 | 0.11177804 |\n",
       "| Pará | uf              | Pará                | 2019 | S016P | 0.9134246 | 0.8575382 | 0.9693110 | 0.03121660 |\n",
       "| Amapá | uf              | Amapá               | 2019 | S016P | 0.9555542 | 0.8885170 | 1.0225915 | 0.03579421 |\n",
       "| Tocantins | uf              | Tocantins           | 2019 | S016P | 0.8106428 | 0.6778693 | 0.9434163 | 0.08356679 |\n",
       "| Maranhão | uf              | Maranhão            | 2019 | S016P | 0.8095186 | 0.7336835 | 0.8853537 | 0.04779642 |\n",
       "| Piauí | uf              | Piauí               | 2019 | S016P | 0.9391357 | 0.8887311 | 0.9895403 | 0.02738380 |\n",
       "| Ceará | uf              | Ceará               | 2019 | S016P | 0.8040217 | 0.7193974 | 0.8886460 | 0.05370064 |\n",
       "| Rio Grande do Norte | uf              | Rio Grande do Norte | 2019 | S016P | 0.9353931 | 0.8588831 | 1.0119032 | 0.04173267 |\n",
       "| Paraíba | uf              | Paraíba             | 2019 | S016P | 0.8566499 | 0.7581708 | 0.9551291 | 0.05865337 |\n",
       "| Pernambuco | uf              | Pernambuco          | 2019 | S016P | 0.8711616 | 0.8068706 | 0.9354526 | 0.03765332 |\n",
       "| Alagoas | uf              | Alagoas             | 2019 | S016P | 0.8033046 | 0.7070219 | 0.8995873 | 0.06115329 |\n",
       "| Sergipe | uf              | Sergipe             | 2019 | S016P | 0.8516848 | 0.7504449 | 0.9529247 | 0.06064918 |\n",
       "| Bahia | uf              | Bahia               | 2019 | S016P | 0.9096653 | 0.8455323 | 0.9737983 | 0.03597093 |\n",
       "| ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |\n",
       "| Rio Branco3 | capital | Rio Branco                            | 2019 | S019P | 0.8528056 | 0.73447058 | 0.9711407 | 7.079706e-02 |\n",
       "| Manaus3 | capital | Manaus                                | 2019 | S019P | 0.8827997 | 0.77794640 | 0.9876530 | 6.059989e-02 |\n",
       "| Boa Vista3 | capital | Boa Vista                             | 2019 | S019P | 0.8884627 | 0.79679075 | 0.9801346 | 5.264403e-02 |\n",
       "| Belém3 | capital | Belém                                 | 2019 | S019P | 0.9571920 | 0.89676894 | 1.0176151 | 3.220740e-02 |\n",
       "| Macapá3 | capital | Macapá                                | 2019 | S019P | 0.4130939 | 0.06835764 | 0.7578301 | 4.257847e-01 |\n",
       "| Palmas3 | capital | Palmas                                | 2019 | S019P | 1.0000000 | 1.00000000 | 1.0000000 | 0.000000e+00 |\n",
       "| São Luís3 | capital | São Luís                              | 2019 | S019P | 0.9072290 | 0.79492742 | 1.0195307 | 6.315693e-02 |\n",
       "| Teresina3 | capital | Teresina                              | 2019 | S019P | 1.0000000 | 1.00000000 | 1.0000000 | 2.414201e-17 |\n",
       "| Fortaleza3 | capital | Fortaleza                             | 2019 | S019P | 0.8528462 | 0.70056621 | 1.0051261 | 9.110117e-02 |\n",
       "| Natal3 | capital | Natal                                 | 2019 | S019P | 0.9574035 | 0.89567915 | 1.0191278 | 3.289375e-02 |\n",
       "| João Pessoa3 | capital | João Pessoa                           | 2019 | S019P | 0.8469751 | 0.72489071 | 0.9690595 | 7.354301e-02 |\n",
       "| Recife3 | capital | Recife                                | 2019 | S019P | 0.7957699 | 0.59439109 | 0.9971488 | 1.291155e-01 |\n",
       "| Maceió3 | capital | Maceió                                | 2019 | S019P | 0.9052185 | 0.82355588 | 0.9868812 | 4.602799e-02 |\n",
       "| Aracaju3 | capital | Aracaju                               | 2019 | S019P | 0.8719312 | 0.72567301 | 1.0181894 | 8.558347e-02 |\n",
       "| Salvador3 | capital | Salvador                              | 2019 | S019P | 0.9772048 | 0.93134998 | 1.0230596 | 2.394149e-02 |\n",
       "| Belo Horizonte3 | capital | Belo Horizonte                        | 2019 | S019P | 0.8377275 | 0.71752331 | 0.9579316 | 7.320970e-02 |\n",
       "| Vitória3 | capital | Vitória                               | 2019 | S019P | 1.0000000 | 1.00000000 | 1.0000000 | 0.000000e+00 |\n",
       "| Rio de Janeiro7 | capital | Rio de Janeiro                        | 2019 | S019P | 0.9813696 | 0.94454301 | 1.0181962 | 1.914613e-02 |\n",
       "| São Paulo6 | capital | São Paulo                             | 2019 | S019P | 0.9485502 | 0.89371537 | 1.0033849 | 2.949496e-02 |\n",
       "| Curitiba3 | capital | Curitiba                              | 2019 | S019P | 0.8922268 | 0.69385031 | 1.0906034 | 1.134402e-01 |\n",
       "| Florianópolis3 | capital | Florianópolis                         | 2019 | S019P | 1.0000000 | 1.00000000 | 1.0000000 | 2.862188e-17 |\n",
       "| Porto Alegre3 | capital | Porto Alegre                          | 2019 | S019P | 0.9766329 | 0.93037992 | 1.0228859 | 2.416353e-02 |\n",
       "| Campo Grande3 | capital | Campo Grande                          | 2019 | S019P | 0.9786548 | 0.94878671 | 1.0085229 | 1.557148e-02 |\n",
       "| Cuiabá3 | capital | Cuiabá                                | 2019 | S019P | 0.9146546 | 0.79753409 | 1.0317751 | 6.533226e-02 |\n",
       "| Goiânia3 | capital | Goiânia                               | 2019 | S019P | 0.8985256 | 0.76221954 | 1.0348317 | 7.739925e-02 |\n",
       "| Brasília3 | capital | Brasília                              | 2019 | S019P | 0.8662223 | 0.73669275 | 0.9957519 | 7.629419e-02 |\n",
       "| Fundamental incompleto ou equivalente3 | gescol  | Fundamental incompleto ou equivalente | 2019 | S019P | 0.7421529 | 0.68603013 | 0.7982757 | 3.858315e-02 |\n",
       "| Médio incompleto ou equivalente3 | gescol  | Médio incompleto ou equivalente       | 2019 | S019P | 0.8300336 | 0.78011145 | 0.8799558 | 3.068667e-02 |\n",
       "| Superior incompleto ou equivalente3 | gescol  | Superior incompleto ou equivalente    | 2019 | S019P | 0.9019019 | 0.87235022 | 0.9314535 | 1.671761e-02 |\n",
       "| Superior completo3 | gescol  | Superior completo                     | 2019 | S019P | 0.9757760 | 0.95978718 | 0.9917647 | 8.360210e-03 |\n",
       "\n"
      ],
      "text/plain": [
       "                                       abr_tipo       \n",
       "Branca                                 raça           \n",
       "Preta                                  raça           \n",
       "Parda                                  raça           \n",
       "Até 1/2 SM                             rend_per_capita\n",
       "1/2 até 1 SM                           rend_per_capita\n",
       "1 até 2 SM                             rend_per_capita\n",
       "2 até 3 SM                             rend_per_capita\n",
       "Mais de 3 SM                           rend_per_capita\n",
       "18 a 24 anos                           fx_idade_s     \n",
       "25 a 29 anos                           fx_idade_s     \n",
       "30 a 39 anos                           fx_idade_s     \n",
       "40 anos ou mais                        fx_idade_s     \n",
       "urbano                                 urb_rur        \n",
       "rural                                  urb_rur        \n",
       "Rondônia                               uf             \n",
       "Acre                                   uf             \n",
       "Amazonas                               uf             \n",
       "Roraima                                uf             \n",
       "Pará                                   uf             \n",
       "Amapá                                  uf             \n",
       "Tocantins                              uf             \n",
       "Maranhão                               uf             \n",
       "Piauí                                  uf             \n",
       "Ceará                                  uf             \n",
       "Rio Grande do Norte                    uf             \n",
       "Paraíba                                uf             \n",
       "Pernambuco                             uf             \n",
       "Alagoas                                uf             \n",
       "Sergipe                                uf             \n",
       "Bahia                                  uf             \n",
       "⋮                                      ⋮              \n",
       "Rio Branco3                            capital        \n",
       "Manaus3                                capital        \n",
       "Boa Vista3                             capital        \n",
       "Belém3                                 capital        \n",
       "Macapá3                                capital        \n",
       "Palmas3                                capital        \n",
       "São Luís3                              capital        \n",
       "Teresina3                              capital        \n",
       "Fortaleza3                             capital        \n",
       "Natal3                                 capital        \n",
       "João Pessoa3                           capital        \n",
       "Recife3                                capital        \n",
       "Maceió3                                capital        \n",
       "Aracaju3                               capital        \n",
       "Salvador3                              capital        \n",
       "Belo Horizonte3                        capital        \n",
       "Vitória3                               capital        \n",
       "Rio de Janeiro7                        capital        \n",
       "São Paulo6                             capital        \n",
       "Curitiba3                              capital        \n",
       "Florianópolis3                         capital        \n",
       "Porto Alegre3                          capital        \n",
       "Campo Grande3                          capital        \n",
       "Cuiabá3                                capital        \n",
       "Goiânia3                               capital        \n",
       "Brasília3                              capital        \n",
       "Fundamental incompleto ou equivalente3 gescol         \n",
       "Médio incompleto ou equivalente3       gescol         \n",
       "Superior incompleto ou equivalente3    gescol         \n",
       "Superior completo3                     gescol         \n",
       "                                       abr_nome                             \n",
       "Branca                                 Branca                               \n",
       "Preta                                  Preta                                \n",
       "Parda                                  Parda                                \n",
       "Até 1/2 SM                             Até 1/2 SM                           \n",
       "1/2 até 1 SM                           1/2 até 1 SM                         \n",
       "1 até 2 SM                             1 até 2 SM                           \n",
       "2 até 3 SM                             2 até 3 SM                           \n",
       "Mais de 3 SM                           Mais de 3 SM                         \n",
       "18 a 24 anos                           18 a 24 anos                         \n",
       "25 a 29 anos                           25 a 29 anos                         \n",
       "30 a 39 anos                           30 a 39 anos                         \n",
       "40 anos ou mais                        40 anos ou mais                      \n",
       "urbano                                 urbano                               \n",
       "rural                                  rural                                \n",
       "Rondônia                               Rondônia                             \n",
       "Acre                                   Acre                                 \n",
       "Amazonas                               Amazonas                             \n",
       "Roraima                                Roraima                              \n",
       "Pará                                   Pará                                 \n",
       "Amapá                                  Amapá                                \n",
       "Tocantins                              Tocantins                            \n",
       "Maranhão                               Maranhão                             \n",
       "Piauí                                  Piauí                                \n",
       "Ceará                                  Ceará                                \n",
       "Rio Grande do Norte                    Rio Grande do Norte                  \n",
       "Paraíba                                Paraíba                              \n",
       "Pernambuco                             Pernambuco                           \n",
       "Alagoas                                Alagoas                              \n",
       "Sergipe                                Sergipe                              \n",
       "Bahia                                  Bahia                                \n",
       "⋮                                      ⋮                                    \n",
       "Rio Branco3                            Rio Branco                           \n",
       "Manaus3                                Manaus                               \n",
       "Boa Vista3                             Boa Vista                            \n",
       "Belém3                                 Belém                                \n",
       "Macapá3                                Macapá                               \n",
       "Palmas3                                Palmas                               \n",
       "São Luís3                              São Luís                             \n",
       "Teresina3                              Teresina                             \n",
       "Fortaleza3                             Fortaleza                            \n",
       "Natal3                                 Natal                                \n",
       "João Pessoa3                           João Pessoa                          \n",
       "Recife3                                Recife                               \n",
       "Maceió3                                Maceió                               \n",
       "Aracaju3                               Aracaju                              \n",
       "Salvador3                              Salvador                             \n",
       "Belo Horizonte3                        Belo Horizonte                       \n",
       "Vitória3                               Vitória                              \n",
       "Rio de Janeiro7                        Rio de Janeiro                       \n",
       "São Paulo6                             São Paulo                            \n",
       "Curitiba3                              Curitiba                             \n",
       "Florianópolis3                         Florianópolis                        \n",
       "Porto Alegre3                          Porto Alegre                         \n",
       "Campo Grande3                          Campo Grande                         \n",
       "Cuiabá3                                Cuiabá                               \n",
       "Goiânia3                               Goiânia                              \n",
       "Brasília3                              Brasília                             \n",
       "Fundamental incompleto ou equivalente3 Fundamental incompleto ou equivalente\n",
       "Médio incompleto ou equivalente3       Médio incompleto ou equivalente      \n",
       "Superior incompleto ou equivalente3    Superior incompleto ou equivalente   \n",
       "Superior completo3                     Superior completo                    \n",
       "                                       Ano  Indicador Sim       LowerS    \n",
       "Branca                                 2019 S016P     0.8747043 0.8394447 \n",
       "Preta                                  2019 S016P     0.9270440 0.8819540 \n",
       "Parda                                  2019 S016P     0.8998264 0.8813427 \n",
       "Até 1/2 SM                             2019 S016P     0.8811666 0.8556610 \n",
       "1/2 até 1 SM                           2019 S016P     0.8986344 0.8672705 \n",
       "1 até 2 SM                             2019 S016P     0.9321180 0.8983597 \n",
       "2 até 3 SM                             2019 S016P     0.9131325 0.8480609 \n",
       "Mais de 3 SM                           2019 S016P     0.8449011 0.7501941 \n",
       "18 a 24 anos                           2019 S016P     0.8784567 0.8471783 \n",
       "25 a 29 anos                           2019 S016P     0.9121180 0.8854396 \n",
       "30 a 39 anos                           2019 S016P     0.8996282 0.8718667 \n",
       "40 anos ou mais                        2019 S016P     0.8549542 0.7687697 \n",
       "urbano                                 2019 S016P     0.9007125 0.8821043 \n",
       "rural                                  2019 S016P     0.8541637 0.8152466 \n",
       "Rondônia                               2019 S016P     0.9657274 0.9374381 \n",
       "Acre                                   2019 S016P     0.9341028 0.8604602 \n",
       "Amazonas                               2019 S016P     0.9073433 0.8454635 \n",
       "Roraima                                2019 S016P     0.7734318 0.6039876 \n",
       "Pará                                   2019 S016P     0.9134246 0.8575382 \n",
       "Amapá                                  2019 S016P     0.9555542 0.8885170 \n",
       "Tocantins                              2019 S016P     0.8106428 0.6778693 \n",
       "Maranhão                               2019 S016P     0.8095186 0.7336835 \n",
       "Piauí                                  2019 S016P     0.9391357 0.8887311 \n",
       "Ceará                                  2019 S016P     0.8040217 0.7193974 \n",
       "Rio Grande do Norte                    2019 S016P     0.9353931 0.8588831 \n",
       "Paraíba                                2019 S016P     0.8566499 0.7581708 \n",
       "Pernambuco                             2019 S016P     0.8711616 0.8068706 \n",
       "Alagoas                                2019 S016P     0.8033046 0.7070219 \n",
       "Sergipe                                2019 S016P     0.8516848 0.7504449 \n",
       "Bahia                                  2019 S016P     0.9096653 0.8455323 \n",
       "⋮                                      ⋮    ⋮         ⋮         ⋮         \n",
       "Rio Branco3                            2019 S019P     0.8528056 0.73447058\n",
       "Manaus3                                2019 S019P     0.8827997 0.77794640\n",
       "Boa Vista3                             2019 S019P     0.8884627 0.79679075\n",
       "Belém3                                 2019 S019P     0.9571920 0.89676894\n",
       "Macapá3                                2019 S019P     0.4130939 0.06835764\n",
       "Palmas3                                2019 S019P     1.0000000 1.00000000\n",
       "São Luís3                              2019 S019P     0.9072290 0.79492742\n",
       "Teresina3                              2019 S019P     1.0000000 1.00000000\n",
       "Fortaleza3                             2019 S019P     0.8528462 0.70056621\n",
       "Natal3                                 2019 S019P     0.9574035 0.89567915\n",
       "João Pessoa3                           2019 S019P     0.8469751 0.72489071\n",
       "Recife3                                2019 S019P     0.7957699 0.59439109\n",
       "Maceió3                                2019 S019P     0.9052185 0.82355588\n",
       "Aracaju3                               2019 S019P     0.8719312 0.72567301\n",
       "Salvador3                              2019 S019P     0.9772048 0.93134998\n",
       "Belo Horizonte3                        2019 S019P     0.8377275 0.71752331\n",
       "Vitória3                               2019 S019P     1.0000000 1.00000000\n",
       "Rio de Janeiro7                        2019 S019P     0.9813696 0.94454301\n",
       "São Paulo6                             2019 S019P     0.9485502 0.89371537\n",
       "Curitiba3                              2019 S019P     0.8922268 0.69385031\n",
       "Florianópolis3                         2019 S019P     1.0000000 1.00000000\n",
       "Porto Alegre3                          2019 S019P     0.9766329 0.93037992\n",
       "Campo Grande3                          2019 S019P     0.9786548 0.94878671\n",
       "Cuiabá3                                2019 S019P     0.9146546 0.79753409\n",
       "Goiânia3                               2019 S019P     0.8985256 0.76221954\n",
       "Brasília3                              2019 S019P     0.8662223 0.73669275\n",
       "Fundamental incompleto ou equivalente3 2019 S019P     0.7421529 0.68603013\n",
       "Médio incompleto ou equivalente3       2019 S019P     0.8300336 0.78011145\n",
       "Superior incompleto ou equivalente3    2019 S019P     0.9019019 0.87235022\n",
       "Superior completo3                     2019 S019P     0.9757760 0.95978718\n",
       "                                       UpperS    cvS         \n",
       "Branca                                 0.9099639 0.02056687  \n",
       "Preta                                  0.9721340 0.02481599  \n",
       "Parda                                  0.9183100 0.01048046  \n",
       "Até 1/2 SM                             0.9066723 0.01476830  \n",
       "1/2 até 1 SM                           0.9299982 0.01780731  \n",
       "1 até 2 SM                             0.9658762 0.01847824  \n",
       "2 até 3 SM                             0.9782041 0.03635882  \n",
       "Mais de 3 SM                           0.9396081 0.05719106  \n",
       "18 a 24 anos                           0.9097351 0.01816671  \n",
       "25 a 29 anos                           0.9387963 0.01492314  \n",
       "30 a 39 anos                           0.9273898 0.01574462  \n",
       "40 anos ou mais                        0.9411388 0.05143260  \n",
       "urbano                                 0.9193208 0.01054074  \n",
       "rural                                  0.8930807 0.02324614  \n",
       "Rondônia                               0.9940167 0.01494582  \n",
       "Acre                                   1.0077454 0.04022411  \n",
       "Amazonas                               0.9692231 0.03479597  \n",
       "Roraima                                0.9428759 0.11177804  \n",
       "Pará                                   0.9693110 0.03121660  \n",
       "Amapá                                  1.0225915 0.03579421  \n",
       "Tocantins                              0.9434163 0.08356679  \n",
       "Maranhão                               0.8853537 0.04779642  \n",
       "Piauí                                  0.9895403 0.02738380  \n",
       "Ceará                                  0.8886460 0.05370064  \n",
       "Rio Grande do Norte                    1.0119032 0.04173267  \n",
       "Paraíba                                0.9551291 0.05865337  \n",
       "Pernambuco                             0.9354526 0.03765332  \n",
       "Alagoas                                0.8995873 0.06115329  \n",
       "Sergipe                                0.9529247 0.06064918  \n",
       "Bahia                                  0.9737983 0.03597093  \n",
       "⋮                                      ⋮         ⋮           \n",
       "Rio Branco3                            0.9711407 7.079706e-02\n",
       "Manaus3                                0.9876530 6.059989e-02\n",
       "Boa Vista3                             0.9801346 5.264403e-02\n",
       "Belém3                                 1.0176151 3.220740e-02\n",
       "Macapá3                                0.7578301 4.257847e-01\n",
       "Palmas3                                1.0000000 0.000000e+00\n",
       "São Luís3                              1.0195307 6.315693e-02\n",
       "Teresina3                              1.0000000 2.414201e-17\n",
       "Fortaleza3                             1.0051261 9.110117e-02\n",
       "Natal3                                 1.0191278 3.289375e-02\n",
       "João Pessoa3                           0.9690595 7.354301e-02\n",
       "Recife3                                0.9971488 1.291155e-01\n",
       "Maceió3                                0.9868812 4.602799e-02\n",
       "Aracaju3                               1.0181894 8.558347e-02\n",
       "Salvador3                              1.0230596 2.394149e-02\n",
       "Belo Horizonte3                        0.9579316 7.320970e-02\n",
       "Vitória3                               1.0000000 0.000000e+00\n",
       "Rio de Janeiro7                        1.0181962 1.914613e-02\n",
       "São Paulo6                             1.0033849 2.949496e-02\n",
       "Curitiba3                              1.0906034 1.134402e-01\n",
       "Florianópolis3                         1.0000000 2.862188e-17\n",
       "Porto Alegre3                          1.0228859 2.416353e-02\n",
       "Campo Grande3                          1.0085229 1.557148e-02\n",
       "Cuiabá3                                1.0317751 6.533226e-02\n",
       "Goiânia3                               1.0348317 7.739925e-02\n",
       "Brasília3                              0.9957519 7.629419e-02\n",
       "Fundamental incompleto ou equivalente3 0.7982757 3.858315e-02\n",
       "Médio incompleto ou equivalente3       0.8799558 3.068667e-02\n",
       "Superior incompleto ou equivalente3    0.9314535 1.671761e-02\n",
       "Superior completo3                     0.9917647 8.360210e-03"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matriz_indicadores"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Preenchendo a tabela com as abrangencia Brasil e total das capitais"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "matriz_totais <- popula_indicadores(design_por_abrangencia, totais, indicadores, Ano, \"total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 8 × 8</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>abr_tipo</th><th scope=col>abr_nome</th><th scope=col>Ano</th><th scope=col>Indicador</th><th scope=col>Sim</th><th scope=col>LowerS</th><th scope=col>UpperS</th><th scope=col>cvS</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>S016PSim</th><td>total</td><td>Brasil </td><td>2019</td><td>S016P</td><td>0.8936008</td><td>0.8767389</td><td>0.9104627</td><td>0.00962753</td></tr>\n",
       "\t<tr><th scope=row>S016PSim1</th><td>total</td><td>Capital</td><td>2019</td><td>S016P</td><td>0.8709017</td><td>0.8300706</td><td>0.9117328</td><td>0.02392071</td></tr>\n",
       "\t<tr><th scope=row>S017PSim</th><td>total</td><td>Brasil </td><td>2019</td><td>S017P</td><td>0.8731066</td><td>0.8539498</td><td>0.8922634</td><td>0.01119456</td></tr>\n",
       "\t<tr><th scope=row>S017PSim1</th><td>total</td><td>Capital</td><td>2019</td><td>S017P</td><td>0.8488005</td><td>0.8054984</td><td>0.8921025</td><td>0.02602884</td></tr>\n",
       "\t<tr><th scope=row>S018PSim</th><td>total</td><td>Brasil </td><td>2019</td><td>S018P</td><td>0.8320475</td><td>0.8093523</td><td>0.8547428</td><td>0.01391678</td></tr>\n",
       "\t<tr><th scope=row>S018PSim1</th><td>total</td><td>Capital</td><td>2019</td><td>S018P</td><td>0.8717783</td><td>0.8414178</td><td>0.9021387</td><td>0.01776864</td></tr>\n",
       "\t<tr><th scope=row>S019PSim</th><td>total</td><td>Brasil </td><td>2019</td><td>S019P</td><td>0.8731421</td><td>0.8528793</td><td>0.8934049</td><td>0.01184042</td></tr>\n",
       "\t<tr><th scope=row>S019PSim1</th><td>total</td><td>Capital</td><td>2019</td><td>S019P</td><td>0.9094361</td><td>0.8822897</td><td>0.9365825</td><td>0.01522971</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 8 × 8\n",
       "\\begin{tabular}{r|llllllll}\n",
       "  & abr\\_tipo & abr\\_nome & Ano & Indicador & Sim & LowerS & UpperS & cvS\\\\\n",
       "  & <chr> & <chr> & <chr> & <chr> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\tS016PSim & total & Brasil  & 2019 & S016P & 0.8936008 & 0.8767389 & 0.9104627 & 0.00962753\\\\\n",
       "\tS016PSim1 & total & Capital & 2019 & S016P & 0.8709017 & 0.8300706 & 0.9117328 & 0.02392071\\\\\n",
       "\tS017PSim & total & Brasil  & 2019 & S017P & 0.8731066 & 0.8539498 & 0.8922634 & 0.01119456\\\\\n",
       "\tS017PSim1 & total & Capital & 2019 & S017P & 0.8488005 & 0.8054984 & 0.8921025 & 0.02602884\\\\\n",
       "\tS018PSim & total & Brasil  & 2019 & S018P & 0.8320475 & 0.8093523 & 0.8547428 & 0.01391678\\\\\n",
       "\tS018PSim1 & total & Capital & 2019 & S018P & 0.8717783 & 0.8414178 & 0.9021387 & 0.01776864\\\\\n",
       "\tS019PSim & total & Brasil  & 2019 & S019P & 0.8731421 & 0.8528793 & 0.8934049 & 0.01184042\\\\\n",
       "\tS019PSim1 & total & Capital & 2019 & S019P & 0.9094361 & 0.8822897 & 0.9365825 & 0.01522971\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 8 × 8\n",
       "\n",
       "| <!--/--> | abr_tipo &lt;chr&gt; | abr_nome &lt;chr&gt; | Ano &lt;chr&gt; | Indicador &lt;chr&gt; | Sim &lt;dbl&gt; | LowerS &lt;dbl&gt; | UpperS &lt;dbl&gt; | cvS &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|\n",
       "| S016PSim | total | Brasil  | 2019 | S016P | 0.8936008 | 0.8767389 | 0.9104627 | 0.00962753 |\n",
       "| S016PSim1 | total | Capital | 2019 | S016P | 0.8709017 | 0.8300706 | 0.9117328 | 0.02392071 |\n",
       "| S017PSim | total | Brasil  | 2019 | S017P | 0.8731066 | 0.8539498 | 0.8922634 | 0.01119456 |\n",
       "| S017PSim1 | total | Capital | 2019 | S017P | 0.8488005 | 0.8054984 | 0.8921025 | 0.02602884 |\n",
       "| S018PSim | total | Brasil  | 2019 | S018P | 0.8320475 | 0.8093523 | 0.8547428 | 0.01391678 |\n",
       "| S018PSim1 | total | Capital | 2019 | S018P | 0.8717783 | 0.8414178 | 0.9021387 | 0.01776864 |\n",
       "| S019PSim | total | Brasil  | 2019 | S019P | 0.8731421 | 0.8528793 | 0.8934049 | 0.01184042 |\n",
       "| S019PSim1 | total | Capital | 2019 | S019P | 0.9094361 | 0.8822897 | 0.9365825 | 0.01522971 |\n",
       "\n"
      ],
      "text/plain": [
       "          abr_tipo abr_nome Ano  Indicador Sim       LowerS    UpperS   \n",
       "S016PSim  total    Brasil   2019 S016P     0.8936008 0.8767389 0.9104627\n",
       "S016PSim1 total    Capital  2019 S016P     0.8709017 0.8300706 0.9117328\n",
       "S017PSim  total    Brasil   2019 S017P     0.8731066 0.8539498 0.8922634\n",
       "S017PSim1 total    Capital  2019 S017P     0.8488005 0.8054984 0.8921025\n",
       "S018PSim  total    Brasil   2019 S018P     0.8320475 0.8093523 0.8547428\n",
       "S018PSim1 total    Capital  2019 S018P     0.8717783 0.8414178 0.9021387\n",
       "S019PSim  total    Brasil   2019 S019P     0.8731421 0.8528793 0.8934049\n",
       "S019PSim1 total    Capital  2019 S019P     0.9094361 0.8822897 0.9365825\n",
       "          cvS       \n",
       "S016PSim  0.00962753\n",
       "S016PSim1 0.02392071\n",
       "S017PSim  0.01119456\n",
       "S017PSim1 0.02602884\n",
       "S018PSim  0.01391678\n",
       "S018PSim1 0.01776864\n",
       "S019PSim  0.01184042\n",
       "S019PSim1 0.01522971"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matriz_totais"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Unindo tabela de indicadores e de totais"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "matriz_final <-rbind(matriz_indicadores,matriz_totais)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Visualizando tabela de indicadores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 316 × 8</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>abr_tipo</th><th scope=col>abr_nome</th><th scope=col>Ano</th><th scope=col>Indicador</th><th scope=col>Sim</th><th scope=col>LowerS</th><th scope=col>UpperS</th><th scope=col>cvS</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Branca</th><td>raça           </td><td>Branca             </td><td>2019</td><td>S016P</td><td>0.8747043</td><td>0.8394447</td><td>0.9099639</td><td>0.02056687</td></tr>\n",
       "\t<tr><th scope=row>Preta</th><td>raça           </td><td>Preta              </td><td>2019</td><td>S016P</td><td>0.9270440</td><td>0.8819540</td><td>0.9721340</td><td>0.02481599</td></tr>\n",
       "\t<tr><th scope=row>Parda</th><td>raça           </td><td>Parda              </td><td>2019</td><td>S016P</td><td>0.8998264</td><td>0.8813427</td><td>0.9183100</td><td>0.01048046</td></tr>\n",
       "\t<tr><th scope=row>Até 1/2 SM</th><td>rend_per_capita</td><td>Até 1/2 SM         </td><td>2019</td><td>S016P</td><td>0.8811666</td><td>0.8556610</td><td>0.9066723</td><td>0.01476830</td></tr>\n",
       "\t<tr><th scope=row>1/2 até 1 SM</th><td>rend_per_capita</td><td>1/2 até 1 SM       </td><td>2019</td><td>S016P</td><td>0.8986344</td><td>0.8672705</td><td>0.9299982</td><td>0.01780731</td></tr>\n",
       "\t<tr><th scope=row>1 até 2 SM</th><td>rend_per_capita</td><td>1 até 2 SM         </td><td>2019</td><td>S016P</td><td>0.9321180</td><td>0.8983597</td><td>0.9658762</td><td>0.01847824</td></tr>\n",
       "\t<tr><th scope=row>2 até 3 SM</th><td>rend_per_capita</td><td>2 até 3 SM         </td><td>2019</td><td>S016P</td><td>0.9131325</td><td>0.8480609</td><td>0.9782041</td><td>0.03635882</td></tr>\n",
       "\t<tr><th scope=row>Mais de 3 SM</th><td>rend_per_capita</td><td>Mais de 3 SM       </td><td>2019</td><td>S016P</td><td>0.8449011</td><td>0.7501941</td><td>0.9396081</td><td>0.05719106</td></tr>\n",
       "\t<tr><th scope=row>18 a 24 anos</th><td>fx_idade_s     </td><td>18 a 24 anos       </td><td>2019</td><td>S016P</td><td>0.8784567</td><td>0.8471783</td><td>0.9097351</td><td>0.01816671</td></tr>\n",
       "\t<tr><th scope=row>25 a 29 anos</th><td>fx_idade_s     </td><td>25 a 29 anos       </td><td>2019</td><td>S016P</td><td>0.9121180</td><td>0.8854396</td><td>0.9387963</td><td>0.01492314</td></tr>\n",
       "\t<tr><th scope=row>30 a 39 anos</th><td>fx_idade_s     </td><td>30 a 39 anos       </td><td>2019</td><td>S016P</td><td>0.8996282</td><td>0.8718667</td><td>0.9273898</td><td>0.01574462</td></tr>\n",
       "\t<tr><th scope=row>40 anos ou mais</th><td>fx_idade_s     </td><td>40 anos ou mais    </td><td>2019</td><td>S016P</td><td>0.8549542</td><td>0.7687697</td><td>0.9411388</td><td>0.05143260</td></tr>\n",
       "\t<tr><th scope=row>urbano</th><td>urb_rur        </td><td>urbano             </td><td>2019</td><td>S016P</td><td>0.9007125</td><td>0.8821043</td><td>0.9193208</td><td>0.01054074</td></tr>\n",
       "\t<tr><th scope=row>rural</th><td>urb_rur        </td><td>rural              </td><td>2019</td><td>S016P</td><td>0.8541637</td><td>0.8152466</td><td>0.8930807</td><td>0.02324614</td></tr>\n",
       "\t<tr><th scope=row>Rondônia</th><td>uf             </td><td>Rondônia           </td><td>2019</td><td>S016P</td><td>0.9657274</td><td>0.9374381</td><td>0.9940167</td><td>0.01494582</td></tr>\n",
       "\t<tr><th scope=row>Acre</th><td>uf             </td><td>Acre               </td><td>2019</td><td>S016P</td><td>0.9341028</td><td>0.8604602</td><td>1.0077454</td><td>0.04022411</td></tr>\n",
       "\t<tr><th scope=row>Amazonas</th><td>uf             </td><td>Amazonas           </td><td>2019</td><td>S016P</td><td>0.9073433</td><td>0.8454635</td><td>0.9692231</td><td>0.03479597</td></tr>\n",
       "\t<tr><th scope=row>Roraima</th><td>uf             </td><td>Roraima            </td><td>2019</td><td>S016P</td><td>0.7734318</td><td>0.6039876</td><td>0.9428759</td><td>0.11177804</td></tr>\n",
       "\t<tr><th scope=row>Pará</th><td>uf             </td><td>Pará               </td><td>2019</td><td>S016P</td><td>0.9134246</td><td>0.8575382</td><td>0.9693110</td><td>0.03121660</td></tr>\n",
       "\t<tr><th scope=row>Amapá</th><td>uf             </td><td>Amapá              </td><td>2019</td><td>S016P</td><td>0.9555542</td><td>0.8885170</td><td>1.0225915</td><td>0.03579421</td></tr>\n",
       "\t<tr><th scope=row>Tocantins</th><td>uf             </td><td>Tocantins          </td><td>2019</td><td>S016P</td><td>0.8106428</td><td>0.6778693</td><td>0.9434163</td><td>0.08356679</td></tr>\n",
       "\t<tr><th scope=row>Maranhão</th><td>uf             </td><td>Maranhão           </td><td>2019</td><td>S016P</td><td>0.8095186</td><td>0.7336835</td><td>0.8853537</td><td>0.04779642</td></tr>\n",
       "\t<tr><th scope=row>Piauí</th><td>uf             </td><td>Piauí              </td><td>2019</td><td>S016P</td><td>0.9391357</td><td>0.8887311</td><td>0.9895403</td><td>0.02738380</td></tr>\n",
       "\t<tr><th scope=row>Ceará</th><td>uf             </td><td>Ceará              </td><td>2019</td><td>S016P</td><td>0.8040217</td><td>0.7193974</td><td>0.8886460</td><td>0.05370064</td></tr>\n",
       "\t<tr><th scope=row>Rio Grande do Norte</th><td>uf             </td><td>Rio Grande do Norte</td><td>2019</td><td>S016P</td><td>0.9353931</td><td>0.8588831</td><td>1.0119032</td><td>0.04173267</td></tr>\n",
       "\t<tr><th scope=row>Paraíba</th><td>uf             </td><td>Paraíba            </td><td>2019</td><td>S016P</td><td>0.8566499</td><td>0.7581708</td><td>0.9551291</td><td>0.05865337</td></tr>\n",
       "\t<tr><th scope=row>Pernambuco</th><td>uf             </td><td>Pernambuco         </td><td>2019</td><td>S016P</td><td>0.8711616</td><td>0.8068706</td><td>0.9354526</td><td>0.03765332</td></tr>\n",
       "\t<tr><th scope=row>Alagoas</th><td>uf             </td><td>Alagoas            </td><td>2019</td><td>S016P</td><td>0.8033046</td><td>0.7070219</td><td>0.8995873</td><td>0.06115329</td></tr>\n",
       "\t<tr><th scope=row>Sergipe</th><td>uf             </td><td>Sergipe            </td><td>2019</td><td>S016P</td><td>0.8516848</td><td>0.7504449</td><td>0.9529247</td><td>0.06064918</td></tr>\n",
       "\t<tr><th scope=row>Bahia</th><td>uf             </td><td>Bahia              </td><td>2019</td><td>S016P</td><td>0.9096653</td><td>0.8455323</td><td>0.9737983</td><td>0.03597093</td></tr>\n",
       "\t<tr><th scope=row>⋮</th><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n",
       "\t<tr><th scope=row>Fortaleza3</th><td>capital</td><td>Fortaleza                            </td><td>2019</td><td>S019P</td><td>0.8528462</td><td>0.7005662</td><td>1.0051261</td><td>9.110117e-02</td></tr>\n",
       "\t<tr><th scope=row>Natal3</th><td>capital</td><td>Natal                                </td><td>2019</td><td>S019P</td><td>0.9574035</td><td>0.8956791</td><td>1.0191278</td><td>3.289375e-02</td></tr>\n",
       "\t<tr><th scope=row>João Pessoa3</th><td>capital</td><td>João Pessoa                          </td><td>2019</td><td>S019P</td><td>0.8469751</td><td>0.7248907</td><td>0.9690595</td><td>7.354301e-02</td></tr>\n",
       "\t<tr><th scope=row>Recife3</th><td>capital</td><td>Recife                               </td><td>2019</td><td>S019P</td><td>0.7957699</td><td>0.5943911</td><td>0.9971488</td><td>1.291155e-01</td></tr>\n",
       "\t<tr><th scope=row>Maceió3</th><td>capital</td><td>Maceió                               </td><td>2019</td><td>S019P</td><td>0.9052185</td><td>0.8235559</td><td>0.9868812</td><td>4.602799e-02</td></tr>\n",
       "\t<tr><th scope=row>Aracaju3</th><td>capital</td><td>Aracaju                              </td><td>2019</td><td>S019P</td><td>0.8719312</td><td>0.7256730</td><td>1.0181894</td><td>8.558347e-02</td></tr>\n",
       "\t<tr><th scope=row>Salvador3</th><td>capital</td><td>Salvador                             </td><td>2019</td><td>S019P</td><td>0.9772048</td><td>0.9313500</td><td>1.0230596</td><td>2.394149e-02</td></tr>\n",
       "\t<tr><th scope=row>Belo Horizonte3</th><td>capital</td><td>Belo Horizonte                       </td><td>2019</td><td>S019P</td><td>0.8377275</td><td>0.7175233</td><td>0.9579316</td><td>7.320970e-02</td></tr>\n",
       "\t<tr><th scope=row>Vitória3</th><td>capital</td><td>Vitória                              </td><td>2019</td><td>S019P</td><td>1.0000000</td><td>1.0000000</td><td>1.0000000</td><td>0.000000e+00</td></tr>\n",
       "\t<tr><th scope=row>Rio de Janeiro7</th><td>capital</td><td>Rio de Janeiro                       </td><td>2019</td><td>S019P</td><td>0.9813696</td><td>0.9445430</td><td>1.0181962</td><td>1.914613e-02</td></tr>\n",
       "\t<tr><th scope=row>São Paulo6</th><td>capital</td><td>São Paulo                            </td><td>2019</td><td>S019P</td><td>0.9485502</td><td>0.8937154</td><td>1.0033849</td><td>2.949496e-02</td></tr>\n",
       "\t<tr><th scope=row>Curitiba3</th><td>capital</td><td>Curitiba                             </td><td>2019</td><td>S019P</td><td>0.8922268</td><td>0.6938503</td><td>1.0906034</td><td>1.134402e-01</td></tr>\n",
       "\t<tr><th scope=row>Florianópolis3</th><td>capital</td><td>Florianópolis                        </td><td>2019</td><td>S019P</td><td>1.0000000</td><td>1.0000000</td><td>1.0000000</td><td>2.862188e-17</td></tr>\n",
       "\t<tr><th scope=row>Porto Alegre3</th><td>capital</td><td>Porto Alegre                         </td><td>2019</td><td>S019P</td><td>0.9766329</td><td>0.9303799</td><td>1.0228859</td><td>2.416353e-02</td></tr>\n",
       "\t<tr><th scope=row>Campo Grande3</th><td>capital</td><td>Campo Grande                         </td><td>2019</td><td>S019P</td><td>0.9786548</td><td>0.9487867</td><td>1.0085229</td><td>1.557148e-02</td></tr>\n",
       "\t<tr><th scope=row>Cuiabá3</th><td>capital</td><td>Cuiabá                               </td><td>2019</td><td>S019P</td><td>0.9146546</td><td>0.7975341</td><td>1.0317751</td><td>6.533226e-02</td></tr>\n",
       "\t<tr><th scope=row>Goiânia3</th><td>capital</td><td>Goiânia                              </td><td>2019</td><td>S019P</td><td>0.8985256</td><td>0.7622195</td><td>1.0348317</td><td>7.739925e-02</td></tr>\n",
       "\t<tr><th scope=row>Brasília3</th><td>capital</td><td>Brasília                             </td><td>2019</td><td>S019P</td><td>0.8662223</td><td>0.7366927</td><td>0.9957519</td><td>7.629419e-02</td></tr>\n",
       "\t<tr><th scope=row>Fundamental incompleto ou equivalente3</th><td>gescol </td><td>Fundamental incompleto ou equivalente</td><td>2019</td><td>S019P</td><td>0.7421529</td><td>0.6860301</td><td>0.7982757</td><td>3.858315e-02</td></tr>\n",
       "\t<tr><th scope=row>Médio incompleto ou equivalente3</th><td>gescol </td><td>Médio incompleto ou equivalente      </td><td>2019</td><td>S019P</td><td>0.8300336</td><td>0.7801115</td><td>0.8799558</td><td>3.068667e-02</td></tr>\n",
       "\t<tr><th scope=row>Superior incompleto ou equivalente3</th><td>gescol </td><td>Superior incompleto ou equivalente   </td><td>2019</td><td>S019P</td><td>0.9019019</td><td>0.8723502</td><td>0.9314535</td><td>1.671761e-02</td></tr>\n",
       "\t<tr><th scope=row>Superior completo3</th><td>gescol </td><td>Superior completo                    </td><td>2019</td><td>S019P</td><td>0.9757760</td><td>0.9597872</td><td>0.9917647</td><td>8.360210e-03</td></tr>\n",
       "\t<tr><th scope=row>S016PSim</th><td>total  </td><td>Brasil                               </td><td>2019</td><td>S016P</td><td>0.8936008</td><td>0.8767389</td><td>0.9104627</td><td>9.627530e-03</td></tr>\n",
       "\t<tr><th scope=row>S016PSim1</th><td>total  </td><td>Capital                              </td><td>2019</td><td>S016P</td><td>0.8709017</td><td>0.8300706</td><td>0.9117328</td><td>2.392071e-02</td></tr>\n",
       "\t<tr><th scope=row>S017PSim</th><td>total  </td><td>Brasil                               </td><td>2019</td><td>S017P</td><td>0.8731066</td><td>0.8539498</td><td>0.8922634</td><td>1.119456e-02</td></tr>\n",
       "\t<tr><th scope=row>S017PSim1</th><td>total  </td><td>Capital                              </td><td>2019</td><td>S017P</td><td>0.8488005</td><td>0.8054984</td><td>0.8921025</td><td>2.602884e-02</td></tr>\n",
       "\t<tr><th scope=row>S018PSim</th><td>total  </td><td>Brasil                               </td><td>2019</td><td>S018P</td><td>0.8320475</td><td>0.8093523</td><td>0.8547428</td><td>1.391678e-02</td></tr>\n",
       "\t<tr><th scope=row>S018PSim1</th><td>total  </td><td>Capital                              </td><td>2019</td><td>S018P</td><td>0.8717783</td><td>0.8414178</td><td>0.9021387</td><td>1.776864e-02</td></tr>\n",
       "\t<tr><th scope=row>S019PSim</th><td>total  </td><td>Brasil                               </td><td>2019</td><td>S019P</td><td>0.8731421</td><td>0.8528793</td><td>0.8934049</td><td>1.184042e-02</td></tr>\n",
       "\t<tr><th scope=row>S019PSim1</th><td>total  </td><td>Capital                              </td><td>2019</td><td>S019P</td><td>0.9094361</td><td>0.8822897</td><td>0.9365825</td><td>1.522971e-02</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 316 × 8\n",
       "\\begin{tabular}{r|llllllll}\n",
       "  & abr\\_tipo & abr\\_nome & Ano & Indicador & Sim & LowerS & UpperS & cvS\\\\\n",
       "  & <chr> & <fct> & <chr> & <chr> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\tBranca & raça            & Branca              & 2019 & S016P & 0.8747043 & 0.8394447 & 0.9099639 & 0.02056687\\\\\n",
       "\tPreta & raça            & Preta               & 2019 & S016P & 0.9270440 & 0.8819540 & 0.9721340 & 0.02481599\\\\\n",
       "\tParda & raça            & Parda               & 2019 & S016P & 0.8998264 & 0.8813427 & 0.9183100 & 0.01048046\\\\\n",
       "\tAté 1/2 SM & rend\\_per\\_capita & Até 1/2 SM          & 2019 & S016P & 0.8811666 & 0.8556610 & 0.9066723 & 0.01476830\\\\\n",
       "\t1/2 até 1 SM & rend\\_per\\_capita & 1/2 até 1 SM        & 2019 & S016P & 0.8986344 & 0.8672705 & 0.9299982 & 0.01780731\\\\\n",
       "\t1 até 2 SM & rend\\_per\\_capita & 1 até 2 SM          & 2019 & S016P & 0.9321180 & 0.8983597 & 0.9658762 & 0.01847824\\\\\n",
       "\t2 até 3 SM & rend\\_per\\_capita & 2 até 3 SM          & 2019 & S016P & 0.9131325 & 0.8480609 & 0.9782041 & 0.03635882\\\\\n",
       "\tMais de 3 SM & rend\\_per\\_capita & Mais de 3 SM        & 2019 & S016P & 0.8449011 & 0.7501941 & 0.9396081 & 0.05719106\\\\\n",
       "\t18 a 24 anos & fx\\_idade\\_s      & 18 a 24 anos        & 2019 & S016P & 0.8784567 & 0.8471783 & 0.9097351 & 0.01816671\\\\\n",
       "\t25 a 29 anos & fx\\_idade\\_s      & 25 a 29 anos        & 2019 & S016P & 0.9121180 & 0.8854396 & 0.9387963 & 0.01492314\\\\\n",
       "\t30 a 39 anos & fx\\_idade\\_s      & 30 a 39 anos        & 2019 & S016P & 0.8996282 & 0.8718667 & 0.9273898 & 0.01574462\\\\\n",
       "\t40 anos ou mais & fx\\_idade\\_s      & 40 anos ou mais     & 2019 & S016P & 0.8549542 & 0.7687697 & 0.9411388 & 0.05143260\\\\\n",
       "\turbano & urb\\_rur         & urbano              & 2019 & S016P & 0.9007125 & 0.8821043 & 0.9193208 & 0.01054074\\\\\n",
       "\trural & urb\\_rur         & rural               & 2019 & S016P & 0.8541637 & 0.8152466 & 0.8930807 & 0.02324614\\\\\n",
       "\tRondônia & uf              & Rondônia            & 2019 & S016P & 0.9657274 & 0.9374381 & 0.9940167 & 0.01494582\\\\\n",
       "\tAcre & uf              & Acre                & 2019 & S016P & 0.9341028 & 0.8604602 & 1.0077454 & 0.04022411\\\\\n",
       "\tAmazonas & uf              & Amazonas            & 2019 & S016P & 0.9073433 & 0.8454635 & 0.9692231 & 0.03479597\\\\\n",
       "\tRoraima & uf              & Roraima             & 2019 & S016P & 0.7734318 & 0.6039876 & 0.9428759 & 0.11177804\\\\\n",
       "\tPará & uf              & Pará                & 2019 & S016P & 0.9134246 & 0.8575382 & 0.9693110 & 0.03121660\\\\\n",
       "\tAmapá & uf              & Amapá               & 2019 & S016P & 0.9555542 & 0.8885170 & 1.0225915 & 0.03579421\\\\\n",
       "\tTocantins & uf              & Tocantins           & 2019 & S016P & 0.8106428 & 0.6778693 & 0.9434163 & 0.08356679\\\\\n",
       "\tMaranhão & uf              & Maranhão            & 2019 & S016P & 0.8095186 & 0.7336835 & 0.8853537 & 0.04779642\\\\\n",
       "\tPiauí & uf              & Piauí               & 2019 & S016P & 0.9391357 & 0.8887311 & 0.9895403 & 0.02738380\\\\\n",
       "\tCeará & uf              & Ceará               & 2019 & S016P & 0.8040217 & 0.7193974 & 0.8886460 & 0.05370064\\\\\n",
       "\tRio Grande do Norte & uf              & Rio Grande do Norte & 2019 & S016P & 0.9353931 & 0.8588831 & 1.0119032 & 0.04173267\\\\\n",
       "\tParaíba & uf              & Paraíba             & 2019 & S016P & 0.8566499 & 0.7581708 & 0.9551291 & 0.05865337\\\\\n",
       "\tPernambuco & uf              & Pernambuco          & 2019 & S016P & 0.8711616 & 0.8068706 & 0.9354526 & 0.03765332\\\\\n",
       "\tAlagoas & uf              & Alagoas             & 2019 & S016P & 0.8033046 & 0.7070219 & 0.8995873 & 0.06115329\\\\\n",
       "\tSergipe & uf              & Sergipe             & 2019 & S016P & 0.8516848 & 0.7504449 & 0.9529247 & 0.06064918\\\\\n",
       "\tBahia & uf              & Bahia               & 2019 & S016P & 0.9096653 & 0.8455323 & 0.9737983 & 0.03597093\\\\\n",
       "\t⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮\\\\\n",
       "\tFortaleza3 & capital & Fortaleza                             & 2019 & S019P & 0.8528462 & 0.7005662 & 1.0051261 & 9.110117e-02\\\\\n",
       "\tNatal3 & capital & Natal                                 & 2019 & S019P & 0.9574035 & 0.8956791 & 1.0191278 & 3.289375e-02\\\\\n",
       "\tJoão Pessoa3 & capital & João Pessoa                           & 2019 & S019P & 0.8469751 & 0.7248907 & 0.9690595 & 7.354301e-02\\\\\n",
       "\tRecife3 & capital & Recife                                & 2019 & S019P & 0.7957699 & 0.5943911 & 0.9971488 & 1.291155e-01\\\\\n",
       "\tMaceió3 & capital & Maceió                                & 2019 & S019P & 0.9052185 & 0.8235559 & 0.9868812 & 4.602799e-02\\\\\n",
       "\tAracaju3 & capital & Aracaju                               & 2019 & S019P & 0.8719312 & 0.7256730 & 1.0181894 & 8.558347e-02\\\\\n",
       "\tSalvador3 & capital & Salvador                              & 2019 & S019P & 0.9772048 & 0.9313500 & 1.0230596 & 2.394149e-02\\\\\n",
       "\tBelo Horizonte3 & capital & Belo Horizonte                        & 2019 & S019P & 0.8377275 & 0.7175233 & 0.9579316 & 7.320970e-02\\\\\n",
       "\tVitória3 & capital & Vitória                               & 2019 & S019P & 1.0000000 & 1.0000000 & 1.0000000 & 0.000000e+00\\\\\n",
       "\tRio de Janeiro7 & capital & Rio de Janeiro                        & 2019 & S019P & 0.9813696 & 0.9445430 & 1.0181962 & 1.914613e-02\\\\\n",
       "\tSão Paulo6 & capital & São Paulo                             & 2019 & S019P & 0.9485502 & 0.8937154 & 1.0033849 & 2.949496e-02\\\\\n",
       "\tCuritiba3 & capital & Curitiba                              & 2019 & S019P & 0.8922268 & 0.6938503 & 1.0906034 & 1.134402e-01\\\\\n",
       "\tFlorianópolis3 & capital & Florianópolis                         & 2019 & S019P & 1.0000000 & 1.0000000 & 1.0000000 & 2.862188e-17\\\\\n",
       "\tPorto Alegre3 & capital & Porto Alegre                          & 2019 & S019P & 0.9766329 & 0.9303799 & 1.0228859 & 2.416353e-02\\\\\n",
       "\tCampo Grande3 & capital & Campo Grande                          & 2019 & S019P & 0.9786548 & 0.9487867 & 1.0085229 & 1.557148e-02\\\\\n",
       "\tCuiabá3 & capital & Cuiabá                                & 2019 & S019P & 0.9146546 & 0.7975341 & 1.0317751 & 6.533226e-02\\\\\n",
       "\tGoiânia3 & capital & Goiânia                               & 2019 & S019P & 0.8985256 & 0.7622195 & 1.0348317 & 7.739925e-02\\\\\n",
       "\tBrasília3 & capital & Brasília                              & 2019 & S019P & 0.8662223 & 0.7366927 & 0.9957519 & 7.629419e-02\\\\\n",
       "\tFundamental incompleto ou equivalente3 & gescol  & Fundamental incompleto ou equivalente & 2019 & S019P & 0.7421529 & 0.6860301 & 0.7982757 & 3.858315e-02\\\\\n",
       "\tMédio incompleto ou equivalente3 & gescol  & Médio incompleto ou equivalente       & 2019 & S019P & 0.8300336 & 0.7801115 & 0.8799558 & 3.068667e-02\\\\\n",
       "\tSuperior incompleto ou equivalente3 & gescol  & Superior incompleto ou equivalente    & 2019 & S019P & 0.9019019 & 0.8723502 & 0.9314535 & 1.671761e-02\\\\\n",
       "\tSuperior completo3 & gescol  & Superior completo                     & 2019 & S019P & 0.9757760 & 0.9597872 & 0.9917647 & 8.360210e-03\\\\\n",
       "\tS016PSim & total   & Brasil                                & 2019 & S016P & 0.8936008 & 0.8767389 & 0.9104627 & 9.627530e-03\\\\\n",
       "\tS016PSim1 & total   & Capital                               & 2019 & S016P & 0.8709017 & 0.8300706 & 0.9117328 & 2.392071e-02\\\\\n",
       "\tS017PSim & total   & Brasil                                & 2019 & S017P & 0.8731066 & 0.8539498 & 0.8922634 & 1.119456e-02\\\\\n",
       "\tS017PSim1 & total   & Capital                               & 2019 & S017P & 0.8488005 & 0.8054984 & 0.8921025 & 2.602884e-02\\\\\n",
       "\tS018PSim & total   & Brasil                                & 2019 & S018P & 0.8320475 & 0.8093523 & 0.8547428 & 1.391678e-02\\\\\n",
       "\tS018PSim1 & total   & Capital                               & 2019 & S018P & 0.8717783 & 0.8414178 & 0.9021387 & 1.776864e-02\\\\\n",
       "\tS019PSim & total   & Brasil                                & 2019 & S019P & 0.8731421 & 0.8528793 & 0.8934049 & 1.184042e-02\\\\\n",
       "\tS019PSim1 & total   & Capital                               & 2019 & S019P & 0.9094361 & 0.8822897 & 0.9365825 & 1.522971e-02\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 316 × 8\n",
       "\n",
       "| <!--/--> | abr_tipo &lt;chr&gt; | abr_nome &lt;fct&gt; | Ano &lt;chr&gt; | Indicador &lt;chr&gt; | Sim &lt;dbl&gt; | LowerS &lt;dbl&gt; | UpperS &lt;dbl&gt; | cvS &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|\n",
       "| Branca | raça            | Branca              | 2019 | S016P | 0.8747043 | 0.8394447 | 0.9099639 | 0.02056687 |\n",
       "| Preta | raça            | Preta               | 2019 | S016P | 0.9270440 | 0.8819540 | 0.9721340 | 0.02481599 |\n",
       "| Parda | raça            | Parda               | 2019 | S016P | 0.8998264 | 0.8813427 | 0.9183100 | 0.01048046 |\n",
       "| Até 1/2 SM | rend_per_capita | Até 1/2 SM          | 2019 | S016P | 0.8811666 | 0.8556610 | 0.9066723 | 0.01476830 |\n",
       "| 1/2 até 1 SM | rend_per_capita | 1/2 até 1 SM        | 2019 | S016P | 0.8986344 | 0.8672705 | 0.9299982 | 0.01780731 |\n",
       "| 1 até 2 SM | rend_per_capita | 1 até 2 SM          | 2019 | S016P | 0.9321180 | 0.8983597 | 0.9658762 | 0.01847824 |\n",
       "| 2 até 3 SM | rend_per_capita | 2 até 3 SM          | 2019 | S016P | 0.9131325 | 0.8480609 | 0.9782041 | 0.03635882 |\n",
       "| Mais de 3 SM | rend_per_capita | Mais de 3 SM        | 2019 | S016P | 0.8449011 | 0.7501941 | 0.9396081 | 0.05719106 |\n",
       "| 18 a 24 anos | fx_idade_s      | 18 a 24 anos        | 2019 | S016P | 0.8784567 | 0.8471783 | 0.9097351 | 0.01816671 |\n",
       "| 25 a 29 anos | fx_idade_s      | 25 a 29 anos        | 2019 | S016P | 0.9121180 | 0.8854396 | 0.9387963 | 0.01492314 |\n",
       "| 30 a 39 anos | fx_idade_s      | 30 a 39 anos        | 2019 | S016P | 0.8996282 | 0.8718667 | 0.9273898 | 0.01574462 |\n",
       "| 40 anos ou mais | fx_idade_s      | 40 anos ou mais     | 2019 | S016P | 0.8549542 | 0.7687697 | 0.9411388 | 0.05143260 |\n",
       "| urbano | urb_rur         | urbano              | 2019 | S016P | 0.9007125 | 0.8821043 | 0.9193208 | 0.01054074 |\n",
       "| rural | urb_rur         | rural               | 2019 | S016P | 0.8541637 | 0.8152466 | 0.8930807 | 0.02324614 |\n",
       "| Rondônia | uf              | Rondônia            | 2019 | S016P | 0.9657274 | 0.9374381 | 0.9940167 | 0.01494582 |\n",
       "| Acre | uf              | Acre                | 2019 | S016P | 0.9341028 | 0.8604602 | 1.0077454 | 0.04022411 |\n",
       "| Amazonas | uf              | Amazonas            | 2019 | S016P | 0.9073433 | 0.8454635 | 0.9692231 | 0.03479597 |\n",
       "| Roraima | uf              | Roraima             | 2019 | S016P | 0.7734318 | 0.6039876 | 0.9428759 | 0.11177804 |\n",
       "| Pará | uf              | Pará                | 2019 | S016P | 0.9134246 | 0.8575382 | 0.9693110 | 0.03121660 |\n",
       "| Amapá | uf              | Amapá               | 2019 | S016P | 0.9555542 | 0.8885170 | 1.0225915 | 0.03579421 |\n",
       "| Tocantins | uf              | Tocantins           | 2019 | S016P | 0.8106428 | 0.6778693 | 0.9434163 | 0.08356679 |\n",
       "| Maranhão | uf              | Maranhão            | 2019 | S016P | 0.8095186 | 0.7336835 | 0.8853537 | 0.04779642 |\n",
       "| Piauí | uf              | Piauí               | 2019 | S016P | 0.9391357 | 0.8887311 | 0.9895403 | 0.02738380 |\n",
       "| Ceará | uf              | Ceará               | 2019 | S016P | 0.8040217 | 0.7193974 | 0.8886460 | 0.05370064 |\n",
       "| Rio Grande do Norte | uf              | Rio Grande do Norte | 2019 | S016P | 0.9353931 | 0.8588831 | 1.0119032 | 0.04173267 |\n",
       "| Paraíba | uf              | Paraíba             | 2019 | S016P | 0.8566499 | 0.7581708 | 0.9551291 | 0.05865337 |\n",
       "| Pernambuco | uf              | Pernambuco          | 2019 | S016P | 0.8711616 | 0.8068706 | 0.9354526 | 0.03765332 |\n",
       "| Alagoas | uf              | Alagoas             | 2019 | S016P | 0.8033046 | 0.7070219 | 0.8995873 | 0.06115329 |\n",
       "| Sergipe | uf              | Sergipe             | 2019 | S016P | 0.8516848 | 0.7504449 | 0.9529247 | 0.06064918 |\n",
       "| Bahia | uf              | Bahia               | 2019 | S016P | 0.9096653 | 0.8455323 | 0.9737983 | 0.03597093 |\n",
       "| ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |\n",
       "| Fortaleza3 | capital | Fortaleza                             | 2019 | S019P | 0.8528462 | 0.7005662 | 1.0051261 | 9.110117e-02 |\n",
       "| Natal3 | capital | Natal                                 | 2019 | S019P | 0.9574035 | 0.8956791 | 1.0191278 | 3.289375e-02 |\n",
       "| João Pessoa3 | capital | João Pessoa                           | 2019 | S019P | 0.8469751 | 0.7248907 | 0.9690595 | 7.354301e-02 |\n",
       "| Recife3 | capital | Recife                                | 2019 | S019P | 0.7957699 | 0.5943911 | 0.9971488 | 1.291155e-01 |\n",
       "| Maceió3 | capital | Maceió                                | 2019 | S019P | 0.9052185 | 0.8235559 | 0.9868812 | 4.602799e-02 |\n",
       "| Aracaju3 | capital | Aracaju                               | 2019 | S019P | 0.8719312 | 0.7256730 | 1.0181894 | 8.558347e-02 |\n",
       "| Salvador3 | capital | Salvador                              | 2019 | S019P | 0.9772048 | 0.9313500 | 1.0230596 | 2.394149e-02 |\n",
       "| Belo Horizonte3 | capital | Belo Horizonte                        | 2019 | S019P | 0.8377275 | 0.7175233 | 0.9579316 | 7.320970e-02 |\n",
       "| Vitória3 | capital | Vitória                               | 2019 | S019P | 1.0000000 | 1.0000000 | 1.0000000 | 0.000000e+00 |\n",
       "| Rio de Janeiro7 | capital | Rio de Janeiro                        | 2019 | S019P | 0.9813696 | 0.9445430 | 1.0181962 | 1.914613e-02 |\n",
       "| São Paulo6 | capital | São Paulo                             | 2019 | S019P | 0.9485502 | 0.8937154 | 1.0033849 | 2.949496e-02 |\n",
       "| Curitiba3 | capital | Curitiba                              | 2019 | S019P | 0.8922268 | 0.6938503 | 1.0906034 | 1.134402e-01 |\n",
       "| Florianópolis3 | capital | Florianópolis                         | 2019 | S019P | 1.0000000 | 1.0000000 | 1.0000000 | 2.862188e-17 |\n",
       "| Porto Alegre3 | capital | Porto Alegre                          | 2019 | S019P | 0.9766329 | 0.9303799 | 1.0228859 | 2.416353e-02 |\n",
       "| Campo Grande3 | capital | Campo Grande                          | 2019 | S019P | 0.9786548 | 0.9487867 | 1.0085229 | 1.557148e-02 |\n",
       "| Cuiabá3 | capital | Cuiabá                                | 2019 | S019P | 0.9146546 | 0.7975341 | 1.0317751 | 6.533226e-02 |\n",
       "| Goiânia3 | capital | Goiânia                               | 2019 | S019P | 0.8985256 | 0.7622195 | 1.0348317 | 7.739925e-02 |\n",
       "| Brasília3 | capital | Brasília                              | 2019 | S019P | 0.8662223 | 0.7366927 | 0.9957519 | 7.629419e-02 |\n",
       "| Fundamental incompleto ou equivalente3 | gescol  | Fundamental incompleto ou equivalente | 2019 | S019P | 0.7421529 | 0.6860301 | 0.7982757 | 3.858315e-02 |\n",
       "| Médio incompleto ou equivalente3 | gescol  | Médio incompleto ou equivalente       | 2019 | S019P | 0.8300336 | 0.7801115 | 0.8799558 | 3.068667e-02 |\n",
       "| Superior incompleto ou equivalente3 | gescol  | Superior incompleto ou equivalente    | 2019 | S019P | 0.9019019 | 0.8723502 | 0.9314535 | 1.671761e-02 |\n",
       "| Superior completo3 | gescol  | Superior completo                     | 2019 | S019P | 0.9757760 | 0.9597872 | 0.9917647 | 8.360210e-03 |\n",
       "| S016PSim | total   | Brasil                                | 2019 | S016P | 0.8936008 | 0.8767389 | 0.9104627 | 9.627530e-03 |\n",
       "| S016PSim1 | total   | Capital                               | 2019 | S016P | 0.8709017 | 0.8300706 | 0.9117328 | 2.392071e-02 |\n",
       "| S017PSim | total   | Brasil                                | 2019 | S017P | 0.8731066 | 0.8539498 | 0.8922634 | 1.119456e-02 |\n",
       "| S017PSim1 | total   | Capital                               | 2019 | S017P | 0.8488005 | 0.8054984 | 0.8921025 | 2.602884e-02 |\n",
       "| S018PSim | total   | Brasil                                | 2019 | S018P | 0.8320475 | 0.8093523 | 0.8547428 | 1.391678e-02 |\n",
       "| S018PSim1 | total   | Capital                               | 2019 | S018P | 0.8717783 | 0.8414178 | 0.9021387 | 1.776864e-02 |\n",
       "| S019PSim | total   | Brasil                                | 2019 | S019P | 0.8731421 | 0.8528793 | 0.8934049 | 1.184042e-02 |\n",
       "| S019PSim1 | total   | Capital                               | 2019 | S019P | 0.9094361 | 0.8822897 | 0.9365825 | 1.522971e-02 |\n",
       "\n"
      ],
      "text/plain": [
       "                                       abr_tipo       \n",
       "Branca                                 raça           \n",
       "Preta                                  raça           \n",
       "Parda                                  raça           \n",
       "Até 1/2 SM                             rend_per_capita\n",
       "1/2 até 1 SM                           rend_per_capita\n",
       "1 até 2 SM                             rend_per_capita\n",
       "2 até 3 SM                             rend_per_capita\n",
       "Mais de 3 SM                           rend_per_capita\n",
       "18 a 24 anos                           fx_idade_s     \n",
       "25 a 29 anos                           fx_idade_s     \n",
       "30 a 39 anos                           fx_idade_s     \n",
       "40 anos ou mais                        fx_idade_s     \n",
       "urbano                                 urb_rur        \n",
       "rural                                  urb_rur        \n",
       "Rondônia                               uf             \n",
       "Acre                                   uf             \n",
       "Amazonas                               uf             \n",
       "Roraima                                uf             \n",
       "Pará                                   uf             \n",
       "Amapá                                  uf             \n",
       "Tocantins                              uf             \n",
       "Maranhão                               uf             \n",
       "Piauí                                  uf             \n",
       "Ceará                                  uf             \n",
       "Rio Grande do Norte                    uf             \n",
       "Paraíba                                uf             \n",
       "Pernambuco                             uf             \n",
       "Alagoas                                uf             \n",
       "Sergipe                                uf             \n",
       "Bahia                                  uf             \n",
       "⋮                                      ⋮              \n",
       "Fortaleza3                             capital        \n",
       "Natal3                                 capital        \n",
       "João Pessoa3                           capital        \n",
       "Recife3                                capital        \n",
       "Maceió3                                capital        \n",
       "Aracaju3                               capital        \n",
       "Salvador3                              capital        \n",
       "Belo Horizonte3                        capital        \n",
       "Vitória3                               capital        \n",
       "Rio de Janeiro7                        capital        \n",
       "São Paulo6                             capital        \n",
       "Curitiba3                              capital        \n",
       "Florianópolis3                         capital        \n",
       "Porto Alegre3                          capital        \n",
       "Campo Grande3                          capital        \n",
       "Cuiabá3                                capital        \n",
       "Goiânia3                               capital        \n",
       "Brasília3                              capital        \n",
       "Fundamental incompleto ou equivalente3 gescol         \n",
       "Médio incompleto ou equivalente3       gescol         \n",
       "Superior incompleto ou equivalente3    gescol         \n",
       "Superior completo3                     gescol         \n",
       "S016PSim                               total          \n",
       "S016PSim1                              total          \n",
       "S017PSim                               total          \n",
       "S017PSim1                              total          \n",
       "S018PSim                               total          \n",
       "S018PSim1                              total          \n",
       "S019PSim                               total          \n",
       "S019PSim1                              total          \n",
       "                                       abr_nome                             \n",
       "Branca                                 Branca                               \n",
       "Preta                                  Preta                                \n",
       "Parda                                  Parda                                \n",
       "Até 1/2 SM                             Até 1/2 SM                           \n",
       "1/2 até 1 SM                           1/2 até 1 SM                         \n",
       "1 até 2 SM                             1 até 2 SM                           \n",
       "2 até 3 SM                             2 até 3 SM                           \n",
       "Mais de 3 SM                           Mais de 3 SM                         \n",
       "18 a 24 anos                           18 a 24 anos                         \n",
       "25 a 29 anos                           25 a 29 anos                         \n",
       "30 a 39 anos                           30 a 39 anos                         \n",
       "40 anos ou mais                        40 anos ou mais                      \n",
       "urbano                                 urbano                               \n",
       "rural                                  rural                                \n",
       "Rondônia                               Rondônia                             \n",
       "Acre                                   Acre                                 \n",
       "Amazonas                               Amazonas                             \n",
       "Roraima                                Roraima                              \n",
       "Pará                                   Pará                                 \n",
       "Amapá                                  Amapá                                \n",
       "Tocantins                              Tocantins                            \n",
       "Maranhão                               Maranhão                             \n",
       "Piauí                                  Piauí                                \n",
       "Ceará                                  Ceará                                \n",
       "Rio Grande do Norte                    Rio Grande do Norte                  \n",
       "Paraíba                                Paraíba                              \n",
       "Pernambuco                             Pernambuco                           \n",
       "Alagoas                                Alagoas                              \n",
       "Sergipe                                Sergipe                              \n",
       "Bahia                                  Bahia                                \n",
       "⋮                                      ⋮                                    \n",
       "Fortaleza3                             Fortaleza                            \n",
       "Natal3                                 Natal                                \n",
       "João Pessoa3                           João Pessoa                          \n",
       "Recife3                                Recife                               \n",
       "Maceió3                                Maceió                               \n",
       "Aracaju3                               Aracaju                              \n",
       "Salvador3                              Salvador                             \n",
       "Belo Horizonte3                        Belo Horizonte                       \n",
       "Vitória3                               Vitória                              \n",
       "Rio de Janeiro7                        Rio de Janeiro                       \n",
       "São Paulo6                             São Paulo                            \n",
       "Curitiba3                              Curitiba                             \n",
       "Florianópolis3                         Florianópolis                        \n",
       "Porto Alegre3                          Porto Alegre                         \n",
       "Campo Grande3                          Campo Grande                         \n",
       "Cuiabá3                                Cuiabá                               \n",
       "Goiânia3                               Goiânia                              \n",
       "Brasília3                              Brasília                             \n",
       "Fundamental incompleto ou equivalente3 Fundamental incompleto ou equivalente\n",
       "Médio incompleto ou equivalente3       Médio incompleto ou equivalente      \n",
       "Superior incompleto ou equivalente3    Superior incompleto ou equivalente   \n",
       "Superior completo3                     Superior completo                    \n",
       "S016PSim                               Brasil                               \n",
       "S016PSim1                              Capital                              \n",
       "S017PSim                               Brasil                               \n",
       "S017PSim1                              Capital                              \n",
       "S018PSim                               Brasil                               \n",
       "S018PSim1                              Capital                              \n",
       "S019PSim                               Brasil                               \n",
       "S019PSim1                              Capital                              \n",
       "                                       Ano  Indicador Sim       LowerS   \n",
       "Branca                                 2019 S016P     0.8747043 0.8394447\n",
       "Preta                                  2019 S016P     0.9270440 0.8819540\n",
       "Parda                                  2019 S016P     0.8998264 0.8813427\n",
       "Até 1/2 SM                             2019 S016P     0.8811666 0.8556610\n",
       "1/2 até 1 SM                           2019 S016P     0.8986344 0.8672705\n",
       "1 até 2 SM                             2019 S016P     0.9321180 0.8983597\n",
       "2 até 3 SM                             2019 S016P     0.9131325 0.8480609\n",
       "Mais de 3 SM                           2019 S016P     0.8449011 0.7501941\n",
       "18 a 24 anos                           2019 S016P     0.8784567 0.8471783\n",
       "25 a 29 anos                           2019 S016P     0.9121180 0.8854396\n",
       "30 a 39 anos                           2019 S016P     0.8996282 0.8718667\n",
       "40 anos ou mais                        2019 S016P     0.8549542 0.7687697\n",
       "urbano                                 2019 S016P     0.9007125 0.8821043\n",
       "rural                                  2019 S016P     0.8541637 0.8152466\n",
       "Rondônia                               2019 S016P     0.9657274 0.9374381\n",
       "Acre                                   2019 S016P     0.9341028 0.8604602\n",
       "Amazonas                               2019 S016P     0.9073433 0.8454635\n",
       "Roraima                                2019 S016P     0.7734318 0.6039876\n",
       "Pará                                   2019 S016P     0.9134246 0.8575382\n",
       "Amapá                                  2019 S016P     0.9555542 0.8885170\n",
       "Tocantins                              2019 S016P     0.8106428 0.6778693\n",
       "Maranhão                               2019 S016P     0.8095186 0.7336835\n",
       "Piauí                                  2019 S016P     0.9391357 0.8887311\n",
       "Ceará                                  2019 S016P     0.8040217 0.7193974\n",
       "Rio Grande do Norte                    2019 S016P     0.9353931 0.8588831\n",
       "Paraíba                                2019 S016P     0.8566499 0.7581708\n",
       "Pernambuco                             2019 S016P     0.8711616 0.8068706\n",
       "Alagoas                                2019 S016P     0.8033046 0.7070219\n",
       "Sergipe                                2019 S016P     0.8516848 0.7504449\n",
       "Bahia                                  2019 S016P     0.9096653 0.8455323\n",
       "⋮                                      ⋮    ⋮         ⋮         ⋮        \n",
       "Fortaleza3                             2019 S019P     0.8528462 0.7005662\n",
       "Natal3                                 2019 S019P     0.9574035 0.8956791\n",
       "João Pessoa3                           2019 S019P     0.8469751 0.7248907\n",
       "Recife3                                2019 S019P     0.7957699 0.5943911\n",
       "Maceió3                                2019 S019P     0.9052185 0.8235559\n",
       "Aracaju3                               2019 S019P     0.8719312 0.7256730\n",
       "Salvador3                              2019 S019P     0.9772048 0.9313500\n",
       "Belo Horizonte3                        2019 S019P     0.8377275 0.7175233\n",
       "Vitória3                               2019 S019P     1.0000000 1.0000000\n",
       "Rio de Janeiro7                        2019 S019P     0.9813696 0.9445430\n",
       "São Paulo6                             2019 S019P     0.9485502 0.8937154\n",
       "Curitiba3                              2019 S019P     0.8922268 0.6938503\n",
       "Florianópolis3                         2019 S019P     1.0000000 1.0000000\n",
       "Porto Alegre3                          2019 S019P     0.9766329 0.9303799\n",
       "Campo Grande3                          2019 S019P     0.9786548 0.9487867\n",
       "Cuiabá3                                2019 S019P     0.9146546 0.7975341\n",
       "Goiânia3                               2019 S019P     0.8985256 0.7622195\n",
       "Brasília3                              2019 S019P     0.8662223 0.7366927\n",
       "Fundamental incompleto ou equivalente3 2019 S019P     0.7421529 0.6860301\n",
       "Médio incompleto ou equivalente3       2019 S019P     0.8300336 0.7801115\n",
       "Superior incompleto ou equivalente3    2019 S019P     0.9019019 0.8723502\n",
       "Superior completo3                     2019 S019P     0.9757760 0.9597872\n",
       "S016PSim                               2019 S016P     0.8936008 0.8767389\n",
       "S016PSim1                              2019 S016P     0.8709017 0.8300706\n",
       "S017PSim                               2019 S017P     0.8731066 0.8539498\n",
       "S017PSim1                              2019 S017P     0.8488005 0.8054984\n",
       "S018PSim                               2019 S018P     0.8320475 0.8093523\n",
       "S018PSim1                              2019 S018P     0.8717783 0.8414178\n",
       "S019PSim                               2019 S019P     0.8731421 0.8528793\n",
       "S019PSim1                              2019 S019P     0.9094361 0.8822897\n",
       "                                       UpperS    cvS         \n",
       "Branca                                 0.9099639 0.02056687  \n",
       "Preta                                  0.9721340 0.02481599  \n",
       "Parda                                  0.9183100 0.01048046  \n",
       "Até 1/2 SM                             0.9066723 0.01476830  \n",
       "1/2 até 1 SM                           0.9299982 0.01780731  \n",
       "1 até 2 SM                             0.9658762 0.01847824  \n",
       "2 até 3 SM                             0.9782041 0.03635882  \n",
       "Mais de 3 SM                           0.9396081 0.05719106  \n",
       "18 a 24 anos                           0.9097351 0.01816671  \n",
       "25 a 29 anos                           0.9387963 0.01492314  \n",
       "30 a 39 anos                           0.9273898 0.01574462  \n",
       "40 anos ou mais                        0.9411388 0.05143260  \n",
       "urbano                                 0.9193208 0.01054074  \n",
       "rural                                  0.8930807 0.02324614  \n",
       "Rondônia                               0.9940167 0.01494582  \n",
       "Acre                                   1.0077454 0.04022411  \n",
       "Amazonas                               0.9692231 0.03479597  \n",
       "Roraima                                0.9428759 0.11177804  \n",
       "Pará                                   0.9693110 0.03121660  \n",
       "Amapá                                  1.0225915 0.03579421  \n",
       "Tocantins                              0.9434163 0.08356679  \n",
       "Maranhão                               0.8853537 0.04779642  \n",
       "Piauí                                  0.9895403 0.02738380  \n",
       "Ceará                                  0.8886460 0.05370064  \n",
       "Rio Grande do Norte                    1.0119032 0.04173267  \n",
       "Paraíba                                0.9551291 0.05865337  \n",
       "Pernambuco                             0.9354526 0.03765332  \n",
       "Alagoas                                0.8995873 0.06115329  \n",
       "Sergipe                                0.9529247 0.06064918  \n",
       "Bahia                                  0.9737983 0.03597093  \n",
       "⋮                                      ⋮         ⋮           \n",
       "Fortaleza3                             1.0051261 9.110117e-02\n",
       "Natal3                                 1.0191278 3.289375e-02\n",
       "João Pessoa3                           0.9690595 7.354301e-02\n",
       "Recife3                                0.9971488 1.291155e-01\n",
       "Maceió3                                0.9868812 4.602799e-02\n",
       "Aracaju3                               1.0181894 8.558347e-02\n",
       "Salvador3                              1.0230596 2.394149e-02\n",
       "Belo Horizonte3                        0.9579316 7.320970e-02\n",
       "Vitória3                               1.0000000 0.000000e+00\n",
       "Rio de Janeiro7                        1.0181962 1.914613e-02\n",
       "São Paulo6                             1.0033849 2.949496e-02\n",
       "Curitiba3                              1.0906034 1.134402e-01\n",
       "Florianópolis3                         1.0000000 2.862188e-17\n",
       "Porto Alegre3                          1.0228859 2.416353e-02\n",
       "Campo Grande3                          1.0085229 1.557148e-02\n",
       "Cuiabá3                                1.0317751 6.533226e-02\n",
       "Goiânia3                               1.0348317 7.739925e-02\n",
       "Brasília3                              0.9957519 7.629419e-02\n",
       "Fundamental incompleto ou equivalente3 0.7982757 3.858315e-02\n",
       "Médio incompleto ou equivalente3       0.8799558 3.068667e-02\n",
       "Superior incompleto ou equivalente3    0.9314535 1.671761e-02\n",
       "Superior completo3                     0.9917647 8.360210e-03\n",
       "S016PSim                               0.9104627 9.627530e-03\n",
       "S016PSim1                              0.9117328 2.392071e-02\n",
       "S017PSim                               0.8922634 1.119456e-02\n",
       "S017PSim1                              0.8921025 2.602884e-02\n",
       "S018PSim                               0.8547428 1.391678e-02\n",
       "S018PSim1                              0.9021387 1.776864e-02\n",
       "S019PSim                               0.8934049 1.184042e-02\n",
       "S019PSim1                              0.9365825 1.522971e-02"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matriz_final"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Exportando tabela de indicadores calculados - Módulo S 2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "diretorio_saida <- \"<coloque aqui o diretório>\"\n",
    "write.table(matrizIndicadores,file=paste0(diretorio_saida,\"Indicadores_2019S_R.csv\"),sep = \";\",dec = \",\",row.names = FALSE)"
   ]
  }
 ],
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   "file_extension": ".r",
   "mimetype": "text/x-r-source",
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