R/process_cnes.R
In rfsaldanha/microdatasus: Download and preprocess DataSUS files
Defines functions
process_cnes
Documented in
process_cnes
#' Process CNES variables from DataSUS
#'
#' \code{process_cnes} processes CNES variables retrieved by \code{fetch_datasus()}.
#'
#' This function processes CNES-ST (Estabelecimentos) or CNES-PF (Pessoa f\\u00edsica) variables retrieved by \code{fetch_datasus()}, informing labels for categoric variables including NA values.
#'
#' @param data \code{data.frame} created by \code{fetch_datasus()}.
#' @param information_system \code{string}. \code{CNES-ST} or \code{CNES-PF}
#' @param nomes optional logical. \code{TRUE} by default, add \code{FANTASIA} and \code{RAZÃO SOCIAL} names to the dataset.
#' @param municipality_data optional logical. \code{TRUE} by default, creates new variables in the dataset informing the full name and other details about the municipality of residence.
#'
#' @examples \dontrun{
#' df <- fetch_datasus(year_start = 2015, month_start = 1,
#' year_end = 2015, month_end = 1,
#' uf = "RJ",
#' information_system = "CNES-ST")
#' df_a <- process_cnes(df, information_system = "CNES-ST")
#' df_b <- process_cnes(df, information_system = "CNES-ST", nomes = FALSE, municipality_data = FALSE)
#' }
#' @export
process_cnes <- function(data, information_system = c("CNES-ST", "CNES-PF"), nomes = TRUE, municipality_data = TRUE) {
# Check information system
checkmate::assert_choice(x = information_system, choices = c("CNES-ST", "CNES-PF"))
# Variables names
variables_names <- names(data)
# Use dtplyr
data <- dtplyr::lazy_dt(data)
if(information_system == "CNES-ST"){
# CNES
if("CNES" %in% variables_names){
data <- data %>%
dplyr::mutate(CNES = as.character(.data$CNES))
}
# Nome fantasia e razão social
if(nomes == TRUE){
data <- data %>%
dplyr::mutate(CNES_integer = as.integer(.data$CNES)) %>%
dplyr::left_join(microdatasus::cadger, by = c("CNES_integer" = "CNES")) %>%
dplyr::select(-"CNES_integer")
}
# CODUFMUN
if ("CODUFMUN" %in% variables_names & municipality_data == TRUE) {
colnames(tabMun)[1] <- "CODUFMUN"
tabMun$CODUFMUN <- as.character(tabMun$CODUFMUN)
data <- data %>%
dplyr::left_join(tabMun, by = "CODUFMUN")
}
# COD_CEP
if("COD_CEP" %in% variables_names){
data <- data %>%
dplyr::mutate(COD_CEP = as.integer(.data$COD_CEP))
}
# CPF_CNPJ
if("CPF_CNPJ" %in% variables_names){
data <- data %>%
dplyr::mutate(CPF_CNPJ = as.character(.data$CPF_CNPJ))
}
# PF_PJ
if("PF_PJ" %in% variables_names){
data <- data %>%
dplyr::mutate(
PF_PJ = dplyr::case_match(
.data$PF_PJ,
"1" ~ "Pessoa f\u00edsica",
"3" ~ "Pessoa jur\u00eddica",
.default = .data$PF_PJ
)
) %>%
dplyr::mutate(PF_PJ = as.factor(.data$PF_PJ))
}
# NIV_DEP
if("NIV_DEP" %in% variables_names){
data <- data %>%
dplyr::mutate(
NIV_DEP = dplyr::case_match(
.data$NIV_DEP,
"1" ~ "Individual",
"3" ~ "Mantida",
.default = .data$NIV_DEP
)
) %>%
dplyr::mutate(NIV_DEP = as.factor(.data$NIV_DEP))
}
# CNPJ_MAN
if("CNPJ_MAN" %in% variables_names){
data <- data %>%
dplyr::mutate(CNPJ_MAN = as.numeric(.data$CNPJ_MAN))
}
# COD_IR
if("COD_IR" %in% variables_names){
data <- data %>%
dplyr::mutate(
COD_IR = dplyr::case_match(
.data$COD_IR,
"0" ~ NA,
"10" ~ "Estabelecimento p\u00fablico",
"11" ~ "Estabelecimento filantr\u00f3pico",
"12" ~ "Estabelecimento sem fins lucrativos",
"13" ~ "Estabelecimento privado luvrativa simples",
"14" ~ "Estabelecimento privado luvrativa",
"15" ~ "Estabelecimento sindical",
"16" ~ "Estabelecimento pessoa f\u00edsica",
"19" ~ "Estabelecimento Ret.Manten.c\u00f3digo 19",
.default = .data$COD_IR
)
) %>%
dplyr::mutate(COD_IR = as.factor(.data$COD_IR))
}
# REGSAUDE
if("REGSAUDE" %in% variables_names){
data <- data %>%
dplyr::mutate(REGSAUDE = as.character(.data$REGSAUDE))
}
# MICR_REG
if("MICR_REG" %in% variables_names){
data <- data %>%
dplyr::mutate(MICR_REG = as.integer(.data$MICR_REG))
}
# DISTRSAN
if("DISTRSAN" %in% variables_names){
data <- data %>%
dplyr::mutate(DISTRSAN = as.integer(.data$DISTRSAN))
}
# VINC_SUS
if("VINC_SUS" %in% variables_names){
data <- data %>%
dplyr::mutate(
VINC_SUS = dplyr::case_match(
.data$VINC_SUS,
"0" ~ "N\u00e3o",
"1" ~ "Sim",
"2" ~ "N\u00e3o",
.default = .data$VINC_SUS
)
) %>%
dplyr::mutate(VINC_SUS = as.factor(.data$VINC_SUS))
}
# TPGESTAO
if("TPGESTAO" %in% variables_names){
data <- data %>%
dplyr::mutate(
TPGESTAO = dplyr::case_match(
.data$TPGESTAO,
"D" ~ "Dupla",
"E" ~ "Estadual",
"M" ~ "Municipal",
"Z" ~ "Sem gest\u00e3o",
"S" ~ "Sem gest\u00e3o",
.default = .data$TPGESTAO
)
) %>%
dplyr::mutate(TPGESTAO = as.factor(.data$TPGESTAO))
}
# ESFERA_A
if("ESFERA_A" %in% variables_names){
data <- data %>%
dplyr::mutate(
ESFERA_A = dplyr::case_match(
.data$ESFERA_A,
"1" ~ "Federal",
"2" ~ "Estadual",
"3" ~ "Municipal",
"4" ~ "Privada",
"-99" ~ NA,
.default = .data$ESFERA_A
)
) %>%
dplyr::mutate(ESFERA_A = as.factor(.data$ESFERA_A))
}
# RETENCAO
if("RETENCAO" %in% variables_names){
data <- data %>%
dplyr::mutate(
RETENCAO = dplyr::case_match(
.data$RETENCAO,
"0" ~ NA,
"10" ~ "Estabelecimento p\u00fablico",
"11" ~ "Estabelecimento filantr\u00f3pico",
"12" ~ "Estabelecimento sem fins lucrativos",
"13" ~ "Estabelecimento privado luvrativa simples",
"14" ~ "Estabelecimento privado luvrativa",
"15" ~ "Estabelecimento sindical",
"16" ~ "Estabelecimento pessoa f\u00edsica",
.default = .data$RETENCAO
)
) %>%
dplyr::mutate(RETENCAO = as.factor(.data$RETENCAO))
}
# ATIVIDAD
if("ATIVIDAD" %in% variables_names){
data <- data %>%
dplyr::mutate(
ATIVIDAD = dplyr::case_match(
.data$ATIVIDAD,
"-99" ~ NA,
"1" ~ "Unidade Universit\u00e1ria",
"2" ~ "Unidade Escola Superior Isolada",
"3" ~ "Unidade Auxiliar de Ensino",
"4" ~ "Unidade sem atividade de Ensino",
"5" ~ "Hospital de ensino",
.default = .data$ATIVIDAD
)
) %>%
dplyr::mutate(ATIVIDAD = as.factor(.data$ATIVIDAD))
}
# NATUREZA
if("NATUREZA" %in% variables_names){
data <- data %>%
dplyr::mutate(
NATUREZA = dplyr::case_match(
.data$NATUREZA,
"-99" ~ NA,
"1" ~ "Administra\u00e7\u00e3o Direta da Sa\u00fade (MS, SES, e SMS)",
"2" ~ "Adm Direta outros org\u00e3os (MEX, MEx, Marinha,...)",
"3" ~ "Adm Indireta - Autarquias",
"4" ~ "Adm Indireta - Funda\u00e7\u00e3o P\u00fablica",
"5" ~ "Adm Indireta - Empresa P\u00fablica",
"6" ~ "Adm Indireta - Organiza\u00e7\u00e3o Social P\u00fablica",
"7" ~ "Empresa Privada",
"8" ~ "Funda\u00e7\u00e3o Privada",
"9" ~ "Cooperativa",
"10" ~ "Servi\u00e7o Social Aut\u00f4nomo",
"11" ~ "Entidade Beneficente sem fins lucrativos",
"12" ~ "Economia Mista",
"13" ~ "Sindicato",
"0" ~ "Natureza inexistente",
.default = .data$NATUREZA
)
) %>%
dplyr::mutate(NATUREZA = as.factor(.data$NATUREZA))
}
# NAT_JUR
if("NAT_JUR" %in% variables_names){
data <- data %>%
dplyr::mutate(
NAT_JUR = dplyr::case_match(
.data$NAT_JUR,
"1015" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Executivo Federal",
"1023" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Executivo Estadual ou do Distrito Federal",
"1031" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Executivo Municipal",
"1040" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Legislativo Federal",
"1058" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Legislativo Estadual ou do Distrito Federal",
"1066" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Legislativo Municipal",
"1074" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Judici\u00e1rio Federal",
"1082" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Judici\u00e1rio Estadual",
"1104" ~ "Autarquia Federal",
"1112" ~ "Autarquia Estadual ou do Distrito Federal",
"1120" ~ "Autarquia Municipal",
"1139" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito P\u00fablico Federal",
"1147" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito P\u00fablico Estadual ou do Distrito Federal",
"1155" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito P\u00fablico Municipal",
"1163" ~ "\u00d3rg\u00e3o P\u00fablico Aut\u00f4nomo Federal",
"1171" ~ "\u00d3rg\u00e3o P\u00fablico Aut\u00f4nomo Estadual ou do Distrito Federal",
"1180" ~ "\u00d3rg\u00e3o P\u00fablico Aut\u00f4nomo Municipal",
"1198" ~ "Comiss\u00e3o Polinacional",
"1201" ~ "Fundo P\u00fablico",
"1210" ~ "Cons\u00f3rcio P\u00fablico de Direito P\u00fablico (Associa\u00e7\u00e3o P\u00fablica)",
"1228" ~ "Cons\u00f3rcio P\u00fablico de Direito Privado",
"1236" ~ "Estado ou Distrito Federal",
"1244" ~ "Munic\u00edpio",
"1252" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito Privado Federal",
"1260" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito Privado Estadual ou do Distrito Federal",
"1279" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito Privado Municipal",
"2011" ~ "Empresa P\u00fablica",
"2038" ~ "Sociedade de Economia Mista",
"2046" ~ "Sociedade An\u00f4nima Aberta",
"2054" ~ "Sociedade An\u00f4nima Fechada",
"2062" ~ "Sociedade Empres\u00e1ria Limitada",
"2070" ~ "Sociedade Empres\u00e1ria em Nome Coletivo",
"2089" ~ "Sociedade Empres\u00e1ria em Comandita Simples",
"2097" ~ "Sociedade Empres\u00e1ria em Comandita por A\u00e7\u00f5es",
"2127" ~ "Sociedade em Conta de Participa\u00e7\u00e3o",
"2135" ~ "Empres\u00e1rio (Individual)",
"2143" ~ "Cooperativa",
"2151" ~ "Cons\u00f3rcio de Sociedades",
"2160" ~ "Grupo de Sociedades",
"2178" ~ "Estabelecimento, no Brasil, de Sociedade Estrangeira",
"2194" ~ "Estabelecimento, no Brasil, de Empresa Binacional Argentino-Brasileira",
"2216" ~ "Empresa Domiciliada no Exterior",
"2224" ~ "Clube/Fundo de Investimento",
"2232" ~ "Sociedade Simples Pura",
"2240" ~ "Sociedade Simples Limitada",
"2259" ~ "Sociedade Simples em Nome Coletivo",
"2267" ~ "Sociedade Simples em Comandita Simples",
"2275" ~ "Empresa Binacional",
"2283" ~ "Cons\u00f3rcio de Empregadores",
"2291" ~ "Cons\u00f3rcio Simples",
"2305" ~ "Empresa Individual de Responsabilidade Limitada (de Natureza Empres\u00e1ria)",
"2313" ~ "Empresa Individual de Responsabilidade Limitada (de Natureza Simples)",
"2321" ~ "Sociedade Unipessoal de Advogados",
"2330" ~ "Cooperativas de Consumo",
"3034" ~ "Servi\u00e7o Notarial e Registral (Cart\u00f3rio)",
"3069" ~ "Funda\u00e7\u00e3o Privada",
"3077" ~ "Servi\u00e7o Social Aut\u00f4nomo",
"3085" ~ "Condom\u00ednio Edil\u00edcio",
"3107" ~ "Comiss\u00e3o de Concilia\u00e7\u00e3o Pr\u00e9via",
"3115" ~ "Entidade de Media\u00e7\u00e3o e Arbitragem",
"3131" ~ "Entidade Sindical",
"3204" ~ "Estabelecimento, no Brasil, de Funda\u00e7\u00e3o ou Associa\u00e7\u00e3o Estrangeiras",
"3212" ~ "Funda\u00e7\u00e3o ou Associa\u00e7\u00e3o Domiciliada no Exterior",
"3220" ~ "Organiza\u00e7\u00e3o Religiosa",
"3239" ~ "Comunidade Ind\u00edgena",
"3247" ~ "Fundo Privado",
"3255" ~ "\u00d3rg\u00e3o de Dire\u00e7\u00e3o Nacional de Partido Pol\u00edtico",
"3263" ~ "\u00d3rg\u00e3o de Dire\u00e7\u00e3o Regional de Partido Pol\u00edtico",
"3271" ~ "\u00d3rg\u00e3o de Dire\u00e7\u00e3o Local de Partido Pol\u00edtico",
"3280" ~ "Comit\u00ea Financeiro de Partido Pol\u00edtico",
"3298" ~ "Frente Plebiscit\u00e1ria ou Referend\u00e1ria",
"3306" ~ "Organiza\u00e7\u00e3o Social (OS)",
"3310" ~ "Demais Condom\u00ednios",
"3999" ~ "Associa\u00e7\u00e3o Privada",
"4014" ~ "Empresa Individual Imobili\u00e1ria",
"4022" ~ "Segurado Especial",
"4081" ~ "Contribuinte individual",
"4090" ~ "Candidato a Cargo Pol\u00edtico Eletivo",
"4111" ~ "Leiloeiro",
"4124" ~ "Produtor Rural (Pessoa F\u00edsica)",
"5010" ~ "Organiza\u00e7\u00e3o Internacional",
"5029" ~ "Representa\u00e7\u00e3o Diplom\u00e1tica Estrangeira",
"5037" ~ "Outras Institui\u00e7\u00f5es Extraterritoriais",
"0" ~ "N\u00e3o especificado ou ignorado",
.default = .data$NAT_JUR
)
) %>%
dplyr::mutate(NAT_JUR = as.factor(.data$NAT_JUR))
}
# CLIENTEL
if("CLIENTEL" %in% variables_names){
data <- data %>%
dplyr::mutate(
CLIENTEL = dplyr::case_match(
.data$CLIENTEL,
"-99" ~ NA,
"1" ~ "Atendimento de demanda espont\u00e2nea",
"2" ~ "Atendimento de demanda referenciada",
"3" ~ "Atendimento de demanda espont\u00e2nea e referenciada",
"0" ~ "Fluxo de Clientela n\u00e3o exigido",
.default = .data$CLIENTEL
)
) %>%
dplyr::mutate(CLIENTEL = as.factor(.data$CLIENTEL))
}
# TP_UNID
if("TP_UNID" %in% variables_names){
data <- data %>%
dplyr::mutate(
TP_UNID = dplyr::case_match(
.data$TP_UNID,
"1" ~ "Posto de sa\u00fade",
"2" ~ "Centro de sa\u00fade / Unidade b\u00e1sica",
"4" ~ "Policl\u00ednica",
"5" ~ "Hospital geral",
"7" ~ "Hospital Especializado",
"9" ~ "Pronto socorro de hospital geral (antigo)",
"12" ~ "Pronto socorro traumato-ortop\u00e9dico (antigo)",
"15" ~ "Unidade mista",
"20" ~ "Pronto socorro geral",
"21" ~ "Pronto socorro especializado",
"22" ~ "Consult\u00f3rio isolado",
"32" ~ "Unidade m\u00f3vel fluvial",
"36" ~ "Cl\u00ednica / Centro de sa\u00fade de especialidade",
"39" ~ "Unidade de apoio diagnose e terapia (SADT isolado)",
"40" ~ "Unidade m\u00f3vel terrestre",
"42" ~ "Unidade m\u00f3vel de n\u00edvel pr\u00e9-hospitalar na \u00e1rea de urg\u00eancia",
"43" ~ "Farm\u00e1cia",
"45" ~ "Unidade de sa\u00fade da fam\u00edlia",
"50" ~ "Unidade de vigil\u00e2ncia em sa\u00fade",
"60" ~ "Cooperativa ou empresa de cess\u00e3o de trabalhadores na sa\u00fade",
"61" ~ "Centro de parto normal - isolado",
"62" ~ "Hospital / Dia - Isolado",
"63" ~ "Unidade autorizadora",
"64" ~ "Central de regula\u00e7\u00e3o de servi\u00e7os de sa\u00fade",
"65" ~ "Unidade de vigil\u00e2ncia epidemiol\u00f3gica (antigo)",
"66" ~ "Unidade de vigil\u00e2ncia sanit\u00e1ria (antigo)",
"67" ~ "Laborat\u00f3rio central de sa\u00fade p\u00fablica LACEN",
"68" ~ "Central de gest\u00e3o em sa\u00fade",
"69" ~ "Centro de aten\u00e7\u00e3o hemoterapia e/ou hematologica",
"70" ~ "Centro de aten\u00e7\u00e3o psicosocial",
"71" ~ "Centro de apoio a sa\u00fade da fam\u00edlia",
"72" ~ "Unidade de aten\u00e7\u00e3o a sa\u00fade ind\u00edgena",
"73" ~ "Pronto atendimento",
"74" ~ "P\u00f3lo academia da sa\u00fade",
"75" ~ "Telessa\u00fade",
"76" ~ "Central de regula\u00e7\u00e3o m\u00e9dica das urg\u00eancias",
"77" ~ "Servi\u00e7o de aten\u00e7\u00e3o domiciliar isolado (Home care)",
"78" ~ "Unidade de aten\u00e7\u00e3o em regime residencial",
"79" ~ "Oficina ortop\u00e9dica",
"80" ~ "Laborat\u00f3rio de sa\u00fade p\u00fablica",
"81" ~ "Central de regula\u00e7\u00e3o do acesso",
"82" ~ "Central de notifica\u00e7\u00e3o, capta\u00e7\u00e3o e distribui\u00e7\u00e3o de \u00f3rg\u00e3os estadual",
"83" ~ "P\u00f3lo de preven\u00e7\u00e3o de doen\u00e7as e agravos e promo\u00e7\u00e3o da sa\u00fade",
.default = .data$TP_UNID
)
) %>%
dplyr::mutate(TP_UNID = as.factor(.data$TP_UNID))
}
# TURNO_AT
if("TURNO_AT" %in% variables_names){
data <- data %>%
dplyr::mutate(
TURNO_AT = dplyr::case_match(
.data$TURNO_AT,
"-99" ~ NA,
"1" ~ "Turnos intermitentes",
"2" ~ "Cont\u00ednuo 24h/dia (Pl Sab Dom Fer)",
"3" ~ "Manh\u00e3 / Tarde / Noite",
"4" ~ "Manh\u00e3",
"5" ~ "Tarde",
"6" ~ "Manh\u00e3 / Tarde",
"7" ~ "Noite",
.default = .data$TURNO_AT
)
) %>%
dplyr::mutate(TURNO_AT = as.factor(.data$TURNO_AT))
}
# NIV_HIER
if("NIV_HIER" %in% variables_names){
data <- data %>%
dplyr::mutate(
NIV_HIER = dplyr::case_match(
.data$NIV_HIER,
"0" ~ NA,
"-99" ~ NA,
"1" ~ "PAB-PABA",
"2" ~ "M\u00e9dia M1",
"3" ~ "M\u00e9dia M2 e M3",
"4" ~ "Alta complexidade ambulatorial",
"5" ~ "Baixa M1 e M2",
"6" ~ "M\u00e9dia M2 e M3",
"7" ~ "M\u00e9dia M3",
"8" ~ "Alta complexidade hospitalar / ambulatorial",
.default = .data$NIV_HIER
)
) %>%
dplyr::mutate(NIV_HIER = as.factor(.data$NIV_HIER))
}
# TP_PREST
if("TP_PREST" %in% variables_names){
data <- data %>%
dplyr::mutate(
TP_PREST = dplyr::case_match(
.data$TP_PREST,
"-99" ~ NA,
"30" ~ "P\u00fablico federal",
"40" ~ "P\u00fablico estadual",
"50" ~ "P\u00fablico municipal",
"61" ~ "Filantr\u00f3pico com CNAS v\u00e1lido",
"80" ~ "Sindicato",
"20" ~ "Privado com fins lucrativos",
"22" ~ "Privado optantes pelo simples",
"60" ~ "Privado sem fins lucrativos",
.default = .data$TP_PREST
)
) %>%
dplyr::mutate(TP_PREST = as.factor(.data$TP_PREST))
}
# CO_BANCO
if("CO_BANCO" %in% variables_names){
data <- data %>%
dplyr::mutate(CO_BANCO = as.character(.data$CO_BANCO))
}
# CO_AGENC
if("CO_AGENC" %in% variables_names){
data <- data %>%
dplyr::mutate(CO_AGENC = as.character(.data$CO_AGENC))
}
# C_CORREN
if("C_CORREN" %in% variables_names){
data <- data %>%
dplyr::mutate(C_CORREN = as.character(.data$C_CORREN))
}
# CONTRATM
if("CONTRATM" %in% variables_names){
data <- data %>%
dplyr::mutate(CONTRATM = as.character(.data$CONTRATM))
}
# DT_PUBLM
if("DT_PUBLM" %in% variables_names){
data <- data %>%
dplyr::mutate(DT_PUBLM = as.character(.data$DT_PUBLM))
}
# CONTRATE
if("CONTRATE" %in% variables_names){
data <- data %>%
dplyr::mutate(CONTRATE = as.character(.data$CONTRATE))
}
# DT_PUBLE
if("DT_PUBLE" %in% variables_names){
data <- data %>%
dplyr::mutate(DT_PUBLE = as.character(.data$DT_PUBLE))
}
# ALVARA
if("ALVARA" %in% variables_names){
data <- data %>%
dplyr::mutate(ALVARA = as.character(.data$ALVARA))
}
# DT_EXPED
if("DT_EXPED" %in% variables_names){
data <- data %>%
dplyr::mutate(DT_EXPED = as.character(.data$DT_EXPED))
}
# ORGEXPED
if("ORGEXPED" %in% variables_names){
data <- data %>%
dplyr::mutate(
ORGEXPED = dplyr::case_match(
.data$ORGEXPED,
"1" ~ "SES",
"2" ~ "SMS",
.default = .data$ORGEXPED
)
) %>%
dplyr::mutate(ORGEXPED = as.factor(.data$ORGEXPED))
}
# AV_ACRED
if("AV_ACRED" %in% variables_names){
data <- data %>%
dplyr::mutate(
AV_ACRED = dplyr::case_match(
.data$AV_ACRED,
"1" ~ "Sim",
"2" ~ "N\u00e3o",
"0" ~ "N\u00e3o",
.default = .data$AV_ACRED
)
) %>%
dplyr::mutate(AV_ACRED = as.factor(.data$AV_ACRED))
}
# CLASAVAL
if("CLASAVAL" %in% variables_names){
data <- data %>%
dplyr::mutate(
CLASAVAL = dplyr::case_match(
.data$CLASAVAL,
"-9" ~ NA,
"1" ~ "Acreditado no n\u00edvel 1",
"2" ~ "Acreditado no n\u00edvel 2",
"3" ~ "Acreditado no n\u00edvel 3",
"0" ~ "N\u00e3o atendeu aos padr\u00f5es m\u00ednimos",
.default = .data$CLASAVAL
)
) %>%
dplyr::mutate(CLASAVAL = as.factor(.data$CLASAVAL))
}
# DT_ACRED
if("DT_ACRED" %in% variables_names){
data <- data %>%
dplyr::mutate(DT_ACRED = as.integer(.data$DT_ACRED))
}
# AV_PNASS
if("AV_PNASS" %in% variables_names){
data <- data %>%
dplyr::mutate(
AV_PNASS = dplyr::case_match(
.data$AV_PNASS,
"1" ~ "Sim",
"2" ~ "N\u00e3o",
"0" ~ "N\u00e3o",
.default = .data$AV_PNASS
)
) %>%
dplyr::mutate(AV_PNASS = as.factor(.data$AV_PNASS))
}
# DT_PNASS
if("DT_PNASS" %in% variables_names){
data <- data %>%
dplyr::mutate(DT_PNASS = as.integer(.data$DT_PNASS))
}
# GESPRG1E
if("GESPRG1E" %in% variables_names){
data$GESPRG1E <- as.numeric(levels(data$GESPRG1E))[data$GESPRG1E]
data$GESPRG1E[data$GESPRG1E==1] <- "Sim"
data$GESPRG1E[data$GESPRG1E==0] <- "N\u00e3o"
data$GESPRG1E <- factor(data$GESPRG1E)
}
# GESPRG1M
if("GESPRG1M" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG1M = dplyr::case_match(
.data$GESPRG1M,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG1M
)
) %>%
dplyr::mutate(GESPRG1M = as.factor(.data$GESPRG1M))
}
# GESPRG2E
if("GESPRG2E" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG2E = dplyr::case_match(
.data$GESPRG2E,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG2E
)
) %>%
dplyr::mutate(GESPRG2E = as.factor(.data$GESPRG2E))
}
# GESPRG2M
if("GESPRG2M" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG2M = dplyr::case_match(
.data$GESPRG2M,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG2M
)
) %>%
dplyr::mutate(GESPRG2M = as.factor(.data$GESPRG2M))
}
# GESPRG4E
if("GESPRG4E" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG4E = dplyr::case_match(
.data$GESPRG4E,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG4E
)
) %>%
dplyr::mutate(GESPRG4E = as.factor(.data$GESPRG4E))
}
# GESPRG4M
if("GESPRG4M" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG4M = dplyr::case_match(
.data$GESPRG4M,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG4M
)
) %>%
dplyr::mutate(GESPRG4M = as.factor(.data$GESPRG4M))
}
# NIVATE_A
if("NIVATE_A" %in% variables_names){
data <- data %>%
dplyr::mutate(
NIVATE_A = dplyr::case_match(
.data$NIVATE_A,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$NIVATE_A
)
) %>%
dplyr::mutate(NIVATE_A = as.factor(.data$NIVATE_A))
}
# GESPRG3E
if("GESPRG3E" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG3E = dplyr::case_match(
.data$GESPRG3E,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG3E
)
) %>%
dplyr::mutate(GESPRG3E = as.factor(.data$GESPRG3E))
}
# GESPRG3M
if("GESPRG3M" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG3M = dplyr::case_match(
.data$GESPRG3M,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG3M
)
) %>%
dplyr::mutate(GESPRG3M = as.factor(.data$GESPRG3M))
}
# GESPRG5E
if("GESPRG5E" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG5E = dplyr::case_match(
.data$GESPRG5E,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG5E
)
) %>%
dplyr::mutate(GESPRG5E = as.factor(.data$GESPRG5E))
}
# GESPRG5M
if("GESPRG5M" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG5M = dplyr::case_match(
.data$GESPRG5M,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG5M
)
) %>%
dplyr::mutate(GESPRG5M = as.factor(.data$GESPRG5M))
}
# GESPRG6E
if("GESPRG6E" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG6E = dplyr::case_match(
.data$GESPRG6E,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG6E
)
) %>%
dplyr::mutate(GESPRG6E = as.factor(.data$GESPRG6E))
}
# GESPRG6M
if("GESPRG6M" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG6M = dplyr::case_match(
.data$GESPRG6M,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG6M
)
) %>%
dplyr::mutate(GESPRG6M = as.factor(.data$GESPRG6M))
}
# NIVATE_H
if("NIVATE_H" %in% variables_names){
data <- data %>%
dplyr::mutate(
NIVATE_H = dplyr::case_match(
.data$NIVATE_H,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$NIVATE_H
)
) %>%
dplyr::mutate(NIVATE_H = as.factor(.data$NIVATE_H))
}
# URGEMERG
if("URGEMERG" %in% variables_names){
data <- data %>%
dplyr::mutate(
URGEMERG = dplyr::case_match(
.data$URGEMERG,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$URGEMERG
)
) %>%
dplyr::mutate(URGEMERG = as.factor(.data$URGEMERG))
}
# ATENDAMB
if("ATENDAMB" %in% variables_names){
data <- data %>%
dplyr::mutate(
ATENDAMB = dplyr::case_match(
.data$ATENDAMB,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$ATENDAMB
)
) %>%
dplyr::mutate(ATENDAMB = as.factor(.data$ATENDAMB))
}
# CENTROBS
if("CENTROBS" %in% variables_names){
data <- data %>%
dplyr::mutate(
CENTROBS = dplyr::case_match(
.data$CENTROBS,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$CENTROBS
)
) %>%
dplyr::mutate(CENTROBS = as.factor(.data$CENTROBS))
}
# CENTRNEO
if("CENTRNEO" %in% variables_names){
data <- data %>%
dplyr::mutate(
CENTRNEO = dplyr::case_match(
.data$CENTRNEO,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$CENTRNEO
)
) %>%
dplyr::mutate(CENTRNEO = as.factor(.data$CENTRNEO))
}
# ATENDHOS
if("ATENDHOS" %in% variables_names){
data <- data %>%
dplyr::mutate(
ATENDHOS = dplyr::case_match(
.data$ATENDHOS,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$ATENDHOS
)
) %>%
dplyr::mutate(ATENDHOS = as.factor(.data$ATENDHOS))
}
# SERAP01P
if("SERAP01P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP01P = dplyr::case_match(
.data$SERAP01P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP01P
)
) %>%
dplyr::mutate(SERAP01P = as.factor(.data$SERAP01P))
}
# SERAP01T
if("SERAP01T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP01T = dplyr::case_match(
.data$SERAP01T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP01T
)
) %>%
dplyr::mutate(SERAP01T = as.factor(.data$SERAP01T))
}
# SERAP02P
if("SERAP02P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP02P = dplyr::case_match(
.data$SERAP02P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP02P
)
) %>%
dplyr::mutate(SERAP02P = as.factor(.data$SERAP02P))
}
# SERAP02T
if("SERAP02T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP02T = dplyr::case_match(
.data$SERAP02T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP02T
)
) %>%
dplyr::mutate(SERAP02T = as.factor(.data$SERAP02T))
}
# SERAP03P
if("SERAP03P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP03P = dplyr::case_match(
.data$SERAP03P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP03P
)
) %>%
dplyr::mutate(SERAP03P = as.factor(.data$SERAP03P))
}
# SERAP03T
if("SERAP03T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP03T = dplyr::case_match(
.data$SERAP03T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP03T
)
) %>%
dplyr::mutate(SERAP03T = as.factor(.data$SERAP03T))
}
# SERAP04P
if("SERAP04P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP04P = dplyr::case_match(
.data$SERAP04P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP04P
)
) %>%
dplyr::mutate(SERAP04P = as.factor(.data$SERAP04P))
}
# SERAP04T
if("SERAP04T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP04T = dplyr::case_match(
.data$SERAP04T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP04T
)
) %>%
dplyr::mutate(SERAP04T = as.factor(.data$SERAP04T))
}
# SERAP05P
if("SERAP05P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP05P = dplyr::case_match(
.data$SERAP05P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP05P
)
) %>%
dplyr::mutate(SERAP05P = as.factor(.data$SERAP05P))
}
# SERAP05T
if("SERAP05T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP05T = dplyr::case_match(
.data$SERAP05T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP05T
)
) %>%
dplyr::mutate(SERAP05T = as.factor(.data$SERAP05T))
}
# SERAP06P
if("SERAP06P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP06P = dplyr::case_match(
.data$SERAP06P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP06P
)
) %>%
dplyr::mutate(SERAP06P = as.factor(.data$SERAP06P))
}
# SERAP06T
if("SERAP06T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP06T = dplyr::case_match(
.data$SERAP06T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP06T
)
) %>%
dplyr::mutate(SERAP06T = as.factor(.data$SERAP06T))
}
# SERAP07P
if("SERAP07P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP07P = dplyr::case_match(
.data$SERAP07P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP07P
)
) %>%
dplyr::mutate(SERAP07P = as.factor(.data$SERAP07P))
}
# SERAP07T
if("SERAP07T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP07T = dplyr::case_match(
.data$SERAP07T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP07T
)
) %>%
dplyr::mutate(SERAP07T = as.factor(.data$SERAP07T))
}
# SERAP08P
if("SERAP08P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP08P = dplyr::case_match(
.data$SERAP08P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP08P
)
) %>%
dplyr::mutate(SERAP08P = as.factor(.data$SERAP08P))
}
# SERAP08T
if("SERAP08T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP08T = dplyr::case_match(
.data$SERAP08T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP08T
)
) %>%
dplyr::mutate(SERAP08T = as.factor(.data$SERAP08T))
}
# SERAP09P
if("SERAP09P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP09P = dplyr::case_match(
.data$SERAP09P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP09P
)
) %>%
dplyr::mutate(SERAP09P = as.factor(.data$SERAP09P))
}
# SERAP09T
if("SERAP09T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP09T = dplyr::case_match(
.data$SERAP09T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP09T
)
) %>%
dplyr::mutate(SERAP09T = as.factor(.data$SERAP09T))
}
# SERAP10P
if("SERAP10P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP10P = dplyr::case_match(
.data$SERAP10P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP10P
)
) %>%
dplyr::mutate(SERAP10P = as.factor(.data$SERAP10P))
}
# SERAP10T
if("SERAP10T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP10T = dplyr::case_match(
.data$SERAP10T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP10T
)
) %>%
dplyr::mutate(SERAP10T = as.factor(.data$SERAP10T))
}
# SERAP11P
if("SERAP11P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP11P = dplyr::case_match(
.data$SERAP11P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP11P
)
) %>%
dplyr::mutate(SERAP11P = as.factor(.data$SERAP11P))
}
# SERAP11T
if("SERAP11T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP11T = dplyr::case_match(
.data$SERAP11T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP11T
)
) %>%
dplyr::mutate(SERAP11T = as.factor(.data$SERAP11T))
}
# SERAPOIO
if("SERAPOIO" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAPOIO = dplyr::case_match(
.data$SERAPOIO,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAPOIO
)
) %>%
dplyr::mutate(SERAPOIO = as.factor(.data$SERAPOIO))
}
# RES_BIOL
if("RES_BIOL" %in% variables_names){
data <- data %>%
dplyr::mutate(
RES_BIOL = dplyr::case_match(
.data$RES_BIOL,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$RES_BIOL
)
) %>%
dplyr::mutate(RES_BIOL = as.factor(.data$RES_BIOL))
}
# RES_QUIM
if("RES_QUIM" %in% variables_names){
data <- data %>%
dplyr::mutate(
RES_QUIM = dplyr::case_match(
.data$RES_QUIM,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$RES_QUIM
)
) %>%
dplyr::mutate(RES_QUIM = as.factor(.data$RES_QUIM))
}
# RES_RADI
if("RES_RADI" %in% variables_names){
data <- data %>%
dplyr::mutate(
RES_RADI = dplyr::case_match(
.data$RES_RADI,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$RES_RADI
)
) %>%
dplyr::mutate(RES_RADI = as.factor(.data$RES_RADI))
}
# RES_COMU
if("RES_COMU" %in% variables_names){
data <- data %>%
dplyr::mutate(
RES_COMU = dplyr::case_match(
.data$RES_COMU,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$RES_COMU
)
) %>%
dplyr::mutate(RES_COMU = as.factor(.data$RES_COMU))
}
# COLETRES
if("COLETRES" %in% variables_names){
data <- data %>%
dplyr::mutate(
COLETRES = dplyr::case_match(
.data$COLETRES,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COLETRES
)
) %>%
dplyr::mutate(COLETRES = as.factor(.data$COLETRES))
}
# COMISS01
if("COMISS01" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS01 = dplyr::case_match(
.data$COMISS01,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS01
)
) %>%
dplyr::mutate(COMISS01 = as.factor(.data$COMISS01))
}
# COMISS02
if("COMISS02" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS02 = dplyr::case_match(
.data$COMISS02,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS02
)
) %>%
dplyr::mutate(COMISS02 = as.factor(.data$COMISS02))
}
# COMISS03
if("COMISS03" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS03 = dplyr::case_match(
.data$COMISS03,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS03
)
) %>%
dplyr::mutate(COMISS03 = as.factor(.data$COMISS03))
}
# COMISS04
if("COMISS04" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS04 = dplyr::case_match(
.data$COMISS04,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS04
)
) %>%
dplyr::mutate(COMISS04 = as.factor(.data$COMISS04))
}
# COMISS05
if("COMISS05" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS05 = dplyr::case_match(
.data$COMISS05,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS05
)
) %>%
dplyr::mutate(COMISS05 = as.factor(.data$COMISS05))
}
# COMISS06
if("COMISS06" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS06 = dplyr::case_match(
.data$COMISS06,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS06
)
) %>%
dplyr::mutate(COMISS06 = as.factor(.data$COMISS06))
}
# COMISS07
if("COMISS07" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS07 = dplyr::case_match(
.data$COMISS07,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS07
)
) %>%
dplyr::mutate(COMISS07 = as.factor(.data$COMISS07))
}
# COMISS08
if("COMISS08" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS08 = dplyr::case_match(
.data$COMISS08,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS08
)
) %>%
dplyr::mutate(COMISS08 = as.factor(.data$COMISS08))
}
# COMISS09
if("COMISS09" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS09 = dplyr::case_match(
.data$COMISS09,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS09
)
) %>%
dplyr::mutate(COMISS09 = as.factor(.data$COMISS09))
}
# COMISS10
if("COMISS10" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS10 = dplyr::case_match(
.data$COMISS10,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS10
)
) %>%
dplyr::mutate(COMISS10 = as.factor(.data$COMISS10))
}
# COMISS11
if("COMISS11" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS11 = dplyr::case_match(
.data$COMISS11,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS11
)
) %>%
dplyr::mutate(COMISS11 = as.factor(.data$COMISS11))
}
# COMISS12
if("COMISS12" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS12 = dplyr::case_match(
.data$COMISS12,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS12
)
) %>%
dplyr::mutate(COMISS12 = as.factor(.data$COMISS12))
}
# COMISSAO
if("COMISSAO" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISSAO = dplyr::case_match(
.data$COMISSAO,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISSAO
)
) %>%
dplyr::mutate(COMISSAO = as.factor(.data$COMISSAO))
}
# AP01CV01
if("AP01CV01" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP01CV01 = dplyr::case_match(
.data$AP01CV01,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP01CV01
)
) %>%
dplyr::mutate(AP01CV01 = as.factor(.data$AP01CV01))
}
# AP01CV02
if("AP01CV02" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP01CV02 = dplyr::case_match(
.data$AP01CV02,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP01CV02
)
) %>%
dplyr::mutate(AP01CV02 = as.factor(.data$AP01CV02))
}
# AP01CV05
if("AP01CV05" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP01CV05 = dplyr::case_match(
.data$AP01CV05,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP01CV05
)
) %>%
dplyr::mutate(AP01CV05 = as.factor(.data$AP01CV05))
}
# AP01CV06
if("AP01CV06" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP01CV06 = dplyr::case_match(
.data$AP01CV06,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP01CV06
)
) %>%
dplyr::mutate(AP01CV06 = as.factor(.data$AP01CV06))
}
# AP01CV03
if("AP01CV03" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP01CV03 = dplyr::case_match(
.data$AP01CV03,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP01CV03
)
) %>%
dplyr::mutate(AP01CV03 = as.factor(.data$AP01CV03))
}
# AP01CV04
if("AP01CV04" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP01CV04 = dplyr::case_match(
.data$AP01CV04,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP01CV04
)
) %>%
dplyr::mutate(AP01CV04 = as.factor(.data$AP01CV04))
}
# AP02CV01
if("AP02CV01" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP02CV01 = dplyr::case_match(
.data$AP02CV01,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP02CV01
)
) %>%
dplyr::mutate(AP02CV01 = as.factor(.data$AP02CV01))
}
# AP02CV02
if("AP02CV02" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP02CV02 = dplyr::case_match(
.data$AP02CV02,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP02CV02
)
) %>%
dplyr::mutate(AP02CV02 = as.factor(.data$AP02CV02))
}
# AP02CV05
if("AP02CV05" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP02CV05 = dplyr::case_match(
.data$AP02CV05,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP02CV05
)
) %>%
dplyr::mutate(AP02CV05 = as.factor(.data$AP02CV05))
}
# AP02CV06
if("AP02CV06" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP02CV06 = dplyr::case_match(
.data$AP02CV06,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP02CV06
)
) %>%
dplyr::mutate(AP02CV06 = as.factor(.data$AP02CV06))
}
# AP02CV03
if("AP02CV03" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP02CV03 = dplyr::case_match(
.data$AP02CV03,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP02CV03
)
) %>%
dplyr::mutate(AP02CV03 = as.factor(.data$AP02CV03))
}
# AP02CV04
if("AP02CV04" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP02CV04 = dplyr::case_match(
.data$AP02CV04,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP02CV04
)
) %>%
dplyr::mutate(AP02CV04 = as.factor(.data$AP02CV04))
}
# AP03CV01
if("AP03CV01" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP03CV01 = dplyr::case_match(
.data$AP03CV01,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP03CV01
)
) %>%
dplyr::mutate(AP03CV01 = as.factor(.data$AP03CV01))
}
# AP03CV02
if("AP03CV02" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP03CV02 = dplyr::case_match(
.data$AP03CV02,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP03CV02
)
) %>%
dplyr::mutate(AP03CV02 = as.factor(.data$AP03CV02))
}
# AP03CV05
if("AP03CV05" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP03CV05 = dplyr::case_match(
.data$AP03CV05,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP03CV05
)
) %>%
dplyr::mutate(AP03CV05 = as.factor(.data$AP03CV05))
}
# AP03CV06
if("AP03CV06" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP03CV06 = dplyr::case_match(
.data$AP03CV06,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP03CV06
)
) %>%
dplyr::mutate(AP03CV06 = as.factor(.data$AP03CV06))
}
# AP03CV03
if("AP03CV03" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP03CV03 = dplyr::case_match(
.data$AP03CV03,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP03CV03
)
) %>%
dplyr::mutate(AP03CV03 = as.factor(.data$AP03CV03))
}
# AP03CV04
if("AP03CV04" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP03CV04 = dplyr::case_match(
.data$AP03CV04,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP03CV04
)
) %>%
dplyr::mutate(AP03CV04 = as.factor(.data$AP03CV04))
}
# AP04CV01
if("AP04CV01" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP04CV01 = dplyr::case_match(
.data$AP04CV01,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP04CV01
)
) %>%
dplyr::mutate(AP04CV01 = as.factor(.data$AP04CV01))
}
# AP04CV02
if("AP04CV02" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP04CV02 = dplyr::case_match(
.data$AP04CV02,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP04CV02
)
) %>%
dplyr::mutate(AP04CV02 = as.factor(.data$AP04CV02))
}
# AP04CV05
if("AP04CV05" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP04CV05 = dplyr::case_match(
.data$AP04CV05,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP04CV05
)
) %>%
dplyr::mutate(AP04CV05 = as.factor(.data$AP04CV05))
}
# AP04CV06
if("AP04CV06" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP04CV06 = dplyr::case_match(
.data$AP04CV06,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP04CV06
)
) %>%
dplyr::mutate(AP04CV06 = as.factor(.data$AP04CV06))
}
# AP04CV03
if("AP04CV03" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP04CV03 = dplyr::case_match(
.data$AP04CV03,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP04CV03
)
) %>%
dplyr::mutate(AP04CV03 = as.factor(.data$AP04CV03))
}
# AP04CV04
if("AP04CV04" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP04CV04 = dplyr::case_match(
.data$AP04CV04,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP04CV04
)
) %>%
dplyr::mutate(AP04CV04 = as.factor(.data$AP04CV04))
}
# AP05CV01
if("AP05CV01" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP05CV01 = dplyr::case_match(
.data$AP05CV01,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP05CV01
)
) %>%
dplyr::mutate(AP05CV01 = as.factor(.data$AP05CV01))
}
# AP05CV02
if("AP05CV02" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP05CV02 = dplyr::case_match(
.data$AP05CV02,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP05CV02
)
) %>%
dplyr::mutate(AP05CV02 = as.factor(.data$AP05CV02))
}
# AP05CV05
if("AP05CV05" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP05CV05 = dplyr::case_match(
.data$AP05CV05,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP05CV05
)
) %>%
dplyr::mutate(AP05CV05 = as.factor(.data$AP05CV05))
}
# AP05CV06
if("AP05CV06" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP05CV06 = dplyr::case_match(
.data$AP05CV06,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP05CV06
)
) %>%
dplyr::mutate(AP05CV06 = as.factor(.data$AP05CV06))
}
# AP05CV03
if("AP05CV03" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP05CV03 = dplyr::case_match(
.data$AP05CV03,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP05CV03
)
) %>%
dplyr::mutate(AP05CV03 = as.factor(.data$AP05CV03))
}
# AP05CV04
if("AP05CV04" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP05CV04 = dplyr::case_match(
.data$AP05CV04,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP05CV04
)
) %>%
dplyr::mutate(AP05CV04 = as.factor(.data$AP05CV04))
}
# AP06CV01
if("AP06CV01" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP06CV01 = dplyr::case_match(
.data$AP06CV01,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP06CV01
)
) %>%
dplyr::mutate(AP06CV01 = as.factor(.data$AP06CV01))
}
# AP06CV02
if("AP06CV02" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP06CV02 = dplyr::case_match(
.data$AP06CV02,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP06CV02
)
) %>%
dplyr::mutate(AP06CV02 = as.factor(.data$AP06CV02))
}
# AP06CV05
if("AP06CV05" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP06CV05 = dplyr::case_match(
.data$AP06CV05,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP06CV05
)
) %>%
dplyr::mutate(AP06CV05 = as.factor(.data$AP06CV05))
}
# AP06CV06
if("AP06CV06" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP06CV06 = dplyr::case_match(
.data$AP06CV06,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP06CV06
)
) %>%
dplyr::mutate(AP06CV06 = as.factor(.data$AP06CV06))
}
# AP06CV03
if("AP06CV03" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP06CV03 = dplyr::case_match(
.data$AP06CV03,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP06CV03
)
) %>%
dplyr::mutate(AP06CV03 = as.factor(.data$AP06CV03))
}
# AP06CV04
if("AP06CV04" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP06CV04 = dplyr::case_match(
.data$AP06CV04,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP06CV04
)
) %>%
dplyr::mutate(AP06CV04 = as.factor(.data$AP06CV04))
}
# AP07CV01
if("AP07CV01" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP07CV01 = dplyr::case_match(
.data$AP07CV01,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP07CV01
)
) %>%
dplyr::mutate(AP07CV01 = as.factor(.data$AP07CV01))
}
# AP07CV02
if("AP07CV02" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP07CV02 = dplyr::case_match(
.data$AP07CV02,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP07CV02
)
) %>%
dplyr::mutate(AP07CV02 = as.factor(.data$AP07CV02))
}
# AP07CV05
if("AP07CV05" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP07CV05 = dplyr::case_match(
.data$AP07CV05,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP07CV05
)
) %>%
dplyr::mutate(AP07CV05 = as.factor(.data$AP07CV05))
}
# AP07CV06
if("AP07CV06" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP07CV06 = dplyr::case_match(
.data$AP07CV06,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP07CV06
)
) %>%
dplyr::mutate(AP07CV06 = as.factor(.data$AP07CV06))
}
# AP07CV03
if("AP07CV03" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP07CV03 = dplyr::case_match(
.data$AP07CV03,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP07CV03
)
) %>%
dplyr::mutate(AP07CV03 = as.factor(.data$AP07CV03))
}
# AP07CV04
if("AP07CV04" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP07CV04 = dplyr::case_match(
.data$AP07CV04,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP07CV04
)
) %>%
dplyr::mutate(AP07CV04 = as.factor(.data$AP07CV04))
}
# ATEND_PR
if("ATEND_PR" %in% variables_names){
data <- data %>%
dplyr::mutate(
ATEND_PR = dplyr::case_match(
.data$ATEND_PR,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$ATEND_PR
)
) %>%
dplyr::mutate(ATEND_PR = as.factor(.data$ATEND_PR))
}
} else if(information_system == "CNES-PF"){
# CNES
if("CNES" %in% variables_names){
data <- data %>%
dplyr::mutate(CNES = as.character(.data$CNES))
}
# UFMUNRES
if ("UFMUNRES" %in% variables_names & municipality_data == TRUE) {
colnames(tabMun)[5] <- "UFMUNRES"
tabMun$UFMUNRES <- as.character(tabMun$UFMUNRES)
data <- data %>%
dplyr::left_join(tabMun, by = "UFMUNRES")
}
# REGSAUDE
if("REGSAUDE" %in% variables_names){
data <- data %>%
dplyr::mutate(REGSAUDE = as.character(.data$REGSAUDE))
}
# MICR_REG
if("MICR_REG" %in% variables_names){
data <- data %>%
dplyr::mutate(MICR_REG = as.integer(.data$MICR_REG))
}
# DISTRSAN
if("DISTRSAN" %in% variables_names){
data <- data %>%
dplyr::mutate(DISTRSAN = as.integer(.data$DISTRSAN))
}
# DISTRADM
if("DISTRADM" %in% variables_names){
data <- data %>%
dplyr::mutate(DISTRADM = as.integer(.data$DISTRADM))
}
# TPGESTAO
if("TPGESTAO" %in% variables_names){
data <- data %>%
dplyr::mutate(
TPGESTAO = dplyr::case_match(
.data$TPGESTAO,
"D" ~ "Dupla",
"E" ~ "Estadual",
"M" ~ "Municipal",
"Z" ~ "Sem gest\u00e3o",
"S" ~ "Sem gest\u00e3o",
.default = .data$TPGESTAO
)
) %>%
dplyr::mutate(TPGESTAO = as.factor(.data$TPGESTAO))
}
# PF_PJ
if("PF_PJ" %in% variables_names){
data <- data %>%
dplyr::mutate(
PF_PJ = dplyr::case_match(
.data$PF_PJ,
"1" ~ "Pessoa f\u00edsica",
"3" ~ "Pessoa jur\u00eddica",
.default = .data$PF_PJ
)
) %>%
dplyr::mutate(PF_PJ = as.factor(.data$PF_PJ))
}
# CPF_CNPJ
if("CPF_CNPJ" %in% variables_names){
data <- data %>%
dplyr::mutate(CPF_CNPJ = as.numeric(.data$CPF_CNPJ))
}
# NIV_DEP
if("NIV_DEP" %in% variables_names){
data <- data %>%
dplyr::mutate(
NIV_DEP = dplyr::case_match(
.data$NIV_DEP,
"1" ~ "Individual",
"3" ~ "Mantida",
.default = .data$NIV_DEP
)
) %>%
dplyr::mutate(NIV_DEP = as.factor(.data$NIV_DEP))
}
# CNPJ_MAN
if("CNPJ_MAN" %in% variables_names){
data <- data %>%
dplyr::mutate(CNPJ_MAN = as.numeric(.data$CNPJ_MAN))
}
# ESFERA_A
if("ESFERA_A" %in% variables_names){
data <- data %>%
dplyr::mutate(
ESFERA_A = dplyr::case_match(
.data$ESFERA_A,
"-99" ~ NA,
"1" ~ "Federal",
"2" ~ "Estadual",
"3" ~ "Municipal",
"4" ~ "Privada",
.default = .data$ESFERA_A
)
) %>%
dplyr::mutate(ESFERA_A = as.factor(.data$ESFERA_A))
}
# ATIVIDAD
if("ATIVIDAD" %in% variables_names){
data <- data %>%
dplyr::mutate(
ATIVIDAD = dplyr::case_match(
.data$ATIVIDAD,
"-99" ~ NA,
"1" ~ "Unidade Universit\u00e1ria",
"2" ~ "Unidade Escola Superior Isolada",
"3" ~ "Unidade Auxiliar de Ensino",
"4" ~ "Unidade sem atividade de Ensino",
"5" ~ "Hospital de ensino",
.default = .data$ATIVIDAD
)
) %>%
dplyr::mutate(ATIVIDAD = as.factor(.data$ATIVIDAD))
}
# RETENCAO
if("RETENCAO" %in% variables_names){
data <- data %>%
dplyr::mutate(
RETENCAO = dplyr::case_match(
.data$RETENCAO,
"0" ~ NA,
"10" ~ "Estabelecimento p\u00fablico",
"11" ~ "Estabelecimento filantr\u00f3pico",
"12" ~ "Estabelecimento sem fins lucrativos",
"13" ~ "Estabelecimento privado luvrativa simples",
"14" ~ "Estabelecimento privado luvrativa",
"15" ~ "Estabelecimento sindical",
"16" ~ "Estabelecimento pessoa f\u00edsica",
.default = .data$RETENCAO
)
) %>%
dplyr::mutate(RETENCAO = as.factor(.data$RETENCAO))
}
# NATUREZA
if("NATUREZA" %in% variables_names){
data <- data %>%
dplyr::mutate(
NATUREZA = dplyr::case_match(
.data$NATUREZA,
"-99" ~ NA,
"1" ~ "Administra\u00e7\u00e3o Direta da Sa\u00fade (MS, SES, e SMS)",
"2" ~ "Adm Direta outros org\u00e3os (MEX, MEx, Marinha,...)",
"3" ~ "Adm Indireta - Autarquias",
"4" ~ "Adm Indireta - Funda\u00e7\u00e3o P\u00fablica",
"5" ~ "Adm Indireta - Empresa P\u00fablica",
"6" ~ "Adm Indireta - Organiza\u00e7\u00e3o Social P\u00fablica",
"7" ~ "Empresa Privada",
"8" ~ "Funda\u00e7\u00e3o Privada",
"9" ~ "Cooperativa",
"10" ~ "Servi\u00e7o Social Aut\u00f4nomo",
"11" ~ "Entidade Beneficente sem fins lucrativos",
"12" ~ "Economia Mista",
"13" ~ "Sindicato",
"0" ~ "Natureza inexistente",
.default = .data$NATUREZA
)
) %>%
dplyr::mutate(NATUREZA = as.factor(.data$NATUREZA))
}
# CLIENTEL
if("CLIENTEL" %in% variables_names){
data <- data %>%
dplyr::mutate(
CLIENTEL = dplyr::case_match(
.data$CLIENTEL,
"-99" ~ NA,
"1" ~ "Atendimento de demanda espont\u00e2nea",
"2" ~ "Atendimento de demanda referenciada",
"3" ~ "Atendimento de demanda espont\u00e2nea e referenciada",
"0" ~ "Fluxo de Clientela n\u00e3o exigido",
.default = .data$CLIENTEL
)
) %>%
dplyr::mutate(CLIENTEL = as.factor(.data$CLIENTEL))
}
# TP_UNID
if("TP_UNID" %in% variables_names){
data <- data %>%
dplyr::mutate(
TP_UNID = dplyr::case_match(
.data$TP_UNID,
"1" ~ "Posto de sa\u00fade",
"2" ~ "Centro de sa\u00fade / Unidade b\u00e1sica",
"4" ~ "Policl\u00ednica",
"5" ~ "Hospital geral",
"7" ~ "Hospital Especializado",
"9" ~ "Pronto socorro de hospital geral (antigo)",
"12" ~ "Pronto socorro traumato-ortop\u00e9dico (antigo)",
"15" ~ "Unidade mista",
"20" ~ "Pronto socorro geral",
"21" ~ "Pronto socorro especializado",
"22" ~ "Consult\u00f3rio isolado",
"32" ~ "Unidade m\u00f3vel fluvial",
"36" ~ "Cl\u00ednica / Centro de sa\u00fade de especialidade",
"39" ~ "Unidade de apoio diagnose e terapia (SADT isolado)",
"40" ~ "Unidade m\u00f3vel terrestre",
"42" ~ "Unidade m\u00f3vel de n\u00edvel pr\u00e9-hospitalar na \u00e1rea de urg\u00eancia",
"43" ~ "Farm\u00e1cia",
"45" ~ "Unidade de sa\u00fade da fam\u00edlia",
"50" ~ "Unidade de vigil\u00e2ncia em sa\u00fade",
"60" ~ "Cooperativa ou empresa de cess\u00e3o de trabalhadores na sa\u00fade",
"61" ~ "Centro de parto normal - isolado",
"62" ~ "Hospital / Dia - Isolado",
"63" ~ "Unidade autorizadora",
"64" ~ "Central de regula\u00e7\u00e3o de servi\u00e7os de sa\u00fade",
"65" ~ "Unidade de vigil\u00e2ncia epidemiol\u00f3gica (antigo)",
"66" ~ "Unidade de vigil\u00e2ncia sanit\u00e1ria (antigo)",
"67" ~ "Laborat\u00f3rio central de sa\u00fade p\u00fablica LACEN",
"68" ~ "Central de gest\u00e3o em sa\u00fade",
"69" ~ "Centro de aten\u00e7\u00e3o hemoterapia e/ou hematologica",
"70" ~ "Centro de aten\u00e7\u00e3o psicosocial",
"71" ~ "Centro de apoio a sa\u00fade da fam\u00edlia",
"72" ~ "Unidade de aten\u00e7\u00e3o a sa\u00fade ind\u00edgena",
"73" ~ "Pronto atendimento",
"74" ~ "P\u00f3lo academia da sa\u00fade",
"75" ~ "Telessa\u00fade",
"76" ~ "Central de regula\u00e7\u00e3o m\u00e9dica das urg\u00eancias",
"77" ~ "Servi\u00e7o de aten\u00e7\u00e3o domiciliar isolado (Home care)",
"78" ~ "Unidade de aten\u00e7\u00e3o em regime residencial",
"79" ~ "Oficina ortop\u00e9dica",
"80" ~ "Laborat\u00f3rio de sa\u00fade p\u00fablica",
"81" ~ "Central de regula\u00e7\u00e3o do acesso",
"82" ~ "Central de notifica\u00e7\u00e3o, capta\u00e7\u00e3o e distribui\u00e7\u00e3o de \u00f3rg\u00e3os estadual",
"83" ~ "P\u00f3lo de preven\u00e7\u00e3o de doen\u00e7as e agravos e promo\u00e7\u00e3o da sa\u00fade",
.default = .data$TP_UNID
)
) %>%
dplyr::mutate(TP_UNID = as.factor(.data$TP_UNID))
}
# TURNO_AT
if("TURNO_AT" %in% variables_names){
data <- data %>%
dplyr::mutate(
TURNO_AT = dplyr::case_match(
.data$TURNO_AT,
"-99" ~ NA,
"1" ~ "Turnos intermitentes",
"2" ~ "Cont\u00ednuo 24h/dia (Pl Sab Dom Fer)",
"3" ~ "Manh\u00e3 / Tarde / Noite",
"4" ~ "Manh\u00e3",
"5" ~ "Tarde",
"6" ~ "Manh\u00e3 / Tarde",
"7" ~ "Noite",
.default = .data$TURNO_AT
)
) %>%
dplyr::mutate(TURNO_AT = as.factor(.data$TURNO_AT))
}
# NIV_HIER
if("NIV_HIER" %in% variables_names){
data <- data %>%
dplyr::mutate(
NIV_HIER = dplyr::case_match(
.data$NIV_HIER,
"-99" ~ NA,
"99" ~ NA,
"0" ~ NA,
"1"~ "PAB-PABA",
"2"~ "M\u00e9dia M1",
"3"~ "M\u00e9dia M2 e M3",
"4"~ "Alta complexidade ambulatorial",
"5"~ "Baixa M1 e M2",
"6"~ "M\u00e9dia M2 e M3",
"7"~ "M\u00e9dia M3",
"8"~ "Alta complexidade hospitalar / ambulatorial",
.default = .data$NIV_HIER
)
) %>%
dplyr::mutate(NIV_HIER = as.factor(.data$NIV_HIER))
}
# TERCEIRO
if("TERCEIRO" %in% variables_names){
data <- data %>%
dplyr::mutate(
TERCEIRO = dplyr::case_match(
.data$TERCEIRO,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$TERCEIRO
)
) %>%
dplyr::mutate(TERCEIRO = as.factor(.data$TERCEIRO))
}
# CPF_PROF
if("CPF_PROF" %in% variables_names){
data <- data %>%
dplyr::mutate(
CPF_PROF = dplyr::case_match(
.data$CPF_PROF,
"99999999999" ~ NA,
"00000000000000" ~ NA,
.default = .data$CPF_PROF
)
) %>%
dplyr::mutate(CPF_PROF = as.factor(.data$CPF_PROF))
}
# CBO
if ("CBO" %in% variables_names) {
data <- data %>%
dplyr::mutate(CBO = as.character(.data$CBO)) %>%
dplyr::left_join(microdatasus::tabCBO, by = c("CBO" = "cod"))
}
# NOMEPROF
if("NOMEPROF" %in% variables_names){
data <- data %>%
dplyr::mutate(NOMEPROF = as.character(.data$NOMEPROF))
}
# VINCULAC
if("VINCULAC" %in% variables_names){
data <- data %>%
dplyr::mutate(
VINCULAC = dplyr::case_match(
.data$VINCULAC,
"1" ~ "Profissional CONTRATADO",
"2" ~ "Profissional AUT\u00d4NOMO",
"3" ~ "Profissional V\u00cdNCULO N\u00c3O IDENTIFICADO",
.default = .data$VINCULAC
)
) %>%
dplyr::mutate(VINCULAC = as.factor(.data$VINCULAC))
}
# NAT_JUR
if("NAT_JUR" %in% variables_names){
data <- data %>%
dplyr::mutate(
NAT_JUR = dplyr::case_match(
.data$NAT_JUR,
"0" ~ NA,
"1000" ~ "Administra\u00e7\u00e3o P\u00fablica",
"1015" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Executivo Federal",
"1023" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Executivo Estadual ou do Distrito Federal",
"1031" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Executivo Municipal",
"1040" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Legislativo Federal",
"1058" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Legislativo Estadual ou do Distrito Federal",
"1066" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Legislativo Municipal",
"1074" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Judici\u00e1rio Federal",
"1082" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Judici\u00e1rio Estadual",
"1104" ~ "Autarquia Federal",
"1112" ~ "Autarquia Estadual ou do Distrito Federal",
"1120" ~ "Autarquia Municipal",
"1139" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito P\u00fablico Federal",
"1147" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito P\u00fablico Estadual ou do Distrito Federal",
"1155" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito P\u00fablico Municipal",
"1163" ~ "\u00d3rg\u00e3o P\u00fablico Aut\u00f4nomo Federal",
"1171" ~ "\u00d3rg\u00e3o P\u00fablico Aut\u00f4nomo Estadual ou do Distrito Federal",
"1180" ~ "\u00d3rg\u00e3o P\u00fablico Aut\u00f4nomo Municipal",
"1198" ~ "Comiss\u00e3o Polinacional",
"1201" ~ "Fundo P\u00fablico",
"1210" ~ "Cons\u00f3rcio P\u00fablico de Direito P\u00fablico (Associa\u00e7\u00e3o P\u00fablica)",
"1228" ~ "Cons\u00f3rcio P\u00fablico de Direito Privado",
"1236" ~ "Estado ou Distrito Federal",
"1244" ~ "Munic\u00edpio",
"1252" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito Privado Federal",
"1260" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito Privado Estadual ou do Distrito Federal",
"1279" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito Privado Municipal",
"2000" ~ "Entidades Empresariais",
"2001" ~ "Empresa P\u00fablica",
"2038" ~ "Sociedade de Economia Mista",
"2046" ~ "Sociedade An\u00f4nima Aberta",
"2054" ~ "Sociedade An\u00f4nima Fechada",
"2062" ~ "Sociedade Empres\u00e1ria Limitada",
"2070" ~ "Sociedade Empres\u00e1ria em Nome Coletivo",
"2089" ~ "Sociedade Empres\u00e1ria em Comandita Simples",
"2097" ~ "Sociedade Empres\u00e1ria em Comandita por A\u00e7\u00f5es",
"2127" ~ "Sociedade em Conta de Participa\u00e7\u00e3o",
"2135" ~ "Empres\u00e1rio (Individual)",
"2143" ~ "Cooperativa",
"2151" ~ "Cons\u00f3rcio de Sociedades",
"2160" ~ "Grupo de Sociedades",
"2178" ~ "Estabelecimento, no Brasil, de Sociedade Estrangeira",
"2194" ~ "Estabelecimento, no Brasil, de Empresa Binacional Argentino-Brasileira",
"2216" ~ "Empresa Domiciliada no Exterior",
"2224" ~ "Clube/Fundo de Investimento",
"2232" ~ "Sociedade Simples Pura",
"2240" ~ "Sociedade Simples Limitada",
"2259" ~ "Sociedade Simples em Nome Coletivo",
"2267" ~ "Sociedade Simples em Comandita Simples",
"2275" ~ "Empresa Binacional",
"2283" ~ "Cons\u00f3rcio de Empregadores",
"2291" ~ "Cons\u00f3rcio Simples",
"2305" ~ "Empresa Individual de Responsabilidade Limitada (de Natureza Empres\u00e1ria)",
"2313" ~ "Empresa Individual de Responsabilidade Limitada (de Natureza Simples)",
"2321" ~ "Sociedade Unipessoal de Advogados",
"2330" ~ "Cooperativas de Consumo",
"3000" ~ "Entidades sem Fins Lucrativos",
"3034" ~ "Servi\u00e7o Notarial e Registral (Cart\u00f3rio)",
"3069" ~ "Funda\u00e7\u00e3o Privada",
"3077" ~ "Servi\u00e7o Social Aut\u00f4nomo",
"3085" ~ "Condom\u00ednio Edil\u00edcio",
"3107" ~ "Comiss\u00e3o de Concilia\u00e7\u00e3o Pr\u00e9via",
"3115" ~ "Entidade de Media\u00e7\u00e3o e Arbitragem",
"3131" ~ "Entidade Sindical",
"3204" ~ "Estabelecimento, no Brasil, de Funda\u00e7\u00e3o ou Associa\u00e7\u00e3o Estrangeiras",
"3212" ~ "Funda\u00e7\u00e3o ou Associa\u00e7\u00e3o Domiciliada no Exterior",
"3220" ~ "Organiza\u00e7\u00e3o Religiosa",
"3239" ~ "Comunidade Ind\u00edgena",
"3247" ~ "Fundo Privado",
"3255" ~ "\u00d3rg\u00e3o de Dire\u00e7\u00e3o Nacional de Partido Pol\u00edtico",
"3263" ~ "\u00d3rg\u00e3o de Dire\u00e7\u00e3o Regional de Partido Pol\u00edtico",
"3271" ~ "\u00d3rg\u00e3o de Dire\u00e7\u00e3o Local de Partido Pol\u00edtico",
"3280" ~ "Comit\u00ea Financeiro de Partido Pol\u00edtico",
"3298" ~ "Frente Plebiscit\u00e1ria ou Referend\u00e1ria",
"3306" ~ "Organiza\u00e7\u00e3o Social (OS)",
"3310" ~ "Demais Condom\u00ednios",
"3999" ~ "Associa\u00e7\u00e3o Privada",
"4000" ~ "Pessoas F\u00edsicas",
"4014" ~ "Empresa Individual Imobili\u00e1ria",
"4022" ~ "Segurado Especial",
"4081" ~ "Contribuinte individual",
"4090" ~ "Candidato a Cargo Pol\u00edtico Eletivo",
"4111" ~ "Leiloeiro",
"4124" ~ "Produtor Rural (Pessoa F\u00edsica)",
"5000" ~ "Organiza\u00e7\u00f5es Internacionais e Outras Institui\u00e7\u00f5es Extraterritoriais",
"5010" ~ "Organiza\u00e7\u00e3o Internacional",
"5029" ~ "Representa\u00e7\u00e3o Diplom\u00e1tica Estrangeira",
"5037" ~ "Outras Institui\u00e7\u00f5es Extraterritoriais",
.default = .data$NAT_JUR
)
) %>%
dplyr::mutate(NAT_JUR = as.factor(.data$NAT_JUR))
}
}
# From data.table to tibble
data <- tibble::as_tibble(data)
# Purge levels
data <- droplevels(data)
# Unescape unicode characters
data <- suppressWarnings(tibble::as_tibble(lapply(X = data, FUN = stringi::stri_unescape_unicode)))
# Return
return(data)
}
rfsaldanha/microdatasus documentation built on April 13, 2024, 2:25 p.m.
R Package Documentation
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Defines functions process_cnes
Documented in process_cnes
#' Process CNES variables from DataSUS
#'
#' \code{process_cnes} processes CNES variables retrieved by \code{fetch_datasus()}.
#'
#' This function processes CNES-ST (Estabelecimentos) or CNES-PF (Pessoa f\\u00edsica) variables retrieved by \code{fetch_datasus()}, informing labels for categoric variables including NA values.
#'
#' @param data \code{data.frame} created by \code{fetch_datasus()}.
#' @param information_system \code{string}. \code{CNES-ST} or \code{CNES-PF}
#' @param nomes optional logical. \code{TRUE} by default, add \code{FANTASIA} and \code{RAZÃO SOCIAL} names to the dataset.
#' @param municipality_data optional logical. \code{TRUE} by default, creates new variables in the dataset informing the full name and other details about the municipality of residence.
#'
#' @examples \dontrun{
#' df <- fetch_datasus(year_start = 2015, month_start = 1,
#' year_end = 2015, month_end = 1,
#' uf = "RJ",
#' information_system = "CNES-ST")
#' df_a <- process_cnes(df, information_system = "CNES-ST")
#' df_b <- process_cnes(df, information_system = "CNES-ST", nomes = FALSE, municipality_data = FALSE)
#' }
#' @export
process_cnes <- function(data, information_system = c("CNES-ST", "CNES-PF"), nomes = TRUE, municipality_data = TRUE) {
# Check information system
checkmate::assert_choice(x = information_system, choices = c("CNES-ST", "CNES-PF"))
# Variables names
variables_names <- names(data)
# Use dtplyr
data <- dtplyr::lazy_dt(data)
if(information_system == "CNES-ST"){
# CNES
if("CNES" %in% variables_names){
data <- data %>%
dplyr::mutate(CNES = as.character(.data$CNES))
}
# Nome fantasia e razão social
if(nomes == TRUE){
data <- data %>%
dplyr::mutate(CNES_integer = as.integer(.data$CNES)) %>%
dplyr::left_join(microdatasus::cadger, by = c("CNES_integer" = "CNES")) %>%
dplyr::select(-"CNES_integer")
}
# CODUFMUN
if ("CODUFMUN" %in% variables_names & municipality_data == TRUE) {
colnames(tabMun)[1] <- "CODUFMUN"
tabMun$CODUFMUN <- as.character(tabMun$CODUFMUN)
data <- data %>%
dplyr::left_join(tabMun, by = "CODUFMUN")
}
# COD_CEP
if("COD_CEP" %in% variables_names){
data <- data %>%
dplyr::mutate(COD_CEP = as.integer(.data$COD_CEP))
}
# CPF_CNPJ
if("CPF_CNPJ" %in% variables_names){
data <- data %>%
dplyr::mutate(CPF_CNPJ = as.character(.data$CPF_CNPJ))
}
# PF_PJ
if("PF_PJ" %in% variables_names){
data <- data %>%
dplyr::mutate(
PF_PJ = dplyr::case_match(
.data$PF_PJ,
"1" ~ "Pessoa f\u00edsica",
"3" ~ "Pessoa jur\u00eddica",
.default = .data$PF_PJ
)
) %>%
dplyr::mutate(PF_PJ = as.factor(.data$PF_PJ))
}
# NIV_DEP
if("NIV_DEP" %in% variables_names){
data <- data %>%
dplyr::mutate(
NIV_DEP = dplyr::case_match(
.data$NIV_DEP,
"1" ~ "Individual",
"3" ~ "Mantida",
.default = .data$NIV_DEP
)
) %>%
dplyr::mutate(NIV_DEP = as.factor(.data$NIV_DEP))
}
# CNPJ_MAN
if("CNPJ_MAN" %in% variables_names){
data <- data %>%
dplyr::mutate(CNPJ_MAN = as.numeric(.data$CNPJ_MAN))
}
# COD_IR
if("COD_IR" %in% variables_names){
data <- data %>%
dplyr::mutate(
COD_IR = dplyr::case_match(
.data$COD_IR,
"0" ~ NA,
"10" ~ "Estabelecimento p\u00fablico",
"11" ~ "Estabelecimento filantr\u00f3pico",
"12" ~ "Estabelecimento sem fins lucrativos",
"13" ~ "Estabelecimento privado luvrativa simples",
"14" ~ "Estabelecimento privado luvrativa",
"15" ~ "Estabelecimento sindical",
"16" ~ "Estabelecimento pessoa f\u00edsica",
"19" ~ "Estabelecimento Ret.Manten.c\u00f3digo 19",
.default = .data$COD_IR
)
) %>%
dplyr::mutate(COD_IR = as.factor(.data$COD_IR))
}
# REGSAUDE
if("REGSAUDE" %in% variables_names){
data <- data %>%
dplyr::mutate(REGSAUDE = as.character(.data$REGSAUDE))
}
# MICR_REG
if("MICR_REG" %in% variables_names){
data <- data %>%
dplyr::mutate(MICR_REG = as.integer(.data$MICR_REG))
}
# DISTRSAN
if("DISTRSAN" %in% variables_names){
data <- data %>%
dplyr::mutate(DISTRSAN = as.integer(.data$DISTRSAN))
}
# VINC_SUS
if("VINC_SUS" %in% variables_names){
data <- data %>%
dplyr::mutate(
VINC_SUS = dplyr::case_match(
.data$VINC_SUS,
"0" ~ "N\u00e3o",
"1" ~ "Sim",
"2" ~ "N\u00e3o",
.default = .data$VINC_SUS
)
) %>%
dplyr::mutate(VINC_SUS = as.factor(.data$VINC_SUS))
}
# TPGESTAO
if("TPGESTAO" %in% variables_names){
data <- data %>%
dplyr::mutate(
TPGESTAO = dplyr::case_match(
.data$TPGESTAO,
"D" ~ "Dupla",
"E" ~ "Estadual",
"M" ~ "Municipal",
"Z" ~ "Sem gest\u00e3o",
"S" ~ "Sem gest\u00e3o",
.default = .data$TPGESTAO
)
) %>%
dplyr::mutate(TPGESTAO = as.factor(.data$TPGESTAO))
}
# ESFERA_A
if("ESFERA_A" %in% variables_names){
data <- data %>%
dplyr::mutate(
ESFERA_A = dplyr::case_match(
.data$ESFERA_A,
"1" ~ "Federal",
"2" ~ "Estadual",
"3" ~ "Municipal",
"4" ~ "Privada",
"-99" ~ NA,
.default = .data$ESFERA_A
)
) %>%
dplyr::mutate(ESFERA_A = as.factor(.data$ESFERA_A))
}
# RETENCAO
if("RETENCAO" %in% variables_names){
data <- data %>%
dplyr::mutate(
RETENCAO = dplyr::case_match(
.data$RETENCAO,
"0" ~ NA,
"10" ~ "Estabelecimento p\u00fablico",
"11" ~ "Estabelecimento filantr\u00f3pico",
"12" ~ "Estabelecimento sem fins lucrativos",
"13" ~ "Estabelecimento privado luvrativa simples",
"14" ~ "Estabelecimento privado luvrativa",
"15" ~ "Estabelecimento sindical",
"16" ~ "Estabelecimento pessoa f\u00edsica",
.default = .data$RETENCAO
)
) %>%
dplyr::mutate(RETENCAO = as.factor(.data$RETENCAO))
}
# ATIVIDAD
if("ATIVIDAD" %in% variables_names){
data <- data %>%
dplyr::mutate(
ATIVIDAD = dplyr::case_match(
.data$ATIVIDAD,
"-99" ~ NA,
"1" ~ "Unidade Universit\u00e1ria",
"2" ~ "Unidade Escola Superior Isolada",
"3" ~ "Unidade Auxiliar de Ensino",
"4" ~ "Unidade sem atividade de Ensino",
"5" ~ "Hospital de ensino",
.default = .data$ATIVIDAD
)
) %>%
dplyr::mutate(ATIVIDAD = as.factor(.data$ATIVIDAD))
}
# NATUREZA
if("NATUREZA" %in% variables_names){
data <- data %>%
dplyr::mutate(
NATUREZA = dplyr::case_match(
.data$NATUREZA,
"-99" ~ NA,
"1" ~ "Administra\u00e7\u00e3o Direta da Sa\u00fade (MS, SES, e SMS)",
"2" ~ "Adm Direta outros org\u00e3os (MEX, MEx, Marinha,...)",
"3" ~ "Adm Indireta - Autarquias",
"4" ~ "Adm Indireta - Funda\u00e7\u00e3o P\u00fablica",
"5" ~ "Adm Indireta - Empresa P\u00fablica",
"6" ~ "Adm Indireta - Organiza\u00e7\u00e3o Social P\u00fablica",
"7" ~ "Empresa Privada",
"8" ~ "Funda\u00e7\u00e3o Privada",
"9" ~ "Cooperativa",
"10" ~ "Servi\u00e7o Social Aut\u00f4nomo",
"11" ~ "Entidade Beneficente sem fins lucrativos",
"12" ~ "Economia Mista",
"13" ~ "Sindicato",
"0" ~ "Natureza inexistente",
.default = .data$NATUREZA
)
) %>%
dplyr::mutate(NATUREZA = as.factor(.data$NATUREZA))
}
# NAT_JUR
if("NAT_JUR" %in% variables_names){
data <- data %>%
dplyr::mutate(
NAT_JUR = dplyr::case_match(
.data$NAT_JUR,
"1015" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Executivo Federal",
"1023" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Executivo Estadual ou do Distrito Federal",
"1031" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Executivo Municipal",
"1040" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Legislativo Federal",
"1058" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Legislativo Estadual ou do Distrito Federal",
"1066" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Legislativo Municipal",
"1074" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Judici\u00e1rio Federal",
"1082" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Judici\u00e1rio Estadual",
"1104" ~ "Autarquia Federal",
"1112" ~ "Autarquia Estadual ou do Distrito Federal",
"1120" ~ "Autarquia Municipal",
"1139" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito P\u00fablico Federal",
"1147" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito P\u00fablico Estadual ou do Distrito Federal",
"1155" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito P\u00fablico Municipal",
"1163" ~ "\u00d3rg\u00e3o P\u00fablico Aut\u00f4nomo Federal",
"1171" ~ "\u00d3rg\u00e3o P\u00fablico Aut\u00f4nomo Estadual ou do Distrito Federal",
"1180" ~ "\u00d3rg\u00e3o P\u00fablico Aut\u00f4nomo Municipal",
"1198" ~ "Comiss\u00e3o Polinacional",
"1201" ~ "Fundo P\u00fablico",
"1210" ~ "Cons\u00f3rcio P\u00fablico de Direito P\u00fablico (Associa\u00e7\u00e3o P\u00fablica)",
"1228" ~ "Cons\u00f3rcio P\u00fablico de Direito Privado",
"1236" ~ "Estado ou Distrito Federal",
"1244" ~ "Munic\u00edpio",
"1252" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito Privado Federal",
"1260" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito Privado Estadual ou do Distrito Federal",
"1279" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito Privado Municipal",
"2011" ~ "Empresa P\u00fablica",
"2038" ~ "Sociedade de Economia Mista",
"2046" ~ "Sociedade An\u00f4nima Aberta",
"2054" ~ "Sociedade An\u00f4nima Fechada",
"2062" ~ "Sociedade Empres\u00e1ria Limitada",
"2070" ~ "Sociedade Empres\u00e1ria em Nome Coletivo",
"2089" ~ "Sociedade Empres\u00e1ria em Comandita Simples",
"2097" ~ "Sociedade Empres\u00e1ria em Comandita por A\u00e7\u00f5es",
"2127" ~ "Sociedade em Conta de Participa\u00e7\u00e3o",
"2135" ~ "Empres\u00e1rio (Individual)",
"2143" ~ "Cooperativa",
"2151" ~ "Cons\u00f3rcio de Sociedades",
"2160" ~ "Grupo de Sociedades",
"2178" ~ "Estabelecimento, no Brasil, de Sociedade Estrangeira",
"2194" ~ "Estabelecimento, no Brasil, de Empresa Binacional Argentino-Brasileira",
"2216" ~ "Empresa Domiciliada no Exterior",
"2224" ~ "Clube/Fundo de Investimento",
"2232" ~ "Sociedade Simples Pura",
"2240" ~ "Sociedade Simples Limitada",
"2259" ~ "Sociedade Simples em Nome Coletivo",
"2267" ~ "Sociedade Simples em Comandita Simples",
"2275" ~ "Empresa Binacional",
"2283" ~ "Cons\u00f3rcio de Empregadores",
"2291" ~ "Cons\u00f3rcio Simples",
"2305" ~ "Empresa Individual de Responsabilidade Limitada (de Natureza Empres\u00e1ria)",
"2313" ~ "Empresa Individual de Responsabilidade Limitada (de Natureza Simples)",
"2321" ~ "Sociedade Unipessoal de Advogados",
"2330" ~ "Cooperativas de Consumo",
"3034" ~ "Servi\u00e7o Notarial e Registral (Cart\u00f3rio)",
"3069" ~ "Funda\u00e7\u00e3o Privada",
"3077" ~ "Servi\u00e7o Social Aut\u00f4nomo",
"3085" ~ "Condom\u00ednio Edil\u00edcio",
"3107" ~ "Comiss\u00e3o de Concilia\u00e7\u00e3o Pr\u00e9via",
"3115" ~ "Entidade de Media\u00e7\u00e3o e Arbitragem",
"3131" ~ "Entidade Sindical",
"3204" ~ "Estabelecimento, no Brasil, de Funda\u00e7\u00e3o ou Associa\u00e7\u00e3o Estrangeiras",
"3212" ~ "Funda\u00e7\u00e3o ou Associa\u00e7\u00e3o Domiciliada no Exterior",
"3220" ~ "Organiza\u00e7\u00e3o Religiosa",
"3239" ~ "Comunidade Ind\u00edgena",
"3247" ~ "Fundo Privado",
"3255" ~ "\u00d3rg\u00e3o de Dire\u00e7\u00e3o Nacional de Partido Pol\u00edtico",
"3263" ~ "\u00d3rg\u00e3o de Dire\u00e7\u00e3o Regional de Partido Pol\u00edtico",
"3271" ~ "\u00d3rg\u00e3o de Dire\u00e7\u00e3o Local de Partido Pol\u00edtico",
"3280" ~ "Comit\u00ea Financeiro de Partido Pol\u00edtico",
"3298" ~ "Frente Plebiscit\u00e1ria ou Referend\u00e1ria",
"3306" ~ "Organiza\u00e7\u00e3o Social (OS)",
"3310" ~ "Demais Condom\u00ednios",
"3999" ~ "Associa\u00e7\u00e3o Privada",
"4014" ~ "Empresa Individual Imobili\u00e1ria",
"4022" ~ "Segurado Especial",
"4081" ~ "Contribuinte individual",
"4090" ~ "Candidato a Cargo Pol\u00edtico Eletivo",
"4111" ~ "Leiloeiro",
"4124" ~ "Produtor Rural (Pessoa F\u00edsica)",
"5010" ~ "Organiza\u00e7\u00e3o Internacional",
"5029" ~ "Representa\u00e7\u00e3o Diplom\u00e1tica Estrangeira",
"5037" ~ "Outras Institui\u00e7\u00f5es Extraterritoriais",
"0" ~ "N\u00e3o especificado ou ignorado",
.default = .data$NAT_JUR
)
) %>%
dplyr::mutate(NAT_JUR = as.factor(.data$NAT_JUR))
}
# CLIENTEL
if("CLIENTEL" %in% variables_names){
data <- data %>%
dplyr::mutate(
CLIENTEL = dplyr::case_match(
.data$CLIENTEL,
"-99" ~ NA,
"1" ~ "Atendimento de demanda espont\u00e2nea",
"2" ~ "Atendimento de demanda referenciada",
"3" ~ "Atendimento de demanda espont\u00e2nea e referenciada",
"0" ~ "Fluxo de Clientela n\u00e3o exigido",
.default = .data$CLIENTEL
)
) %>%
dplyr::mutate(CLIENTEL = as.factor(.data$CLIENTEL))
}
# TP_UNID
if("TP_UNID" %in% variables_names){
data <- data %>%
dplyr::mutate(
TP_UNID = dplyr::case_match(
.data$TP_UNID,
"1" ~ "Posto de sa\u00fade",
"2" ~ "Centro de sa\u00fade / Unidade b\u00e1sica",
"4" ~ "Policl\u00ednica",
"5" ~ "Hospital geral",
"7" ~ "Hospital Especializado",
"9" ~ "Pronto socorro de hospital geral (antigo)",
"12" ~ "Pronto socorro traumato-ortop\u00e9dico (antigo)",
"15" ~ "Unidade mista",
"20" ~ "Pronto socorro geral",
"21" ~ "Pronto socorro especializado",
"22" ~ "Consult\u00f3rio isolado",
"32" ~ "Unidade m\u00f3vel fluvial",
"36" ~ "Cl\u00ednica / Centro de sa\u00fade de especialidade",
"39" ~ "Unidade de apoio diagnose e terapia (SADT isolado)",
"40" ~ "Unidade m\u00f3vel terrestre",
"42" ~ "Unidade m\u00f3vel de n\u00edvel pr\u00e9-hospitalar na \u00e1rea de urg\u00eancia",
"43" ~ "Farm\u00e1cia",
"45" ~ "Unidade de sa\u00fade da fam\u00edlia",
"50" ~ "Unidade de vigil\u00e2ncia em sa\u00fade",
"60" ~ "Cooperativa ou empresa de cess\u00e3o de trabalhadores na sa\u00fade",
"61" ~ "Centro de parto normal - isolado",
"62" ~ "Hospital / Dia - Isolado",
"63" ~ "Unidade autorizadora",
"64" ~ "Central de regula\u00e7\u00e3o de servi\u00e7os de sa\u00fade",
"65" ~ "Unidade de vigil\u00e2ncia epidemiol\u00f3gica (antigo)",
"66" ~ "Unidade de vigil\u00e2ncia sanit\u00e1ria (antigo)",
"67" ~ "Laborat\u00f3rio central de sa\u00fade p\u00fablica LACEN",
"68" ~ "Central de gest\u00e3o em sa\u00fade",
"69" ~ "Centro de aten\u00e7\u00e3o hemoterapia e/ou hematologica",
"70" ~ "Centro de aten\u00e7\u00e3o psicosocial",
"71" ~ "Centro de apoio a sa\u00fade da fam\u00edlia",
"72" ~ "Unidade de aten\u00e7\u00e3o a sa\u00fade ind\u00edgena",
"73" ~ "Pronto atendimento",
"74" ~ "P\u00f3lo academia da sa\u00fade",
"75" ~ "Telessa\u00fade",
"76" ~ "Central de regula\u00e7\u00e3o m\u00e9dica das urg\u00eancias",
"77" ~ "Servi\u00e7o de aten\u00e7\u00e3o domiciliar isolado (Home care)",
"78" ~ "Unidade de aten\u00e7\u00e3o em regime residencial",
"79" ~ "Oficina ortop\u00e9dica",
"80" ~ "Laborat\u00f3rio de sa\u00fade p\u00fablica",
"81" ~ "Central de regula\u00e7\u00e3o do acesso",
"82" ~ "Central de notifica\u00e7\u00e3o, capta\u00e7\u00e3o e distribui\u00e7\u00e3o de \u00f3rg\u00e3os estadual",
"83" ~ "P\u00f3lo de preven\u00e7\u00e3o de doen\u00e7as e agravos e promo\u00e7\u00e3o da sa\u00fade",
.default = .data$TP_UNID
)
) %>%
dplyr::mutate(TP_UNID = as.factor(.data$TP_UNID))
}
# TURNO_AT
if("TURNO_AT" %in% variables_names){
data <- data %>%
dplyr::mutate(
TURNO_AT = dplyr::case_match(
.data$TURNO_AT,
"-99" ~ NA,
"1" ~ "Turnos intermitentes",
"2" ~ "Cont\u00ednuo 24h/dia (Pl Sab Dom Fer)",
"3" ~ "Manh\u00e3 / Tarde / Noite",
"4" ~ "Manh\u00e3",
"5" ~ "Tarde",
"6" ~ "Manh\u00e3 / Tarde",
"7" ~ "Noite",
.default = .data$TURNO_AT
)
) %>%
dplyr::mutate(TURNO_AT = as.factor(.data$TURNO_AT))
}
# NIV_HIER
if("NIV_HIER" %in% variables_names){
data <- data %>%
dplyr::mutate(
NIV_HIER = dplyr::case_match(
.data$NIV_HIER,
"0" ~ NA,
"-99" ~ NA,
"1" ~ "PAB-PABA",
"2" ~ "M\u00e9dia M1",
"3" ~ "M\u00e9dia M2 e M3",
"4" ~ "Alta complexidade ambulatorial",
"5" ~ "Baixa M1 e M2",
"6" ~ "M\u00e9dia M2 e M3",
"7" ~ "M\u00e9dia M3",
"8" ~ "Alta complexidade hospitalar / ambulatorial",
.default = .data$NIV_HIER
)
) %>%
dplyr::mutate(NIV_HIER = as.factor(.data$NIV_HIER))
}
# TP_PREST
if("TP_PREST" %in% variables_names){
data <- data %>%
dplyr::mutate(
TP_PREST = dplyr::case_match(
.data$TP_PREST,
"-99" ~ NA,
"30" ~ "P\u00fablico federal",
"40" ~ "P\u00fablico estadual",
"50" ~ "P\u00fablico municipal",
"61" ~ "Filantr\u00f3pico com CNAS v\u00e1lido",
"80" ~ "Sindicato",
"20" ~ "Privado com fins lucrativos",
"22" ~ "Privado optantes pelo simples",
"60" ~ "Privado sem fins lucrativos",
.default = .data$TP_PREST
)
) %>%
dplyr::mutate(TP_PREST = as.factor(.data$TP_PREST))
}
# CO_BANCO
if("CO_BANCO" %in% variables_names){
data <- data %>%
dplyr::mutate(CO_BANCO = as.character(.data$CO_BANCO))
}
# CO_AGENC
if("CO_AGENC" %in% variables_names){
data <- data %>%
dplyr::mutate(CO_AGENC = as.character(.data$CO_AGENC))
}
# C_CORREN
if("C_CORREN" %in% variables_names){
data <- data %>%
dplyr::mutate(C_CORREN = as.character(.data$C_CORREN))
}
# CONTRATM
if("CONTRATM" %in% variables_names){
data <- data %>%
dplyr::mutate(CONTRATM = as.character(.data$CONTRATM))
}
# DT_PUBLM
if("DT_PUBLM" %in% variables_names){
data <- data %>%
dplyr::mutate(DT_PUBLM = as.character(.data$DT_PUBLM))
}
# CONTRATE
if("CONTRATE" %in% variables_names){
data <- data %>%
dplyr::mutate(CONTRATE = as.character(.data$CONTRATE))
}
# DT_PUBLE
if("DT_PUBLE" %in% variables_names){
data <- data %>%
dplyr::mutate(DT_PUBLE = as.character(.data$DT_PUBLE))
}
# ALVARA
if("ALVARA" %in% variables_names){
data <- data %>%
dplyr::mutate(ALVARA = as.character(.data$ALVARA))
}
# DT_EXPED
if("DT_EXPED" %in% variables_names){
data <- data %>%
dplyr::mutate(DT_EXPED = as.character(.data$DT_EXPED))
}
# ORGEXPED
if("ORGEXPED" %in% variables_names){
data <- data %>%
dplyr::mutate(
ORGEXPED = dplyr::case_match(
.data$ORGEXPED,
"1" ~ "SES",
"2" ~ "SMS",
.default = .data$ORGEXPED
)
) %>%
dplyr::mutate(ORGEXPED = as.factor(.data$ORGEXPED))
}
# AV_ACRED
if("AV_ACRED" %in% variables_names){
data <- data %>%
dplyr::mutate(
AV_ACRED = dplyr::case_match(
.data$AV_ACRED,
"1" ~ "Sim",
"2" ~ "N\u00e3o",
"0" ~ "N\u00e3o",
.default = .data$AV_ACRED
)
) %>%
dplyr::mutate(AV_ACRED = as.factor(.data$AV_ACRED))
}
# CLASAVAL
if("CLASAVAL" %in% variables_names){
data <- data %>%
dplyr::mutate(
CLASAVAL = dplyr::case_match(
.data$CLASAVAL,
"-9" ~ NA,
"1" ~ "Acreditado no n\u00edvel 1",
"2" ~ "Acreditado no n\u00edvel 2",
"3" ~ "Acreditado no n\u00edvel 3",
"0" ~ "N\u00e3o atendeu aos padr\u00f5es m\u00ednimos",
.default = .data$CLASAVAL
)
) %>%
dplyr::mutate(CLASAVAL = as.factor(.data$CLASAVAL))
}
# DT_ACRED
if("DT_ACRED" %in% variables_names){
data <- data %>%
dplyr::mutate(DT_ACRED = as.integer(.data$DT_ACRED))
}
# AV_PNASS
if("AV_PNASS" %in% variables_names){
data <- data %>%
dplyr::mutate(
AV_PNASS = dplyr::case_match(
.data$AV_PNASS,
"1" ~ "Sim",
"2" ~ "N\u00e3o",
"0" ~ "N\u00e3o",
.default = .data$AV_PNASS
)
) %>%
dplyr::mutate(AV_PNASS = as.factor(.data$AV_PNASS))
}
# DT_PNASS
if("DT_PNASS" %in% variables_names){
data <- data %>%
dplyr::mutate(DT_PNASS = as.integer(.data$DT_PNASS))
}
# GESPRG1E
if("GESPRG1E" %in% variables_names){
data$GESPRG1E <- as.numeric(levels(data$GESPRG1E))[data$GESPRG1E]
data$GESPRG1E[data$GESPRG1E==1] <- "Sim"
data$GESPRG1E[data$GESPRG1E==0] <- "N\u00e3o"
data$GESPRG1E <- factor(data$GESPRG1E)
}
# GESPRG1M
if("GESPRG1M" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG1M = dplyr::case_match(
.data$GESPRG1M,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG1M
)
) %>%
dplyr::mutate(GESPRG1M = as.factor(.data$GESPRG1M))
}
# GESPRG2E
if("GESPRG2E" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG2E = dplyr::case_match(
.data$GESPRG2E,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG2E
)
) %>%
dplyr::mutate(GESPRG2E = as.factor(.data$GESPRG2E))
}
# GESPRG2M
if("GESPRG2M" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG2M = dplyr::case_match(
.data$GESPRG2M,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG2M
)
) %>%
dplyr::mutate(GESPRG2M = as.factor(.data$GESPRG2M))
}
# GESPRG4E
if("GESPRG4E" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG4E = dplyr::case_match(
.data$GESPRG4E,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG4E
)
) %>%
dplyr::mutate(GESPRG4E = as.factor(.data$GESPRG4E))
}
# GESPRG4M
if("GESPRG4M" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG4M = dplyr::case_match(
.data$GESPRG4M,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG4M
)
) %>%
dplyr::mutate(GESPRG4M = as.factor(.data$GESPRG4M))
}
# NIVATE_A
if("NIVATE_A" %in% variables_names){
data <- data %>%
dplyr::mutate(
NIVATE_A = dplyr::case_match(
.data$NIVATE_A,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$NIVATE_A
)
) %>%
dplyr::mutate(NIVATE_A = as.factor(.data$NIVATE_A))
}
# GESPRG3E
if("GESPRG3E" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG3E = dplyr::case_match(
.data$GESPRG3E,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG3E
)
) %>%
dplyr::mutate(GESPRG3E = as.factor(.data$GESPRG3E))
}
# GESPRG3M
if("GESPRG3M" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG3M = dplyr::case_match(
.data$GESPRG3M,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG3M
)
) %>%
dplyr::mutate(GESPRG3M = as.factor(.data$GESPRG3M))
}
# GESPRG5E
if("GESPRG5E" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG5E = dplyr::case_match(
.data$GESPRG5E,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG5E
)
) %>%
dplyr::mutate(GESPRG5E = as.factor(.data$GESPRG5E))
}
# GESPRG5M
if("GESPRG5M" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG5M = dplyr::case_match(
.data$GESPRG5M,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG5M
)
) %>%
dplyr::mutate(GESPRG5M = as.factor(.data$GESPRG5M))
}
# GESPRG6E
if("GESPRG6E" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG6E = dplyr::case_match(
.data$GESPRG6E,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG6E
)
) %>%
dplyr::mutate(GESPRG6E = as.factor(.data$GESPRG6E))
}
# GESPRG6M
if("GESPRG6M" %in% variables_names){
data <- data %>%
dplyr::mutate(
GESPRG6M = dplyr::case_match(
.data$GESPRG6M,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$GESPRG6M
)
) %>%
dplyr::mutate(GESPRG6M = as.factor(.data$GESPRG6M))
}
# NIVATE_H
if("NIVATE_H" %in% variables_names){
data <- data %>%
dplyr::mutate(
NIVATE_H = dplyr::case_match(
.data$NIVATE_H,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$NIVATE_H
)
) %>%
dplyr::mutate(NIVATE_H = as.factor(.data$NIVATE_H))
}
# URGEMERG
if("URGEMERG" %in% variables_names){
data <- data %>%
dplyr::mutate(
URGEMERG = dplyr::case_match(
.data$URGEMERG,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$URGEMERG
)
) %>%
dplyr::mutate(URGEMERG = as.factor(.data$URGEMERG))
}
# ATENDAMB
if("ATENDAMB" %in% variables_names){
data <- data %>%
dplyr::mutate(
ATENDAMB = dplyr::case_match(
.data$ATENDAMB,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$ATENDAMB
)
) %>%
dplyr::mutate(ATENDAMB = as.factor(.data$ATENDAMB))
}
# CENTROBS
if("CENTROBS" %in% variables_names){
data <- data %>%
dplyr::mutate(
CENTROBS = dplyr::case_match(
.data$CENTROBS,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$CENTROBS
)
) %>%
dplyr::mutate(CENTROBS = as.factor(.data$CENTROBS))
}
# CENTRNEO
if("CENTRNEO" %in% variables_names){
data <- data %>%
dplyr::mutate(
CENTRNEO = dplyr::case_match(
.data$CENTRNEO,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$CENTRNEO
)
) %>%
dplyr::mutate(CENTRNEO = as.factor(.data$CENTRNEO))
}
# ATENDHOS
if("ATENDHOS" %in% variables_names){
data <- data %>%
dplyr::mutate(
ATENDHOS = dplyr::case_match(
.data$ATENDHOS,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$ATENDHOS
)
) %>%
dplyr::mutate(ATENDHOS = as.factor(.data$ATENDHOS))
}
# SERAP01P
if("SERAP01P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP01P = dplyr::case_match(
.data$SERAP01P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP01P
)
) %>%
dplyr::mutate(SERAP01P = as.factor(.data$SERAP01P))
}
# SERAP01T
if("SERAP01T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP01T = dplyr::case_match(
.data$SERAP01T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP01T
)
) %>%
dplyr::mutate(SERAP01T = as.factor(.data$SERAP01T))
}
# SERAP02P
if("SERAP02P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP02P = dplyr::case_match(
.data$SERAP02P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP02P
)
) %>%
dplyr::mutate(SERAP02P = as.factor(.data$SERAP02P))
}
# SERAP02T
if("SERAP02T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP02T = dplyr::case_match(
.data$SERAP02T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP02T
)
) %>%
dplyr::mutate(SERAP02T = as.factor(.data$SERAP02T))
}
# SERAP03P
if("SERAP03P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP03P = dplyr::case_match(
.data$SERAP03P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP03P
)
) %>%
dplyr::mutate(SERAP03P = as.factor(.data$SERAP03P))
}
# SERAP03T
if("SERAP03T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP03T = dplyr::case_match(
.data$SERAP03T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP03T
)
) %>%
dplyr::mutate(SERAP03T = as.factor(.data$SERAP03T))
}
# SERAP04P
if("SERAP04P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP04P = dplyr::case_match(
.data$SERAP04P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP04P
)
) %>%
dplyr::mutate(SERAP04P = as.factor(.data$SERAP04P))
}
# SERAP04T
if("SERAP04T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP04T = dplyr::case_match(
.data$SERAP04T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP04T
)
) %>%
dplyr::mutate(SERAP04T = as.factor(.data$SERAP04T))
}
# SERAP05P
if("SERAP05P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP05P = dplyr::case_match(
.data$SERAP05P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP05P
)
) %>%
dplyr::mutate(SERAP05P = as.factor(.data$SERAP05P))
}
# SERAP05T
if("SERAP05T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP05T = dplyr::case_match(
.data$SERAP05T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP05T
)
) %>%
dplyr::mutate(SERAP05T = as.factor(.data$SERAP05T))
}
# SERAP06P
if("SERAP06P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP06P = dplyr::case_match(
.data$SERAP06P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP06P
)
) %>%
dplyr::mutate(SERAP06P = as.factor(.data$SERAP06P))
}
# SERAP06T
if("SERAP06T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP06T = dplyr::case_match(
.data$SERAP06T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP06T
)
) %>%
dplyr::mutate(SERAP06T = as.factor(.data$SERAP06T))
}
# SERAP07P
if("SERAP07P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP07P = dplyr::case_match(
.data$SERAP07P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP07P
)
) %>%
dplyr::mutate(SERAP07P = as.factor(.data$SERAP07P))
}
# SERAP07T
if("SERAP07T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP07T = dplyr::case_match(
.data$SERAP07T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP07T
)
) %>%
dplyr::mutate(SERAP07T = as.factor(.data$SERAP07T))
}
# SERAP08P
if("SERAP08P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP08P = dplyr::case_match(
.data$SERAP08P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP08P
)
) %>%
dplyr::mutate(SERAP08P = as.factor(.data$SERAP08P))
}
# SERAP08T
if("SERAP08T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP08T = dplyr::case_match(
.data$SERAP08T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP08T
)
) %>%
dplyr::mutate(SERAP08T = as.factor(.data$SERAP08T))
}
# SERAP09P
if("SERAP09P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP09P = dplyr::case_match(
.data$SERAP09P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP09P
)
) %>%
dplyr::mutate(SERAP09P = as.factor(.data$SERAP09P))
}
# SERAP09T
if("SERAP09T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP09T = dplyr::case_match(
.data$SERAP09T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP09T
)
) %>%
dplyr::mutate(SERAP09T = as.factor(.data$SERAP09T))
}
# SERAP10P
if("SERAP10P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP10P = dplyr::case_match(
.data$SERAP10P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP10P
)
) %>%
dplyr::mutate(SERAP10P = as.factor(.data$SERAP10P))
}
# SERAP10T
if("SERAP10T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP10T = dplyr::case_match(
.data$SERAP10T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP10T
)
) %>%
dplyr::mutate(SERAP10T = as.factor(.data$SERAP10T))
}
# SERAP11P
if("SERAP11P" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP11P = dplyr::case_match(
.data$SERAP11P,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP11P
)
) %>%
dplyr::mutate(SERAP11P = as.factor(.data$SERAP11P))
}
# SERAP11T
if("SERAP11T" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAP11T = dplyr::case_match(
.data$SERAP11T,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAP11T
)
) %>%
dplyr::mutate(SERAP11T = as.factor(.data$SERAP11T))
}
# SERAPOIO
if("SERAPOIO" %in% variables_names){
data <- data %>%
dplyr::mutate(
SERAPOIO = dplyr::case_match(
.data$SERAPOIO,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$SERAPOIO
)
) %>%
dplyr::mutate(SERAPOIO = as.factor(.data$SERAPOIO))
}
# RES_BIOL
if("RES_BIOL" %in% variables_names){
data <- data %>%
dplyr::mutate(
RES_BIOL = dplyr::case_match(
.data$RES_BIOL,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$RES_BIOL
)
) %>%
dplyr::mutate(RES_BIOL = as.factor(.data$RES_BIOL))
}
# RES_QUIM
if("RES_QUIM" %in% variables_names){
data <- data %>%
dplyr::mutate(
RES_QUIM = dplyr::case_match(
.data$RES_QUIM,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$RES_QUIM
)
) %>%
dplyr::mutate(RES_QUIM = as.factor(.data$RES_QUIM))
}
# RES_RADI
if("RES_RADI" %in% variables_names){
data <- data %>%
dplyr::mutate(
RES_RADI = dplyr::case_match(
.data$RES_RADI,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$RES_RADI
)
) %>%
dplyr::mutate(RES_RADI = as.factor(.data$RES_RADI))
}
# RES_COMU
if("RES_COMU" %in% variables_names){
data <- data %>%
dplyr::mutate(
RES_COMU = dplyr::case_match(
.data$RES_COMU,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$RES_COMU
)
) %>%
dplyr::mutate(RES_COMU = as.factor(.data$RES_COMU))
}
# COLETRES
if("COLETRES" %in% variables_names){
data <- data %>%
dplyr::mutate(
COLETRES = dplyr::case_match(
.data$COLETRES,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COLETRES
)
) %>%
dplyr::mutate(COLETRES = as.factor(.data$COLETRES))
}
# COMISS01
if("COMISS01" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS01 = dplyr::case_match(
.data$COMISS01,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS01
)
) %>%
dplyr::mutate(COMISS01 = as.factor(.data$COMISS01))
}
# COMISS02
if("COMISS02" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS02 = dplyr::case_match(
.data$COMISS02,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS02
)
) %>%
dplyr::mutate(COMISS02 = as.factor(.data$COMISS02))
}
# COMISS03
if("COMISS03" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS03 = dplyr::case_match(
.data$COMISS03,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS03
)
) %>%
dplyr::mutate(COMISS03 = as.factor(.data$COMISS03))
}
# COMISS04
if("COMISS04" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS04 = dplyr::case_match(
.data$COMISS04,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS04
)
) %>%
dplyr::mutate(COMISS04 = as.factor(.data$COMISS04))
}
# COMISS05
if("COMISS05" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS05 = dplyr::case_match(
.data$COMISS05,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS05
)
) %>%
dplyr::mutate(COMISS05 = as.factor(.data$COMISS05))
}
# COMISS06
if("COMISS06" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS06 = dplyr::case_match(
.data$COMISS06,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS06
)
) %>%
dplyr::mutate(COMISS06 = as.factor(.data$COMISS06))
}
# COMISS07
if("COMISS07" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS07 = dplyr::case_match(
.data$COMISS07,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS07
)
) %>%
dplyr::mutate(COMISS07 = as.factor(.data$COMISS07))
}
# COMISS08
if("COMISS08" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS08 = dplyr::case_match(
.data$COMISS08,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS08
)
) %>%
dplyr::mutate(COMISS08 = as.factor(.data$COMISS08))
}
# COMISS09
if("COMISS09" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS09 = dplyr::case_match(
.data$COMISS09,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS09
)
) %>%
dplyr::mutate(COMISS09 = as.factor(.data$COMISS09))
}
# COMISS10
if("COMISS10" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS10 = dplyr::case_match(
.data$COMISS10,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS10
)
) %>%
dplyr::mutate(COMISS10 = as.factor(.data$COMISS10))
}
# COMISS11
if("COMISS11" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS11 = dplyr::case_match(
.data$COMISS11,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS11
)
) %>%
dplyr::mutate(COMISS11 = as.factor(.data$COMISS11))
}
# COMISS12
if("COMISS12" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISS12 = dplyr::case_match(
.data$COMISS12,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISS12
)
) %>%
dplyr::mutate(COMISS12 = as.factor(.data$COMISS12))
}
# COMISSAO
if("COMISSAO" %in% variables_names){
data <- data %>%
dplyr::mutate(
COMISSAO = dplyr::case_match(
.data$COMISSAO,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$COMISSAO
)
) %>%
dplyr::mutate(COMISSAO = as.factor(.data$COMISSAO))
}
# AP01CV01
if("AP01CV01" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP01CV01 = dplyr::case_match(
.data$AP01CV01,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP01CV01
)
) %>%
dplyr::mutate(AP01CV01 = as.factor(.data$AP01CV01))
}
# AP01CV02
if("AP01CV02" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP01CV02 = dplyr::case_match(
.data$AP01CV02,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP01CV02
)
) %>%
dplyr::mutate(AP01CV02 = as.factor(.data$AP01CV02))
}
# AP01CV05
if("AP01CV05" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP01CV05 = dplyr::case_match(
.data$AP01CV05,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP01CV05
)
) %>%
dplyr::mutate(AP01CV05 = as.factor(.data$AP01CV05))
}
# AP01CV06
if("AP01CV06" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP01CV06 = dplyr::case_match(
.data$AP01CV06,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP01CV06
)
) %>%
dplyr::mutate(AP01CV06 = as.factor(.data$AP01CV06))
}
# AP01CV03
if("AP01CV03" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP01CV03 = dplyr::case_match(
.data$AP01CV03,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP01CV03
)
) %>%
dplyr::mutate(AP01CV03 = as.factor(.data$AP01CV03))
}
# AP01CV04
if("AP01CV04" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP01CV04 = dplyr::case_match(
.data$AP01CV04,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP01CV04
)
) %>%
dplyr::mutate(AP01CV04 = as.factor(.data$AP01CV04))
}
# AP02CV01
if("AP02CV01" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP02CV01 = dplyr::case_match(
.data$AP02CV01,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP02CV01
)
) %>%
dplyr::mutate(AP02CV01 = as.factor(.data$AP02CV01))
}
# AP02CV02
if("AP02CV02" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP02CV02 = dplyr::case_match(
.data$AP02CV02,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP02CV02
)
) %>%
dplyr::mutate(AP02CV02 = as.factor(.data$AP02CV02))
}
# AP02CV05
if("AP02CV05" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP02CV05 = dplyr::case_match(
.data$AP02CV05,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP02CV05
)
) %>%
dplyr::mutate(AP02CV05 = as.factor(.data$AP02CV05))
}
# AP02CV06
if("AP02CV06" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP02CV06 = dplyr::case_match(
.data$AP02CV06,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP02CV06
)
) %>%
dplyr::mutate(AP02CV06 = as.factor(.data$AP02CV06))
}
# AP02CV03
if("AP02CV03" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP02CV03 = dplyr::case_match(
.data$AP02CV03,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP02CV03
)
) %>%
dplyr::mutate(AP02CV03 = as.factor(.data$AP02CV03))
}
# AP02CV04
if("AP02CV04" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP02CV04 = dplyr::case_match(
.data$AP02CV04,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP02CV04
)
) %>%
dplyr::mutate(AP02CV04 = as.factor(.data$AP02CV04))
}
# AP03CV01
if("AP03CV01" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP03CV01 = dplyr::case_match(
.data$AP03CV01,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP03CV01
)
) %>%
dplyr::mutate(AP03CV01 = as.factor(.data$AP03CV01))
}
# AP03CV02
if("AP03CV02" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP03CV02 = dplyr::case_match(
.data$AP03CV02,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP03CV02
)
) %>%
dplyr::mutate(AP03CV02 = as.factor(.data$AP03CV02))
}
# AP03CV05
if("AP03CV05" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP03CV05 = dplyr::case_match(
.data$AP03CV05,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP03CV05
)
) %>%
dplyr::mutate(AP03CV05 = as.factor(.data$AP03CV05))
}
# AP03CV06
if("AP03CV06" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP03CV06 = dplyr::case_match(
.data$AP03CV06,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP03CV06
)
) %>%
dplyr::mutate(AP03CV06 = as.factor(.data$AP03CV06))
}
# AP03CV03
if("AP03CV03" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP03CV03 = dplyr::case_match(
.data$AP03CV03,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP03CV03
)
) %>%
dplyr::mutate(AP03CV03 = as.factor(.data$AP03CV03))
}
# AP03CV04
if("AP03CV04" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP03CV04 = dplyr::case_match(
.data$AP03CV04,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP03CV04
)
) %>%
dplyr::mutate(AP03CV04 = as.factor(.data$AP03CV04))
}
# AP04CV01
if("AP04CV01" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP04CV01 = dplyr::case_match(
.data$AP04CV01,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP04CV01
)
) %>%
dplyr::mutate(AP04CV01 = as.factor(.data$AP04CV01))
}
# AP04CV02
if("AP04CV02" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP04CV02 = dplyr::case_match(
.data$AP04CV02,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP04CV02
)
) %>%
dplyr::mutate(AP04CV02 = as.factor(.data$AP04CV02))
}
# AP04CV05
if("AP04CV05" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP04CV05 = dplyr::case_match(
.data$AP04CV05,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP04CV05
)
) %>%
dplyr::mutate(AP04CV05 = as.factor(.data$AP04CV05))
}
# AP04CV06
if("AP04CV06" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP04CV06 = dplyr::case_match(
.data$AP04CV06,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP04CV06
)
) %>%
dplyr::mutate(AP04CV06 = as.factor(.data$AP04CV06))
}
# AP04CV03
if("AP04CV03" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP04CV03 = dplyr::case_match(
.data$AP04CV03,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP04CV03
)
) %>%
dplyr::mutate(AP04CV03 = as.factor(.data$AP04CV03))
}
# AP04CV04
if("AP04CV04" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP04CV04 = dplyr::case_match(
.data$AP04CV04,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP04CV04
)
) %>%
dplyr::mutate(AP04CV04 = as.factor(.data$AP04CV04))
}
# AP05CV01
if("AP05CV01" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP05CV01 = dplyr::case_match(
.data$AP05CV01,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP05CV01
)
) %>%
dplyr::mutate(AP05CV01 = as.factor(.data$AP05CV01))
}
# AP05CV02
if("AP05CV02" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP05CV02 = dplyr::case_match(
.data$AP05CV02,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP05CV02
)
) %>%
dplyr::mutate(AP05CV02 = as.factor(.data$AP05CV02))
}
# AP05CV05
if("AP05CV05" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP05CV05 = dplyr::case_match(
.data$AP05CV05,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP05CV05
)
) %>%
dplyr::mutate(AP05CV05 = as.factor(.data$AP05CV05))
}
# AP05CV06
if("AP05CV06" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP05CV06 = dplyr::case_match(
.data$AP05CV06,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP05CV06
)
) %>%
dplyr::mutate(AP05CV06 = as.factor(.data$AP05CV06))
}
# AP05CV03
if("AP05CV03" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP05CV03 = dplyr::case_match(
.data$AP05CV03,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP05CV03
)
) %>%
dplyr::mutate(AP05CV03 = as.factor(.data$AP05CV03))
}
# AP05CV04
if("AP05CV04" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP05CV04 = dplyr::case_match(
.data$AP05CV04,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP05CV04
)
) %>%
dplyr::mutate(AP05CV04 = as.factor(.data$AP05CV04))
}
# AP06CV01
if("AP06CV01" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP06CV01 = dplyr::case_match(
.data$AP06CV01,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP06CV01
)
) %>%
dplyr::mutate(AP06CV01 = as.factor(.data$AP06CV01))
}
# AP06CV02
if("AP06CV02" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP06CV02 = dplyr::case_match(
.data$AP06CV02,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP06CV02
)
) %>%
dplyr::mutate(AP06CV02 = as.factor(.data$AP06CV02))
}
# AP06CV05
if("AP06CV05" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP06CV05 = dplyr::case_match(
.data$AP06CV05,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP06CV05
)
) %>%
dplyr::mutate(AP06CV05 = as.factor(.data$AP06CV05))
}
# AP06CV06
if("AP06CV06" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP06CV06 = dplyr::case_match(
.data$AP06CV06,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP06CV06
)
) %>%
dplyr::mutate(AP06CV06 = as.factor(.data$AP06CV06))
}
# AP06CV03
if("AP06CV03" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP06CV03 = dplyr::case_match(
.data$AP06CV03,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP06CV03
)
) %>%
dplyr::mutate(AP06CV03 = as.factor(.data$AP06CV03))
}
# AP06CV04
if("AP06CV04" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP06CV04 = dplyr::case_match(
.data$AP06CV04,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP06CV04
)
) %>%
dplyr::mutate(AP06CV04 = as.factor(.data$AP06CV04))
}
# AP07CV01
if("AP07CV01" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP07CV01 = dplyr::case_match(
.data$AP07CV01,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP07CV01
)
) %>%
dplyr::mutate(AP07CV01 = as.factor(.data$AP07CV01))
}
# AP07CV02
if("AP07CV02" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP07CV02 = dplyr::case_match(
.data$AP07CV02,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP07CV02
)
) %>%
dplyr::mutate(AP07CV02 = as.factor(.data$AP07CV02))
}
# AP07CV05
if("AP07CV05" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP07CV05 = dplyr::case_match(
.data$AP07CV05,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP07CV05
)
) %>%
dplyr::mutate(AP07CV05 = as.factor(.data$AP07CV05))
}
# AP07CV06
if("AP07CV06" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP07CV06 = dplyr::case_match(
.data$AP07CV06,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP07CV06
)
) %>%
dplyr::mutate(AP07CV06 = as.factor(.data$AP07CV06))
}
# AP07CV03
if("AP07CV03" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP07CV03 = dplyr::case_match(
.data$AP07CV03,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP07CV03
)
) %>%
dplyr::mutate(AP07CV03 = as.factor(.data$AP07CV03))
}
# AP07CV04
if("AP07CV04" %in% variables_names){
data <- data %>%
dplyr::mutate(
AP07CV04 = dplyr::case_match(
.data$AP07CV04,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$AP07CV04
)
) %>%
dplyr::mutate(AP07CV04 = as.factor(.data$AP07CV04))
}
# ATEND_PR
if("ATEND_PR" %in% variables_names){
data <- data %>%
dplyr::mutate(
ATEND_PR = dplyr::case_match(
.data$ATEND_PR,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$ATEND_PR
)
) %>%
dplyr::mutate(ATEND_PR = as.factor(.data$ATEND_PR))
}
} else if(information_system == "CNES-PF"){
# CNES
if("CNES" %in% variables_names){
data <- data %>%
dplyr::mutate(CNES = as.character(.data$CNES))
}
# UFMUNRES
if ("UFMUNRES" %in% variables_names & municipality_data == TRUE) {
colnames(tabMun)[5] <- "UFMUNRES"
tabMun$UFMUNRES <- as.character(tabMun$UFMUNRES)
data <- data %>%
dplyr::left_join(tabMun, by = "UFMUNRES")
}
# REGSAUDE
if("REGSAUDE" %in% variables_names){
data <- data %>%
dplyr::mutate(REGSAUDE = as.character(.data$REGSAUDE))
}
# MICR_REG
if("MICR_REG" %in% variables_names){
data <- data %>%
dplyr::mutate(MICR_REG = as.integer(.data$MICR_REG))
}
# DISTRSAN
if("DISTRSAN" %in% variables_names){
data <- data %>%
dplyr::mutate(DISTRSAN = as.integer(.data$DISTRSAN))
}
# DISTRADM
if("DISTRADM" %in% variables_names){
data <- data %>%
dplyr::mutate(DISTRADM = as.integer(.data$DISTRADM))
}
# TPGESTAO
if("TPGESTAO" %in% variables_names){
data <- data %>%
dplyr::mutate(
TPGESTAO = dplyr::case_match(
.data$TPGESTAO,
"D" ~ "Dupla",
"E" ~ "Estadual",
"M" ~ "Municipal",
"Z" ~ "Sem gest\u00e3o",
"S" ~ "Sem gest\u00e3o",
.default = .data$TPGESTAO
)
) %>%
dplyr::mutate(TPGESTAO = as.factor(.data$TPGESTAO))
}
# PF_PJ
if("PF_PJ" %in% variables_names){
data <- data %>%
dplyr::mutate(
PF_PJ = dplyr::case_match(
.data$PF_PJ,
"1" ~ "Pessoa f\u00edsica",
"3" ~ "Pessoa jur\u00eddica",
.default = .data$PF_PJ
)
) %>%
dplyr::mutate(PF_PJ = as.factor(.data$PF_PJ))
}
# CPF_CNPJ
if("CPF_CNPJ" %in% variables_names){
data <- data %>%
dplyr::mutate(CPF_CNPJ = as.numeric(.data$CPF_CNPJ))
}
# NIV_DEP
if("NIV_DEP" %in% variables_names){
data <- data %>%
dplyr::mutate(
NIV_DEP = dplyr::case_match(
.data$NIV_DEP,
"1" ~ "Individual",
"3" ~ "Mantida",
.default = .data$NIV_DEP
)
) %>%
dplyr::mutate(NIV_DEP = as.factor(.data$NIV_DEP))
}
# CNPJ_MAN
if("CNPJ_MAN" %in% variables_names){
data <- data %>%
dplyr::mutate(CNPJ_MAN = as.numeric(.data$CNPJ_MAN))
}
# ESFERA_A
if("ESFERA_A" %in% variables_names){
data <- data %>%
dplyr::mutate(
ESFERA_A = dplyr::case_match(
.data$ESFERA_A,
"-99" ~ NA,
"1" ~ "Federal",
"2" ~ "Estadual",
"3" ~ "Municipal",
"4" ~ "Privada",
.default = .data$ESFERA_A
)
) %>%
dplyr::mutate(ESFERA_A = as.factor(.data$ESFERA_A))
}
# ATIVIDAD
if("ATIVIDAD" %in% variables_names){
data <- data %>%
dplyr::mutate(
ATIVIDAD = dplyr::case_match(
.data$ATIVIDAD,
"-99" ~ NA,
"1" ~ "Unidade Universit\u00e1ria",
"2" ~ "Unidade Escola Superior Isolada",
"3" ~ "Unidade Auxiliar de Ensino",
"4" ~ "Unidade sem atividade de Ensino",
"5" ~ "Hospital de ensino",
.default = .data$ATIVIDAD
)
) %>%
dplyr::mutate(ATIVIDAD = as.factor(.data$ATIVIDAD))
}
# RETENCAO
if("RETENCAO" %in% variables_names){
data <- data %>%
dplyr::mutate(
RETENCAO = dplyr::case_match(
.data$RETENCAO,
"0" ~ NA,
"10" ~ "Estabelecimento p\u00fablico",
"11" ~ "Estabelecimento filantr\u00f3pico",
"12" ~ "Estabelecimento sem fins lucrativos",
"13" ~ "Estabelecimento privado luvrativa simples",
"14" ~ "Estabelecimento privado luvrativa",
"15" ~ "Estabelecimento sindical",
"16" ~ "Estabelecimento pessoa f\u00edsica",
.default = .data$RETENCAO
)
) %>%
dplyr::mutate(RETENCAO = as.factor(.data$RETENCAO))
}
# NATUREZA
if("NATUREZA" %in% variables_names){
data <- data %>%
dplyr::mutate(
NATUREZA = dplyr::case_match(
.data$NATUREZA,
"-99" ~ NA,
"1" ~ "Administra\u00e7\u00e3o Direta da Sa\u00fade (MS, SES, e SMS)",
"2" ~ "Adm Direta outros org\u00e3os (MEX, MEx, Marinha,...)",
"3" ~ "Adm Indireta - Autarquias",
"4" ~ "Adm Indireta - Funda\u00e7\u00e3o P\u00fablica",
"5" ~ "Adm Indireta - Empresa P\u00fablica",
"6" ~ "Adm Indireta - Organiza\u00e7\u00e3o Social P\u00fablica",
"7" ~ "Empresa Privada",
"8" ~ "Funda\u00e7\u00e3o Privada",
"9" ~ "Cooperativa",
"10" ~ "Servi\u00e7o Social Aut\u00f4nomo",
"11" ~ "Entidade Beneficente sem fins lucrativos",
"12" ~ "Economia Mista",
"13" ~ "Sindicato",
"0" ~ "Natureza inexistente",
.default = .data$NATUREZA
)
) %>%
dplyr::mutate(NATUREZA = as.factor(.data$NATUREZA))
}
# CLIENTEL
if("CLIENTEL" %in% variables_names){
data <- data %>%
dplyr::mutate(
CLIENTEL = dplyr::case_match(
.data$CLIENTEL,
"-99" ~ NA,
"1" ~ "Atendimento de demanda espont\u00e2nea",
"2" ~ "Atendimento de demanda referenciada",
"3" ~ "Atendimento de demanda espont\u00e2nea e referenciada",
"0" ~ "Fluxo de Clientela n\u00e3o exigido",
.default = .data$CLIENTEL
)
) %>%
dplyr::mutate(CLIENTEL = as.factor(.data$CLIENTEL))
}
# TP_UNID
if("TP_UNID" %in% variables_names){
data <- data %>%
dplyr::mutate(
TP_UNID = dplyr::case_match(
.data$TP_UNID,
"1" ~ "Posto de sa\u00fade",
"2" ~ "Centro de sa\u00fade / Unidade b\u00e1sica",
"4" ~ "Policl\u00ednica",
"5" ~ "Hospital geral",
"7" ~ "Hospital Especializado",
"9" ~ "Pronto socorro de hospital geral (antigo)",
"12" ~ "Pronto socorro traumato-ortop\u00e9dico (antigo)",
"15" ~ "Unidade mista",
"20" ~ "Pronto socorro geral",
"21" ~ "Pronto socorro especializado",
"22" ~ "Consult\u00f3rio isolado",
"32" ~ "Unidade m\u00f3vel fluvial",
"36" ~ "Cl\u00ednica / Centro de sa\u00fade de especialidade",
"39" ~ "Unidade de apoio diagnose e terapia (SADT isolado)",
"40" ~ "Unidade m\u00f3vel terrestre",
"42" ~ "Unidade m\u00f3vel de n\u00edvel pr\u00e9-hospitalar na \u00e1rea de urg\u00eancia",
"43" ~ "Farm\u00e1cia",
"45" ~ "Unidade de sa\u00fade da fam\u00edlia",
"50" ~ "Unidade de vigil\u00e2ncia em sa\u00fade",
"60" ~ "Cooperativa ou empresa de cess\u00e3o de trabalhadores na sa\u00fade",
"61" ~ "Centro de parto normal - isolado",
"62" ~ "Hospital / Dia - Isolado",
"63" ~ "Unidade autorizadora",
"64" ~ "Central de regula\u00e7\u00e3o de servi\u00e7os de sa\u00fade",
"65" ~ "Unidade de vigil\u00e2ncia epidemiol\u00f3gica (antigo)",
"66" ~ "Unidade de vigil\u00e2ncia sanit\u00e1ria (antigo)",
"67" ~ "Laborat\u00f3rio central de sa\u00fade p\u00fablica LACEN",
"68" ~ "Central de gest\u00e3o em sa\u00fade",
"69" ~ "Centro de aten\u00e7\u00e3o hemoterapia e/ou hematologica",
"70" ~ "Centro de aten\u00e7\u00e3o psicosocial",
"71" ~ "Centro de apoio a sa\u00fade da fam\u00edlia",
"72" ~ "Unidade de aten\u00e7\u00e3o a sa\u00fade ind\u00edgena",
"73" ~ "Pronto atendimento",
"74" ~ "P\u00f3lo academia da sa\u00fade",
"75" ~ "Telessa\u00fade",
"76" ~ "Central de regula\u00e7\u00e3o m\u00e9dica das urg\u00eancias",
"77" ~ "Servi\u00e7o de aten\u00e7\u00e3o domiciliar isolado (Home care)",
"78" ~ "Unidade de aten\u00e7\u00e3o em regime residencial",
"79" ~ "Oficina ortop\u00e9dica",
"80" ~ "Laborat\u00f3rio de sa\u00fade p\u00fablica",
"81" ~ "Central de regula\u00e7\u00e3o do acesso",
"82" ~ "Central de notifica\u00e7\u00e3o, capta\u00e7\u00e3o e distribui\u00e7\u00e3o de \u00f3rg\u00e3os estadual",
"83" ~ "P\u00f3lo de preven\u00e7\u00e3o de doen\u00e7as e agravos e promo\u00e7\u00e3o da sa\u00fade",
.default = .data$TP_UNID
)
) %>%
dplyr::mutate(TP_UNID = as.factor(.data$TP_UNID))
}
# TURNO_AT
if("TURNO_AT" %in% variables_names){
data <- data %>%
dplyr::mutate(
TURNO_AT = dplyr::case_match(
.data$TURNO_AT,
"-99" ~ NA,
"1" ~ "Turnos intermitentes",
"2" ~ "Cont\u00ednuo 24h/dia (Pl Sab Dom Fer)",
"3" ~ "Manh\u00e3 / Tarde / Noite",
"4" ~ "Manh\u00e3",
"5" ~ "Tarde",
"6" ~ "Manh\u00e3 / Tarde",
"7" ~ "Noite",
.default = .data$TURNO_AT
)
) %>%
dplyr::mutate(TURNO_AT = as.factor(.data$TURNO_AT))
}
# NIV_HIER
if("NIV_HIER" %in% variables_names){
data <- data %>%
dplyr::mutate(
NIV_HIER = dplyr::case_match(
.data$NIV_HIER,
"-99" ~ NA,
"99" ~ NA,
"0" ~ NA,
"1"~ "PAB-PABA",
"2"~ "M\u00e9dia M1",
"3"~ "M\u00e9dia M2 e M3",
"4"~ "Alta complexidade ambulatorial",
"5"~ "Baixa M1 e M2",
"6"~ "M\u00e9dia M2 e M3",
"7"~ "M\u00e9dia M3",
"8"~ "Alta complexidade hospitalar / ambulatorial",
.default = .data$NIV_HIER
)
) %>%
dplyr::mutate(NIV_HIER = as.factor(.data$NIV_HIER))
}
# TERCEIRO
if("TERCEIRO" %in% variables_names){
data <- data %>%
dplyr::mutate(
TERCEIRO = dplyr::case_match(
.data$TERCEIRO,
"1" ~ "Sim",
"0" ~ "N\u00e3o",
"2" ~ "N\u00e3o",
.default = .data$TERCEIRO
)
) %>%
dplyr::mutate(TERCEIRO = as.factor(.data$TERCEIRO))
}
# CPF_PROF
if("CPF_PROF" %in% variables_names){
data <- data %>%
dplyr::mutate(
CPF_PROF = dplyr::case_match(
.data$CPF_PROF,
"99999999999" ~ NA,
"00000000000000" ~ NA,
.default = .data$CPF_PROF
)
) %>%
dplyr::mutate(CPF_PROF = as.factor(.data$CPF_PROF))
}
# CBO
if ("CBO" %in% variables_names) {
data <- data %>%
dplyr::mutate(CBO = as.character(.data$CBO)) %>%
dplyr::left_join(microdatasus::tabCBO, by = c("CBO" = "cod"))
}
# NOMEPROF
if("NOMEPROF" %in% variables_names){
data <- data %>%
dplyr::mutate(NOMEPROF = as.character(.data$NOMEPROF))
}
# VINCULAC
if("VINCULAC" %in% variables_names){
data <- data %>%
dplyr::mutate(
VINCULAC = dplyr::case_match(
.data$VINCULAC,
"1" ~ "Profissional CONTRATADO",
"2" ~ "Profissional AUT\u00d4NOMO",
"3" ~ "Profissional V\u00cdNCULO N\u00c3O IDENTIFICADO",
.default = .data$VINCULAC
)
) %>%
dplyr::mutate(VINCULAC = as.factor(.data$VINCULAC))
}
# NAT_JUR
if("NAT_JUR" %in% variables_names){
data <- data %>%
dplyr::mutate(
NAT_JUR = dplyr::case_match(
.data$NAT_JUR,
"0" ~ NA,
"1000" ~ "Administra\u00e7\u00e3o P\u00fablica",
"1015" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Executivo Federal",
"1023" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Executivo Estadual ou do Distrito Federal",
"1031" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Executivo Municipal",
"1040" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Legislativo Federal",
"1058" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Legislativo Estadual ou do Distrito Federal",
"1066" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Legislativo Municipal",
"1074" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Judici\u00e1rio Federal",
"1082" ~ "\u00d3rg\u00e3o P\u00fablico do Poder Judici\u00e1rio Estadual",
"1104" ~ "Autarquia Federal",
"1112" ~ "Autarquia Estadual ou do Distrito Federal",
"1120" ~ "Autarquia Municipal",
"1139" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito P\u00fablico Federal",
"1147" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito P\u00fablico Estadual ou do Distrito Federal",
"1155" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito P\u00fablico Municipal",
"1163" ~ "\u00d3rg\u00e3o P\u00fablico Aut\u00f4nomo Federal",
"1171" ~ "\u00d3rg\u00e3o P\u00fablico Aut\u00f4nomo Estadual ou do Distrito Federal",
"1180" ~ "\u00d3rg\u00e3o P\u00fablico Aut\u00f4nomo Municipal",
"1198" ~ "Comiss\u00e3o Polinacional",
"1201" ~ "Fundo P\u00fablico",
"1210" ~ "Cons\u00f3rcio P\u00fablico de Direito P\u00fablico (Associa\u00e7\u00e3o P\u00fablica)",
"1228" ~ "Cons\u00f3rcio P\u00fablico de Direito Privado",
"1236" ~ "Estado ou Distrito Federal",
"1244" ~ "Munic\u00edpio",
"1252" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito Privado Federal",
"1260" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito Privado Estadual ou do Distrito Federal",
"1279" ~ "Funda\u00e7\u00e3o P\u00fablica de Direito Privado Municipal",
"2000" ~ "Entidades Empresariais",
"2001" ~ "Empresa P\u00fablica",
"2038" ~ "Sociedade de Economia Mista",
"2046" ~ "Sociedade An\u00f4nima Aberta",
"2054" ~ "Sociedade An\u00f4nima Fechada",
"2062" ~ "Sociedade Empres\u00e1ria Limitada",
"2070" ~ "Sociedade Empres\u00e1ria em Nome Coletivo",
"2089" ~ "Sociedade Empres\u00e1ria em Comandita Simples",
"2097" ~ "Sociedade Empres\u00e1ria em Comandita por A\u00e7\u00f5es",
"2127" ~ "Sociedade em Conta de Participa\u00e7\u00e3o",
"2135" ~ "Empres\u00e1rio (Individual)",
"2143" ~ "Cooperativa",
"2151" ~ "Cons\u00f3rcio de Sociedades",
"2160" ~ "Grupo de Sociedades",
"2178" ~ "Estabelecimento, no Brasil, de Sociedade Estrangeira",
"2194" ~ "Estabelecimento, no Brasil, de Empresa Binacional Argentino-Brasileira",
"2216" ~ "Empresa Domiciliada no Exterior",
"2224" ~ "Clube/Fundo de Investimento",
"2232" ~ "Sociedade Simples Pura",
"2240" ~ "Sociedade Simples Limitada",
"2259" ~ "Sociedade Simples em Nome Coletivo",
"2267" ~ "Sociedade Simples em Comandita Simples",
"2275" ~ "Empresa Binacional",
"2283" ~ "Cons\u00f3rcio de Empregadores",
"2291" ~ "Cons\u00f3rcio Simples",
"2305" ~ "Empresa Individual de Responsabilidade Limitada (de Natureza Empres\u00e1ria)",
"2313" ~ "Empresa Individual de Responsabilidade Limitada (de Natureza Simples)",
"2321" ~ "Sociedade Unipessoal de Advogados",
"2330" ~ "Cooperativas de Consumo",
"3000" ~ "Entidades sem Fins Lucrativos",
"3034" ~ "Servi\u00e7o Notarial e Registral (Cart\u00f3rio)",
"3069" ~ "Funda\u00e7\u00e3o Privada",
"3077" ~ "Servi\u00e7o Social Aut\u00f4nomo",
"3085" ~ "Condom\u00ednio Edil\u00edcio",
"3107" ~ "Comiss\u00e3o de Concilia\u00e7\u00e3o Pr\u00e9via",
"3115" ~ "Entidade de Media\u00e7\u00e3o e Arbitragem",
"3131" ~ "Entidade Sindical",
"3204" ~ "Estabelecimento, no Brasil, de Funda\u00e7\u00e3o ou Associa\u00e7\u00e3o Estrangeiras",
"3212" ~ "Funda\u00e7\u00e3o ou Associa\u00e7\u00e3o Domiciliada no Exterior",
"3220" ~ "Organiza\u00e7\u00e3o Religiosa",
"3239" ~ "Comunidade Ind\u00edgena",
"3247" ~ "Fundo Privado",
"3255" ~ "\u00d3rg\u00e3o de Dire\u00e7\u00e3o Nacional de Partido Pol\u00edtico",
"3263" ~ "\u00d3rg\u00e3o de Dire\u00e7\u00e3o Regional de Partido Pol\u00edtico",
"3271" ~ "\u00d3rg\u00e3o de Dire\u00e7\u00e3o Local de Partido Pol\u00edtico",
"3280" ~ "Comit\u00ea Financeiro de Partido Pol\u00edtico",
"3298" ~ "Frente Plebiscit\u00e1ria ou Referend\u00e1ria",
"3306" ~ "Organiza\u00e7\u00e3o Social (OS)",
"3310" ~ "Demais Condom\u00ednios",
"3999" ~ "Associa\u00e7\u00e3o Privada",
"4000" ~ "Pessoas F\u00edsicas",
"4014" ~ "Empresa Individual Imobili\u00e1ria",
"4022" ~ "Segurado Especial",
"4081" ~ "Contribuinte individual",
"4090" ~ "Candidato a Cargo Pol\u00edtico Eletivo",
"4111" ~ "Leiloeiro",
"4124" ~ "Produtor Rural (Pessoa F\u00edsica)",
"5000" ~ "Organiza\u00e7\u00f5es Internacionais e Outras Institui\u00e7\u00f5es Extraterritoriais",
"5010" ~ "Organiza\u00e7\u00e3o Internacional",
"5029" ~ "Representa\u00e7\u00e3o Diplom\u00e1tica Estrangeira",
"5037" ~ "Outras Institui\u00e7\u00f5es Extraterritoriais",
.default = .data$NAT_JUR
)
) %>%
dplyr::mutate(NAT_JUR = as.factor(.data$NAT_JUR))
}
}
# From data.table to tibble
data <- tibble::as_tibble(data)
# Purge levels
data <- droplevels(data)
# Unescape unicode characters
data <- suppressWarnings(tibble::as_tibble(lapply(X = data, FUN = stringi::stri_unescape_unicode)))
# Return
return(data)
}
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