PIAUÍ

##ANALISE

#Leitura dos arquivos SIVEP

## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --

## v ggplot2 3.3.5     v purrr   0.3.4
## v tibble  3.1.6     v dplyr   1.0.7
## v tidyr   1.1.3     v stringr 1.4.0
## v readr   1.4.0     v forcats 0.5.1

## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

## 
## Attaching package: 'scales'

## The following object is masked from 'package:purrr':
## 
##     discard

## The following object is masked from 'package:readr':
## 
##     col_factor

## 
## Attaching package: 'lubridate'

## The following objects are masked from 'package:base':
## 
##     date, intersect, setdiff, union

## 
## -- Column specification --------------------------------------------------------
## cols(
##   .default = col_double(),
##   DT_NOTIFIC = col_character(),
##   DT_SIN_PRI = col_character(),
##   SG_UF_NOT = col_character(),
##   ID_REGIONA = col_character(),
##   ID_MUNICIP = col_character(),
##   ID_UNIDADE = col_character(),
##   CS_SEXO = col_character(),
##   DT_NASC = col_character(),
##   ID_PAIS = col_character(),
##   SG_UF = col_character(),
##   ID_RG_RESI = col_character(),
##   ID_MN_RESI = col_character(),
##   SURTO_SG = col_logical(),
##   OUTRO_DES = col_character(),
##   OBES_IMC = col_number(),
##   MORB_DESC = col_character(),
##   DT_UT_DOSE = col_character(),
##   DT_VAC_MAE = col_character(),
##   DT_DOSEUNI = col_logical(),
##   DT_1_DOSE = col_logical()
##   # ... with 56 more columns
## )
## i Use `spec()` for the full column specifications.

## 
## -- Column specification --------------------------------------------------------
## cols(
##   .default = col_double(),
##   DT_NOTIFIC = col_character(),
##   DT_SIN_PRI = col_character(),
##   SG_UF_NOT = col_character(),
##   ID_REGIONA = col_character(),
##   ID_MUNICIP = col_character(),
##   ID_UNIDADE = col_character(),
##   CS_SEXO = col_character(),
##   DT_NASC = col_character(),
##   ID_PAIS = col_character(),
##   SG_UF = col_character(),
##   ID_RG_RESI = col_character(),
##   ID_MN_RESI = col_character(),
##   OUTRO_DES = col_character(),
##   OBES_IMC = col_character(),
##   MORB_DESC = col_character(),
##   DT_UT_DOSE = col_character(),
##   DT_VAC_MAE = col_logical(),
##   DT_DOSEUNI = col_logical(),
##   DT_1_DOSE = col_logical(),
##   DT_2_DOSE = col_logical()
##   # ... with 57 more columns
## )
## i Use `spec()` for the full column specifications.

## 
## -- Column specification --------------------------------------------------------
## cols(
##   .default = col_double(),
##   DT_NOTIFIC = col_character(),
##   DT_SIN_PRI = col_character(),
##   SG_UF_NOT = col_character(),
##   ID_REGIONA = col_character(),
##   ID_MUNICIP = col_character(),
##   ID_UNIDADE = col_character(),
##   CS_SEXO = col_character(),
##   DT_NASC = col_character(),
##   ID_PAIS = col_character(),
##   SG_UF = col_character(),
##   ID_RG_RESI = col_character(),
##   ID_MN_RESI = col_character(),
##   OUTRO_DES = col_character(),
##   FATOR_RISC = col_character(),
##   OBES_IMC = col_number(),
##   MORB_DESC = col_character(),
##   DT_UT_DOSE = col_character(),
##   DT_VAC_MAE = col_logical(),
##   DT_DOSEUNI = col_logical(),
##   DT_1_DOSE = col_character()
##   # ... with 42 more columns
## )
## i Use `spec()` for the full column specifications.

#Levantando os banco e selecionando variaveis

#Unificando os bancos

#Codificando variáveis

#Agregando dados

#Exportando o banco tratado

#Importando o banco tratado

## 
## -- Column specification --------------------------------------------------------
## cols(
##   SG_UF = col_character(),
##   EVOLUCAO = col_character(),
##   UTI = col_character(),
##   CLASSI_FIN = col_character(),
##   Mes_ANO_OBITO = col_date(format = ""),
##   Mes_ANO_INTERNA = col_date(format = ""),
##   ID_MN_RESI = col_character(),
##   CO_MUN_RES = col_double(),
##   ID_REGIONA = col_character(),
##   CO_REGIONA = col_double(),
##   ID_MUNICIP = col_character(),
##   CO_MUN_NOT = col_double(),
##   ID_UNIDADE = col_character(),
##   CO_UNI_NOT = col_double(),
##   n = col_double()
## )

#Tabela fluxo

## `summarise()` has grouped output by 'origins'. You can override using the `.groups` argument.

#Tabelas Fluxos municipios

#Fluxo externo

#Fluxo interno

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.