IVACC

tmmn v 2.0

Equipo Data Science

DataIntelligence
30-12-2021
library('DT')
library('tidyverse')
library('expss')

1 IVACC

tabla_tmmx <- readRDS("tabla_tmmx.rds")
tabla_tmmn <- readRDS("tabla_tmmn.rds")
tabla_pr <- readRDS("tabla_pr.rds")
tabla_pdsi <- readRDS("tabla_pdsi.rds")
tabla_def <- readRDS("tabla_def.rds")

Construímos los xlsx:

writexl::write_xlsx(tabla_tmmx, "tabla_tmmx.xlsx")
writexl::write_xlsx(tabla_tmmn, "tabla_tmmn.xlsx")
writexl::write_xlsx(tabla_pr, "tabla_pr.xlsx")
writexl::write_xlsx(tabla_pdsi, "tabla_pdsi.xlsx")
writexl::write_xlsx(tabla_def,"tabla_def.xlsx")
union_de_las_tablas1 <- merge(tabla_tmmx,tabla_tmmn, by = "comuna")
union_de_las_tablas1 <- merge(union_de_las_tablas1,tabla_pr, by = "comuna")
union_de_las_tablas1 <- merge(union_de_las_tablas1,tabla_pdsi, by = "comuna")
union_de_las_tablas1 <- merge(union_de_las_tablas1,tabla_def, by = "comuna")

union_de_las_tablas1$ivacc <- union_de_las_tablas1$promedios_sd.parte_del_ivacc_tmmx*0.25   + union_de_las_tablas1$promedios_sd.parte_del_ivacc_tmmn*0.15  + union_de_las_tablas1$promedios_sd.parte_del_ivacc_pr*0.25  + union_de_las_tablas1$promedios_sd.parte_del_ivacc_pdsi*0.1 + union_de_las_tablas1$promedios_sd.parte_del_ivacc_def*0.2

names(union_de_las_tablas1)[17] <- "IVACC"
df <- union_de_las_tablas1 
minimo <- min(df$IVACC)
maximo <- max(df$IVACC)
df$IVACC_norm <- (df$IVACC-minimo)/(maximo-minimo)

maxi <- max(df$IVACC_norm )
mini <- min(df$IVACC_norm )
incremento <- (maxi-mini)/5

uno <- mini
dos <- mini + incremento
tres <- dos  + incremento
cuatro <- tres  + incremento
quinto <- cuatro  + incremento
sexto <- quinto  + incremento
rango <- c(1, 2, 3, 4, 5)
uno <- round(uno, digits = 3)
dos <- round(dos, digits = 3)
primer_rango <- paste(uno, "-", dos) 
dos <- round(dos, digits = 3)
tres <- round(tres, digits = 3)
segundo_rango <- paste(dos, "-", tres) 
tres <- round(tres, digits = 3)
cuatro <- round(cuatro, digits = 3)
tercer_rango <- paste(tres, "-", cuatro) 
cuatro <- round(cuatro, digits = 3)
quinto <- round(quinto, digits = 3)
cuarto_rango <- paste(cuatro, "-", quinto) 
quinto <- round(quinto, digits = 3)
sexto <- round(sexto, digits = 3)
quinto_rango <- paste(quinto, "-", sexto) 
rango <- c(1,2,3,4,5)
intervalos <- c(primer_rango, segundo_rango , tercer_rango , cuarto_rango , quinto_rango )
df2 <- data.frame(rango, intervalos)

df$IVACC_norm_rango <- ifelse(df$IVACC_norm >= uno     & df$IVACC_norm < dos , 1, 
            ifelse(df$IVACC_norm >= dos     & df$IVACC_norm < tres , 2, 
            ifelse(df$IVACC_norm >= tres    & df$IVACC_norm < cuatro , 3, 
            ifelse(df$IVACC_norm >= cuatro  & df$IVACC_norm < quinto ,4, 
            ifelse(df$IVACC_norm >= quinto ,5,"")))))

 
df$IVACC_norm_rango_cat <- ifelse(df$IVACC_norm_rango == "1" , "muy baja vulnerabilidad - IVACC", 
                 ifelse(df$IVACC_norm_rango == "2" , "baja vulnerabilidad  - IVACC", 
                 ifelse(df$IVACC_norm_rango == "3" , "moderada vulnerabilidad  - IVACC", 
                 ifelse(df$IVACC_norm_rango == "4" , "alta vulnerabilidad  - IVACC",
                 ifelse(df$IVACC_norm_rango == "5" , "muy alta vulnerabilidad  - IVACC","")))))

La quintilización se efectúa sobre el IVACC normalizado

datatable(df, extensions = 'Buttons', escape = FALSE, rownames = TRUE,
          options = list(dom = 'Bfrtip',
          buttons = list('colvis', list(extend = 'collection',
          buttons = list(
          list(extend='copy'),
          list(extend='excel',
            filename = 'tabla'),
          list(extend='pdf',
            filename= 'tabla')),
          text = 'Download')), scrollX = TRUE))
writexl::write_xlsx(df, "ivacc.xlsx")